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https://api.github.com/repos/huggingface/datasets/issues/6879	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6879/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6879/comments	https://api.github.com/repos/huggingface/datasets/issues/6879/events	https://github.com/huggingface/datasets/issues/6879	2,282,968,259	I_kwDODunzps6IE1TD	6,879	Batched mapping does not raise an error if values for an existing column are empty	{ "login": "felix-schneider", "id": 208336, "node_id": "MDQ6VXNlcjIwODMzNg==", "avatar_url": "https://avatars.githubusercontent.com/u/208336?v=4", "gravatar_id": "", "url": "https://api.github.com/users/felix-schneider", "html_url": "https://github.com/felix-schneider", "followers_url": "https://api.github.com/users/felix-schneider/followers", "following_url": "https://api.github.com/users/felix-schneider/following{/other_user}", "gists_url": "https://api.github.com/users/felix-schneider/gists{/gist_id}", "starred_url": "https://api.github.com/users/felix-schneider/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/felix-schneider/subscriptions", "organizations_url": "https://api.github.com/users/felix-schneider/orgs", "repos_url": "https://api.github.com/users/felix-schneider/repos", "events_url": "https://api.github.com/users/felix-schneider/events{/privacy}", "received_events_url": "https://api.github.com/users/felix-schneider/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	open	false	null	[]	null	[]	2024-05-07T11:02:40	2024-05-07T11:02:40	null	NONE	null	null	null	### Describe the bug Using `Dataset.map(fn, batched=True)` allows resizing the dataset by returning a dict of lists, all of which must be the same size. If they are not the same size, an error like `pyarrow.lib.ArrowInvalid: Column 1 named x expected length 1 but got length 0` is raised. This is not the case if the function returns an empty list for an existing column in the dataset. In that case, the dataset is silently resized to 0 rows. ### Steps to reproduce the bug MWE: ``` import datasets data = datasets.Dataset.from_dict({"test": [1]}) def mapping_fn(examples): return {"test": [], "y": [1]} data = data.map(mapping_fn, batched=True) print(len(data)) ``` Note that when returning `"x": []`, the error is raised correctly, also when returning `"test": [1,2]`. ### Expected behavior Expected an exception: `pyarrow.lib.ArrowInvalid: Column 1 named test expected length 1 but got length 0` or `pyarrow.lib.ArrowInvalid: Column 2 named y expected length 0 but got length 1`. Any exception would be acceptable. ### Environment info - `datasets` version: 2.19.1 - Platform: Linux-5.4.0-153-generic-x86_64-with-glibc2.31 - Python version: 3.11.8 - `huggingface_hub` version: 0.22.2 - PyArrow version: 15.0.2 - Pandas version: 2.2.1 - `fsspec` version: 2024.2.0	null	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6879/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6879/timeline	null	null	false
https://api.github.com/repos/huggingface/datasets/issues/6878	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6878/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6878/comments	https://api.github.com/repos/huggingface/datasets/issues/6878/events	https://github.com/huggingface/datasets/pull/6878	2,282,879,491	PR_kwDODunzps5uviBh	6,878	Create function to convert to parquet	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	null	[]	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6878). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005519 / 0.011353 (-0.005834) \| 0.003877 / 0.011008 (-0.007131) \| 0.063989 / 0.038508 (0.025480) \| 0.032348 / 0.023109 (0.009239) \| 0.238288 / 0.275898 (-0.037611) \| 0.265337 / 0.323480 (-0.058143) \| 0.004363 / 0.007986 (-0.003623) \| 0.002755 / 0.004328 (-0.001574) \| 0.049836 / 0.004250 (0.045585) \| 0.048456 / 0.037052 (0.011403) \| 0.246526 / 0.258489 (-0.011963) \| 0.280753 / 0.293841 (-0.013088) \| 0.027721 / 0.128546 (-0.100825) \| 0.011031 / 0.075646 (-0.064615) \| 0.204168 / 0.419271 (-0.215104) \| 0.036203 / 0.043533 (-0.007330) \| 0.238282 / 0.255139 (-0.016857) \| 0.259608 / 0.283200 (-0.023591) \| 0.017781 / 0.141683 (-0.123902) \| 1.147821 / 1.452155 (-0.304334) \| 1.194855 / 1.492716 (-0.297861) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.102837 / 0.018006 (0.084831) \| 0.312300 / 0.000490 (0.311811) \| 0.000224 / 0.000200 (0.000024) \| 0.000047 / 0.000054 (-0.000008) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.019410 / 0.037411 (-0.018001) \| 0.065114 / 0.014526 (0.050588) \| 0.076828 / 0.176557 (-0.099728) \| 0.121741 / 0.737135 (-0.615394) \| 0.079864 / 0.296338 (-0.216474) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.287773 / 0.215209 (0.072564) \| 2.848936 / 2.077655 (0.771281) \| 1.543819 / 1.504120 (0.039700) \| 1.412708 / 1.541195 (-0.128487) \| 1.454685 / 1.468490 (-0.013805) \| 0.580155 / 4.584777 (-4.004622) \| 2.372783 / 3.745712 (-1.372929) \| 2.910514 / 5.269862 (-2.359347) \| 1.813542 / 4.565676 (-2.752134) \| 0.064569 / 0.424275 (-0.359706) \| 0.005434 / 0.007607 (-0.002173) \| 0.339309 / 0.226044 (0.113265) \| 3.329972 / 2.268929 (1.061043) \| 1.827597 / 55.444624 (-53.617028) \| 1.592324 / 6.876477 (-5.284152) \| 1.619743 / 2.142072 (-0.522329) \| 0.659358 / 4.805227 (-4.145869) \| 0.119887 / 6.500664 (-6.380777) \| 0.043649 / 0.075469 (-0.031821) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.984563 / 1.841788 (-0.857225) \| 12.395302 / 8.074308 (4.320994) \| 9.904944 / 10.191392 (-0.286448) \| 0.136141 / 0.680424 (-0.544282) \| 0.014779 / 0.534201 (-0.519422) \| 0.286146 / 0.579283 (-0.293137) \| 0.265392 / 0.434364 (-0.168972) \| 0.329484 / 0.540337 (-0.210854) \| 0.425530 / 1.386936 (-0.961406) \|\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005920 / 0.011353 (-0.005433) \| 0.004068 / 0.011008 (-0.006940) \| 0.052281 / 0.038508 (0.013773) \| 0.034907 / 0.023109 (0.011798) \| 0.269551 / 0.275898 (-0.006347) \| 0.292390 / 0.323480 (-0.031090) \| 0.004340 / 0.007986 (-0.003646) \| 0.002864 / 0.004328 (-0.001464) \| 0.051466 / 0.004250 (0.047216) \| 0.046410 / 0.037052 (0.009358) \| 0.280103 / 0.258489 (0.021614) \| 0.310616 / 0.293841 (0.016775) \| 0.031044 / 0.128546 (-0.097502) \| 0.011004 / 0.075646 (-0.064643) \| 0.059955 / 0.419271 (-0.359316) \| 0.034156 / 0.043533 (-0.009377) \| 0.268113 / 0.255139 (0.012974) \| 0.283569 / 0.283200 (0.000369) \| 0.019758 / 0.141683 (-0.121925) \| 1.155583 / 1.452155 (-0.296572) \| 1.225611 / 1.492716 (-0.267106) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.104302 / 0.018006 (0.086295) \| 0.307324 / 0.000490 (0.306834) \| 0.000219 / 0.000200 (0.000019) \| 0.000045 / 0.000054 (-0.000009) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.023672 / 0.037411 (-0.013739) \| 0.081110 / 0.014526 (0.066584) \| 0.091783 / 0.176557 (-0.084773) \| 0.131738 / 0.737135 (-0.605397) \| 0.092391 / 0.296338 (-0.203948) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.289341 / 0.215209 (0.074132) \| 2.849894 / 2.077655 (0.772239) \| 1.539679 / 1.504120 (0.035559) \| 1.417975 / 1.541195 (-0.123220) \| 1.473631 / 1.468490 (0.005141) \| 0.583013 / 4.584777 (-4.001764) \| 0.960106 / 3.745712 (-2.785606) \| 2.962785 / 5.269862 (-2.307077) \| 1.827539 / 4.565676 (-2.738138) \| 0.063875 / 0.424275 (-0.360400) \| 0.005251 / 0.007607 (-0.002356) \| 0.347127 / 0.226044 (0.121082) \| 3.417364 / 2.268929 (1.148435) \| 1.965901 / 55.444624 (-53.478723) \| 1.632337 / 6.876477 (-5.244140) \| 1.683100 / 2.142072 (-0.458972) \| 0.664951 / 4.805227 (-4.140277) \| 0.119046 / 6.500664 (-6.381618) \| 0.042828 / 0.075469 (-0.032641) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.999569 / 1.841788 (-0.842218) \| 13.366482 / 8.074308 (5.292174) \| 10.635396 / 10.191392 (0.444004) \| 0.133840 / 0.680424 (-0.546584) \| 0.016232 / 0.534201 (-0.517969) \| 0.292764 / 0.579283 (-0.286519) \| 0.128558 / 0.434364 (-0.305806) \| 0.405596 / 0.540337 (-0.134741) \| 0.429633 / 1.386936 (-0.957303) \|\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#4d92856bbfda0d48d07e82bb520d9434d20fae4b \"CML watermark\")\n" ]	2024-05-07T10:27:07	2024-05-16T14:46:44	2024-05-16T14:38:23	MEMBER	null	false	{ "url": "https://api.github.com/repos/huggingface/datasets/pulls/6878", "html_url": "https://github.com/huggingface/datasets/pull/6878", "diff_url": "https://github.com/huggingface/datasets/pull/6878.diff", "patch_url": "https://github.com/huggingface/datasets/pull/6878.patch", "merged_at": "2024-05-16T14:38:22" }	Analogously with `delete_from_hub`, this PR: - creates the Python function `convert_to_parquet` - makes the corresponding CLI command use that function. This way, the functionality can be used both from a terminal and from a Python console. This PR also implements a test for convert_to_parquet function.	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6878/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6878/timeline	null	null	true
https://api.github.com/repos/huggingface/datasets/issues/6877	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6877/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6877/comments	https://api.github.com/repos/huggingface/datasets/issues/6877/events	https://github.com/huggingface/datasets/issues/6877	2,282,068,337	I_kwDODunzps6IBZlx	6,877	OSError: [Errno 24] Too many open files	{ "login": "loicmagne", "id": 53355258, "node_id": "MDQ6VXNlcjUzMzU1MjU4", "avatar_url": "https://avatars.githubusercontent.com/u/53355258?v=4", "gravatar_id": "", "url": "https://api.github.com/users/loicmagne", "html_url": "https://github.com/loicmagne", "followers_url": "https://api.github.com/users/loicmagne/followers", "following_url": "https://api.github.com/users/loicmagne/following{/other_user}", "gists_url": "https://api.github.com/users/loicmagne/gists{/gist_id}", "starred_url": "https://api.github.com/users/loicmagne/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/loicmagne/subscriptions", "organizations_url": "https://api.github.com/users/loicmagne/orgs", "repos_url": "https://api.github.com/users/loicmagne/repos", "events_url": "https://api.github.com/users/loicmagne/events{/privacy}", "received_events_url": "https://api.github.com/users/loicmagne/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[ { "id": 1935892857, "node_id": "MDU6TGFiZWwxOTM1ODkyODU3", "url": "https://api.github.com/repos/huggingface/datasets/labels/bug", "name": "bug", "color": "d73a4a", "default": true, "description": "Something isn't working" } ]	closed	false	null	[]	null	[ "ulimit -n 8192 can solve this problem", "> ulimit -n 8192 can solve this problem\r\n\r\nWould there be a systematic way to do this ? The data loading is part of the [MTEB](https://github.com/embeddings-benchmark/mteb) library", "> > ulimit -n 8192 can solve this problem\r\n> \r\n> Would there be a systematic way to do this ? The data loading is part of the [MTEB](https://github.com/embeddings-benchmark/mteb) library\r\n\r\n I think we could modify the _prepare_split_single function", "I fixed it with https://github.com/huggingface/datasets/pull/6893, feel free to re-open if you're still having the issue :)", "> I fixed it with #6893, feel free to re-open if you're still having the issue :)\r\n\r\nThanks a lot!" ]	2024-05-07T01:15:09	2024-06-02T14:22:23	2024-05-13T13:01:55	NONE	null	null	null	### Describe the bug I am trying to load the 'default' subset of the following dataset which contains lots of files (828 per split): [https://huggingface.co/datasets/mteb/biblenlp-corpus-mmteb](https://huggingface.co/datasets/mteb/biblenlp-corpus-mmteb) When trying to load it using the `load_dataset` function I get the following error ```python >>> from datasets import load_dataset >>> d = load_dataset('mteb/biblenlp-corpus-mmteb') Downloading readme: 100%\|████████████████████████████████████████████████████████████████████████\| 201k/201k [00:00<00:00, 1.07MB/s] Resolving data files: 100%\|█████████████████████████████████████████████████████████████████████\| 828/828 [00:00<00:00, 1069.15it/s] Resolving data files: 100%\|███████████████████████████████████████████████████████████████████\| 828/828 [00:00<00:00, 436182.33it/s] Resolving data files: 100%\|█████████████████████████████████████████████████████████████████████\| 828/828 [00:00<00:00, 2228.75it/s] Resolving data files: 100%\|███████████████████████████████████████████████████████████████████\| 828/828 [00:00<00:00, 646478.73it/s] Resolving data files: 100%\|███████████████████████████████████████████████████████████████████\| 828/828 [00:00<00:00, 831032.24it/s] Resolving data files: 100%\|███████████████████████████████████████████████████████████████████\| 828/828 [00:00<00:00, 517645.51it/s] Downloading data: 100%\|████████████████████████████████████████████████████████████████████████\| 828/828 [00:33<00:00, 24.87files/s] Downloading data: 100%\|████████████████████████████████████████████████████████████████████████\| 828/828 [00:30<00:00, 27.48files/s] Downloading data: 100%\|████████████████████████████████████████████████████████████████████████\| 828/828 [00:30<00:00, 26.94files/s] Generating train split: 1571592 examples [00:03, 461438.97 examples/s] Generating test split: 11163 examples [00:00, 118190.72 examples/s] Traceback (most recent call last): File ".env/lib/python3.12/site-packages/datasets/builder.py", line 1995, in _prepare_split_single for _, table in generator: File ".env/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 99, in _generate_tables with open(file, "rb") as f: ^^^^^^^^^^^^^^^^ File ".env/lib/python3.12/site-packages/datasets/streaming.py", line 75, in wrapper return function(args, download_config=download_config, kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File ".env/lib/python3.12/site-packages/datasets/utils/file_utils.py", line 1224, in xopen file_obj = fsspec.open(file, mode=mode, args, kwargs).open() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File ".env/lib/python3.12/site-packages/fsspec/core.py", line 135, in open return self.__enter__() ^^^^^^^^^^^^^^^^ File ".env/lib/python3.12/site-packages/fsspec/core.py", line 103, in __enter__ f = self.fs.open(self.path, mode=mode) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File ".env/lib/python3.12/site-packages/fsspec/spec.py", line 1293, in open f = self._open( ^^^^^^^^^^^ File ".env/lib/python3.12/site-packages/datasets/filesystems/compression.py", line 81, in _open return self.file.open() ^^^^^^^^^^^^^^^^ File ".env/lib/python3.12/site-packages/fsspec/core.py", line 135, in open return self.__enter__() ^^^^^^^^^^^^^^^^ File ".env/lib/python3.12/site-packages/fsspec/core.py", line 103, in __enter__ f = self.fs.open(self.path, mode=mode) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File ".env/lib/python3.12/site-packages/fsspec/spec.py", line 1293, in open f = self._open( ^^^^^^^^^^^ File ".env/lib/python3.12/site-packages/fsspec/implementations/local.py", line 197, in _open return LocalFileOpener(path, mode, fs=self, kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File ".env/lib/python3.12/site-packages/fsspec/implementations/local.py", line 322, in __init__ self._open() File ".env/lib/python3.12/site-packages/fsspec/implementations/local.py", line 327, in _open self.f = open(self.path, mode=self.mode) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ OSError: [Errno 24] Too many open files: '.cache/huggingface/datasets/downloads/3a347186abfc0f9c924dde0221d246db758c7232c0101523f04a87c17d696618' The above exception was the direct cause of the following exception: Traceback (most recent call last): File ".env/lib/python3.12/site-packages/datasets/builder.py", line 981, in incomplete_dir yield tmp_dir File ".env/lib/python3.12/site-packages/datasets/builder.py", line 1027, in download_and_prepare self._download_and_prepare( File ".env/lib/python3.12/site-packages/datasets/builder.py", line 1122, in _download_and_prepare self._prepare_split(split_generator, **prepare_split_kwargs) File ".env/lib/python3.12/site-packages/datasets/builder.py", line 1882, in _prepare_split for job_id, done, content in self._prepare_split_single( File ".env/lib/python3.12/site-packages/datasets/builder.py", line 2038, in _prepare_split_single raise DatasetGenerationError("An error occurred while generating the dataset") from e datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset During handling of the above exception, another exception occurred: Traceback (most recent call last): File "<stdin>", line 1, in <module> File ".env/lib/python3.12/site-packages/datasets/load.py", line 2609, in load_dataset builder_instance.download_and_prepare( File ".env/lib/python3.12/site-packages/datasets/builder.py", line 1007, in download_and_prepare with incomplete_dir(self._output_dir) as tmp_output_dir: File "/usr/lib/python3.12/contextlib.py", line 158, in __exit__ self.gen.throw(value) File ".env/lib/python3.12/site-packages/datasets/builder.py", line 988, in incomplete_dir shutil.rmtree(tmp_dir) File "/usr/lib/python3.12/shutil.py", line 785, in rmtree _rmtree_safe_fd(fd, path, onexc) File "/usr/lib/python3.12/shutil.py", line 661, in _rmtree_safe_fd onexc(os.scandir, path, err) File "/usr/lib/python3.12/shutil.py", line 657, in _rmtree_safe_fd with os.scandir(topfd) as scandir_it: ^^^^^^^^^^^^^^^^^ OSError: [Errno 24] Too many open files: '.cache/huggingface/datasets/mteb___biblenlp-corpus-mmteb/default/0.0.0/3912ed967b0834547f35b2da9470c4976b357c9a.incomplete' ``` I looked for the maximum number of open files on my machine (Ubuntu 24.04) and it seems to be 1024, but even when I try to load a single split (`load_dataset('mteb/biblenlp-corpus-mmteb', split='train')`) I get the same error ### Steps to reproduce the bug ```python from datasets import load_dataset d = load_dataset('mteb/biblenlp-corpus-mmteb') ``` ### Expected behavior Load the dataset without error ### Environment info - `datasets` version: 2.19.0 - Platform: Linux-6.8.0-31-generic-x86_64-with-glibc2.39 - Python version: 3.12.3 - `huggingface_hub` version: 0.23.0 - PyArrow version: 16.0.0 - Pandas version: 2.2.2 - `fsspec` version: 2024.3.1	{ "login": "lhoestq", "id": 42851186, "node_id": "MDQ6VXNlcjQyODUxMTg2", "avatar_url": "https://avatars.githubusercontent.com/u/42851186?v=4", "gravatar_id": "", "url": "https://api.github.com/users/lhoestq", "html_url": "https://github.com/lhoestq", "followers_url": "https://api.github.com/users/lhoestq/followers", "following_url": "https://api.github.com/users/lhoestq/following{/other_user}", "gists_url": "https://api.github.com/users/lhoestq/gists{/gist_id}", "starred_url": "https://api.github.com/users/lhoestq/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/lhoestq/subscriptions", "organizations_url": "https://api.github.com/users/lhoestq/orgs", "repos_url": "https://api.github.com/users/lhoestq/repos", "events_url": "https://api.github.com/users/lhoestq/events{/privacy}", "received_events_url": "https://api.github.com/users/lhoestq/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6877/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6877/timeline	null	completed	false
https://api.github.com/repos/huggingface/datasets/issues/6876	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6876/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6876/comments	https://api.github.com/repos/huggingface/datasets/issues/6876/events	https://github.com/huggingface/datasets/pull/6876	2,281,450,743	PR_kwDODunzps5uqs46	6,876	Unpin hfh	{ "login": "lhoestq", "id": 42851186, "node_id": "MDQ6VXNlcjQyODUxMTg2", "avatar_url": "https://avatars.githubusercontent.com/u/42851186?v=4", "gravatar_id": "", "url": "https://api.github.com/users/lhoestq", "html_url": "https://github.com/lhoestq", "followers_url": "https://api.github.com/users/lhoestq/followers", "following_url": "https://api.github.com/users/lhoestq/following{/other_user}", "gists_url": "https://api.github.com/users/lhoestq/gists{/gist_id}", "starred_url": "https://api.github.com/users/lhoestq/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/lhoestq/subscriptions", "organizations_url": "https://api.github.com/users/lhoestq/orgs", "repos_url": "https://api.github.com/users/lhoestq/repos", "events_url": "https://api.github.com/users/lhoestq/events{/privacy}", "received_events_url": "https://api.github.com/users/lhoestq/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	null	[]	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6876). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "transformers 4.40.2 was release yesterday but not sure if it contains the fix", "@lhoestq yes I knew transformers 4.40.2 was released yesterday, but I had checked that it does not contain the fix: only 2 bug fixes. That is why our CI continues failing in this PR. We will have to wait until the next minor version.", "> If we urgently need some dev feature for dataset-viewer, I would suggest pushing the feature (cherry-picked) to a dedicated branch with 2.19.1 as its starting point (without opening a PR), and install datasets from that branch.\r\n\r\nI have done so:\r\n- Created a branch from 2.19.1: https://github.com/huggingface/datasets/tree/datasets-2.19.1-hotfix\r\n- Cherry-picked the commit in this PR: https://github.com/huggingface/datasets/commit/3638183e2f7e0dce8924e46e7cc21bf6d5d7adfb\r\n- Opened a PR in dataset-viewer to update datasets to this revision: https://github.com/huggingface/dataset-viewer/pull/2783", "hfh 0.23.1 and transformers 4.41.0 as are out out, let's unpin no ?", "I have re-run the CI to check that is green before.", "The errors were coming from `transformers` having FutureWarning when loading models or tokenizers. I disabled the warnings for the `transformers`-related calls since they're not related to `datasets`", "I opened an issue in transformers:\r\n- https://github.com/huggingface/transformers/issues/31002", "It's because the error from the FutureWarning happened when running `cache_file()` from `transformers`, which has some code that try/except and re-raise an OSError", "Opened https://github.com/huggingface/transformers/pull/31007 to fix the FutureWarning in transformers. Sorry, thought it was fixed by https://github.com/huggingface/transformers/issues/30618 but clearly an oversight from my side.\r\n\r\nRegarding the pytest config, yes I remember adding it and in general I still think it's a good idea to have it. Will be more careful next time to update `transformers` before `huggingface_hub`'s release and not the other way around (first time it happens since I've set this value :grimacing:). For a temporary fix in `datasets` I would rather temporarily disable the filterwarnings in `datasets` rather then adding filters in the test code. ", "alright I disabled the errors on FutureWarning, do you see anything else @albertvillanova or we can merge ?", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005165 / 0.011353 (-0.006188) \| 0.003991 / 0.011008 (-0.007017) \| 0.064029 / 0.038508 (0.025521) \| 0.031578 / 0.023109 (0.008468) \| 0.242646 / 0.275898 (-0.033252) \| 0.261834 / 0.323480 (-0.061646) \| 0.003032 / 0.007986 (-0.004953) \| 0.002659 / 0.004328 (-0.001670) \| 0.049868 / 0.004250 (0.045618) \| 0.047607 / 0.037052 (0.010555) \| 0.250537 / 0.258489 (-0.007952) \| 0.289460 / 0.293841 (-0.004381) \| 0.027225 / 0.128546 (-0.101321) \| 0.010496 / 0.075646 (-0.065151) \| 0.208455 / 0.419271 (-0.210816) \| 0.036813 / 0.043533 (-0.006720) \| 0.243361 / 0.255139 (-0.011778) \| 0.267477 / 0.283200 (-0.015723) \| 0.020402 / 0.141683 (-0.121281) \| 1.117118 / 1.452155 (-0.335037) \| 1.154868 / 1.492716 (-0.337849) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.096796 / 0.018006 (0.078790) \| 0.304588 / 0.000490 (0.304098) \| 0.000217 / 0.000200 (0.000017) \| 0.000043 / 0.000054 (-0.000011) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.019221 / 0.037411 (-0.018190) \| 0.062897 / 0.014526 (0.048371) \| 0.076446 / 0.176557 (-0.100111) \| 0.124476 / 0.737135 (-0.612659) \| 0.079921 / 0.296338 (-0.216418) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.284442 / 0.215209 (0.069233) \| 2.799419 / 2.077655 (0.721764) \| 1.468022 / 1.504120 (-0.036098) \| 1.354013 / 1.541195 (-0.187182) \| 1.379985 / 1.468490 (-0.088505) \| 0.561723 / 4.584777 (-4.023054) \| 2.408887 / 3.745712 (-1.336825) \| 2.712591 / 5.269862 (-2.557271) \| 1.803132 / 4.565676 (-2.762544) \| 0.063010 / 0.424275 (-0.361265) \| 0.005030 / 0.007607 (-0.002577) \| 0.339065 / 0.226044 (0.113021) \| 3.373667 / 2.268929 (1.104738) \| 1.861569 / 55.444624 (-53.583056) \| 1.551357 / 6.876477 (-5.325120) \| 1.701885 / 2.142072 (-0.440187) \| 0.645685 / 4.805227 (-4.159543) \| 0.117915 / 6.500664 (-6.382749) \| 0.042656 / 0.075469 (-0.032814) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.957397 / 1.841788 (-0.884391) \| 11.544300 / 8.074308 (3.469992) \| 9.761814 / 10.191392 (-0.429578) \| 0.134766 / 0.680424 (-0.545658) \| 0.015387 / 0.534201 (-0.518814) \| 0.285692 / 0.579283 (-0.293591) \| 0.269201 / 0.434364 (-0.165163) \| 0.328198 / 0.540337 (-0.212140) \| 0.422315 / 1.386936 (-0.964621) \|\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005333 / 0.011353 (-0.006020) \| 0.003638 / 0.011008 (-0.007370) \| 0.050503 / 0.038508 (0.011994) \| 0.032240 / 0.023109 (0.009130) \| 0.267602 / 0.275898 (-0.008296) \| 0.293125 / 0.323480 (-0.030355) \| 0.004275 / 0.007986 (-0.003710) \| 0.002714 / 0.004328 (-0.001615) \| 0.049341 / 0.004250 (0.045090) \| 0.040364 / 0.037052 (0.003311) \| 0.281096 / 0.258489 (0.022607) \| 0.312615 / 0.293841 (0.018774) \| 0.029981 / 0.128546 (-0.098565) \| 0.010230 / 0.075646 (-0.065416) \| 0.059218 / 0.419271 (-0.360054) \| 0.033360 / 0.043533 (-0.010172) \| 0.269518 / 0.255139 (0.014379) \| 0.287559 / 0.283200 (0.004360) \| 0.018159 / 0.141683 (-0.123524) \| 1.107148 / 1.452155 (-0.345006) \| 1.170731 / 1.492716 (-0.321985) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.095942 / 0.018006 (0.077936) \| 0.304914 / 0.000490 (0.304425) \| 0.000227 / 0.000200 (0.000027) \| 0.000051 / 0.000054 (-0.000003) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.022609 / 0.037411 (-0.014803) \| 0.076455 / 0.014526 (0.061929) \| 0.088170 / 0.176557 (-0.088386) \| 0.128485 / 0.737135 (-0.608651) \| 0.092471 / 0.296338 (-0.203867) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.291471 / 0.215209 (0.076262) \| 2.822666 / 2.077655 (0.745012) \| 1.531679 / 1.504120 (0.027559) \| 1.405931 / 1.541195 (-0.135263) \| 1.418893 / 1.468490 (-0.049597) \| 0.576128 / 4.584777 (-4.008649) \| 0.969466 / 3.745712 (-2.776246) \| 2.831998 / 5.269862 (-2.437863) \| 1.788814 / 4.565676 (-2.776863) \| 0.064141 / 0.424275 (-0.360134) \| 0.005126 / 0.007607 (-0.002482) \| 0.341699 / 0.226044 (0.115654) \| 3.320551 / 2.268929 (1.051622) \| 1.903350 / 55.444624 (-53.541274) \| 1.611809 / 6.876477 (-5.264668) \| 1.729355 / 2.142072 (-0.412717) \| 0.654622 / 4.805227 (-4.150605) \| 0.118739 / 6.500664 (-6.381925) \| 0.041453 / 0.075469 (-0.034016) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 1.017635 / 1.841788 (-0.824153) \| 12.275948 / 8.074308 (4.201640) \| 10.416224 / 10.191392 (0.224832) \| 0.142288 / 0.680424 (-0.538135) \| 0.015591 / 0.534201 (-0.518610) \| 0.286515 / 0.579283 (-0.292768) \| 0.128661 / 0.434364 (-0.305703) \| 0.325728 / 0.540337 (-0.214609) \| 0.415827 / 1.386936 (-0.971109) \|\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#b442aa2d3efc83ba0dc369adaa63cc496e3d9836 \"CML watermark\")\n" ]	2024-05-06T18:10:49	2024-05-27T10:20:42	2024-05-27T10:14:40	MEMBER	null	false	{ "url": "https://api.github.com/repos/huggingface/datasets/pulls/6876", "html_url": "https://github.com/huggingface/datasets/pull/6876", "diff_url": "https://github.com/huggingface/datasets/pull/6876.diff", "patch_url": "https://github.com/huggingface/datasets/pull/6876.patch", "merged_at": "2024-05-27T10:14:40" }	Needed to use those in dataset-viewer: - dev version of hfh https://github.com/huggingface/dataset-viewer/pull/2781: don't span the hub with /paths-info requests - dev version of datasets at https://github.com/huggingface/datasets/pull/6875: don't write too big logs in the viewer close https://github.com/huggingface/datasets/issues/6863	{ "login": "lhoestq", "id": 42851186, "node_id": "MDQ6VXNlcjQyODUxMTg2", "avatar_url": "https://avatars.githubusercontent.com/u/42851186?v=4", "gravatar_id": "", "url": "https://api.github.com/users/lhoestq", "html_url": "https://github.com/lhoestq", "followers_url": "https://api.github.com/users/lhoestq/followers", "following_url": "https://api.github.com/users/lhoestq/following{/other_user}", "gists_url": "https://api.github.com/users/lhoestq/gists{/gist_id}", "starred_url": "https://api.github.com/users/lhoestq/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/lhoestq/subscriptions", "organizations_url": "https://api.github.com/users/lhoestq/orgs", "repos_url": "https://api.github.com/users/lhoestq/repos", "events_url": "https://api.github.com/users/lhoestq/events{/privacy}", "received_events_url": "https://api.github.com/users/lhoestq/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6876/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6876/timeline	null	null	true
https://api.github.com/repos/huggingface/datasets/issues/6875	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6875/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6875/comments	https://api.github.com/repos/huggingface/datasets/issues/6875/events	https://github.com/huggingface/datasets/pull/6875	2,281,428,826	PR_kwDODunzps5uqoJ_	6,875	Shorten long logs	{ "login": "lhoestq", "id": 42851186, "node_id": "MDQ6VXNlcjQyODUxMTg2", "avatar_url": "https://avatars.githubusercontent.com/u/42851186?v=4", "gravatar_id": "", "url": "https://api.github.com/users/lhoestq", "html_url": "https://github.com/lhoestq", "followers_url": "https://api.github.com/users/lhoestq/followers", "following_url": "https://api.github.com/users/lhoestq/following{/other_user}", "gists_url": "https://api.github.com/users/lhoestq/gists{/gist_id}", "starred_url": "https://api.github.com/users/lhoestq/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/lhoestq/subscriptions", "organizations_url": "https://api.github.com/users/lhoestq/orgs", "repos_url": "https://api.github.com/users/lhoestq/repos", "events_url": "https://api.github.com/users/lhoestq/events{/privacy}", "received_events_url": "https://api.github.com/users/lhoestq/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	null	[]	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6875). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005191 / 0.011353 (-0.006162) \| 0.003691 / 0.011008 (-0.007317) \| 0.063511 / 0.038508 (0.025003) \| 0.031849 / 0.023109 (0.008740) \| 0.251691 / 0.275898 (-0.024207) \| 0.276585 / 0.323480 (-0.046895) \| 0.004080 / 0.007986 (-0.003906) \| 0.002751 / 0.004328 (-0.001577) \| 0.049572 / 0.004250 (0.045322) \| 0.043010 / 0.037052 (0.005957) \| 0.267161 / 0.258489 (0.008672) \| 0.301054 / 0.293841 (0.007213) \| 0.028068 / 0.128546 (-0.100479) \| 0.010479 / 0.075646 (-0.065167) \| 0.208458 / 0.419271 (-0.210814) \| 0.035688 / 0.043533 (-0.007845) \| 0.255985 / 0.255139 (0.000846) \| 0.296016 / 0.283200 (0.012817) \| 0.017041 / 0.141683 (-0.124642) \| 1.168626 / 1.452155 (-0.283528) \| 1.173419 / 1.492716 (-0.319297) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.092975 / 0.018006 (0.074969) \| 0.302309 / 0.000490 (0.301820) \| 0.000219 / 0.000200 (0.000020) \| 0.000042 / 0.000054 (-0.000012) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.018809 / 0.037411 (-0.018602) \| 0.062606 / 0.014526 (0.048080) \| 0.073820 / 0.176557 (-0.102736) \| 0.119451 / 0.737135 (-0.617684) \| 0.075086 / 0.296338 (-0.221253) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.280342 / 0.215209 (0.065133) \| 2.742477 / 2.077655 (0.664822) \| 1.409221 / 1.504120 (-0.094899) \| 1.291679 / 1.541195 (-0.249516) \| 1.316628 / 1.468490 (-0.151862) \| 0.554942 / 4.584777 (-4.029835) \| 2.363301 / 3.745712 (-1.382411) \| 2.775766 / 5.269862 (-2.494096) \| 1.729123 / 4.565676 (-2.836554) \| 0.061254 / 0.424275 (-0.363021) \| 0.005444 / 0.007607 (-0.002163) \| 0.330450 / 0.226044 (0.104406) \| 3.249453 / 2.268929 (0.980524) \| 1.782415 / 55.444624 (-53.662210) \| 1.489778 / 6.876477 (-5.386699) \| 1.521809 / 2.142072 (-0.620263) \| 0.626622 / 4.805227 (-4.178605) \| 0.117320 / 6.500664 (-6.383344) \| 0.043110 / 0.075469 (-0.032359) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.981954 / 1.841788 (-0.859834) \| 11.706373 / 8.074308 (3.632064) \| 9.870815 / 10.191392 (-0.320577) \| 0.141768 / 0.680424 (-0.538656) \| 0.014455 / 0.534201 (-0.519746) \| 0.287451 / 0.579283 (-0.291832) \| 0.264559 / 0.434364 (-0.169805) \| 0.326321 / 0.540337 (-0.214017) \| 0.424084 / 1.386936 (-0.962852) \|\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005461 / 0.011353 (-0.005892) \| 0.003804 / 0.011008 (-0.007204) \| 0.049872 / 0.038508 (0.011364) \| 0.029543 / 0.023109 (0.006433) \| 0.260772 / 0.275898 (-0.015126) \| 0.291571 / 0.323480 (-0.031909) \| 0.004305 / 0.007986 (-0.003681) \| 0.002845 / 0.004328 (-0.001484) \| 0.049129 / 0.004250 (0.044879) \| 0.040743 / 0.037052 (0.003690) \| 0.276497 / 0.258489 (0.018008) \| 0.303126 / 0.293841 (0.009285) \| 0.030423 / 0.128546 (-0.098123) \| 0.010660 / 0.075646 (-0.064986) \| 0.058857 / 0.419271 (-0.360415) \| 0.033185 / 0.043533 (-0.010348) \| 0.260452 / 0.255139 (0.005313) \| 0.282648 / 0.283200 (-0.000552) \| 0.018025 / 0.141683 (-0.123658) \| 1.147432 / 1.452155 (-0.304723) \| 1.192034 / 1.492716 (-0.300683) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.093094 / 0.018006 (0.075088) \| 0.301608 / 0.000490 (0.301119) \| 0.000209 / 0.000200 (0.000009) \| 0.000044 / 0.000054 (-0.000010) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.022071 / 0.037411 (-0.015340) \| 0.075244 / 0.014526 (0.060718) \| 0.087157 / 0.176557 (-0.089400) \| 0.127339 / 0.737135 (-0.609797) \| 0.088527 / 0.296338 (-0.207812) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.293033 / 0.215209 (0.077824) \| 2.839842 / 2.077655 (0.762188) \| 1.544730 / 1.504120 (0.040610) \| 1.421727 / 1.541195 (-0.119468) \| 1.446054 / 1.468490 (-0.022436) \| 0.573285 / 4.584777 (-4.011492) \| 0.980977 / 3.745712 (-2.764735) \| 2.829034 / 5.269862 (-2.440828) \| 1.800747 / 4.565676 (-2.764930) \| 0.064916 / 0.424275 (-0.359360) \| 0.005099 / 0.007607 (-0.002508) \| 0.348054 / 0.226044 (0.122009) \| 3.449111 / 2.268929 (1.180182) \| 1.900115 / 55.444624 (-53.544509) \| 1.620564 / 6.876477 (-5.255913) \| 1.675474 / 2.142072 (-0.466598) \| 0.652302 / 4.805227 (-4.152925) \| 0.118438 / 6.500664 (-6.382226) \| 0.041779 / 0.075469 (-0.033690) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 1.003703 / 1.841788 (-0.838085) \| 12.466921 / 8.074308 (4.392613) \| 9.800419 / 10.191392 (-0.390973) \| 0.131567 / 0.680424 (-0.548856) \| 0.015684 / 0.534201 (-0.518517) \| 0.288754 / 0.579283 (-0.290530) \| 0.126435 / 0.434364 (-0.307929) \| 0.398608 / 0.540337 (-0.141729) \| 0.427043 / 1.386936 (-0.959894) \|\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#865e9b1f2ecbe934be49a2d8d46451aba4af3485 \"CML watermark\")\n" ]	2024-05-06T17:57:07	2024-05-07T12:31:46	2024-05-07T12:25:45	MEMBER	null	false	{ "url": "https://api.github.com/repos/huggingface/datasets/pulls/6875", "html_url": "https://github.com/huggingface/datasets/pull/6875", "diff_url": "https://github.com/huggingface/datasets/pull/6875.diff", "patch_url": "https://github.com/huggingface/datasets/pull/6875.patch", "merged_at": "2024-05-07T12:25:45" }	Some datasets may have unexpectedly long features/types (e.g. if the files are not formatted correctly). In that case we should still be able to log something readable	{ "login": "lhoestq", "id": 42851186, "node_id": "MDQ6VXNlcjQyODUxMTg2", "avatar_url": "https://avatars.githubusercontent.com/u/42851186?v=4", "gravatar_id": "", "url": "https://api.github.com/users/lhoestq", "html_url": "https://github.com/lhoestq", "followers_url": "https://api.github.com/users/lhoestq/followers", "following_url": "https://api.github.com/users/lhoestq/following{/other_user}", "gists_url": "https://api.github.com/users/lhoestq/gists{/gist_id}", "starred_url": "https://api.github.com/users/lhoestq/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/lhoestq/subscriptions", "organizations_url": "https://api.github.com/users/lhoestq/orgs", "repos_url": "https://api.github.com/users/lhoestq/repos", "events_url": "https://api.github.com/users/lhoestq/events{/privacy}", "received_events_url": "https://api.github.com/users/lhoestq/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6875/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6875/timeline	null	null	true
https://api.github.com/repos/huggingface/datasets/issues/6874	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6874/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6874/comments	https://api.github.com/repos/huggingface/datasets/issues/6874/events	https://github.com/huggingface/datasets/pull/6874	2,280,717,233	PR_kwDODunzps5uoOk-	6,874	Use pandas ujson in JSON loader to improve performance	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	null	[]	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6874). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "Before pandas-2.2.0, the function `ujson_loads` was named `loads`: https://github.com/pandas-dev/pandas/blob/v2.1.0/pandas/io/json/__init__.py#L5\r\n```python\r\nimport ujson_loads as loads\r\n```", "Thanks for your review, @lhoestq.\r\n\r\nThe performance gain depends on many factors, such as underlying data structures, file size...\r\n\r\nIn my benchmark, the performance gain was around 8.1%. ", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005428 / 0.011353 (-0.005925) \| 0.003682 / 0.011008 (-0.007326) \| 0.064360 / 0.038508 (0.025852) \| 0.032044 / 0.023109 (0.008934) \| 0.238281 / 0.275898 (-0.037617) \| 0.267542 / 0.323480 (-0.055937) \| 0.003152 / 0.007986 (-0.004834) \| 0.003292 / 0.004328 (-0.001037) \| 0.050157 / 0.004250 (0.045906) \| 0.048311 / 0.037052 (0.011259) \| 0.253743 / 0.258489 (-0.004746) \| 0.282729 / 0.293841 (-0.011112) \| 0.027271 / 0.128546 (-0.101275) \| 0.010238 / 0.075646 (-0.065408) \| 0.208179 / 0.419271 (-0.211092) \| 0.035607 / 0.043533 (-0.007925) \| 0.246750 / 0.255139 (-0.008389) \| 0.263362 / 0.283200 (-0.019837) \| 0.018475 / 0.141683 (-0.123208) \| 1.152978 / 1.452155 (-0.299177) \| 1.158545 / 1.492716 (-0.334171) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.096645 / 0.018006 (0.078639) \| 0.313186 / 0.000490 (0.312696) \| 0.000209 / 0.000200 (0.000009) \| 0.000052 / 0.000054 (-0.000003) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.018800 / 0.037411 (-0.018612) \| 0.065833 / 0.014526 (0.051307) \| 0.073668 / 0.176557 (-0.102888) \| 0.120608 / 0.737135 (-0.616527) \| 0.074936 / 0.296338 (-0.221403) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.281596 / 0.215209 (0.066387) \| 2.814537 / 2.077655 (0.736882) \| 1.482781 / 1.504120 (-0.021338) \| 1.349770 / 1.541195 (-0.191424) \| 1.371571 / 1.468490 (-0.096919) \| 0.555068 / 4.584777 (-4.029709) \| 2.369588 / 3.745712 (-1.376124) \| 2.742771 / 5.269862 (-2.527091) \| 1.711519 / 4.565676 (-2.854158) \| 0.060921 / 0.424275 (-0.363354) \| 0.005263 / 0.007607 (-0.002344) \| 0.333721 / 0.226044 (0.107677) \| 3.329598 / 2.268929 (1.060669) \| 1.806983 / 55.444624 (-53.637641) \| 1.515730 / 6.876477 (-5.360746) \| 1.557622 / 2.142072 (-0.584451) \| 0.619564 / 4.805227 (-4.185663) \| 0.115503 / 6.500664 (-6.385161) \| 0.041728 / 0.075469 (-0.033741) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.967300 / 1.841788 (-0.874487) \| 11.295081 / 8.074308 (3.220773) \| 9.535119 / 10.191392 (-0.656273) \| 0.140232 / 0.680424 (-0.540192) \| 0.013774 / 0.534201 (-0.520427) \| 0.281847 / 0.579283 (-0.297436) \| 0.260076 / 0.434364 (-0.174288) \| 0.323657 / 0.540337 (-0.216681) \| 0.421116 / 1.386936 (-0.965820) \|\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005276 / 0.011353 (-0.006077) \| 0.003639 / 0.011008 (-0.007370) \| 0.050451 / 0.038508 (0.011943) \| 0.032787 / 0.023109 (0.009678) \| 0.267029 / 0.275898 (-0.008869) \| 0.299899 / 0.323480 (-0.023581) \| 0.004177 / 0.007986 (-0.003809) \| 0.002697 / 0.004328 (-0.001631) \| 0.049631 / 0.004250 (0.045380) \| 0.041942 / 0.037052 (0.004889) \| 0.279249 / 0.258489 (0.020760) \| 0.306512 / 0.293841 (0.012671) \| 0.029340 / 0.128546 (-0.099207) \| 0.010118 / 0.075646 (-0.065528) \| 0.058243 / 0.419271 (-0.361028) \| 0.033871 / 0.043533 (-0.009662) \| 0.265949 / 0.255139 (0.010810) \| 0.284263 / 0.283200 (0.001064) \| 0.017351 / 0.141683 (-0.124332) \| 1.107081 / 1.452155 (-0.345074) \| 1.184946 / 1.492716 (-0.307770) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.095621 / 0.018006 (0.077614) \| 0.304758 / 0.000490 (0.304269) \| 0.000204 / 0.000200 (0.000004) \| 0.000052 / 0.000054 (-0.000003) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.022444 / 0.037411 (-0.014967) \| 0.075894 / 0.014526 (0.061368) \| 0.089077 / 0.176557 (-0.087480) \| 0.126960 / 0.737135 (-0.610176) \| 0.089120 / 0.296338 (-0.207218) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.289885 / 0.215209 (0.074676) \| 2.843219 / 2.077655 (0.765565) \| 1.582704 / 1.504120 (0.078584) \| 1.426551 / 1.541195 (-0.114644) \| 1.431591 / 1.468490 (-0.036899) \| 0.577265 / 4.584777 (-4.007512) \| 0.956040 / 3.745712 (-2.789673) \| 2.753517 / 5.269862 (-2.516345) \| 1.732503 / 4.565676 (-2.833173) \| 0.063511 / 0.424275 (-0.360764) \| 0.005089 / 0.007607 (-0.002518) \| 0.339205 / 0.226044 (0.113160) \| 3.339148 / 2.268929 (1.070219) \| 1.901543 / 55.444624 (-53.543081) \| 1.618392 / 6.876477 (-5.258084) \| 1.612885 / 2.142072 (-0.529188) \| 0.656563 / 4.805227 (-4.148664) \| 0.116740 / 6.500664 (-6.383924) \| 0.040497 / 0.075469 (-0.034973) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 1.005568 / 1.841788 (-0.836219) \| 11.872770 / 8.074308 (3.798462) \| 9.867118 / 10.191392 (-0.324274) \| 0.130193 / 0.680424 (-0.550231) \| 0.022857 / 0.534201 (-0.511344) \| 0.281908 / 0.579283 (-0.297375) \| 0.125978 / 0.434364 (-0.308386) \| 0.382604 / 0.540337 (-0.157733) \| 0.415078 / 1.386936 (-0.971858) \|\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#1eabcfaf87368a5cbfa0341aa2223f457508b3e9 \"CML watermark\")\n" ]	2024-05-06T12:01:27	2024-05-17T16:28:29	2024-05-17T16:22:27	MEMBER	null	false	{ "url": "https://api.github.com/repos/huggingface/datasets/pulls/6874", "html_url": "https://github.com/huggingface/datasets/pull/6874", "diff_url": "https://github.com/huggingface/datasets/pull/6874.diff", "patch_url": "https://github.com/huggingface/datasets/pull/6874.patch", "merged_at": "2024-05-17T16:22:27" }	Use pandas ujson in JSON loader to improve performance. Note that `datasets` has `pandas` as required dependency. And `pandas` includes `ujson` in `pd.io.json.ujson_loads`. Fix #6867. CC: @natolambert	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6874/reactions", "total_count": 1, "+1": 1, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6874/timeline	null	null	true
https://api.github.com/repos/huggingface/datasets/issues/6873	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6873/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6873/comments	https://api.github.com/repos/huggingface/datasets/issues/6873/events	https://github.com/huggingface/datasets/pull/6873	2,280,463,182	PR_kwDODunzps5unXnq	6,873	Set dev version	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	null	[]	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6873). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005301 / 0.011353 (-0.006052) \| 0.003633 / 0.011008 (-0.007375) \| 0.063414 / 0.038508 (0.024906) \| 0.042406 / 0.023109 (0.019297) \| 0.253414 / 0.275898 (-0.022484) \| 0.276811 / 0.323480 (-0.046668) \| 0.003148 / 0.007986 (-0.004837) \| 0.002614 / 0.004328 (-0.001715) \| 0.049208 / 0.004250 (0.044958) \| 0.045819 / 0.037052 (0.008767) \| 0.268027 / 0.258489 (0.009538) \| 0.298821 / 0.293841 (0.004980) \| 0.028460 / 0.128546 (-0.100086) \| 0.010671 / 0.075646 (-0.064975) \| 0.208602 / 0.419271 (-0.210669) \| 0.036057 / 0.043533 (-0.007476) \| 0.256079 / 0.255139 (0.000940) \| 0.277040 / 0.283200 (-0.006160) \| 0.019018 / 0.141683 (-0.122665) \| 1.147070 / 1.452155 (-0.305085) \| 1.175838 / 1.492716 (-0.316878) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.092216 / 0.018006 (0.074210) \| 0.304774 / 0.000490 (0.304284) \| 0.000212 / 0.000200 (0.000012) \| 0.000044 / 0.000054 (-0.000010) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.018242 / 0.037411 (-0.019170) \| 0.061088 / 0.014526 (0.046562) \| 0.074517 / 0.176557 (-0.102039) \| 0.120444 / 0.737135 (-0.616691) \| 0.074628 / 0.296338 (-0.221710) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.283914 / 0.215209 (0.068705) \| 2.859123 / 2.077655 (0.781469) \| 1.495152 / 1.504120 (-0.008967) \| 1.395514 / 1.541195 (-0.145681) \| 1.454076 / 1.468490 (-0.014414) \| 0.568758 / 4.584777 (-4.016019) \| 2.461304 / 3.745712 (-1.284408) \| 2.836192 / 5.269862 (-2.433670) \| 1.815463 / 4.565676 (-2.750213) \| 0.065762 / 0.424275 (-0.358513) \| 0.006872 / 0.007607 (-0.000736) \| 0.339304 / 0.226044 (0.113260) \| 3.326544 / 2.268929 (1.057616) \| 1.847970 / 55.444624 (-53.596654) \| 1.572667 / 6.876477 (-5.303809) \| 1.595717 / 2.142072 (-0.546355) \| 0.644196 / 4.805227 (-4.161031) \| 0.120320 / 6.500664 (-6.380344) \| 0.043334 / 0.075469 (-0.032135) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.965807 / 1.841788 (-0.875981) \| 11.628715 / 8.074308 (3.554406) \| 9.485618 / 10.191392 (-0.705774) \| 0.152387 / 0.680424 (-0.528037) \| 0.013852 / 0.534201 (-0.520349) \| 0.285833 / 0.579283 (-0.293450) \| 0.263692 / 0.434364 (-0.170672) \| 0.323086 / 0.540337 (-0.217251) \| 0.418178 / 1.386936 (-0.968758) \|\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005505 / 0.011353 (-0.005848) \| 0.003630 / 0.011008 (-0.007378) \| 0.049780 / 0.038508 (0.011272) \| 0.030469 / 0.023109 (0.007359) \| 0.270052 / 0.275898 (-0.005846) \| 0.294370 / 0.323480 (-0.029110) \| 0.004207 / 0.007986 (-0.003779) \| 0.002720 / 0.004328 (-0.001609) \| 0.048952 / 0.004250 (0.044701) \| 0.041006 / 0.037052 (0.003953) \| 0.281585 / 0.258489 (0.023096) \| 0.310600 / 0.293841 (0.016759) \| 0.029457 / 0.128546 (-0.099089) \| 0.010508 / 0.075646 (-0.065138) \| 0.058090 / 0.419271 (-0.361181) \| 0.032814 / 0.043533 (-0.010718) \| 0.272755 / 0.255139 (0.017616) \| 0.292154 / 0.283200 (0.008954) \| 0.018312 / 0.141683 (-0.123371) \| 1.177199 / 1.452155 (-0.274955) \| 1.238803 / 1.492716 (-0.253913) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.093889 / 0.018006 (0.075883) \| 0.303054 / 0.000490 (0.302564) \| 0.000204 / 0.000200 (0.000004) \| 0.000044 / 0.000054 (-0.000011) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.022556 / 0.037411 (-0.014856) \| 0.075951 / 0.014526 (0.061425) \| 0.086824 / 0.176557 (-0.089732) \| 0.128091 / 0.737135 (-0.609044) \| 0.088146 / 0.296338 (-0.208192) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.292563 / 0.215209 (0.077354) \| 2.882656 / 2.077655 (0.805001) \| 1.559814 / 1.504120 (0.055695) \| 1.443760 / 1.541195 (-0.097435) \| 1.460967 / 1.468490 (-0.007523) \| 0.567812 / 4.584777 (-4.016965) \| 0.964407 / 3.745712 (-2.781305) \| 2.819782 / 5.269862 (-2.450079) \| 1.733334 / 4.565676 (-2.832343) \| 0.064745 / 0.424275 (-0.359530) \| 0.005178 / 0.007607 (-0.002429) \| 0.345322 / 0.226044 (0.119278) \| 3.407204 / 2.268929 (1.138275) \| 1.919337 / 55.444624 (-53.525288) \| 1.643463 / 6.876477 (-5.233013) \| 1.682191 / 2.142072 (-0.459881) \| 0.639432 / 4.805227 (-4.165795) \| 0.115659 / 6.500664 (-6.385005) \| 0.041202 / 0.075469 (-0.034267) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 1.004664 / 1.841788 (-0.837123) \| 12.043460 / 8.074308 (3.969152) \| 9.856431 / 10.191392 (-0.334961) \| 0.131351 / 0.680424 (-0.549072) \| 0.015800 / 0.534201 (-0.518401) \| 0.288211 / 0.579283 (-0.291072) \| 0.126065 / 0.434364 (-0.308298) \| 0.386494 / 0.540337 (-0.153843) \| 0.424203 / 1.386936 (-0.962733) \|\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#039e275549627f22d9e04278d7cad2e80c644459 \"CML watermark\")\n" ]	2024-05-06T09:43:18	2024-05-06T10:03:19	2024-05-06T09:57:12	MEMBER	null	false	{ "url": "https://api.github.com/repos/huggingface/datasets/pulls/6873", "html_url": "https://github.com/huggingface/datasets/pull/6873", "diff_url": "https://github.com/huggingface/datasets/pull/6873.diff", "patch_url": "https://github.com/huggingface/datasets/pull/6873.patch", "merged_at": "2024-05-06T09:57:12" }	null	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6873/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6873/timeline	null	null	true
https://api.github.com/repos/huggingface/datasets/issues/6872	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6872/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6872/comments	https://api.github.com/repos/huggingface/datasets/issues/6872/events	https://github.com/huggingface/datasets/pull/6872	2,280,438,432	PR_kwDODunzps5unSPA	6,872	Release 2.19.1	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	null	[]	null	[]	2024-05-06T09:29:15	2024-05-06T09:35:33	2024-05-06T09:35:32	MEMBER	null	false	{ "url": "https://api.github.com/repos/huggingface/datasets/pulls/6872", "html_url": "https://github.com/huggingface/datasets/pull/6872", "diff_url": "https://github.com/huggingface/datasets/pull/6872.diff", "patch_url": "https://github.com/huggingface/datasets/pull/6872.patch", "merged_at": "2024-05-06T09:35:32" }	null	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6872/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6872/timeline	null	null	true
https://api.github.com/repos/huggingface/datasets/issues/6871	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6871/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6871/comments	https://api.github.com/repos/huggingface/datasets/issues/6871/events	https://github.com/huggingface/datasets/pull/6871	2,280,102,869	PR_kwDODunzps5umJS6	6,871	Fix download for dict of dicts of URLs	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	null	[]	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6871). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "Once merged, I think a patch release is needed.", "Once the CI is green, I am merging this PR and making a patch release, @huggingface/datasets. ", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005352 / 0.011353 (-0.006001) \| 0.004140 / 0.011008 (-0.006868) \| 0.063844 / 0.038508 (0.025336) \| 0.030712 / 0.023109 (0.007603) \| 0.232790 / 0.275898 (-0.043108) \| 0.262334 / 0.323480 (-0.061145) \| 0.003264 / 0.007986 (-0.004721) \| 0.002654 / 0.004328 (-0.001674) \| 0.049775 / 0.004250 (0.045524) \| 0.046803 / 0.037052 (0.009751) \| 0.250667 / 0.258489 (-0.007822) \| 0.283581 / 0.293841 (-0.010260) \| 0.027660 / 0.128546 (-0.100886) \| 0.010560 / 0.075646 (-0.065087) \| 0.208676 / 0.419271 (-0.210596) \| 0.035415 / 0.043533 (-0.008118) \| 0.235380 / 0.255139 (-0.019759) \| 0.261220 / 0.283200 (-0.021980) \| 0.019551 / 0.141683 (-0.122132) \| 1.140196 / 1.452155 (-0.311959) \| 1.173021 / 1.492716 (-0.319696) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.092665 / 0.018006 (0.074659) \| 0.301524 / 0.000490 (0.301034) \| 0.000216 / 0.000200 (0.000016) \| 0.000043 / 0.000054 (-0.000011) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.018485 / 0.037411 (-0.018927) \| 0.061722 / 0.014526 (0.047196) \| 0.074701 / 0.176557 (-0.101855) \| 0.121443 / 0.737135 (-0.615692) \| 0.076268 / 0.296338 (-0.220070) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.284143 / 0.215209 (0.068934) \| 2.789979 / 2.077655 (0.712324) \| 1.501156 / 1.504120 (-0.002964) \| 1.379414 / 1.541195 (-0.161781) \| 1.419092 / 1.468490 (-0.049398) \| 0.554107 / 4.584777 (-4.030670) \| 2.365659 / 3.745712 (-1.380053) \| 2.763963 / 5.269862 (-2.505898) \| 1.712587 / 4.565676 (-2.853090) \| 0.060961 / 0.424275 (-0.363314) \| 0.005301 / 0.007607 (-0.002306) \| 0.346253 / 0.226044 (0.120209) \| 3.351833 / 2.268929 (1.082905) \| 1.831946 / 55.444624 (-53.612679) \| 1.556530 / 6.876477 (-5.319947) \| 1.574185 / 2.142072 (-0.567887) \| 0.630396 / 4.805227 (-4.174831) \| 0.116126 / 6.500664 (-6.384538) \| 0.042391 / 0.075469 (-0.033078) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.981430 / 1.841788 (-0.860358) \| 11.619671 / 8.074308 (3.545363) \| 9.718227 / 10.191392 (-0.473165) \| 0.130918 / 0.680424 (-0.549506) \| 0.014116 / 0.534201 (-0.520085) \| 0.288729 / 0.579283 (-0.290554) \| 0.259183 / 0.434364 (-0.175181) \| 0.323764 / 0.540337 (-0.216574) \| 0.420336 / 1.386936 (-0.966600) \|\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005255 / 0.011353 (-0.006098) \| 0.003664 / 0.011008 (-0.007344) \| 0.051376 / 0.038508 (0.012868) \| 0.030429 / 0.023109 (0.007320) \| 0.263090 / 0.275898 (-0.012808) \| 0.289959 / 0.323480 (-0.033521) \| 0.004214 / 0.007986 (-0.003772) \| 0.002782 / 0.004328 (-0.001546) \| 0.049043 / 0.004250 (0.044793) \| 0.041016 / 0.037052 (0.003964) \| 0.275616 / 0.258489 (0.017127) \| 0.303350 / 0.293841 (0.009509) \| 0.029484 / 0.128546 (-0.099062) \| 0.010329 / 0.075646 (-0.065317) \| 0.058680 / 0.419271 (-0.360591) \| 0.032818 / 0.043533 (-0.010715) \| 0.263368 / 0.255139 (0.008229) \| 0.286839 / 0.283200 (0.003640) \| 0.018029 / 0.141683 (-0.123654) \| 1.169207 / 1.452155 (-0.282948) \| 1.206568 / 1.492716 (-0.286148) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.101394 / 0.018006 (0.083387) \| 0.310414 / 0.000490 (0.309924) \| 0.000213 / 0.000200 (0.000013) \| 0.000053 / 0.000054 (-0.000002) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.021662 / 0.037411 (-0.015749) \| 0.075320 / 0.014526 (0.060794) \| 0.086607 / 0.176557 (-0.089949) \| 0.127268 / 0.737135 (-0.609867) \| 0.088244 / 0.296338 (-0.208095) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.293591 / 0.215209 (0.078382) \| 2.871845 / 2.077655 (0.794190) \| 1.543624 / 1.504120 (0.039504) \| 1.426698 / 1.541195 (-0.114497) \| 1.445348 / 1.468490 (-0.023142) \| 0.565156 / 4.584777 (-4.019621) \| 0.961782 / 3.745712 (-2.783930) \| 2.827904 / 5.269862 (-2.441958) \| 1.747728 / 4.565676 (-2.817949) \| 0.063275 / 0.424275 (-0.361000) \| 0.004987 / 0.007607 (-0.002620) \| 0.349652 / 0.226044 (0.123607) \| 3.448635 / 2.268929 (1.179707) \| 1.891734 / 55.444624 (-53.552890) \| 1.624274 / 6.876477 (-5.252202) \| 1.641531 / 2.142072 (-0.500541) \| 0.642081 / 4.805227 (-4.163146) \| 0.116136 / 6.500664 (-6.384528) \| 0.040807 / 0.075469 (-0.034662) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 1.002090 / 1.841788 (-0.839697) \| 12.401097 / 8.074308 (4.326788) \| 9.799316 / 10.191392 (-0.392076) \| 0.131770 / 0.680424 (-0.548654) \| 0.016817 / 0.534201 (-0.517384) \| 0.301136 / 0.579283 (-0.278147) \| 0.136810 / 0.434364 (-0.297554) \| 0.384740 / 0.540337 (-0.155598) \| 0.423779 / 1.386936 (-0.963157) \|\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#2ebd8233ad8142da73bc8b4d380e9a32046d7829 \"CML watermark\")\n" ]	2024-05-06T06:06:52	2024-05-06T09:32:03	2024-05-06T09:25:52	MEMBER	null	false	{ "url": "https://api.github.com/repos/huggingface/datasets/pulls/6871", "html_url": "https://github.com/huggingface/datasets/pull/6871", "diff_url": "https://github.com/huggingface/datasets/pull/6871.diff", "patch_url": "https://github.com/huggingface/datasets/pull/6871.patch", "merged_at": "2024-05-06T09:25:52" }	Fix download for a dict of dicts of URLs when batched (default), introduced by: - #6794 This PR also implements regression tests. Fix #6869, fix #6850.	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6871/reactions", "total_count": 1, "+1": 1, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6871/timeline	null	null	true
https://api.github.com/repos/huggingface/datasets/issues/6870	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6870/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6870/comments	https://api.github.com/repos/huggingface/datasets/issues/6870/events	https://github.com/huggingface/datasets/pull/6870	2,280,084,008	PR_kwDODunzps5umFOL	6,870	Update tqdm >= 4.66.3 to fix vulnerability	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	null	[]	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6870). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.004997 / 0.011353 (-0.006356) \| 0.003260 / 0.011008 (-0.007748) \| 0.063342 / 0.038508 (0.024833) \| 0.030399 / 0.023109 (0.007290) \| 0.235665 / 0.275898 (-0.040233) \| 0.256502 / 0.323480 (-0.066978) \| 0.004113 / 0.007986 (-0.003873) \| 0.002677 / 0.004328 (-0.001652) \| 0.049614 / 0.004250 (0.045363) \| 0.043075 / 0.037052 (0.006022) \| 0.251788 / 0.258489 (-0.006701) \| 0.280875 / 0.293841 (-0.012965) \| 0.027479 / 0.128546 (-0.101067) \| 0.010402 / 0.075646 (-0.065245) \| 0.207296 / 0.419271 (-0.211975) \| 0.035323 / 0.043533 (-0.008209) \| 0.237719 / 0.255139 (-0.017420) \| 0.259401 / 0.283200 (-0.023799) \| 0.017574 / 0.141683 (-0.124109) \| 1.109025 / 1.452155 (-0.343129) \| 1.176264 / 1.492716 (-0.316452) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.098780 / 0.018006 (0.080774) \| 0.304427 / 0.000490 (0.303937) \| 0.000215 / 0.000200 (0.000016) \| 0.000044 / 0.000054 (-0.000010) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.018189 / 0.037411 (-0.019222) \| 0.061356 / 0.014526 (0.046830) \| 0.073568 / 0.176557 (-0.102988) \| 0.122412 / 0.737135 (-0.614723) \| 0.074428 / 0.296338 (-0.221911) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.284719 / 0.215209 (0.069510) \| 2.805719 / 2.077655 (0.728064) \| 1.474386 / 1.504120 (-0.029734) \| 1.341552 / 1.541195 (-0.199642) \| 1.385354 / 1.468490 (-0.083136) \| 0.575694 / 4.584777 (-4.009083) \| 2.435102 / 3.745712 (-1.310610) \| 2.822424 / 5.269862 (-2.447437) \| 1.747609 / 4.565676 (-2.818068) \| 0.064461 / 0.424275 (-0.359815) \| 0.005370 / 0.007607 (-0.002237) \| 0.341511 / 0.226044 (0.115467) \| 3.384546 / 2.268929 (1.115617) \| 1.846960 / 55.444624 (-53.597665) \| 1.549294 / 6.876477 (-5.327183) \| 1.562997 / 2.142072 (-0.579075) \| 0.651108 / 4.805227 (-4.154120) \| 0.118502 / 6.500664 (-6.382162) \| 0.042356 / 0.075469 (-0.033113) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 1.015542 / 1.841788 (-0.826245) \| 11.504899 / 8.074308 (3.430591) \| 9.660870 / 10.191392 (-0.530522) \| 0.145255 / 0.680424 (-0.535169) \| 0.014602 / 0.534201 (-0.519599) \| 0.286148 / 0.579283 (-0.293135) \| 0.268358 / 0.434364 (-0.166006) \| 0.323648 / 0.540337 (-0.216689) \| 0.427384 / 1.386936 (-0.959552) \|\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005671 / 0.011353 (-0.005681) \| 0.004056 / 0.011008 (-0.006952) \| 0.050673 / 0.038508 (0.012165) \| 0.032334 / 0.023109 (0.009225) \| 0.268541 / 0.275898 (-0.007357) \| 0.294528 / 0.323480 (-0.028952) \| 0.004592 / 0.007986 (-0.003393) \| 0.002918 / 0.004328 (-0.001411) \| 0.048857 / 0.004250 (0.044607) \| 0.043072 / 0.037052 (0.006020) \| 0.277031 / 0.258489 (0.018542) \| 0.307189 / 0.293841 (0.013348) \| 0.030500 / 0.128546 (-0.098046) \| 0.010945 / 0.075646 (-0.064701) \| 0.061067 / 0.419271 (-0.358204) \| 0.060311 / 0.043533 (0.016778) \| 0.268011 / 0.255139 (0.012872) \| 0.290423 / 0.283200 (0.007224) \| 0.019578 / 0.141683 (-0.122105) \| 1.136353 / 1.452155 (-0.315802) \| 1.196308 / 1.492716 (-0.296408) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.099429 / 0.018006 (0.081422) \| 0.308350 / 0.000490 (0.307861) \| 0.000221 / 0.000200 (0.000021) \| 0.000045 / 0.000054 (-0.000010) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.022221 / 0.037411 (-0.015190) \| 0.076744 / 0.014526 (0.062218) \| 0.087768 / 0.176557 (-0.088788) \| 0.129939 / 0.737135 (-0.607196) \| 0.089763 / 0.296338 (-0.206576) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.299566 / 0.215209 (0.084357) \| 2.916789 / 2.077655 (0.839134) \| 1.555535 / 1.504120 (0.051415) \| 1.432787 / 1.541195 (-0.108407) \| 1.470983 / 1.468490 (0.002493) \| 0.581468 / 4.584777 (-4.003309) \| 0.993418 / 3.745712 (-2.752294) \| 2.917487 / 5.269862 (-2.352374) \| 1.799045 / 4.565676 (-2.766632) \| 0.064520 / 0.424275 (-0.359755) \| 0.005131 / 0.007607 (-0.002477) \| 0.352277 / 0.226044 (0.126232) \| 3.456564 / 2.268929 (1.187636) \| 1.949195 / 55.444624 (-53.495430) \| 1.627568 / 6.876477 (-5.248909) \| 1.685246 / 2.142072 (-0.456826) \| 0.653161 / 4.805227 (-4.152066) \| 0.118308 / 6.500664 (-6.382356) \| 0.042106 / 0.075469 (-0.033364) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 1.048028 / 1.841788 (-0.793759) \| 12.425232 / 8.074308 (4.350924) \| 10.127637 / 10.191392 (-0.063755) \| 0.133095 / 0.680424 (-0.547329) \| 0.015255 / 0.534201 (-0.518946) \| 0.287927 / 0.579283 (-0.291357) \| 0.129384 / 0.434364 (-0.304980) \| 0.384828 / 0.540337 (-0.155510) \| 0.427881 / 1.386936 (-0.959055) \|\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#a0bdb664436fad1d82c7988d5b413c76207f5037 \"CML watermark\")\n" ]	2024-05-06T05:49:36	2024-05-06T06:08:06	2024-05-06T06:02:00	MEMBER	null	false	{ "url": "https://api.github.com/repos/huggingface/datasets/pulls/6870", "html_url": "https://github.com/huggingface/datasets/pull/6870", "diff_url": "https://github.com/huggingface/datasets/pull/6870.diff", "patch_url": "https://github.com/huggingface/datasets/pull/6870.patch", "merged_at": "2024-05-06T06:02:00" }	Update tqdm >= 4.66.3 to fix vulnerability,	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6870/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6870/timeline	null	null	true
https://api.github.com/repos/huggingface/datasets/issues/6869	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6869/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6869/comments	https://api.github.com/repos/huggingface/datasets/issues/6869/events	https://github.com/huggingface/datasets/issues/6869	2,280,048,297	I_kwDODunzps6H5sap	6,869	Download is broken for dict of dicts: FileNotFoundError	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[ { "id": 1935892857, "node_id": "MDU6TGFiZWwxOTM1ODkyODU3", "url": "https://api.github.com/repos/huggingface/datasets/labels/bug", "name": "bug", "color": "d73a4a", "default": true, "description": "Something isn't working" } ]	closed	false	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[ { "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false } ]	null	[]	2024-05-06T05:13:36	2024-05-06T09:25:53	2024-05-06T09:25:53	MEMBER	null	null	null	It seems there is a bug when downloading a dict of dicts of URLs introduced by: - #6794 ## Steps to reproduce the bug: ```python from datasets import DownloadManager dl_manager = DownloadManager() paths = dl_manager.download({"train": {"frr": "hf://datasets/wikimedia/wikipedia/20231101.frr/train-00000-of-00001.parquet"}}) ``` Stack trace: ``` --------------------------------------------------------------------------- FileNotFoundError Traceback (most recent call last) <ipython-input-7-0e0d76d25b09> in <module> ----> 1 paths = dl_manager.download({"train": {"frr": "hf://datasets/wikimedia/wikipedia/20231101.frr/train-00000-of-00001.parquet"}}) .../huggingface/datasets/src/datasets/download/download_manager.py in download(self, url_or_urls) 255 start_time = datetime.now() 256 with stack_multiprocessing_download_progress_bars(): --> 257 downloaded_path_or_paths = map_nested( 258 download_func, 259 url_or_urls, .../huggingface/datasets/src/datasets/utils/py_utils.py in map_nested(function, data_struct, dict_only, map_list, map_tuple, map_numpy, num_proc, parallel_min_length, batched, batch_size, types, disable_tqdm, desc) 506 batch_size = max(len(iterable) // num_proc + int(len(iterable) % num_proc > 0), 1) 507 iterable = list(iter_batched(iterable, batch_size)) --> 508 mapped = [ 509 _single_map_nested((function, obj, batched, batch_size, types, None, True, None)) 510 for obj in hf_tqdm(iterable, disable=disable_tqdm, desc=desc) .../huggingface/datasets/src/datasets/utils/py_utils.py in <listcomp>(.0) 507 iterable = list(iter_batched(iterable, batch_size)) 508 mapped = [ --> 509 _single_map_nested((function, obj, batched, batch_size, types, None, True, None)) 510 for obj in hf_tqdm(iterable, disable=disable_tqdm, desc=desc) 511 ] .../huggingface/datasets/src/datasets/utils/py_utils.py in _single_map_nested(args) 375 and all(not isinstance(v, types) for v in data_struct) 376 ): --> 377 return [mapped_item for batch in iter_batched(data_struct, batch_size) for mapped_item in function(batch)] 378 379 # Reduce logging to keep things readable in multiprocessing with tqdm .../huggingface/datasets/src/datasets/utils/py_utils.py in <listcomp>(.0) 375 and all(not isinstance(v, types) for v in data_struct) 376 ): --> 377 return [mapped_item for batch in iter_batched(data_struct, batch_size) for mapped_item in function(batch)] 378 379 # Reduce logging to keep things readable in multiprocessing with tqdm .../huggingface/datasets/src/datasets/download/download_manager.py in _download_batched(self, url_or_filenames, download_config) 311 ) 312 else: --> 313 return [ 314 self._download_single(url_or_filename, download_config=download_config) 315 for url_or_filename in url_or_filenames .../huggingface/datasets/src/datasets/download/download_manager.py in <listcomp>(.0) 312 else: 313 return [ --> 314 self._download_single(url_or_filename, download_config=download_config) 315 for url_or_filename in url_or_filenames 316 ] .../huggingface/datasets/src/datasets/download/download_manager.py in _download_single(self, url_or_filename, download_config) 321 # append the relative path to the base_path 322 url_or_filename = url_or_path_join(self._base_path, url_or_filename) --> 323 out = cached_path(url_or_filename, download_config=download_config) 324 out = tracked_str(out) 325 out.set_origin(url_or_filename) .../huggingface/datasets/src/datasets/utils/file_utils.py in cached_path(url_or_filename, download_config, **download_kwargs) 220 elif is_local_path(url_or_filename): 221 # File, but it doesn't exist. --> 222 raise FileNotFoundError(f"Local file {url_or_filename} doesn't exist") 223 else: 224 # Something unknown FileNotFoundError: Local file .../huggingface/datasets/{'frr': 'hf:/datasets/wikimedia/wikipedia/20231101.frr/train-00000-of-00001.parquet'} doesn't exist ``` Related to: - #6850	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6869/reactions", "total_count": 1, "+1": 1, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6869/timeline	null	completed	false
https://api.github.com/repos/huggingface/datasets/issues/6868	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6868/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6868/comments	https://api.github.com/repos/huggingface/datasets/issues/6868/events	https://github.com/huggingface/datasets/issues/6868	2,279,385,159	I_kwDODunzps6H3KhH	6,868	datasets.BuilderConfig does not work.	{ "login": "jdm4pku", "id": 148830652, "node_id": "U_kgDOCN75vA", "avatar_url": "https://avatars.githubusercontent.com/u/148830652?v=4", "gravatar_id": "", "url": "https://api.github.com/users/jdm4pku", "html_url": "https://github.com/jdm4pku", "followers_url": "https://api.github.com/users/jdm4pku/followers", "following_url": "https://api.github.com/users/jdm4pku/following{/other_user}", "gists_url": "https://api.github.com/users/jdm4pku/gists{/gist_id}", "starred_url": "https://api.github.com/users/jdm4pku/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/jdm4pku/subscriptions", "organizations_url": "https://api.github.com/users/jdm4pku/orgs", "repos_url": "https://api.github.com/users/jdm4pku/repos", "events_url": "https://api.github.com/users/jdm4pku/events{/privacy}", "received_events_url": "https://api.github.com/users/jdm4pku/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	null	[]	null	[ "I guess the issue is caused by the customization of BuilderConfig that you use from the repo [https://github.com/BeyonderXX/InstructUIE](https://github.com/BeyonderXX/InstructUIE/blob/master/src/uie_dataset.py). You should report to them.\r\n\r\nI see you already opened an issue in their repo:\r\n- https://github.com/BeyonderXX/InstructUIE/issues/40" ]	2024-05-05T08:08:55	2024-05-05T12:15:02	2024-05-05T12:15:01	NONE	null	null	null	### Describe the bug I custom a BuilderConfig and GeneratorBasedBuilder. Here is the code for BuilderConfig ``` class UIEConfig(datasets.BuilderConfig): def __init__( self, args, data_dir=None, instruction_file=None, instruction_strategy=None, task_config_dir=None, num_examples=None, max_num_instances_per_task=None, max_num_instances_per_eval_task=None, over_sampling=None, kwargs ): super().__init__(args, **kwargs) self.data_dir = data_dir self.num_examples = num_examples self.over_sampling = over_sampling self.instructions = self._parse_instruction(instruction_file) self.task_configs = self._parse_task_config(task_config_dir) self.instruction_strategy = instruction_strategy self.max_num_instances_per_task = max_num_instances_per_task self.max_num_instances_per_eval_task = max_num_instances_per_eval_task ``` Besides, here is the code for GeneratorBasedBuilder. ``` class UIEInstructions(datasets.GeneratorBasedBuilder): VERSION = datasets.Version("2.0.0") BUILDER_CONFIG_CLASS = UIEConfig BUILDER_CONFIGS = [ UIEConfig(name="default", description="Default config for NaturalInstructions") ] DEFAULT_CONFIG_NAME = "default" ``` Here is the load_dataset ``` raw_datasets = load_dataset( os.path.join(CURRENT_DIR, "uie_dataset.py"), data_dir=data_args.data_dir, task_config_dir=data_args.task_config_dir, instruction_file=data_args.instruction_file, instruction_strategy=data_args.instruction_strategy, cache_dir=data_cache_dir, # for debug, change dataset size, otherwise open it max_num_instances_per_task=data_args.max_num_instances_per_task, max_num_instances_per_eval_task=data_args.max_num_instances_per_eval_task, num_examples=data_args.num_examples, over_sampling=data_args.over_sampling ) ``` Finally, I met the error. ``` BuilderConfig UIEConfig(name='default', version=0.0.0, data_dir=None, data_files=None, description='Default config for NaturalInstructions') doesn't have a 'task_config_dir' key. ``` I debugged the code, but I find the parameters added by me may not work. ### Steps to reproduce the bug https://github.com/BeyonderXX/InstructUIE/blob/master/src/uie_dataset.py ### Expected behavior ``` BuilderConfig UIEConfig(name='default', version=0.0.0, data_dir=None, data_files=None, description='Default config for NaturalInstructions') doesn't have a 'task_config_dir' key. ``` ### Environment info torch 2.3.0+cu118 transformers 4.40.1 python 3.8	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6868/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6868/timeline	null	not_planned	false
https://api.github.com/repos/huggingface/datasets/issues/6867	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6867/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6867/comments	https://api.github.com/repos/huggingface/datasets/issues/6867/events	https://github.com/huggingface/datasets/issues/6867	2,279,059,787	I_kwDODunzps6H17FL	6,867	Improve performance of JSON loader	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[ { "id": 1935892871, "node_id": "MDU6TGFiZWwxOTM1ODkyODcx", "url": "https://api.github.com/repos/huggingface/datasets/labels/enhancement", "name": "enhancement", "color": "a2eeef", "default": true, "description": "New feature or request" } ]	closed	false	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[ { "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false } ]	null	[ "Thanks! Feel free to ping me for examples. May not respond immediately because we're all busy but would like to help.", "Hi @natolambert, could you please give some examples of JSON files to benchmark?\r\n\r\nPlease note that this JSON file (https://huggingface.co/datasets/allenai/reward-bench-results/blob/main/eval-set-scores/Ray2333/reward-model-Mistral-7B-instruct-Unified-Feedback.json) is not in \"records\" orient; instead it has the following structure:\r\n```json\r\n{\r\n \"chat_template\": \"tulu\",\r\n \"id\": [30, 34, 35,...],\r\n \"model\": \"Ray2333/reward-model-Mistral-7B-instruct-Unified-Feedback\",\r\n \"model_type\": \"Seq. Classifier\",\r\n \"results\": [1, 1, 1, ...],\r\n \"scores_chosen\": [4.421875, 1.8916015625, 3.8515625,...],\r\n \"scores_rejected\": [-2.416015625, -1.47265625, -0.9912109375,...],\r\n \"subset\": [\"alpacaeval-easy\", \"alpacaeval-easy\", \"alpacaeval-easy\",...]\r\n \"text_chosen\": [\"<s>[INST] How do I detail a...\",...],\r\n \"text_rejected\": [\"<s>[INST] How do I detail a...\",...]\r\n}\r\n```\r\n\r\nNote that \"records\" orient should be a list (not a dict) with each row as one item of the list:\r\n```json\r\n[\r\n {\"chat_template\": \"tulu\", \"id\": 30,... },\r\n {\"chat_template\": \"tulu\", \"id\": 34,... },\r\n ...\r\n]\r\n```", "We use a mix (which is a mess), here's an example with the records orient\r\nhttps://huggingface.co/datasets/allenai/reward-bench-results/blob/main/best-of-n/alpaca_eval/tulu-13b/OpenAssistant/oasst-rm-2.1-pythia-1.4b-epoch-2.5.json\r\n\r\nThere are more in that folder, ~40mb maybe?", "@albertvillanova here's a snippet so you don't need to click\r\n```\r\n{\r\n \"config\": \"top_p=0.9;temp=1.0\",\r\n \"dataset_details\": \"helpful_base\",\r\n \"id\": [\r\n 0,\r\n 0\r\n ],\r\n \"model\": \"allenai/tulu-2-dpo-13b\",\r\n \"scores\": 3.076171875\r\n}\r\n{\r\n \"config\": \"top_p=0.9;temp=1.0\",\r\n \"dataset_details\": \"helpful_base\",\r\n \"id\": [\r\n 0,\r\n 1\r\n ],\r\n \"model\": \"allenai/tulu-2-dpo-13b\",\r\n \"scores\": 3.87890625\r\n}\r\n{\r\n \"config\": \"top_p=0.9;temp=1.0\",\r\n \"dataset_details\": \"helpful_base\",\r\n \"id\": [\r\n 0,\r\n 2\r\n ],\r\n \"model\": \"allenai/tulu-2-dpo-13b\",\r\n \"scores\": 3.287109375\r\n}\r\n{\r\n \"config\": \"top_p=0.9;temp=1.0\",\r\n \"dataset_details\": \"helpful_base\",\r\n \"id\": [\r\n 0,\r\n 3\r\n ],\r\n \"model\": \"allenai/tulu-2-dpo-13b\",\r\n \"scores\": 1.6337890625\r\n}\r\n{\r\n \"config\": \"top_p=0.9;temp=1.0\",\r\n \"dataset_details\": \"helpful_base\",\r\n \"id\": [\r\n 0,\r\n 4\r\n ],\r\n \"model\": \"allenai/tulu-2-dpo-13b\",\r\n \"scores\": 5.27734375\r\n}\r\n{\r\n \"config\": \"top_p=0.9;temp=1.0\",\r\n \"dataset_details\": \"helpful_base\",\r\n \"id\": [\r\n 0,\r\n 5\r\n ],\r\n \"model\": \"allenai/tulu-2-dpo-13b\",\r\n \"scores\": 3.0625\r\n}\r\n{\r\n \"config\": \"top_p=0.9;temp=1.0\",\r\n \"dataset_details\": \"helpful_base\",\r\n \"id\": [\r\n 0,\r\n 6\r\n ],\r\n \"model\": \"allenai/tulu-2-dpo-13b\",\r\n \"scores\": 2.29296875\r\n}\r\n{\r\n \"config\": \"top_p=0.9;temp=1.0\",\r\n \"dataset_details\": \"helpful_base\",\r\n \"id\": [\r\n 0,\r\n 7\r\n ],\r\n \"model\": \"allenai/tulu-2-dpo-13b\",\r\n \"scores\": 6.77734375\r\n}\r\n{\r\n \"config\": \"top_p=0.9;temp=1.0\",\r\n \"dataset_details\": \"helpful_base\",\r\n \"id\": [\r\n 0,\r\n 8\r\n ],\r\n \"model\": \"allenai/tulu-2-dpo-13b\",\r\n \"scores\": 3.853515625\r\n}\r\n{\r\n \"config\": \"top_p=0.9;temp=1.0\",\r\n \"dataset_details\": \"helpful_base\",\r\n \"id\": [\r\n 0,\r\n 9\r\n ],\r\n \"model\": \"allenai/tulu-2-dpo-13b\",\r\n \"scores\": 4.86328125\r\n}\r\n{\r\n \"config\": \"top_p=0.9;temp=1.0\",\r\n \"dataset_details\": \"helpful_base\",\r\n \"id\": [\r\n 0,\r\n 10\r\n ],\r\n \"model\": \"allenai/tulu-2-dpo-13b\",\r\n \"scores\": 2.890625\r\n}\r\n{\r\n \"config\": \"top_p=0.9;temp=1.0\",\r\n \"dataset_details\": \"helpful_base\",\r\n \"id\": [\r\n 0,\r\n 11\r\n ],\r\n \"model\": \"allenai/tulu-2-dpo-13b\",\r\n \"scores\": 4.70703125\r\n}\r\n{\r\n \"config\": \"top_p=0.9;temp=1.0\",\r\n \"dataset_details\": \"helpful_base\",\r\n \"id\": [\r\n 0,\r\n 12\r\n ],\r\n \"model\": \"allenai/tulu-2-dpo-13b\",\r\n \"scores\": 4.45703125\r\n}\r\n```", "Thanks again for your feedback, @natolambert.\r\n\r\nHowever, strictly speaking, the last file is not in JSON format but in kind of JSON-Lines like format (although not properly either because there are multiple newline characters within each object). Not even pandas can read that file format.\r\n\r\nAnyway, for JSON-Lines, I would expect that `datasets` and `pandas` have the same performance for JSON Lines files, as both use `pyarrow` under the hood...\r\n\r\nA proper JSON file in records orient should be a list (a JSON array): the first character should be `[`.\r\n\r\nAnyway, I am generating a JSON file from your JSON-Lines file to test performance." ]	2024-05-04T15:04:16	2024-05-17T16:22:28	2024-05-17T16:22:28	MEMBER	null	null	null	As reported by @natolambert, loading regular JSON files with `datasets` shows poor performance. The cause is that we use the `json` Python standard library instead of other faster libraries. See my old comment: https://github.com/huggingface/datasets/pull/2638#pullrequestreview-706983714 > There are benchmarks that compare different JSON packages, with the Standard Library one among the worst performant: > - https://github.com/ultrajson/ultrajson#benchmarks > - https://github.com/ijl/orjson#performance I remember having a discussion about this and it was decided that it was better not to include an additional dependency on a 3rd-party library. However: - We already depend on `pandas` and `pandas` depends on `ujson`: so we have an indirect dependency on `ujson` - Even if the above were not the case, we always could include `ujson` as an optional extra dependency, and check at runtime if it is installed to decide which library to use, either json or ujson	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6867/reactions", "total_count": 3, "+1": 3, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6867/timeline	null	completed	false
https://api.github.com/repos/huggingface/datasets/issues/6866	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6866/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6866/comments	https://api.github.com/repos/huggingface/datasets/issues/6866/events	https://github.com/huggingface/datasets/issues/6866	2,278,736,221	I_kwDODunzps6H0sFd	6,866	DataFilesNotFoundError for datasets in the open-llm-leaderboard	{ "login": "jerome-white", "id": 6140840, "node_id": "MDQ6VXNlcjYxNDA4NDA=", "avatar_url": "https://avatars.githubusercontent.com/u/6140840?v=4", "gravatar_id": "", "url": "https://api.github.com/users/jerome-white", "html_url": "https://github.com/jerome-white", "followers_url": "https://api.github.com/users/jerome-white/followers", "following_url": "https://api.github.com/users/jerome-white/following{/other_user}", "gists_url": "https://api.github.com/users/jerome-white/gists{/gist_id}", "starred_url": "https://api.github.com/users/jerome-white/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/jerome-white/subscriptions", "organizations_url": "https://api.github.com/users/jerome-white/orgs", "repos_url": "https://api.github.com/users/jerome-white/repos", "events_url": "https://api.github.com/users/jerome-white/events{/privacy}", "received_events_url": "https://api.github.com/users/jerome-white/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[ { "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false } ]	null	[ "Potentially related:\r\n* #6864\r\n* #6850\r\n* #6848\r\n* #6819", "Hi @jerome-white, thnaks for reporting.\r\n\r\nHowever, I cannot reproduce your issue:\r\n```python\r\n>>> from datasets import get_dataset_config_names\r\n\r\n>>> get_dataset_config_names(\"open-llm-leaderboard/details_davidkim205__Rhea-72b-v0.5\")\r\n['harness_arc_challenge_25',\r\n 'harness_gsm8k_5',\r\n 'harness_hellaswag_10',\r\n 'harness_hendrycksTest_5',\r\n 'harness_hendrycksTest_abstract_algebra_5',\r\n 'harness_hendrycksTest_anatomy_5',\r\n 'harness_hendrycksTest_astronomy_5',\r\n 'harness_hendrycksTest_business_ethics_5',\r\n 'harness_hendrycksTest_clinical_knowledge_5',\r\n 'harness_hendrycksTest_college_biology_5',\r\n 'harness_hendrycksTest_college_chemistry_5',\r\n 'harness_hendrycksTest_college_computer_science_5',\r\n 'harness_hendrycksTest_college_mathematics_5',\r\n 'harness_hendrycksTest_college_medicine_5',\r\n 'harness_hendrycksTest_college_physics_5',\r\n 'harness_hendrycksTest_computer_security_5',\r\n 'harness_hendrycksTest_conceptual_physics_5',\r\n 'harness_hendrycksTest_econometrics_5',\r\n 'harness_hendrycksTest_electrical_engineering_5',\r\n 'harness_hendrycksTest_elementary_mathematics_5',\r\n 'harness_hendrycksTest_formal_logic_5',\r\n 'harness_hendrycksTest_global_facts_5',\r\n 'harness_hendrycksTest_high_school_biology_5',\r\n 'harness_hendrycksTest_high_school_chemistry_5',\r\n 'harness_hendrycksTest_high_school_computer_science_5',\r\n 'harness_hendrycksTest_high_school_european_history_5',\r\n 'harness_hendrycksTest_high_school_geography_5',\r\n 'harness_hendrycksTest_high_school_government_and_politics_5',\r\n 'harness_hendrycksTest_high_school_macroeconomics_5',\r\n 'harness_hendrycksTest_high_school_mathematics_5',\r\n 'harness_hendrycksTest_high_school_microeconomics_5',\r\n 'harness_hendrycksTest_high_school_physics_5',\r\n 'harness_hendrycksTest_high_school_psychology_5',\r\n 'harness_hendrycksTest_high_school_statistics_5',\r\n 'harness_hendrycksTest_high_school_us_history_5',\r\n 'harness_hendrycksTest_high_school_world_history_5',\r\n 'harness_hendrycksTest_human_aging_5',\r\n 'harness_hendrycksTest_human_sexuality_5',\r\n 'harness_hendrycksTest_international_law_5',\r\n 'harness_hendrycksTest_jurisprudence_5',\r\n 'harness_hendrycksTest_logical_fallacies_5',\r\n 'harness_hendrycksTest_machine_learning_5',\r\n 'harness_hendrycksTest_management_5',\r\n 'harness_hendrycksTest_marketing_5',\r\n 'harness_hendrycksTest_medical_genetics_5',\r\n 'harness_hendrycksTest_miscellaneous_5',\r\n 'harness_hendrycksTest_moral_disputes_5',\r\n 'harness_hendrycksTest_moral_scenarios_5',\r\n 'harness_hendrycksTest_nutrition_5',\r\n 'harness_hendrycksTest_philosophy_5',\r\n 'harness_hendrycksTest_prehistory_5',\r\n 'harness_hendrycksTest_professional_accounting_5',\r\n 'harness_hendrycksTest_professional_law_5',\r\n 'harness_hendrycksTest_professional_medicine_5',\r\n 'harness_hendrycksTest_professional_psychology_5',\r\n 'harness_hendrycksTest_public_relations_5',\r\n 'harness_hendrycksTest_security_studies_5',\r\n 'harness_hendrycksTest_sociology_5',\r\n 'harness_hendrycksTest_us_foreign_policy_5',\r\n 'harness_hendrycksTest_virology_5',\r\n 'harness_hendrycksTest_world_religions_5',\r\n 'harness_truthfulqa_mc_0',\r\n 'harness_winogrande_5',\r\n 'results']\r\n```\r\n\r\nMaybe it was just a temporary issue...", "> Maybe it was just a temporary issue...\r\n\r\nPerhaps. I've changed my workflow to use the hub's `HfFileSystem`, so for now this is no longer a blocker for me. I'll reopen the issue if that changes." ]	2024-05-04T04:59:00	2024-05-14T08:09:56	2024-05-14T08:09:56	NONE	null	null	null	### Describe the bug When trying to get config names or load any dataset within the open-llm-leaderboard ecosystem (`open-llm-leaderboard/details_`) I receive the DataFilesNotFoundError. For the last month or so I've been loading datasets from the leaderboard almost everyday; yesterday was the first time I started seeing this. ### Steps to reproduce the bug This snippet has three cells: 1. Loads the modules 2. Tries to get config names 3. Tries to load the dataset I've chosen "davidkim205"'s Rhea-72b-v0.5 model because it is one of the best performers on the leaderboard should likely have no dataset issues: ```python In [1]: from datasets import load_dataset, get_dataset_config_names In [2]: get_dataset_config_names("open-llm-leaderboard/details_davidkim205__Rhea ...: -72b-v0.5") --------------------------------------------------------------------------- DataFilesNotFoundError Traceback (most recent call last) Cell In[2], line 1 ----> 1 get_dataset_config_names("open-llm-leaderboard/details_davidkim205__Rhea-72b-v0.5") File ~/open-llm-bda/venv/lib/python3.11/site-packages/datasets/inspect.py:347, in get_dataset_config_names(path, revision, download_config, download_mode, dynamic_modules_path, data_files, download_kwargs) 291 def get_dataset_config_names( 292 path: str, 293 revision: Optional[Union[str, Version]] = None, (...) 298 download_kwargs, 299 ): 300 """Get the list of available config names for a particular dataset. 301 302 Args: (...) 345 ``` 346 """ --> 347 dataset_module = dataset_module_factory( 348 path, 349 revision=revision, 350 download_config=download_config, 351 download_mode=download_mode, 352 dynamic_modules_path=dynamic_modules_path, 353 data_files=data_files, 354 download_kwargs, 355 ) 356 builder_cls = get_dataset_builder_class(dataset_module, dataset_name=os.path.basename(path)) 357 return list(builder_cls.builder_configs.keys()) or [ 358 dataset_module.builder_kwargs.get("config_name", builder_cls.DEFAULT_CONFIG_NAME or "default") 359 ] File ~/open-llm-bda/venv/lib/python3.11/site-packages/datasets/load.py:1821, in dataset_module_factory(path, revision, download_config, download_mode, dynamic_modules_path, data_dir, data_files, cache_dir, trust_remote_code, _require_default_config_name, _require_custom_configs, download_kwargs) 1812 return LocalDatasetModuleFactoryWithScript( 1813 combined_path, 1814 download_mode=download_mode, 1815 dynamic_modules_path=dynamic_modules_path, 1816 trust_remote_code=trust_remote_code, 1817 ).get_module() 1818 elif os.path.isdir(path): 1819 return LocalDatasetModuleFactoryWithoutScript( 1820 path, data_dir=data_dir, data_files=data_files, download_mode=download_mode -> 1821 ).get_module() 1822 # Try remotely 1823 elif is_relative_path(path) and path.count("/") <= 1: File ~/open-llm-bda/venv/lib/python3.11/site-packages/datasets/load.py:1039, in LocalDatasetModuleFactoryWithoutScript.get_module(self) 1033 patterns = get_data_patterns(base_path) 1034 data_files = DataFilesDict.from_patterns( 1035 patterns, 1036 base_path=base_path, 1037 allowed_extensions=ALL_ALLOWED_EXTENSIONS, 1038 ) -> 1039 module_name, default_builder_kwargs = infer_module_for_data_files( 1040 data_files=data_files, 1041 path=self.path, 1042 ) 1043 data_files = data_files.filter_extensions(_MODULE_TO_EXTENSIONS[module_name]) 1044 # Collect metadata files if the module supports them File ~/open-llm-bda/venv/lib/python3.11/site-packages/datasets/load.py:597, in infer_module_for_data_files(data_files, path, download_config) 595 raise ValueError(f"Couldn't infer the same data file format for all splits. Got {split_modules}") 596 if not module_name: --> 597 raise DataFilesNotFoundError("No (supported) data files found" + (f" in {path}" if path else "")) 598 return module_name, default_builder_kwargs DataFilesNotFoundError: No (supported) data files found in open-llm-leaderboard/details_davidkim205__Rhea-72b-v0.5 In [3]: data = load_dataset("open-llm-leaderboard/details_davidkim205__Rhea-72b- ...: v0.5", "harness_winogrande_5") --------------------------------------------------------------------------- DataFilesNotFoundError Traceback (most recent call last) Cell In[3], line 1 ----> 1 data = load_dataset("open-llm-leaderboard/details_davidkim205__Rhea-72b-v0.5", "harness_winogrande_5") File ~/open-llm-bda/venv/lib/python3.11/site-packages/datasets/load.py:2587, in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, verification_mode, ignore_verifications, keep_in_memory, save_infos, revision, token, use_auth_token, task, streaming, num_proc, storage_options, trust_remote_code, config_kwargs) 2582 verification_mode = VerificationMode( 2583 (verification_mode or VerificationMode.BASIC_CHECKS) if not save_infos else VerificationMode.ALL_CHECKS 2584 ) 2586 # Create a dataset builder -> 2587 builder_instance = load_dataset_builder( 2588 path=path, 2589 name=name, 2590 data_dir=data_dir, 2591 data_files=data_files, 2592 cache_dir=cache_dir, 2593 features=features, 2594 download_config=download_config, 2595 download_mode=download_mode, 2596 revision=revision, 2597 token=token, 2598 storage_options=storage_options, 2599 trust_remote_code=trust_remote_code, 2600 _require_default_config_name=name is None, 2601 config_kwargs, 2602 ) 2604 # Return iterable dataset in case of streaming 2605 if streaming: File ~/open-llm-bda/venv/lib/python3.11/site-packages/datasets/load.py:2259, in load_dataset_builder(path, name, data_dir, data_files, cache_dir, features, download_config, download_mode, revision, token, use_auth_token, storage_options, trust_remote_code, _require_default_config_name, config_kwargs) 2257 download_config = download_config.copy() if download_config else DownloadConfig() 2258 download_config.storage_options.update(storage_options) -> 2259 dataset_module = dataset_module_factory( 2260 path, 2261 revision=revision, 2262 download_config=download_config, 2263 download_mode=download_mode, 2264 data_dir=data_dir, 2265 data_files=data_files, 2266 cache_dir=cache_dir, 2267 trust_remote_code=trust_remote_code, 2268 _require_default_config_name=_require_default_config_name, 2269 _require_custom_configs=bool(config_kwargs), 2270 ) 2271 # Get dataset builder class from the processing script 2272 builder_kwargs = dataset_module.builder_kwargs File ~/open-llm-bda/venv/lib/python3.11/site-packages/datasets/load.py:1821, in dataset_module_factory(path, revision, download_config, download_mode, dynamic_modules_path, data_dir, data_files, cache_dir, trust_remote_code, _require_default_config_name, _require_custom_configs, download_kwargs) 1812 return LocalDatasetModuleFactoryWithScript( 1813 combined_path, 1814 download_mode=download_mode, 1815 dynamic_modules_path=dynamic_modules_path, 1816 trust_remote_code=trust_remote_code, 1817 ).get_module() 1818 elif os.path.isdir(path): 1819 return LocalDatasetModuleFactoryWithoutScript( 1820 path, data_dir=data_dir, data_files=data_files, download_mode=download_mode -> 1821 ).get_module() 1822 # Try remotely 1823 elif is_relative_path(path) and path.count("/") <= 1: File ~/open-llm-bda/venv/lib/python3.11/site-packages/datasets/load.py:1039, in LocalDatasetModuleFactoryWithoutScript.get_module(self) 1033 patterns = get_data_patterns(base_path) 1034 data_files = DataFilesDict.from_patterns( 1035 patterns, 1036 base_path=base_path, 1037 allowed_extensions=ALL_ALLOWED_EXTENSIONS, 1038 ) -> 1039 module_name, default_builder_kwargs = infer_module_for_data_files( 1040 data_files=data_files, 1041 path=self.path, 1042 ) 1043 data_files = data_files.filter_extensions(_MODULE_TO_EXTENSIONS[module_name]) 1044 # Collect metadata files if the module supports them File ~/open-llm-bda/venv/lib/python3.11/site-packages/datasets/load.py:597, in infer_module_for_data_files(data_files, path, download_config) 595 raise ValueError(f"Couldn't infer the same data file format for all splits. Got {split_modules}") 596 if not module_name: --> 597 raise DataFilesNotFoundError("No (supported) data files found" + (f" in {path}" if path else "")) 598 return module_name, default_builder_kwargs DataFilesNotFoundError: No (supported) data files found in open-llm-leaderboard/details_davidkim205__Rhea-72b-v0.5 ``` ### Expected behavior No exceptions from `get_dataset_config_names` or `load_dataset` ### Environment info - `datasets` version: 2.19.0 - Platform: Linux-6.5.0-1018-aws-aarch64-with-glibc2.35 - Python version: 3.11.8 - `huggingface_hub` version: 0.23.0 - PyArrow version: 16.0.0 - Pandas version: 2.2.2 - `fsspec` version: 2024.3.1	{ "login": "jerome-white", "id": 6140840, "node_id": "MDQ6VXNlcjYxNDA4NDA=", "avatar_url": "https://avatars.githubusercontent.com/u/6140840?v=4", "gravatar_id": "", "url": "https://api.github.com/users/jerome-white", "html_url": "https://github.com/jerome-white", "followers_url": "https://api.github.com/users/jerome-white/followers", "following_url": "https://api.github.com/users/jerome-white/following{/other_user}", "gists_url": "https://api.github.com/users/jerome-white/gists{/gist_id}", "starred_url": "https://api.github.com/users/jerome-white/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/jerome-white/subscriptions", "organizations_url": "https://api.github.com/users/jerome-white/orgs", "repos_url": "https://api.github.com/users/jerome-white/repos", "events_url": "https://api.github.com/users/jerome-white/events{/privacy}", "received_events_url": "https://api.github.com/users/jerome-white/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6866/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6866/timeline	null	completed	false
https://api.github.com/repos/huggingface/datasets/issues/6865	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6865/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6865/comments	https://api.github.com/repos/huggingface/datasets/issues/6865/events	https://github.com/huggingface/datasets/issues/6865	2,277,304,832	I_kwDODunzps6HvOoA	6,865	Example on Semantic segmentation contains bug	{ "login": "ducha-aiki", "id": 4803565, "node_id": "MDQ6VXNlcjQ4MDM1NjU=", "avatar_url": "https://avatars.githubusercontent.com/u/4803565?v=4", "gravatar_id": "", "url": "https://api.github.com/users/ducha-aiki", "html_url": "https://github.com/ducha-aiki", "followers_url": "https://api.github.com/users/ducha-aiki/followers", "following_url": "https://api.github.com/users/ducha-aiki/following{/other_user}", "gists_url": "https://api.github.com/users/ducha-aiki/gists{/gist_id}", "starred_url": "https://api.github.com/users/ducha-aiki/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/ducha-aiki/subscriptions", "organizations_url": "https://api.github.com/users/ducha-aiki/orgs", "repos_url": "https://api.github.com/users/ducha-aiki/repos", "events_url": "https://api.github.com/users/ducha-aiki/events{/privacy}", "received_events_url": "https://api.github.com/users/ducha-aiki/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	open	false	null	[]	null	[]	2024-05-03T09:40:12	2024-05-03T09:40:12	null	NONE	null	null	null	### Describe the bug https://huggingface.co/docs/datasets/en/semantic_segmentation shows wrong example with torchvision transforms. Specifically, as one can see in screenshot below, the object boundaries have weird colors. <img width="689" alt="image" src="https://github.com/huggingface/datasets/assets/4803565/59aa0e2c-2e3e-415b-9d42-2314044c5aee"> Original example with `albumentations` is correct <img width="705" alt="image" src="https://github.com/huggingface/datasets/assets/4803565/27dbd725-cea5-4e48-ba59-7050c3ce17b3"> That is because `torch vision.transforms.Resize` interpolates with bilinear everything which is wrong when used for segmentation labels - you just cannot mix them. Overall, `torchvision.transforms` is designed for classification only and cannot be used to images and masks together, unless you write two separate branches of augmentations. The correct way would be to use `v2` version of transforms and convert the segmentation labels to https://pytorch.org/vision/main/generated/torchvision.tv_tensors.Mask.html#torchvision.tv_tensors.Mask object ### Steps to reproduce the bug Go to the website. <img width="689" alt="image" src="https://github.com/huggingface/datasets/assets/4803565/ea1276d0-d69a-48cf-b9c2-cd61217815ef"> https://huggingface.co/docs/datasets/en/semantic_segmentation ### Expected behavior Results, similar to `albumentation`. Or remove the torch vision part altogether. Or use `kornia` instead. ### Environment info Irrelevant	null	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6865/reactions", "total_count": 2, "+1": 2, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6865/timeline	null	null	false
https://api.github.com/repos/huggingface/datasets/issues/6864	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6864/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6864/comments	https://api.github.com/repos/huggingface/datasets/issues/6864/events	https://github.com/huggingface/datasets/issues/6864	2,276,986,981	I_kwDODunzps6HuBBl	6,864	Dataset 'rewardsignal/reddit_writing_prompts' doesn't exist on the Hub	{ "login": "vinodrajendran001", "id": 5783246, "node_id": "MDQ6VXNlcjU3ODMyNDY=", "avatar_url": "https://avatars.githubusercontent.com/u/5783246?v=4", "gravatar_id": "", "url": "https://api.github.com/users/vinodrajendran001", "html_url": "https://github.com/vinodrajendran001", "followers_url": "https://api.github.com/users/vinodrajendran001/followers", "following_url": "https://api.github.com/users/vinodrajendran001/following{/other_user}", "gists_url": "https://api.github.com/users/vinodrajendran001/gists{/gist_id}", "starred_url": "https://api.github.com/users/vinodrajendran001/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/vinodrajendran001/subscriptions", "organizations_url": "https://api.github.com/users/vinodrajendran001/orgs", "repos_url": "https://api.github.com/users/vinodrajendran001/repos", "events_url": "https://api.github.com/users/vinodrajendran001/events{/privacy}", "received_events_url": "https://api.github.com/users/vinodrajendran001/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[ { "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false } ]	null	[ "Hi @vinodrajendran001, thanks for reporting.\r\n\r\nIndeed the dataset no longer exists on the Hub. The URL https://huggingface.co/datasets/rewardsignal/reddit_writing_prompts gives 404 Not Found error." ]	2024-05-03T06:03:30	2024-05-06T06:36:42	2024-05-06T06:36:41	NONE	null	null	null	### Describe the bug The dataset `rewardsignal/reddit_writing_prompts` is missing in Huggingface Hub. ### Steps to reproduce the bug ``` from datasets import load_dataset prompt_response_dataset = load_dataset("rewardsignal/reddit_writing_prompts", data_files="prompt_responses_full.csv", split='train[:80%]') ``` ### Expected behavior DatasetNotFoundError: Dataset 'rewardsignal/reddit_writing_prompts' doesn't exist on the Hub or cannot be accessed ### Environment info Nothing to do with versions	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6864/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6864/timeline	null	not_planned	false
https://api.github.com/repos/huggingface/datasets/issues/6863	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6863/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6863/comments	https://api.github.com/repos/huggingface/datasets/issues/6863/events	https://github.com/huggingface/datasets/issues/6863	2,276,977,534	I_kwDODunzps6Ht-t-	6,863	Revert temporary pin huggingface-hub < 0.23.0	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[ { "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false } ]	null	[]	2024-05-03T05:53:55	2024-05-27T10:14:41	2024-05-27T10:14:41	MEMBER	null	null	null	Revert temporary pin huggingface-hub < 0.23.0 introduced by - #6861 once the following issue is fixed and released: - huggingface/transformers#30618	{ "login": "lhoestq", "id": 42851186, "node_id": "MDQ6VXNlcjQyODUxMTg2", "avatar_url": "https://avatars.githubusercontent.com/u/42851186?v=4", "gravatar_id": "", "url": "https://api.github.com/users/lhoestq", "html_url": "https://github.com/lhoestq", "followers_url": "https://api.github.com/users/lhoestq/followers", "following_url": "https://api.github.com/users/lhoestq/following{/other_user}", "gists_url": "https://api.github.com/users/lhoestq/gists{/gist_id}", "starred_url": "https://api.github.com/users/lhoestq/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/lhoestq/subscriptions", "organizations_url": "https://api.github.com/users/lhoestq/orgs", "repos_url": "https://api.github.com/users/lhoestq/repos", "events_url": "https://api.github.com/users/lhoestq/events{/privacy}", "received_events_url": "https://api.github.com/users/lhoestq/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6863/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6863/timeline	null	completed	false
https://api.github.com/repos/huggingface/datasets/issues/6862	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6862/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6862/comments	https://api.github.com/repos/huggingface/datasets/issues/6862/events	https://github.com/huggingface/datasets/pull/6862	2,276,763,745	PR_kwDODunzps5ubOoL	6,862	Fix load_dataset for data_files with protocols other than HF	{ "login": "matstrand", "id": 544843, "node_id": "MDQ6VXNlcjU0NDg0Mw==", "avatar_url": "https://avatars.githubusercontent.com/u/544843?v=4", "gravatar_id": "", "url": "https://api.github.com/users/matstrand", "html_url": "https://github.com/matstrand", "followers_url": "https://api.github.com/users/matstrand/followers", "following_url": "https://api.github.com/users/matstrand/following{/other_user}", "gists_url": "https://api.github.com/users/matstrand/gists{/gist_id}", "starred_url": "https://api.github.com/users/matstrand/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/matstrand/subscriptions", "organizations_url": "https://api.github.com/users/matstrand/orgs", "repos_url": "https://api.github.com/users/matstrand/repos", "events_url": "https://api.github.com/users/matstrand/events{/privacy}", "received_events_url": "https://api.github.com/users/matstrand/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	null	[]	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6862). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005615 / 0.011353 (-0.005738) \| 0.004015 / 0.011008 (-0.006994) \| 0.066769 / 0.038508 (0.028261) \| 0.032983 / 0.023109 (0.009874) \| 0.246301 / 0.275898 (-0.029597) \| 0.266463 / 0.323480 (-0.057017) \| 0.003291 / 0.007986 (-0.004695) \| 0.002905 / 0.004328 (-0.001424) \| 0.049913 / 0.004250 (0.045663) \| 0.046186 / 0.037052 (0.009134) \| 0.248971 / 0.258489 (-0.009518) \| 0.288066 / 0.293841 (-0.005775) \| 0.029638 / 0.128546 (-0.098908) \| 0.012454 / 0.075646 (-0.063192) \| 0.225397 / 0.419271 (-0.193875) \| 0.036075 / 0.043533 (-0.007458) \| 0.250110 / 0.255139 (-0.005029) \| 0.267968 / 0.283200 (-0.015232) \| 0.020943 / 0.141683 (-0.120740) \| 1.116938 / 1.452155 (-0.335216) \| 1.159617 / 1.492716 (-0.333099) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.099813 / 0.018006 (0.081807) \| 0.310770 / 0.000490 (0.310280) \| 0.000223 / 0.000200 (0.000023) \| 0.000043 / 0.000054 (-0.000012) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.018909 / 0.037411 (-0.018503) \| 0.062833 / 0.014526 (0.048307) \| 0.074895 / 0.176557 (-0.101662) \| 0.121213 / 0.737135 (-0.615922) \| 0.076984 / 0.296338 (-0.219355) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.282026 / 0.215209 (0.066817) \| 2.775044 / 2.077655 (0.697390) \| 1.485574 / 1.504120 (-0.018546) \| 1.356639 / 1.541195 (-0.184556) \| 1.378677 / 1.468490 (-0.089813) \| 0.724739 / 4.584777 (-3.860038) \| 2.379279 / 3.745712 (-1.366433) \| 3.030104 / 5.269862 (-2.239758) \| 1.981636 / 4.565676 (-2.584041) \| 0.078758 / 0.424275 (-0.345517) \| 0.005188 / 0.007607 (-0.002419) \| 0.336284 / 0.226044 (0.110240) \| 3.261649 / 2.268929 (0.992720) \| 1.849333 / 55.444624 (-53.595292) \| 1.564988 / 6.876477 (-5.311489) \| 1.598720 / 2.142072 (-0.543353) \| 0.793190 / 4.805227 (-4.012038) \| 0.135384 / 6.500664 (-6.365280) \| 0.043597 / 0.075469 (-0.031872) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.976428 / 1.841788 (-0.865359) \| 12.087446 / 8.074308 (4.013138) \| 9.756592 / 10.191392 (-0.434800) \| 0.140836 / 0.680424 (-0.539588) \| 0.015193 / 0.534201 (-0.519008) \| 0.327789 / 0.579283 (-0.251494) \| 0.265418 / 0.434364 (-0.168945) \| 0.356548 / 0.540337 (-0.183790) \| 0.451014 / 1.386936 (-0.935922) \|\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005879 / 0.011353 (-0.005474) \| 0.004001 / 0.011008 (-0.007008) \| 0.051066 / 0.038508 (0.012558) \| 0.033824 / 0.023109 (0.010714) \| 0.275303 / 0.275898 (-0.000595) \| 0.301223 / 0.323480 (-0.022257) \| 0.004456 / 0.007986 (-0.003530) \| 0.002930 / 0.004328 (-0.001399) \| 0.050674 / 0.004250 (0.046423) \| 0.040798 / 0.037052 (0.003746) \| 0.288702 / 0.258489 (0.030213) \| 0.324865 / 0.293841 (0.031024) \| 0.032935 / 0.128546 (-0.095611) \| 0.012372 / 0.075646 (-0.063274) \| 0.060778 / 0.419271 (-0.358493) \| 0.034369 / 0.043533 (-0.009164) \| 0.277240 / 0.255139 (0.022101) \| 0.300027 / 0.283200 (0.016828) \| 0.018586 / 0.141683 (-0.123097) \| 1.148498 / 1.452155 (-0.303657) \| 1.256665 / 1.492716 (-0.236052) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.105616 / 0.018006 (0.087610) \| 0.328206 / 0.000490 (0.327716) \| 0.000229 / 0.000200 (0.000029) \| 0.000052 / 0.000054 (-0.000003) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.023759 / 0.037411 (-0.013652) \| 0.077709 / 0.014526 (0.063183) \| 0.089840 / 0.176557 (-0.086717) \| 0.129891 / 0.737135 (-0.607244) \| 0.091533 / 0.296338 (-0.204805) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.308228 / 0.215209 (0.093019) \| 2.966868 / 2.077655 (0.889213) \| 1.589914 / 1.504120 (0.085794) \| 1.463263 / 1.541195 (-0.077932) \| 1.508233 / 1.468490 (0.039743) \| 0.722289 / 4.584777 (-3.862488) \| 0.961580 / 3.745712 (-2.784132) \| 2.897209 / 5.269862 (-2.372653) \| 1.969601 / 4.565676 (-2.596076) \| 0.079850 / 0.424275 (-0.344425) \| 0.005394 / 0.007607 (-0.002213) \| 0.355451 / 0.226044 (0.129406) \| 3.486822 / 2.268929 (1.217893) \| 1.987236 / 55.444624 (-53.457388) \| 1.701017 / 6.876477 (-5.175460) \| 1.849909 / 2.142072 (-0.292163) \| 0.785358 / 4.805227 (-4.019870) \| 0.135085 / 6.500664 (-6.365579) \| 0.042056 / 0.075469 (-0.033413) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 1.055287 / 1.841788 (-0.786501) \| 13.696916 / 8.074308 (5.622608) \| 10.801396 / 10.191392 (0.610004) \| 0.134642 / 0.680424 (-0.545782) \| 0.016007 / 0.534201 (-0.518194) \| 0.304163 / 0.579283 (-0.275120) \| 0.124530 / 0.434364 (-0.309834) \| 0.344002 / 0.540337 (-0.196335) \| 0.445138 / 1.386936 (-0.941798) \|\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#5142a8cf61d8a4495eda3d91dc4283a6df01ea14 \"CML watermark\")\n" ]	2024-05-03T01:43:47	2024-07-23T14:37:08	2024-07-23T14:30:09	CONTRIBUTOR	null	false	{ "url": "https://api.github.com/repos/huggingface/datasets/pulls/6862", "html_url": "https://github.com/huggingface/datasets/pull/6862", "diff_url": "https://github.com/huggingface/datasets/pull/6862.diff", "patch_url": "https://github.com/huggingface/datasets/pull/6862.patch", "merged_at": "2024-07-23T14:30:09" }	Fixes huggingface/datasets/issues/6598 I've added a new test case and a solution. Before applying the solution the test case was failing with the same error described in the linked issue. MRE: ``` pip install "datasets[s3]" python -c "from datasets import load_dataset; load_dataset('csv', data_files={'train': 's3://noaa-gsod-pds/2024/A5125600451.csv'})" ```	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6862/reactions", "total_count": 1, "+1": 1, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6862/timeline	null	null	true
https://api.github.com/repos/huggingface/datasets/issues/6861	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6861/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6861/comments	https://api.github.com/repos/huggingface/datasets/issues/6861/events	https://github.com/huggingface/datasets/pull/6861	2,275,988,990	PR_kwDODunzps5uYkMy	6,861	Fix CI by temporarily pinning huggingface-hub < 0.23.0	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	null	[]	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6861). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005029 / 0.011353 (-0.006324) \| 0.003217 / 0.011008 (-0.007791) \| 0.062747 / 0.038508 (0.024239) \| 0.030086 / 0.023109 (0.006976) \| 0.251548 / 0.275898 (-0.024350) \| 0.273215 / 0.323480 (-0.050265) \| 0.003197 / 0.007986 (-0.004789) \| 0.002706 / 0.004328 (-0.001623) \| 0.049013 / 0.004250 (0.044763) \| 0.044160 / 0.037052 (0.007107) \| 0.266556 / 0.258489 (0.008067) \| 0.291854 / 0.293841 (-0.001987) \| 0.027463 / 0.128546 (-0.101083) \| 0.010331 / 0.075646 (-0.065315) \| 0.207195 / 0.419271 (-0.212077) \| 0.035416 / 0.043533 (-0.008116) \| 0.253180 / 0.255139 (-0.001959) \| 0.274663 / 0.283200 (-0.008536) \| 0.019132 / 0.141683 (-0.122551) \| 1.174875 / 1.452155 (-0.277279) \| 1.166828 / 1.492716 (-0.325888) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.092240 / 0.018006 (0.074234) \| 0.299385 / 0.000490 (0.298895) \| 0.000222 / 0.000200 (0.000022) \| 0.000050 / 0.000054 (-0.000004) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.017994 / 0.037411 (-0.019417) \| 0.066868 / 0.014526 (0.052342) \| 0.074616 / 0.176557 (-0.101941) \| 0.120632 / 0.737135 (-0.616503) \| 0.074595 / 0.296338 (-0.221743) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.279008 / 0.215209 (0.063798) \| 2.777927 / 2.077655 (0.700273) \| 1.529495 / 1.504120 (0.025376) \| 1.391528 / 1.541195 (-0.149666) \| 1.420149 / 1.468490 (-0.048341) \| 0.567526 / 4.584777 (-4.017251) \| 2.400467 / 3.745712 (-1.345245) \| 2.735778 / 5.269862 (-2.534083) \| 1.718224 / 4.565676 (-2.847452) \| 0.063009 / 0.424275 (-0.361266) \| 0.005339 / 0.007607 (-0.002268) \| 0.340130 / 0.226044 (0.114086) \| 3.352796 / 2.268929 (1.083868) \| 1.887427 / 55.444624 (-53.557198) \| 1.598804 / 6.876477 (-5.277672) \| 1.601566 / 2.142072 (-0.540506) \| 0.640684 / 4.805227 (-4.164543) \| 0.116694 / 6.500664 (-6.383970) \| 0.041206 / 0.075469 (-0.034263) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.969163 / 1.841788 (-0.872625) \| 11.475685 / 8.074308 (3.401377) \| 9.397987 / 10.191392 (-0.793405) \| 0.140131 / 0.680424 (-0.540293) \| 0.014544 / 0.534201 (-0.519657) \| 0.288122 / 0.579283 (-0.291161) \| 0.262631 / 0.434364 (-0.171733) \| 0.323565 / 0.540337 (-0.216773) \| 0.421775 / 1.386936 (-0.965161) \|\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005059 / 0.011353 (-0.006294) \| 0.003185 / 0.011008 (-0.007824) \| 0.050132 / 0.038508 (0.011624) \| 0.030872 / 0.023109 (0.007763) \| 0.257822 / 0.275898 (-0.018076) \| 0.281645 / 0.323480 (-0.041835) \| 0.004129 / 0.007986 (-0.003857) \| 0.002703 / 0.004328 (-0.001625) \| 0.049695 / 0.004250 (0.045445) \| 0.040452 / 0.037052 (0.003400) \| 0.278701 / 0.258489 (0.020212) \| 0.297726 / 0.293841 (0.003885) \| 0.028829 / 0.128546 (-0.099717) \| 0.010011 / 0.075646 (-0.065636) \| 0.058569 / 0.419271 (-0.360703) \| 0.032564 / 0.043533 (-0.010969) \| 0.259944 / 0.255139 (0.004805) \| 0.279954 / 0.283200 (-0.003245) \| 0.017804 / 0.141683 (-0.123879) \| 1.147748 / 1.452155 (-0.304406) \| 1.188390 / 1.492716 (-0.304327) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.091252 / 0.018006 (0.073246) \| 0.308462 / 0.000490 (0.307972) \| 0.000217 / 0.000200 (0.000017) \| 0.000088 / 0.000054 (0.000033) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.022216 / 0.037411 (-0.015195) \| 0.075547 / 0.014526 (0.061021) \| 0.086085 / 0.176557 (-0.090471) \| 0.128326 / 0.737135 (-0.608809) \| 0.087253 / 0.296338 (-0.209085) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.301886 / 0.215209 (0.086677) \| 2.940181 / 2.077655 (0.862527) \| 1.663247 / 1.504120 (0.159127) \| 1.545711 / 1.541195 (0.004517) \| 1.542904 / 1.468490 (0.074414) \| 0.556951 / 4.584777 (-4.027826) \| 0.941925 / 3.745712 (-2.803788) \| 2.740733 / 5.269862 (-2.529128) \| 1.722801 / 4.565676 (-2.842875) \| 0.060156 / 0.424275 (-0.364120) \| 0.005008 / 0.007607 (-0.002599) \| 0.348988 / 0.226044 (0.122944) \| 3.454972 / 2.268929 (1.186044) \| 2.015828 / 55.444624 (-53.428796) \| 1.737828 / 6.876477 (-5.138649) \| 1.747451 / 2.142072 (-0.394622) \| 0.626865 / 4.805227 (-4.178362) \| 0.114565 / 6.500664 (-6.386099) \| 0.040562 / 0.075469 (-0.034907) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.997070 / 1.841788 (-0.844718) \| 11.748577 / 8.074308 (3.674269) \| 9.591721 / 10.191392 (-0.599671) \| 0.131613 / 0.680424 (-0.548811) \| 0.016560 / 0.534201 (-0.517641) \| 0.288938 / 0.579283 (-0.290345) \| 0.122196 / 0.434364 (-0.312168) \| 0.380217 / 0.540337 (-0.160121) \| 0.429886 / 1.386936 (-0.957050) \|\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#7ae4314c34dae6a5339c11f7d1a2cbdfb76144d7 \"CML watermark\")\n" ]	2024-05-02T16:40:04	2024-05-02T16:59:42	2024-05-02T16:53:42	MEMBER	null	false	{ "url": "https://api.github.com/repos/huggingface/datasets/pulls/6861", "html_url": "https://github.com/huggingface/datasets/pull/6861", "diff_url": "https://github.com/huggingface/datasets/pull/6861.diff", "patch_url": "https://github.com/huggingface/datasets/pull/6861.patch", "merged_at": "2024-05-02T16:53:42" }	As a hotfix for CI, temporarily pin `huggingface-hub` upper version Fix #6860. Revert once root cause is fixed, see: - https://github.com/huggingface/transformers/issues/30618	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6861/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6861/timeline	null	null	true
https://api.github.com/repos/huggingface/datasets/issues/6860	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6860/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6860/comments	https://api.github.com/repos/huggingface/datasets/issues/6860/events	https://github.com/huggingface/datasets/issues/6860	2,275,537,137	I_kwDODunzps6HofDx	6,860	CI fails after huggingface_hub-0.23.0 release: FutureWarning: "resume_download"	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[ { "id": 1935892857, "node_id": "MDU6TGFiZWwxOTM1ODkyODU3", "url": "https://api.github.com/repos/huggingface/datasets/labels/bug", "name": "bug", "color": "d73a4a", "default": true, "description": "Something isn't working" } ]	closed	false	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[ { "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false } ]	null	[ "I think this needs to be fixed on transformers.\r\n\r\nCC: @Wauplin ", "See:\r\n- https://github.com/huggingface/transformers/issues/30618", "Opened https://github.com/huggingface/transformers/pull/30620" ]	2024-05-02T13:24:17	2024-05-02T16:53:45	2024-05-02T16:53:45	MEMBER	null	null	null	CI fails after latest huggingface_hub-0.23.0 release: https://github.com/huggingface/huggingface_hub/releases/tag/v0.23.0 ``` FAILED tests/test_metric_common.py::LocalMetricTest::test_load_metric_bertscore - FutureWarning: `resume_download` is deprecated and will be removed in version 1.0.0. Downloads always resume when possible. If you want to force a new download, use `force_download=True`. FAILED tests/test_metric_common.py::LocalMetricTest::test_load_metric_frugalscore - FutureWarning: `resume_download` is deprecated and will be removed in version 1.0.0. Downloads always resume when possible. If you want to force a new download, use `force_download=True`. FAILED tests/test_metric_common.py::LocalMetricTest::test_load_metric_perplexity - FutureWarning: `resume_download` is deprecated and will be removed in version 1.0.0. Downloads always resume when possible. If you want to force a new download, use `force_download=True`. FAILED tests/test_fingerprint.py::TokenizersHashTest::test_hash_tokenizer - FutureWarning: `resume_download` is deprecated and will be removed in version 1.0.0. Downloads always resume when possible. If you want to force a new download, use `force_download=True`. FAILED tests/test_fingerprint.py::TokenizersHashTest::test_hash_tokenizer_with_cache - FutureWarning: `resume_download` is deprecated and will be removed in version 1.0.0. Downloads always resume when possible. If you want to force a new download, use `force_download=True`. FAILED tests/test_arrow_dataset.py::MiscellaneousDatasetTest::test_set_format_encode - FutureWarning: `resume_download` is deprecated and will be removed in version 1.0.0. Downloads always resume when possible. If you want to force a new download, use `force_download=True`. ```	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6860/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6860/timeline	null	completed	false
https://api.github.com/repos/huggingface/datasets/issues/6859	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6859/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6859/comments	https://api.github.com/repos/huggingface/datasets/issues/6859/events	https://github.com/huggingface/datasets/pull/6859	2,274,996,774	PR_kwDODunzps5uVIoZ	6,859	Support folder-based datasets with large metadata.jsonl	{ "login": "gbenson", "id": 580564, "node_id": "MDQ6VXNlcjU4MDU2NA==", "avatar_url": "https://avatars.githubusercontent.com/u/580564?v=4", "gravatar_id": "", "url": "https://api.github.com/users/gbenson", "html_url": "https://github.com/gbenson", "followers_url": "https://api.github.com/users/gbenson/followers", "following_url": "https://api.github.com/users/gbenson/following{/other_user}", "gists_url": "https://api.github.com/users/gbenson/gists{/gist_id}", "starred_url": "https://api.github.com/users/gbenson/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/gbenson/subscriptions", "organizations_url": "https://api.github.com/users/gbenson/orgs", "repos_url": "https://api.github.com/users/gbenson/repos", "events_url": "https://api.github.com/users/gbenson/events{/privacy}", "received_events_url": "https://api.github.com/users/gbenson/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	open	false	null	[]	null	[]	2024-05-02T09:07:26	2024-05-02T09:07:26	null	NONE	null	false	{ "url": "https://api.github.com/repos/huggingface/datasets/pulls/6859", "html_url": "https://github.com/huggingface/datasets/pull/6859", "diff_url": "https://github.com/huggingface/datasets/pull/6859.diff", "patch_url": "https://github.com/huggingface/datasets/pull/6859.patch", "merged_at": null }	I tried creating an `imagefolder` dataset with a 714MB `metadata.jsonl` but got the error below. This pull request fixes the problem by increasing the block size like the message suggests. ``` >>> from datasets import load_dataset >>> dataset = load_dataset("imagefolder", data_dir="data-for-upload") Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/path/to/datasets/load.py", line 2609, in load_dataset builder_instance.download_and_prepare( ... File "/path/to/datasets/packaged_modules/folder_based_builder/folder_based_builder.py", line 245, in _read_metadata return paj.read_json(f) File "pyarrow/_json.pyx", line 308, in pyarrow._json.read_json File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status pyarrow.lib.ArrowInvalid: straddling object straddles two block boundaries (try to increase block size?) ```	null	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6859/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6859/timeline	null	null	true
https://api.github.com/repos/huggingface/datasets/issues/6858	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6858/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6858/comments	https://api.github.com/repos/huggingface/datasets/issues/6858/events	https://github.com/huggingface/datasets/issues/6858	2,274,917,185	I_kwDODunzps6HmHtB	6,858	Segmentation fault	{ "login": "scampion", "id": 554155, "node_id": "MDQ6VXNlcjU1NDE1NQ==", "avatar_url": "https://avatars.githubusercontent.com/u/554155?v=4", "gravatar_id": "", "url": "https://api.github.com/users/scampion", "html_url": "https://github.com/scampion", "followers_url": "https://api.github.com/users/scampion/followers", "following_url": "https://api.github.com/users/scampion/following{/other_user}", "gists_url": "https://api.github.com/users/scampion/gists{/gist_id}", "starred_url": "https://api.github.com/users/scampion/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/scampion/subscriptions", "organizations_url": "https://api.github.com/users/scampion/orgs", "repos_url": "https://api.github.com/users/scampion/repos", "events_url": "https://api.github.com/users/scampion/events{/privacy}", "received_events_url": "https://api.github.com/users/scampion/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	null	[]	null	[ "I downloaded the jsonl file and extract it manually. \r\nThe issue seems to be related to pyarrow.json \r\n\r\n\r\n\r\npython3 -q -X faulthandler -c \"from datasets import load_dataset; load_dataset('json', data_files='/Users/scampion/Downloads/1998-09.jsonl')\"\r\nGenerating train split: 0 examples [00:00, ? examples/s]Fatal Python error: Segmentation fault\r\n\r\nThread 0x00007000000c1000 (most recent call first):\r\n <no Python frame>\r\n\r\nThread 0x00007000024df000 (most recent call first):\r\n File \"/usr/local/Cellar/python@3.11/3.11.7/Frameworks/Python.framework/Versions/3.11/lib/python3.11/threading.py\", line 331 in wait\r\n File \"/usr/local/Cellar/python@3.11/3.11.7/Frameworks/Python.framework/Versions/3.11/lib/python3.11/threading.py\", line 629 in wait\r\n File \"/Users/scampion/src/test/venv_test/lib/python3.11/site-packages/tqdm/_monitor.py\", line 60 in run\r\n File \"/usr/local/Cellar/python@3.11/3.11.7/Frameworks/Python.framework/Versions/3.11/lib/python3.11/threading.py\", line 1045 in _bootstrap_inner\r\n File \"/usr/local/Cellar/python@3.11/3.11.7/Frameworks/Python.framework/Versions/3.11/lib/python3.11/threading.py\", line 1002 in _bootstrap\r\n\r\nThread 0x00007ff845c66640 (most recent call first):\r\n File \"/Users/scampion/src/test/venv_test/lib/python3.11/site-packages/datasets/packaged_modules/json/json.py\", line 122 in _generate_tables\r\n File \"/Users/scampion/src/test/venv_test/lib/python3.11/site-packages/datasets/builder.py\", line 1995 in _prepare_split_single\r\n File \"/Users/scampion/src/test/venv_test/lib/python3.11/site-packages/datasets/builder.py\", line 1882 in _prepare_split\r\n File \"/Users/scampion/src/test/venv_test/lib/python3.11/site-packages/datasets/builder.py\", line 1122 in _download_and_prepare\r\n File \"/Users/scampion/src/test/venv_test/lib/python3.11/site-packages/datasets/builder.py\", line 1027 in download_and_prepare\r\n File \"/Users/scampion/src/test/venv_test/lib/python3.11/site-packages/datasets/load.py\", line 2609 in load_dataset\r\n File \"<string>\", line 1 in <module>\r\n\r\nExtension modules: numpy.core._multiarray_umath, numpy.core._multiarray_tests, numpy.linalg._umath_linalg, numpy.fft._pocketfft_internal, numpy.random._common, numpy.random.bit_generator, numpy.random._bounded_integers, numpy.random._mt19937, numpy.random.mtrand, numpy.random._philox, numpy.random._pcg64, numpy.random._sfc64, numpy.random._generator, pyarrow.lib, pyarrow._hdfsio, pandas._libs.tslibs.ccalendar, pandas._libs.tslibs.np_datetime, pandas._libs.tslibs.dtypes, pandas._libs.tslibs.base, pandas._libs.tslibs.nattype, pandas._libs.tslibs.timezones, pandas._libs.tslibs.fields, pandas._libs.tslibs.timedeltas, pandas._libs.tslibs.tzconversion, pandas._libs.tslibs.timestamps, pandas._libs.properties, pandas._libs.tslibs.offsets, pandas._libs.tslibs.strptime, pandas._libs.tslibs.parsing, pandas._libs.tslibs.conversion, pandas._libs.tslibs.period, pandas._libs.tslibs.vectorized, pandas._libs.ops_dispatch, pandas._libs.missing, pandas._libs.hashtable, pandas._libs.algos, pandas._libs.interval, pandas._libs.lib, pyarrow._compute, pandas._libs.ops, pandas._libs.hashing, pandas._libs.arrays, pandas._libs.tslib, pandas._libs.sparse, pandas._libs.internals, pandas._libs.indexing, pandas._libs.index, pandas._libs.writers, pandas._libs.join, pandas._libs.window.aggregations, pandas._libs.window.indexers, pandas._libs.reshape, pandas._libs.groupby, pandas._libs.json, pandas._libs.parsers, pandas._libs.testing, charset_normalizer.md, yaml._yaml, pyarrow._parquet, pyarrow._fs, pyarrow._hdfs, pyarrow._gcsfs, pyarrow._s3fs, multidict._multidict, yarl._quoting_c, aiohttp._helpers, aiohttp._http_writer, aiohttp._http_parser, aiohttp._websocket, frozenlist._frozenlist, xxhash._xxhash, pyarrow._json (total: 72)\r\n[1] 56678 segmentation fault python3 -q -X faulthandler -c\r\n/usr/local/Cellar/python@3.11/3.11.7/Frameworks/Python.framework/Versions/3.11/lib/python3.11/multiprocessing/resource_tracker.py:254: UserWarning: resource_tracker: There appear to be 1 leaked semaphore objects to clean up at shutdown\r\n warnings.warn('resource_tracker: There appear to be %d '\r\n(venv_test)", "The error comes from data where one line contains \"null\"" ]	2024-05-02T08:28:49	2024-05-03T08:43:21	2024-05-03T08:42:36	NONE	null	null	null	### Describe the bug Using various version for datasets, I'm no more longer able to load that dataset without a segmentation fault. Several others files are also concerned. ### Steps to reproduce the bug # Create a new venv python3 -m venv venv_test source venv_test/bin/activate # Install the latest version pip install datasets # Load that dataset python3 -q -X faulthandler -c "from datasets import load_dataset; load_dataset('EuropeanParliament/Eurovoc', '1998-09')" ### Expected behavior Data must be loaded ### Environment info datasets==2.19.0 Python 3.11.7 Darwin 22.5.0 Darwin Kernel Version 22.5.0: Mon Apr 24 20:51:50 PDT 2023; root:xnu-8796.121.2~5/RELEASE_X86_64 x86_64	{ "login": "scampion", "id": 554155, "node_id": "MDQ6VXNlcjU1NDE1NQ==", "avatar_url": "https://avatars.githubusercontent.com/u/554155?v=4", "gravatar_id": "", "url": "https://api.github.com/users/scampion", "html_url": "https://github.com/scampion", "followers_url": "https://api.github.com/users/scampion/followers", "following_url": "https://api.github.com/users/scampion/following{/other_user}", "gists_url": "https://api.github.com/users/scampion/gists{/gist_id}", "starred_url": "https://api.github.com/users/scampion/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/scampion/subscriptions", "organizations_url": "https://api.github.com/users/scampion/orgs", "repos_url": "https://api.github.com/users/scampion/repos", "events_url": "https://api.github.com/users/scampion/events{/privacy}", "received_events_url": "https://api.github.com/users/scampion/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6858/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6858/timeline	null	completed	false
https://api.github.com/repos/huggingface/datasets/issues/6857	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6857/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6857/comments	https://api.github.com/repos/huggingface/datasets/issues/6857/events	https://github.com/huggingface/datasets/pull/6857	2,274,849,730	PR_kwDODunzps5uUooF	6,857	Fix line-endings in tests on Windows	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	null	[]	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6857). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005050 / 0.011353 (-0.006303) \| 0.003400 / 0.011008 (-0.007609) \| 0.063488 / 0.038508 (0.024980) \| 0.029112 / 0.023109 (0.006002) \| 0.245872 / 0.275898 (-0.030026) \| 0.270682 / 0.323480 (-0.052798) \| 0.003145 / 0.007986 (-0.004841) \| 0.002671 / 0.004328 (-0.001658) \| 0.048862 / 0.004250 (0.044612) \| 0.044330 / 0.037052 (0.007278) \| 0.269066 / 0.258489 (0.010577) \| 0.294806 / 0.293841 (0.000965) \| 0.027717 / 0.128546 (-0.100829) \| 0.010189 / 0.075646 (-0.065458) \| 0.206853 / 0.419271 (-0.212419) \| 0.035655 / 0.043533 (-0.007877) \| 0.254554 / 0.255139 (-0.000585) \| 0.275104 / 0.283200 (-0.008095) \| 0.018786 / 0.141683 (-0.122897) \| 1.147165 / 1.452155 (-0.304989) \| 1.202755 / 1.492716 (-0.289961) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.094693 / 0.018006 (0.076687) \| 0.303049 / 0.000490 (0.302559) \| 0.000217 / 0.000200 (0.000017) \| 0.000045 / 0.000054 (-0.000010) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.018375 / 0.037411 (-0.019036) \| 0.061080 / 0.014526 (0.046554) \| 0.082140 / 0.176557 (-0.094416) \| 0.119962 / 0.737135 (-0.617173) \| 0.074596 / 0.296338 (-0.221743) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.278483 / 0.215209 (0.063274) \| 2.757734 / 2.077655 (0.680079) \| 1.431875 / 1.504120 (-0.072245) \| 1.320315 / 1.541195 (-0.220879) \| 1.319433 / 1.468490 (-0.149058) \| 0.566134 / 4.584777 (-4.018643) \| 2.407416 / 3.745712 (-1.338296) \| 2.765087 / 5.269862 (-2.504775) \| 1.727335 / 4.565676 (-2.838341) \| 0.065267 / 0.424275 (-0.359008) \| 0.005466 / 0.007607 (-0.002141) \| 0.336667 / 0.226044 (0.110622) \| 3.311721 / 2.268929 (1.042792) \| 1.768960 / 55.444624 (-53.675664) \| 1.510854 / 6.876477 (-5.365623) \| 1.499345 / 2.142072 (-0.642728) \| 0.649205 / 4.805227 (-4.156022) \| 0.118920 / 6.500664 (-6.381744) \| 0.041570 / 0.075469 (-0.033899) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.976127 / 1.841788 (-0.865660) \| 11.646120 / 8.074308 (3.571812) \| 9.710204 / 10.191392 (-0.481188) \| 0.129081 / 0.680424 (-0.551342) \| 0.013874 / 0.534201 (-0.520327) \| 0.287044 / 0.579283 (-0.292239) \| 0.268684 / 0.434364 (-0.165680) \| 0.328465 / 0.540337 (-0.211872) \| 0.420433 / 1.386936 (-0.966503) \|\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005380 / 0.011353 (-0.005973) \| 0.003582 / 0.011008 (-0.007427) \| 0.049539 / 0.038508 (0.011031) \| 0.032363 / 0.023109 (0.009253) \| 0.277697 / 0.275898 (0.001799) \| 0.303861 / 0.323480 (-0.019618) \| 0.004226 / 0.007986 (-0.003759) \| 0.002749 / 0.004328 (-0.001579) \| 0.049404 / 0.004250 (0.045153) \| 0.040602 / 0.037052 (0.003550) \| 0.292995 / 0.258489 (0.034506) \| 0.317958 / 0.293841 (0.024117) \| 0.030052 / 0.128546 (-0.098494) \| 0.010179 / 0.075646 (-0.065467) \| 0.058600 / 0.419271 (-0.360672) \| 0.033202 / 0.043533 (-0.010331) \| 0.282474 / 0.255139 (0.027335) \| 0.299330 / 0.283200 (0.016130) \| 0.017612 / 0.141683 (-0.124071) \| 1.160199 / 1.452155 (-0.291955) \| 1.193248 / 1.492716 (-0.299468) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.093450 / 0.018006 (0.075443) \| 0.311391 / 0.000490 (0.310901) \| 0.000208 / 0.000200 (0.000008) \| 0.000051 / 0.000054 (-0.000003) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.022045 / 0.037411 (-0.015366) \| 0.075238 / 0.014526 (0.060712) \| 0.086648 / 0.176557 (-0.089908) \| 0.128595 / 0.737135 (-0.608540) \| 0.088785 / 0.296338 (-0.207553) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.283928 / 0.215209 (0.068719) \| 2.780663 / 2.077655 (0.703008) \| 1.517870 / 1.504120 (0.013751) \| 1.402606 / 1.541195 (-0.138588) \| 1.408382 / 1.468490 (-0.060108) \| 0.579216 / 4.584777 (-4.005560) \| 0.979349 / 3.745712 (-2.766363) \| 2.847551 / 5.269862 (-2.422311) \| 1.774713 / 4.565676 (-2.790963) \| 0.064635 / 0.424275 (-0.359640) \| 0.005038 / 0.007607 (-0.002569) \| 0.341763 / 0.226044 (0.115719) \| 3.351240 / 2.268929 (1.082311) \| 1.871082 / 55.444624 (-53.573542) \| 1.592683 / 6.876477 (-5.283794) \| 1.619814 / 2.142072 (-0.522259) \| 0.661628 / 4.805227 (-4.143599) \| 0.118287 / 6.500664 (-6.382377) \| 0.041289 / 0.075469 (-0.034180) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 1.010075 / 1.841788 (-0.831712) \| 11.949132 / 8.074308 (3.874824) \| 10.004906 / 10.191392 (-0.186486) \| 0.138622 / 0.680424 (-0.541802) \| 0.015134 / 0.534201 (-0.519067) \| 0.286300 / 0.579283 (-0.292984) \| 0.125163 / 0.434364 (-0.309201) \| 0.378641 / 0.540337 (-0.161696) \| 0.422805 / 1.386936 (-0.964131) \|\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#282379fbd58df2b5065b70330750688acb4eb461 \"CML watermark\")\n" ]	2024-05-02T07:49:15	2024-05-02T11:49:35	2024-05-02T11:43:00	MEMBER	null	false	{ "url": "https://api.github.com/repos/huggingface/datasets/pulls/6857", "html_url": "https://github.com/huggingface/datasets/pull/6857", "diff_url": "https://github.com/huggingface/datasets/pull/6857.diff", "patch_url": "https://github.com/huggingface/datasets/pull/6857.patch", "merged_at": "2024-05-02T11:43:00" }	EDIT: ~~Fix test_delete_from_hub on Windows by passing explicit encoding.~~ Fix test_delete_from_hub and test_xgetsize_private by uploading the README file content directly (encoding the string), instead of writing a local file and uploading it. Note that local files created on Windows will have "\r\n" line endings, instead of "\n". These are no longer transformed to "\n" by the Hub. Fix #6856.	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6857/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6857/timeline	null	null	true
https://api.github.com/repos/huggingface/datasets/issues/6856	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6856/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6856/comments	https://api.github.com/repos/huggingface/datasets/issues/6856/events	https://github.com/huggingface/datasets/issues/6856	2,274,828,933	I_kwDODunzps6HlyKF	6,856	CI fails on Windows for test_delete_from_hub and test_xgetsize_private due to new-line character	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[ { "id": 1935892857, "node_id": "MDU6TGFiZWwxOTM1ODkyODU3", "url": "https://api.github.com/repos/huggingface/datasets/labels/bug", "name": "bug", "color": "d73a4a", "default": true, "description": "Something isn't working" } ]	closed	false	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[ { "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false } ]	null	[ "After investigation, I have found that when a local file is uploaded to the Hub, the new line character is no longer transformed to \"\\n\": on Windows machine now it is kept as \"\\r\\n\".\r\n\r\nAny idea why this changed?\r\nCC: @lhoestq " ]	2024-05-02T07:37:03	2024-05-02T11:43:01	2024-05-02T11:43:01	MEMBER	null	null	null	CI fails on Windows for test_delete_from_hub after the merge of: - #6820 This is weird because the CI was green in the PR branch before merging to main. ``` FAILED tests/test_hub.py::test_delete_from_hub - AssertionError: assert [CommitOperat...\r\n---\r\n')] == [CommitOperat...in/\n---\n')] At index 1 diff: CommitOperationAdd(path_in_repo='README.md', path_or_fileobj=b'---\r\nconfigs:\r\n- config_name: cats\r\n data_files:\r\n - split: train\r\n path: cats/train/\r\n---\r\n') != CommitOperationAdd(path_in_repo='README.md', path_or_fileobj=b'---\nconfigs:\n- config_name: cats\n data_files:\n - split: train\n path: cats/train/\n---\n') Full diff: [ CommitOperationDelete( path_in_repo='dogs/train/0000.csv', is_folder=False, ), CommitOperationAdd( path_in_repo='README.md', - path_or_fileobj=b'---\nconfigs:\n- config_name: cats\n data_files:\n ' ? -------- + path_or_fileobj=b'---\r\nconfigs:\r\n- config_name: cats\r\n data_f' ? ++ ++ ++ - b' - split: train\n path: cats/train/\n---\n', ? ^^^^^^ - + b'iles:\r\n - split: train\r\n path: cats/train/*\r' ? ++++++++++ ++ ^ + b'\n---\r\n', ), ] ```	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6856/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6856/timeline	null	completed	false
https://api.github.com/repos/huggingface/datasets/issues/6855	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6855/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6855/comments	https://api.github.com/repos/huggingface/datasets/issues/6855/events	https://github.com/huggingface/datasets/pull/6855	2,274,777,812	PR_kwDODunzps5uUZNT	6,855	Fix dataset name for community Hub script-datasets	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	null	[]	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6855). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "The CI errors were unrelated. I am merging main once they were fixed:\r\n- #6857", "The new CI tests failing are also unrelated to this PR.\r\n\r\nThey are caused the the release of huggingface_hub-0.23.0, which now raises a FutureWarning for resume_download. See:\r\n- #6860", "I have merged main once the CI was fixed:\r\n- #6861", "This PR is ready for review @huggingface/datasets.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005015 / 0.011353 (-0.006338) \| 0.003576 / 0.011008 (-0.007432) \| 0.063797 / 0.038508 (0.025289) \| 0.030198 / 0.023109 (0.007089) \| 0.237408 / 0.275898 (-0.038490) \| 0.266534 / 0.323480 (-0.056946) \| 0.003133 / 0.007986 (-0.004852) \| 0.002639 / 0.004328 (-0.001689) \| 0.049051 / 0.004250 (0.044801) \| 0.044650 / 0.037052 (0.007597) \| 0.253239 / 0.258489 (-0.005250) \| 0.288301 / 0.293841 (-0.005540) \| 0.027459 / 0.128546 (-0.101087) \| 0.010457 / 0.075646 (-0.065189) \| 0.207209 / 0.419271 (-0.212063) \| 0.035537 / 0.043533 (-0.007996) \| 0.240914 / 0.255139 (-0.014225) \| 0.266817 / 0.283200 (-0.016383) \| 0.019133 / 0.141683 (-0.122550) \| 1.113268 / 1.452155 (-0.338887) \| 1.183576 / 1.492716 (-0.309140) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.091218 / 0.018006 (0.073212) \| 0.301690 / 0.000490 (0.301200) \| 0.000234 / 0.000200 (0.000034) \| 0.000043 / 0.000054 (-0.000011) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.018489 / 0.037411 (-0.018922) \| 0.061379 / 0.014526 (0.046853) \| 0.072854 / 0.176557 (-0.103703) \| 0.120470 / 0.737135 (-0.616665) \| 0.074206 / 0.296338 (-0.222133) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.281725 / 0.215209 (0.066516) \| 2.805469 / 2.077655 (0.727814) \| 1.478755 / 1.504120 (-0.025365) \| 1.361718 / 1.541195 (-0.179477) \| 1.381460 / 1.468490 (-0.087030) \| 0.570758 / 4.584777 (-4.014019) \| 2.434707 / 3.745712 (-1.311005) \| 2.853322 / 5.269862 (-2.416539) \| 1.785684 / 4.565676 (-2.779992) \| 0.063551 / 0.424275 (-0.360724) \| 0.005322 / 0.007607 (-0.002285) \| 0.330938 / 0.226044 (0.104894) \| 3.247414 / 2.268929 (0.978486) \| 1.821401 / 55.444624 (-53.623223) \| 1.554258 / 6.876477 (-5.322219) \| 1.589263 / 2.142072 (-0.552809) \| 0.651232 / 4.805227 (-4.153995) \| 0.117903 / 6.500664 (-6.382761) \| 0.041948 / 0.075469 (-0.033522) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 1.000386 / 1.841788 (-0.841402) \| 11.645406 / 8.074308 (3.571098) \| 9.567803 / 10.191392 (-0.623589) \| 0.142869 / 0.680424 (-0.537555) \| 0.014250 / 0.534201 (-0.519951) \| 0.287054 / 0.579283 (-0.292229) \| 0.268849 / 0.434364 (-0.165515) \| 0.323307 / 0.540337 (-0.217031) \| 0.418965 / 1.386936 (-0.967971) \|\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005216 / 0.011353 (-0.006137) \| 0.003714 / 0.011008 (-0.007294) \| 0.049544 / 0.038508 (0.011036) \| 0.030897 / 0.023109 (0.007788) \| 0.262478 / 0.275898 (-0.013420) \| 0.289693 / 0.323480 (-0.033787) \| 0.004226 / 0.007986 (-0.003760) \| 0.002811 / 0.004328 (-0.001518) \| 0.048256 / 0.004250 (0.044006) \| 0.040974 / 0.037052 (0.003922) \| 0.279431 / 0.258489 (0.020942) \| 0.306538 / 0.293841 (0.012697) \| 0.029493 / 0.128546 (-0.099054) \| 0.010550 / 0.075646 (-0.065097) \| 0.057826 / 0.419271 (-0.361445) \| 0.033045 / 0.043533 (-0.010488) \| 0.264820 / 0.255139 (0.009681) \| 0.282362 / 0.283200 (-0.000838) \| 0.018387 / 0.141683 (-0.123296) \| 1.167956 / 1.452155 (-0.284199) \| 1.247261 / 1.492716 (-0.245455) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.091962 / 0.018006 (0.073956) \| 0.300725 / 0.000490 (0.300236) \| 0.000209 / 0.000200 (0.000009) \| 0.000044 / 0.000054 (-0.000011) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.021835 / 0.037411 (-0.015576) \| 0.076954 / 0.014526 (0.062428) \| 0.087224 / 0.176557 (-0.089332) \| 0.127529 / 0.737135 (-0.609606) \| 0.089651 / 0.296338 (-0.206688) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.290878 / 0.215209 (0.075669) \| 2.845647 / 2.077655 (0.767992) \| 1.550515 / 1.504120 (0.046395) \| 1.422251 / 1.541195 (-0.118944) \| 1.425366 / 1.468490 (-0.043124) \| 0.559228 / 4.584777 (-4.025549) \| 0.970661 / 3.745712 (-2.775051) \| 2.755494 / 5.269862 (-2.514367) \| 1.724285 / 4.565676 (-2.841391) \| 0.062981 / 0.424275 (-0.361294) \| 0.006644 / 0.007607 (-0.000963) \| 0.344315 / 0.226044 (0.118270) \| 3.383452 / 2.268929 (1.114524) \| 1.914809 / 55.444624 (-53.529815) \| 1.626189 / 6.876477 (-5.250288) \| 1.614631 / 2.142072 (-0.527441) \| 0.636415 / 4.805227 (-4.168812) \| 0.115318 / 6.500664 (-6.385346) \| 0.040337 / 0.075469 (-0.035132) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 1.006257 / 1.841788 (-0.835531) \| 12.152942 / 8.074308 (4.078634) \| 9.744413 / 10.191392 (-0.446979) \| 0.139431 / 0.680424 (-0.540993) \| 0.015601 / 0.534201 (-0.518600) \| 0.287069 / 0.579283 (-0.292214) \| 0.125020 / 0.434364 (-0.309344) \| 0.380366 / 0.540337 (-0.159971) \| 0.423486 / 1.386936 (-0.963450) \|\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#1bf8a46cc7b096d5c547ea3794f6a4b6c31ea762 \"CML watermark\")\n" ]	2024-05-02T07:05:44	2024-05-03T15:58:00	2024-05-03T15:51:57	MEMBER	null	false	{ "url": "https://api.github.com/repos/huggingface/datasets/pulls/6855", "html_url": "https://github.com/huggingface/datasets/pull/6855", "diff_url": "https://github.com/huggingface/datasets/pull/6855.diff", "patch_url": "https://github.com/huggingface/datasets/pull/6855.patch", "merged_at": "2024-05-03T15:51:57" }	Fix dataset name for community Hub script-datasets by passing explicit dataset_name to HubDatasetModuleFactoryWithScript. Fix #6854. CC: @Wauplin	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6855/reactions", "total_count": 1, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 1, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6855/timeline	null	null	true
https://api.github.com/repos/huggingface/datasets/issues/6854	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6854/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6854/comments	https://api.github.com/repos/huggingface/datasets/issues/6854/events	https://github.com/huggingface/datasets/issues/6854	2,274,767,686	I_kwDODunzps6HljNG	6,854	Wrong example of usage when config name is missing for community script-datasets	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[ { "id": 1935892857, "node_id": "MDU6TGFiZWwxOTM1ODkyODU3", "url": "https://api.github.com/repos/huggingface/datasets/labels/bug", "name": "bug", "color": "d73a4a", "default": true, "description": "Something isn't working" } ]	closed	false	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[ { "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false } ]	null	[]	2024-05-02T06:59:39	2024-05-03T15:51:59	2024-05-03T15:51:58	MEMBER	null	null	null	As reported by @Wauplin, when loading a community dataset with script, there is a bug in the example of usage of the error message if the dataset has multiple configs (and no default config) and the user does not pass any config. For example: ```python >>> ds = load_dataset("google/fleurs") ValueError: Config name is missing. Please pick one among the available configs: ['af_za', 'am_et', 'ar_eg', 'as_in', 'ast_es', 'az_az', 'be_by', 'bg_bg', 'bn_in', 'bs_ba', 'ca_es', 'ceb_ph', 'ckb_iq', 'cmn_hans_cn', 'cs_cz', 'cy_gb', 'da_dk', 'de_de', 'el_gr', 'en_us', 'es_419', 'et_ee', 'fa_ir', 'ff_sn', 'fi_fi', 'fil_ph', 'fr_fr', 'ga_ie', 'gl_es', 'gu_in', 'ha_ng', 'he_il', 'hi_in', 'hr_hr', 'hu_hu', 'hy_am', 'id_id', 'ig_ng', 'is_is', 'it_it', 'ja_jp', 'jv_id', 'ka_ge', 'kam_ke', 'kea_cv', 'kk_kz', 'km_kh', 'kn_in', 'ko_kr', 'ky_kg', 'lb_lu', 'lg_ug', 'ln_cd', 'lo_la', 'lt_lt', 'luo_ke', 'lv_lv', 'mi_nz', 'mk_mk', 'ml_in', 'mn_mn', 'mr_in', 'ms_my', 'mt_mt', 'my_mm', 'nb_no', 'ne_np', 'nl_nl', 'nso_za', 'ny_mw', 'oc_fr', 'om_et', 'or_in', 'pa_in', 'pl_pl', 'ps_af', 'pt_br', 'ro_ro', 'ru_ru', 'sd_in', 'sk_sk', 'sl_si', 'sn_zw', 'so_so', 'sr_rs', 'sv_se', 'sw_ke', 'ta_in', 'te_in', 'tg_tj', 'th_th', 'tr_tr', 'uk_ua', 'umb_ao', 'ur_pk', 'uz_uz', 'vi_vn', 'wo_sn', 'xh_za', 'yo_ng', 'yue_hant_hk', 'zu_za', 'all'] Example of usage: `load_dataset('fleurs', 'af_za')` ``` Note the example of usage in the error message suggests loading "fleurs" instead of "google/fleurs".	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6854/reactions", "total_count": 1, "+1": 1, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6854/timeline	null	completed	false
https://api.github.com/repos/huggingface/datasets/issues/6853	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6853/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6853/comments	https://api.github.com/repos/huggingface/datasets/issues/6853/events	https://github.com/huggingface/datasets/issues/6853	2,272,570,000	I_kwDODunzps6HdKqQ	6,853	Support soft links for load_datasets imagefolder	{ "login": "billytcl", "id": 10386511, "node_id": "MDQ6VXNlcjEwMzg2NTEx", "avatar_url": "https://avatars.githubusercontent.com/u/10386511?v=4", "gravatar_id": "", "url": "https://api.github.com/users/billytcl", "html_url": "https://github.com/billytcl", "followers_url": "https://api.github.com/users/billytcl/followers", "following_url": "https://api.github.com/users/billytcl/following{/other_user}", "gists_url": "https://api.github.com/users/billytcl/gists{/gist_id}", "starred_url": "https://api.github.com/users/billytcl/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/billytcl/subscriptions", "organizations_url": "https://api.github.com/users/billytcl/orgs", "repos_url": "https://api.github.com/users/billytcl/repos", "events_url": "https://api.github.com/users/billytcl/events{/privacy}", "received_events_url": "https://api.github.com/users/billytcl/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[ { "id": 1935892871, "node_id": "MDU6TGFiZWwxOTM1ODkyODcx", "url": "https://api.github.com/repos/huggingface/datasets/labels/enhancement", "name": "enhancement", "color": "a2eeef", "default": true, "description": "New feature or request" } ]	open	false	null	[]	null	[]	2024-04-30T22:14:29	2024-04-30T22:14:29	null	NONE	null	null	null	### Feature request Load_dataset from a folder of images doesn't seem to support soft links. It would be nice if it did, especially during methods development where image folders are being curated. ### Motivation Images are coming from a complex variety of sources and we'd like to be able to soft link directly from the originating folders as opposed to copying. Having a copy of the file ensures that there may be issues with image versioning as well as having double the amount of required disk space. ### Your contribution N/A	null	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6853/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6853/timeline	null	null	false
https://api.github.com/repos/huggingface/datasets/issues/6852	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6852/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6852/comments	https://api.github.com/repos/huggingface/datasets/issues/6852/events	https://github.com/huggingface/datasets/issues/6852	2,272,465,011	I_kwDODunzps6HcxBz	6,852	Write token isn't working while pushing to datasets	{ "login": "zaibutcooler", "id": 130903099, "node_id": "U_kgDOB81sOw", "avatar_url": "https://avatars.githubusercontent.com/u/130903099?v=4", "gravatar_id": "", "url": "https://api.github.com/users/zaibutcooler", "html_url": "https://github.com/zaibutcooler", "followers_url": "https://api.github.com/users/zaibutcooler/followers", "following_url": "https://api.github.com/users/zaibutcooler/following{/other_user}", "gists_url": "https://api.github.com/users/zaibutcooler/gists{/gist_id}", "starred_url": "https://api.github.com/users/zaibutcooler/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/zaibutcooler/subscriptions", "organizations_url": "https://api.github.com/users/zaibutcooler/orgs", "repos_url": "https://api.github.com/users/zaibutcooler/repos", "events_url": "https://api.github.com/users/zaibutcooler/events{/privacy}", "received_events_url": "https://api.github.com/users/zaibutcooler/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	null	[]	null	[]	2024-04-30T21:18:20	2024-05-02T00:55:46	2024-05-02T00:55:46	NONE	null	null	null	### Describe the bug <img width="1001" alt="Screenshot 2024-05-01 at 3 37 06 AM" src="https://github.com/huggingface/datasets/assets/130903099/00fcf12c-fcc1-4749-8592-d263d4efcbcc"> As you can see I logged in to my account and the write token is valid. But I can't upload on my main account and I am getting that error. It was okay on my test account at first try. (I refreshed the token, tried a new token but still doesn't work) ### Steps to reproduce the bug 1. I loaded a dataset. 2. I logged in using both cli and huggingface_hub 3. I pushed to my down dataset (It went well without any issues on my test account) ### Expected behavior It should have gone smoothly and this is not even my first time uploading to huggingface datasets ### Environment info colab, dataset (tried multiple versions)	{ "login": "zaibutcooler", "id": 130903099, "node_id": "U_kgDOB81sOw", "avatar_url": "https://avatars.githubusercontent.com/u/130903099?v=4", "gravatar_id": "", "url": "https://api.github.com/users/zaibutcooler", "html_url": "https://github.com/zaibutcooler", "followers_url": "https://api.github.com/users/zaibutcooler/followers", "following_url": "https://api.github.com/users/zaibutcooler/following{/other_user}", "gists_url": "https://api.github.com/users/zaibutcooler/gists{/gist_id}", "starred_url": "https://api.github.com/users/zaibutcooler/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/zaibutcooler/subscriptions", "organizations_url": "https://api.github.com/users/zaibutcooler/orgs", "repos_url": "https://api.github.com/users/zaibutcooler/repos", "events_url": "https://api.github.com/users/zaibutcooler/events{/privacy}", "received_events_url": "https://api.github.com/users/zaibutcooler/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6852/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6852/timeline	null	completed	false
https://api.github.com/repos/huggingface/datasets/issues/6851	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6851/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6851/comments	https://api.github.com/repos/huggingface/datasets/issues/6851/events	https://github.com/huggingface/datasets/issues/6851	2,270,965,503	I_kwDODunzps6HXC7_	6,851	load_dataset('emotion') UnicodeDecodeError	{ "login": "L-Block-C", "id": 32314558, "node_id": "MDQ6VXNlcjMyMzE0NTU4", "avatar_url": "https://avatars.githubusercontent.com/u/32314558?v=4", "gravatar_id": "", "url": "https://api.github.com/users/L-Block-C", "html_url": "https://github.com/L-Block-C", "followers_url": "https://api.github.com/users/L-Block-C/followers", "following_url": "https://api.github.com/users/L-Block-C/following{/other_user}", "gists_url": "https://api.github.com/users/L-Block-C/gists{/gist_id}", "starred_url": "https://api.github.com/users/L-Block-C/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/L-Block-C/subscriptions", "organizations_url": "https://api.github.com/users/L-Block-C/orgs", "repos_url": "https://api.github.com/users/L-Block-C/repos", "events_url": "https://api.github.com/users/L-Block-C/events{/privacy}", "received_events_url": "https://api.github.com/users/L-Block-C/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	open	false	null	[]	null	[ "I met the same problem, here is my code:\r\n```\r\nfrom datasets import load_dataset\r\n\r\nds_name = \"togethercomputer/RedPajama-Data-1T\"\r\nds = load_dataset(ds_name, download_mode=DownloadMode.FORCE_REDOWNLOAD)\r\n```\r\nAnd output error is:\r\n```\r\nTraceback (most recent call last):\r\n File \"/home/yatorho/doc/projs/TransformerEngine/local/download_redpajama.py\", line 10, in <module>\r\n ds = load_dataset(ds_name, download_mode=DownloadMode.FORCE_REDOWNLOAD)\r\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\r\n File \"/home/yatorho/anaconda3/envs/t24/lib/python3.12/site-packages/datasets/load.py\", line 2606, in load_dataset\r\n builder_instance = load_dataset_builder(\r\n ^^^^^^^^^^^^^^^^^^^^^\r\n File \"/home/yatorho/anaconda3/envs/t24/lib/python3.12/site-packages/datasets/load.py\", line 2277, in load_dataset_builder\r\n dataset_module = dataset_module_factory(\r\n ^^^^^^^^^^^^^^^^^^^^^^^\r\n File \"/home/yatorho/anaconda3/envs/t24/lib/python3.12/site-packages/datasets/load.py\", line 1923, in dataset_module_factory\r\n raise e1 from None\r\n File \"/home/yatorho/anaconda3/envs/t24/lib/python3.12/site-packages/datasets/load.py\", line 1875, in dataset_module_factory\r\n can_load_config_from_parquet_export = \"DEFAULT_CONFIG_NAME\" not in f.read()\r\n ^^^^^^^^\r\n File \"<frozen codecs>\", line 322, in decode\r\nUnicodeDecodeError: 'utf-8' codec can't decode byte 0xb5 in position 1: invalid start byte\r\n```\r\nMy `datasets` version is 2.21.0. Any help here would be appreciated!\r\n", "> I met the same problem, here is my code:\r\n> \r\n> ```\r\n> from datasets import load_dataset\r\n> \r\n> ds_name = \"togethercomputer/RedPajama-Data-1T\"\r\n> ds = load_dataset(ds_name, download_mode=DownloadMode.FORCE_REDOWNLOAD)\r\n> ```\r\n> \r\n> And output error is:\r\n> \r\n> ```\r\n> Traceback (most recent call last):\r\n> File \"/home/yatorho/doc/projs/TransformerEngine/local/download_redpajama.py\", line 10, in <module>\r\n> ds = load_dataset(ds_name, download_mode=DownloadMode.FORCE_REDOWNLOAD)\r\n> ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\r\n> File \"/home/yatorho/anaconda3/envs/t24/lib/python3.12/site-packages/datasets/load.py\", line 2606, in load_dataset\r\n> builder_instance = load_dataset_builder(\r\n> ^^^^^^^^^^^^^^^^^^^^^\r\n> File \"/home/yatorho/anaconda3/envs/t24/lib/python3.12/site-packages/datasets/load.py\", line 2277, in load_dataset_builder\r\n> dataset_module = dataset_module_factory(\r\n> ^^^^^^^^^^^^^^^^^^^^^^^\r\n> File \"/home/yatorho/anaconda3/envs/t24/lib/python3.12/site-packages/datasets/load.py\", line 1923, in dataset_module_factory\r\n> raise e1 from None\r\n> File \"/home/yatorho/anaconda3/envs/t24/lib/python3.12/site-packages/datasets/load.py\", line 1875, in dataset_module_factory\r\n> can_load_config_from_parquet_export = \"DEFAULT_CONFIG_NAME\" not in f.read()\r\n> ^^^^^^^^\r\n> File \"<frozen codecs>\", line 322, in decode\r\n> UnicodeDecodeError: 'utf-8' codec can't decode byte 0xb5 in position 1: invalid start byte\r\n> ```\r\n> \r\n> My `datasets` version is 2.21.0. Any help here would be appreciated!\r\n\r\nI passed encoding=\"utf-16\" to the `load_dataset` call and now it works for me.\r\n```\r\nds = load_dataset(ds_name, download_mode=DownloadMode.FORCE_REDOWNLOAD, encoding=\"utf-16\")\r\n```" ]	2024-04-30T09:25:01	2024-09-05T03:11:04	null	NONE	null	null	null	### Describe the bug emotions = load_dataset('emotion') _UnicodeDecodeError: 'utf-8' codec can't decode byte 0x8b in position 1: invalid start byte_ ### Steps to reproduce the bug load_dataset('emotion') ### Expected behavior succese ### Environment info py3.10 transformers 4.41.0.dev0 datasets 2.19.0	null	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6851/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6851/timeline	null	null	false
https://api.github.com/repos/huggingface/datasets/issues/6850	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6850/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6850/comments	https://api.github.com/repos/huggingface/datasets/issues/6850/events	https://github.com/huggingface/datasets/issues/6850	2,269,500,624	I_kwDODunzps6HRdTQ	6,850	Problem loading voxpopuli dataset	{ "login": "Namangarg110", "id": 40496687, "node_id": "MDQ6VXNlcjQwNDk2Njg3", "avatar_url": "https://avatars.githubusercontent.com/u/40496687?v=4", "gravatar_id": "", "url": "https://api.github.com/users/Namangarg110", "html_url": "https://github.com/Namangarg110", "followers_url": "https://api.github.com/users/Namangarg110/followers", "following_url": "https://api.github.com/users/Namangarg110/following{/other_user}", "gists_url": "https://api.github.com/users/Namangarg110/gists{/gist_id}", "starred_url": "https://api.github.com/users/Namangarg110/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/Namangarg110/subscriptions", "organizations_url": "https://api.github.com/users/Namangarg110/orgs", "repos_url": "https://api.github.com/users/Namangarg110/repos", "events_url": "https://api.github.com/users/Namangarg110/events{/privacy}", "received_events_url": "https://api.github.com/users/Namangarg110/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[ { "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false } ]	null	[ "Version 2.18 works without problem.", "@Namangarg110 @mohsen-goodarzi The bug appears because the number of urls is less than 16 and the algorithm is meant to work on the previously created mode for a single url as stated on line 314: https://github.com/huggingface/datasets/blob/1bf8a46cc7b096d5c547ea3794f6a4b6c31ea762/src/datasets/download/download_manager.py#L314\r\n\r\nIn addition, previously `map_nested` function was supported without batching and it is meant to be the default performance. \r\n\r\nOne of the shortest walk-arounds would be changing the part of the manager with the current setting:\r\n```\r\n if len(url_or_urls) >= 16:\r\n download_func = partial(self._download_batched, download_config=download_config)\r\n else:\r\n download_func = partial(self._download_single, download_config=download_config)\r\n\r\n start_time = datetime.now()\r\n with stack_multiprocessing_download_progress_bars():\r\n downloaded_path_or_paths = map_nested(\r\n download_func,\r\n url_or_urls,\r\n map_tuple=True,\r\n num_proc=download_config.num_proc,\r\n desc=\"Downloading data files\",\r\n batched=True if len(url_or_urls) >= 16 else False,\r\n batch_size=-1,\r\n )\r\n```\r\n\r\nI would suggest to consider other datasets for similar issues and make a pull-request. ", "Thanks for reporting @Namangarg110 and thanks for the investigation @MilanaShhanukova.\r\n\r\nApparently, there is an issue with the download functionality.\r\nI am proposing a fix." ]	2024-04-29T16:46:51	2024-05-06T09:25:54	2024-05-06T09:25:54	NONE	null	null	null	### Describe the bug ``` Exception has occurred: FileNotFoundError Couldn't find file at https://huggingface.co/datasets/facebook/voxpopuli/resolve/main/{'en': 'data/en/asr_train.tsv'} ``` Error in logic for link url creation. The link should be https://huggingface.co/datasets/facebook/voxpopuli/resolve/main/data/en/asr_train.tsv Basically there should be links directly under ```metadata["train"]```, not under ```metadata["train"][self.config.languages[0]]``` same for audio urls ### Steps to reproduce the bug ``` from datasets import load_dataset dataset = load_dataset("facebook/voxpopuli","en") ``` ### Expected behavior Dataset should be loaded successfully. ### Environment info - `datasets` version: 2.19.0 - Platform: Linux-5.15.0-1041-aws-x86_64-with-glibc2.31 - Python version: 3.10.13 - `huggingface_hub` version: 0.22.2 - PyArrow version: 16.0.0 - Pandas version: 2.2.0 - `fsspec` version: 2023.12.2	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6850/reactions", "total_count": 2, "+1": 2, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6850/timeline	null	completed	false
https://api.github.com/repos/huggingface/datasets/issues/6849	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6849/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6849/comments	https://api.github.com/repos/huggingface/datasets/issues/6849/events	https://github.com/huggingface/datasets/pull/6849	2,268,718,355	PR_kwDODunzps5t_wnu	6,849	fix webdataset filename split	{ "login": "Bowser1704", "id": 43539191, "node_id": "MDQ6VXNlcjQzNTM5MTkx", "avatar_url": "https://avatars.githubusercontent.com/u/43539191?v=4", "gravatar_id": "", "url": "https://api.github.com/users/Bowser1704", "html_url": "https://github.com/Bowser1704", "followers_url": "https://api.github.com/users/Bowser1704/followers", "following_url": "https://api.github.com/users/Bowser1704/following{/other_user}", "gists_url": "https://api.github.com/users/Bowser1704/gists{/gist_id}", "starred_url": "https://api.github.com/users/Bowser1704/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/Bowser1704/subscriptions", "organizations_url": "https://api.github.com/users/Bowser1704/orgs", "repos_url": "https://api.github.com/users/Bowser1704/repos", "events_url": "https://api.github.com/users/Bowser1704/events{/privacy}", "received_events_url": "https://api.github.com/users/Bowser1704/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	null	[]	null	[ "Hi ! This was fixed recently in https://github.com/huggingface/datasets/pull/6904 and https://github.com/huggingface/datasets/pull/6931" ]	2024-04-29T10:57:18	2024-06-04T12:54:04	2024-06-04T12:54:04	NONE	null	false	{ "url": "https://api.github.com/repos/huggingface/datasets/pulls/6849", "html_url": "https://github.com/huggingface/datasets/pull/6849", "diff_url": "https://github.com/huggingface/datasets/pull/6849.diff", "patch_url": "https://github.com/huggingface/datasets/pull/6849.patch", "merged_at": null }	use `os.path.splitext` to parse field_name. fix filename which has dot. like: ``` a.b.jpeg a.b.txt ```	{ "login": "lhoestq", "id": 42851186, "node_id": "MDQ6VXNlcjQyODUxMTg2", "avatar_url": "https://avatars.githubusercontent.com/u/42851186?v=4", "gravatar_id": "", "url": "https://api.github.com/users/lhoestq", "html_url": "https://github.com/lhoestq", "followers_url": "https://api.github.com/users/lhoestq/followers", "following_url": "https://api.github.com/users/lhoestq/following{/other_user}", "gists_url": "https://api.github.com/users/lhoestq/gists{/gist_id}", "starred_url": "https://api.github.com/users/lhoestq/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/lhoestq/subscriptions", "organizations_url": "https://api.github.com/users/lhoestq/orgs", "repos_url": "https://api.github.com/users/lhoestq/repos", "events_url": "https://api.github.com/users/lhoestq/events{/privacy}", "received_events_url": "https://api.github.com/users/lhoestq/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6849/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6849/timeline	null	null	true
https://api.github.com/repos/huggingface/datasets/issues/6848	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6848/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6848/comments	https://api.github.com/repos/huggingface/datasets/issues/6848/events	https://github.com/huggingface/datasets/issues/6848	2,268,622,609	I_kwDODunzps6HOG8R	6,848	Cant Downlaod Common Voice 17.0 hy-AM	{ "login": "mheryerznkanyan", "id": 31586104, "node_id": "MDQ6VXNlcjMxNTg2MTA0", "avatar_url": "https://avatars.githubusercontent.com/u/31586104?v=4", "gravatar_id": "", "url": "https://api.github.com/users/mheryerznkanyan", "html_url": "https://github.com/mheryerznkanyan", "followers_url": "https://api.github.com/users/mheryerznkanyan/followers", "following_url": "https://api.github.com/users/mheryerznkanyan/following{/other_user}", "gists_url": "https://api.github.com/users/mheryerznkanyan/gists{/gist_id}", "starred_url": "https://api.github.com/users/mheryerznkanyan/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/mheryerznkanyan/subscriptions", "organizations_url": "https://api.github.com/users/mheryerznkanyan/orgs", "repos_url": "https://api.github.com/users/mheryerznkanyan/repos", "events_url": "https://api.github.com/users/mheryerznkanyan/events{/privacy}", "received_events_url": "https://api.github.com/users/mheryerznkanyan/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	open	false	null	[]	null	[ "Same issue here." ]	2024-04-29T10:06:02	2024-05-13T06:09:30	null	NONE	null	null	null	### Describe the bug I want to download Common Voice 17.0 hy-AM but it returns an error. ``` The version_base parameter is not specified. Please specify a compatability version level, or None. Will assume defaults for version 1.1 @hydra.main(config_name='hfds_config', config_path=None) /usr/local/lib/python3.10/dist-packages/hydra/_internal/hydra.py:119: UserWarning: Future Hydra versions will no longer change working directory at job runtime by default. See https://hydra.cc/docs/1.2/upgrades/1.1_to_1.2/changes_to_job_working_dir/ for more information. ret = run_job( /usr/local/lib/python3.10/dist-packages/datasets/load.py:1429: FutureWarning: The repository for mozilla-foundation/common_voice_17_0 contains custom code which must be executed to correctly load the dataset. You can inspect the repository content at https://hf.co/datasets/mozilla-foundation/common_voice_17_0 You can avoid this message in future by passing the argument `trust_remote_code=True`. Passing `trust_remote_code=True` will be mandatory to load this dataset from the next major release of `datasets`. warnings.warn( Reading metadata...: 6180it [00:00, 133224.37it/s]les/s] Generating train split: 0 examples [00:00, ? examples/s] HuggingFace datasets failed due to some reason (stack trace below). For certain datasets (eg: MCV), it may be necessary to login to the huggingface-cli (via `huggingface-cli login`). Once logged in, you need to set `use_auth_token=True` when calling this script. Traceback error for reference : Traceback (most recent call last): File "/usr/local/lib/python3.10/dist-packages/datasets/builder.py", line 1743, in _prepare_split_single example = self.info.features.encode_example(record) if self.info.features is not None else record File "/usr/local/lib/python3.10/dist-packages/datasets/features/features.py", line 1878, in encode_example return encode_nested_example(self, example) File "/usr/local/lib/python3.10/dist-packages/datasets/features/features.py", line 1243, in encode_nested_example { File "/usr/local/lib/python3.10/dist-packages/datasets/features/features.py", line 1243, in <dictcomp> { File "/usr/local/lib/python3.10/dist-packages/datasets/utils/py_utils.py", line 326, in zip_dict yield key, tuple(d[key] for d in dicts) File "/usr/local/lib/python3.10/dist-packages/datasets/utils/py_utils.py", line 326, in <genexpr> yield key, tuple(d[key] for d in dicts) KeyError: 'sentence_id' The above exception was the direct cause of the following exception: Traceback (most recent call last): File "/workspace/nemo/scripts/speech_recognition/convert_hf_dataset_to_nemo.py", line 358, in main dataset = load_dataset( File "/usr/local/lib/python3.10/dist-packages/datasets/load.py", line 2549, in load_dataset builder_instance.download_and_prepare( File "/usr/local/lib/python3.10/dist-packages/datasets/builder.py", line 1005, in download_and_prepare self._download_and_prepare( File "/usr/local/lib/python3.10/dist-packages/datasets/builder.py", line 1767, in _download_and_prepare super()._download_and_prepare( File "/usr/local/lib/python3.10/dist-packages/datasets/builder.py", line 1100, in _download_and_prepare self._prepare_split(split_generator, **prepare_split_kwargs) File "/usr/local/lib/python3.10/dist-packages/datasets/builder.py", line 1605, in _prepare_split for job_id, done, content in self._prepare_split_single( File "/usr/local/lib/python3.10/dist-packages/datasets/builder.py", line 1762, in _prepare_split_single raise DatasetGenerationError("An error occurred while generating the dataset") from e datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset ``` ### Steps to reproduce the bug ``` from datasets import load_dataset cv_17 = load_dataset("mozilla-foundation/common_voice_17_0", "hy-AM") ``` ### Expected behavior It works fine with common_voice_16_1 ### Environment info - `datasets` version: 2.18.0 - Platform: Linux-5.15.0-1042-nvidia-x86_64-with-glibc2.35 - Python version: 3.11.6 - `huggingface_hub` version: 0.22.2 - PyArrow version: 15.0.2 - Pandas version: 2.2.2 - `fsspec` version: 2024.2.0	null	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6848/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6848/timeline	null	null	false
https://api.github.com/repos/huggingface/datasets/issues/6847	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6847/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6847/comments	https://api.github.com/repos/huggingface/datasets/issues/6847/events	https://github.com/huggingface/datasets/issues/6847	2,268,589,177	I_kwDODunzps6HN-x5	6,847	[Streaming] Only load requested splits without resolving files for the other splits	{ "login": "lhoestq", "id": 42851186, "node_id": "MDQ6VXNlcjQyODUxMTg2", "avatar_url": "https://avatars.githubusercontent.com/u/42851186?v=4", "gravatar_id": "", "url": "https://api.github.com/users/lhoestq", "html_url": "https://github.com/lhoestq", "followers_url": "https://api.github.com/users/lhoestq/followers", "following_url": "https://api.github.com/users/lhoestq/following{/other_user}", "gists_url": "https://api.github.com/users/lhoestq/gists{/gist_id}", "starred_url": "https://api.github.com/users/lhoestq/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/lhoestq/subscriptions", "organizations_url": "https://api.github.com/users/lhoestq/orgs", "repos_url": "https://api.github.com/users/lhoestq/repos", "events_url": "https://api.github.com/users/lhoestq/events{/privacy}", "received_events_url": "https://api.github.com/users/lhoestq/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	open	false	{ "login": "lhoestq", "id": 42851186, "node_id": "MDQ6VXNlcjQyODUxMTg2", "avatar_url": "https://avatars.githubusercontent.com/u/42851186?v=4", "gravatar_id": "", "url": "https://api.github.com/users/lhoestq", "html_url": "https://github.com/lhoestq", "followers_url": "https://api.github.com/users/lhoestq/followers", "following_url": "https://api.github.com/users/lhoestq/following{/other_user}", "gists_url": "https://api.github.com/users/lhoestq/gists{/gist_id}", "starred_url": "https://api.github.com/users/lhoestq/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/lhoestq/subscriptions", "organizations_url": "https://api.github.com/users/lhoestq/orgs", "repos_url": "https://api.github.com/users/lhoestq/repos", "events_url": "https://api.github.com/users/lhoestq/events{/privacy}", "received_events_url": "https://api.github.com/users/lhoestq/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[ { "login": "lhoestq", "id": 42851186, "node_id": "MDQ6VXNlcjQyODUxMTg2", "avatar_url": "https://avatars.githubusercontent.com/u/42851186?v=4", "gravatar_id": "", "url": "https://api.github.com/users/lhoestq", "html_url": "https://github.com/lhoestq", "followers_url": "https://api.github.com/users/lhoestq/followers", "following_url": "https://api.github.com/users/lhoestq/following{/other_user}", "gists_url": "https://api.github.com/users/lhoestq/gists{/gist_id}", "starred_url": "https://api.github.com/users/lhoestq/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/lhoestq/subscriptions", "organizations_url": "https://api.github.com/users/lhoestq/orgs", "repos_url": "https://api.github.com/users/lhoestq/repos", "events_url": "https://api.github.com/users/lhoestq/events{/privacy}", "received_events_url": "https://api.github.com/users/lhoestq/received_events", "type": "User", "user_view_type": "public", "site_admin": false } ]	null	[ "This should help fixing this issue: https://github.com/huggingface/datasets/pull/6832", "I'm having a similar issue when using splices:\r\n<img width=\"947\" alt=\"image\" src=\"https://github.com/huggingface/datasets/assets/28941213/2153faac-e1fe-4b6d-a79b-30b2699407e8\">\r\n<img width=\"823\" alt=\"image\" src=\"https://github.com/huggingface/datasets/assets/28941213/80919eca-eb6c-407d-8070-52642fdcee54\">\r\n<img width=\"914\" alt=\"image\" src=\"https://github.com/huggingface/datasets/assets/28941213/5219c201-e22e-4536-acc3-a922677785ff\">\r\n\r\n\r\nIt seems to be downloading, loading, and generating splits using the entire dataset." ]	2024-04-29T09:49:32	2024-05-07T04:43:59	null	MEMBER	null	null	null	e.g. [thangvip](https://huggingface.co/thangvip)/[cosmopedia_vi_math](https://huggingface.co/datasets/thangvip/cosmopedia_vi_math) has 300 splits and it takes a very long time to load only one split. This is due to `load_dataset()` resolving the files of all the splits even if only one is needed. In `dataset-viewer` the splits are loaded in different jobs so it results in 300 jobs that resolve 300 splits -> 90k calls to `/paths-info`	null	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6847/reactions", "total_count": 1, "+1": 1, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6847/timeline	null	null	false
https://api.github.com/repos/huggingface/datasets/issues/6846	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6846/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6846/comments	https://api.github.com/repos/huggingface/datasets/issues/6846/events	https://github.com/huggingface/datasets/issues/6846	2,267,352,120	I_kwDODunzps6HJQw4	6,846	Unimaginable super slow iteration	{ "login": "rangehow", "id": 88258534, "node_id": "MDQ6VXNlcjg4MjU4NTM0", "avatar_url": "https://avatars.githubusercontent.com/u/88258534?v=4", "gravatar_id": "", "url": "https://api.github.com/users/rangehow", "html_url": "https://github.com/rangehow", "followers_url": "https://api.github.com/users/rangehow/followers", "following_url": "https://api.github.com/users/rangehow/following{/other_user}", "gists_url": "https://api.github.com/users/rangehow/gists{/gist_id}", "starred_url": "https://api.github.com/users/rangehow/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/rangehow/subscriptions", "organizations_url": "https://api.github.com/users/rangehow/orgs", "repos_url": "https://api.github.com/users/rangehow/repos", "events_url": "https://api.github.com/users/rangehow/events{/privacy}", "received_events_url": "https://api.github.com/users/rangehow/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	null	[]	null	[ "In every iteration you load the full \"random_input\" column in memory, only then to access it's i-th element.\r\n\r\nYou can try using this instead\r\n\r\na,b=dataset[i]['random_input'],dataset[i]['random_output']" ]	2024-04-28T05:24:14	2024-05-06T08:30:03	2024-05-06T08:30:03	NONE	null	null	null	### Describe the bug Assuming there is a dataset with 52000 sentences, each with a length of 500, it takes 20 seconds to extract a sentence from the dataset……？Is there something wrong with my iteration? ### Steps to reproduce the bug ```python import datasets import time import random num_rows = 52000 num_cols = 500 random_input = [[random.randint(1, 100) for _ in range(num_cols)] for _ in range(num_rows)] random_output = [[random.randint(1, 100) for _ in range(num_cols)] for _ in range(num_rows)] s=time.time() d={'random_input':random_input,'random_output':random_output} dataset=datasets.Dataset.from_dict(d) print('from dict',time.time()-s) print(dataset) for i in range(len(dataset)): aa=time.time() a,b=dataset['random_input'][i],dataset['random_output'][i] print(time.time()-aa) ``` corresponding output ```bash from dict 9.215498685836792 Dataset({ features: ['random_input', 'random_output'], num_rows: 52000 }) 19.129778146743774 19.329464197158813 19.27668261528015 19.28557538986206 19.247620582580566 19.624247074127197 19.28673791885376 19.301053047180176 19.290496110916138 19.291821718215942 19.357765197753906 ``` ### Expected behavior Under normal circumstances, iteration should be very rapid as it does not involve the main tasks other than getting items ### Environment info - `datasets` version: 2.19.0 - Platform: Linux-3.10.0-1160.71.1.el7.x86_64-x86_64-with-glibc2.17 - Python version: 3.10.13 - `huggingface_hub` version: 0.21.4 - PyArrow version: 15.0.0 - Pandas version: 2.2.1 - `fsspec` version: 2024.2.0	{ "login": "rangehow", "id": 88258534, "node_id": "MDQ6VXNlcjg4MjU4NTM0", "avatar_url": "https://avatars.githubusercontent.com/u/88258534?v=4", "gravatar_id": "", "url": "https://api.github.com/users/rangehow", "html_url": "https://github.com/rangehow", "followers_url": "https://api.github.com/users/rangehow/followers", "following_url": "https://api.github.com/users/rangehow/following{/other_user}", "gists_url": "https://api.github.com/users/rangehow/gists{/gist_id}", "starred_url": "https://api.github.com/users/rangehow/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/rangehow/subscriptions", "organizations_url": "https://api.github.com/users/rangehow/orgs", "repos_url": "https://api.github.com/users/rangehow/repos", "events_url": "https://api.github.com/users/rangehow/events{/privacy}", "received_events_url": "https://api.github.com/users/rangehow/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6846/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6846/timeline	null	completed	false
https://api.github.com/repos/huggingface/datasets/issues/6845	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6845/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6845/comments	https://api.github.com/repos/huggingface/datasets/issues/6845/events	https://github.com/huggingface/datasets/issues/6845	2,265,876,551	I_kwDODunzps6HDohH	6,845	load_dataset doesn't support list column	{ "login": "arthasking123", "id": 16257131, "node_id": "MDQ6VXNlcjE2MjU3MTMx", "avatar_url": "https://avatars.githubusercontent.com/u/16257131?v=4", "gravatar_id": "", "url": "https://api.github.com/users/arthasking123", "html_url": "https://github.com/arthasking123", "followers_url": "https://api.github.com/users/arthasking123/followers", "following_url": "https://api.github.com/users/arthasking123/following{/other_user}", "gists_url": "https://api.github.com/users/arthasking123/gists{/gist_id}", "starred_url": "https://api.github.com/users/arthasking123/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/arthasking123/subscriptions", "organizations_url": "https://api.github.com/users/arthasking123/orgs", "repos_url": "https://api.github.com/users/arthasking123/repos", "events_url": "https://api.github.com/users/arthasking123/events{/privacy}", "received_events_url": "https://api.github.com/users/arthasking123/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	open	false	null	[]	null	[ "I encountered this same issue when loading a customized dataset for ORPO training, in which there were three columns and two of them were lists. \r\nI debugged and found that it might be caused by the type-infer mechanism and because in some chunks one of the columns is always an empty list ([]), it was regarded as ```list<item: null>```, however in some other chunk it was ```list<item: string>```. This triggered a TypeError running the function ```table_cast()```.\r\n\r\nI temporarily fixed this by re-dumping the file into a regular JSON format instead of lines of JSON dict. I didn't dig deeper for the lack of knowledge and programming ability but I do hope some developer of this repo will find and fix it." ]	2024-04-26T14:11:44	2024-05-15T12:06:59	null	NONE	null	null	null	### Describe the bug dataset = load_dataset("Doraemon-AI/text-to-neo4j-cypher-chinese") got exception: Generating train split: 1834 examples [00:00, 5227.98 examples/s] Traceback (most recent call last): File "/usr/local/lib/python3.11/dist-packages/datasets/builder.py", line 2011, in _prepare_split_single writer.write_table(table) File "/usr/local/lib/python3.11/dist-packages/datasets/arrow_writer.py", line 585, in write_table pa_table = table_cast(pa_table, self._schema) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.11/dist-packages/datasets/table.py", line 2295, in table_cast return cast_table_to_schema(table, schema) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.11/dist-packages/datasets/table.py", line 2254, in cast_table_to_schema arrays = [cast_array_to_feature(table[name], feature) for name, feature in features.items()] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.11/dist-packages/datasets/table.py", line 2254, in <listcomp> arrays = [cast_array_to_feature(table[name], feature) for name, feature in features.items()] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.11/dist-packages/datasets/table.py", line 1802, in wrapper return pa.chunked_array([func(chunk, args, kwargs) for chunk in array.chunks]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.11/dist-packages/datasets/table.py", line 1802, in <listcomp> return pa.chunked_array([func(chunk, args, *kwargs) for chunk in array.chunks]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.11/dist-packages/datasets/table.py", line 2018, in cast_array_to_feature casted_array_values = _c(array.values, feature[0]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.11/dist-packages/datasets/table.py", line 1804, in wrapper return func(array, args, kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.11/dist-packages/datasets/table.py", line 2115, in cast_array_to_feature raise TypeError(f"Couldn't cast array of type\n{array.type}\nto\n{feature}") TypeError: Couldn't cast array of type struct<m.name: string, x.name: string, p.name: string, n.name: string, h.name: string, name: string, c: int64, collect(r.name): list<item: string>, q.name: string, rel.name: string, count(p): int64, 1: int64, p.location: string, max(n.name): null, mn.name: string, p.time: int64, min(q.name): string> to {'q.name': Value(dtype='string', id=None), 'mn.name': Value(dtype='string', id=None), 'x.name': Value(dtype='string', id=None), 'p.name': Value(dtype='string', id=None), 'n.name': Value(dtype='string', id=None), 'name': Value(dtype='string', id=None), 'm.name': Value(dtype='string', id=None), 'h.name': Value(dtype='string', id=None), 'count(p)': Value(dtype='int64', id=None), 'rel.name': Value(dtype='string', id=None), 'c': Value(dtype='int64', id=None), 'collect(r.name)': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), '1': Value(dtype='int64', id=None), 'p.location': Value(dtype='string', id=None), 'substring(h.name,0,5)': Value(dtype='string', id=None), 'p.time': Value(dtype='int64', id=None)} The above exception was the direct cause of the following exception: Traceback (most recent call last): File "/home/ubuntu/llm/train-2.py", line 150, in <module> dataset = load_dataset("Doraemon-AI/text-to-neo4j-cypher-chinese") ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.11/dist-packages/datasets/load.py", line 2609, in load_dataset builder_instance.download_and_prepare( File "/usr/local/lib/python3.11/dist-packages/datasets/builder.py", line 1027, in download_and_prepare self._download_and_prepare( File "/usr/local/lib/python3.11/dist-packages/datasets/builder.py", line 1122, in _download_and_prepare self._prepare_split(split_generator, prepare_split_kwargs) File "/usr/local/lib/python3.11/dist-packages/datasets/builder.py", line 1882, in _prepare_split for job_id, done, content in self._prepare_split_single( File "/usr/local/lib/python3.11/dist-packages/datasets/builder.py", line 2038, in _prepare_split_single raise DatasetGenerationError("An error occurred while generating the dataset") from e datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset ### Steps to reproduce the bug dataset = load_dataset("Doraemon-AI/text-to-neo4j-cypher-chinese") ### Expected behavior no exception ### Environment info python 3.11 datasets 2.19.0	null	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6845/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 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https://api.github.com/repos/huggingface/datasets/issues/6844	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6844/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6844/comments	https://api.github.com/repos/huggingface/datasets/issues/6844/events	https://github.com/huggingface/datasets/pull/6844	2,265,870,546	PR_kwDODunzps5t2PRA	6,844	Retry on HF Hub error when streaming	{ "login": "mariosasko", "id": 47462742, "node_id": "MDQ6VXNlcjQ3NDYyNzQy", "avatar_url": "https://avatars.githubusercontent.com/u/47462742?v=4", "gravatar_id": "", "url": "https://api.github.com/users/mariosasko", "html_url": "https://github.com/mariosasko", "followers_url": "https://api.github.com/users/mariosasko/followers", "following_url": "https://api.github.com/users/mariosasko/following{/other_user}", "gists_url": "https://api.github.com/users/mariosasko/gists{/gist_id}", "starred_url": "https://api.github.com/users/mariosasko/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/mariosasko/subscriptions", "organizations_url": "https://api.github.com/users/mariosasko/orgs", "repos_url": "https://api.github.com/users/mariosasko/repos", "events_url": "https://api.github.com/users/mariosasko/events{/privacy}", "received_events_url": "https://api.github.com/users/mariosasko/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	null	[]	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6844). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "@Wauplin This PR is indeed not needed as explained in https://github.com/huggingface/datasets/issues/6843#issuecomment-2079630389. \r\n\r\nSo, I'm closing it." ]	2024-04-26T14:09:04	2024-04-26T15:37:42	2024-04-26T15:37:42	COLLABORATOR	null	false	{ "url": "https://api.github.com/repos/huggingface/datasets/pulls/6844", "html_url": "https://github.com/huggingface/datasets/pull/6844", "diff_url": "https://github.com/huggingface/datasets/pull/6844.diff", "patch_url": "https://github.com/huggingface/datasets/pull/6844.patch", "merged_at": null }	Retry on the `huggingface_hub`'s `HfHubHTTPError` in the streaming mode. Fix #6843	{ "login": "mariosasko", "id": 47462742, "node_id": "MDQ6VXNlcjQ3NDYyNzQy", "avatar_url": "https://avatars.githubusercontent.com/u/47462742?v=4", "gravatar_id": "", "url": "https://api.github.com/users/mariosasko", "html_url": "https://github.com/mariosasko", "followers_url": "https://api.github.com/users/mariosasko/followers", "following_url": "https://api.github.com/users/mariosasko/following{/other_user}", "gists_url": "https://api.github.com/users/mariosasko/gists{/gist_id}", "starred_url": "https://api.github.com/users/mariosasko/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/mariosasko/subscriptions", "organizations_url": "https://api.github.com/users/mariosasko/orgs", "repos_url": "https://api.github.com/users/mariosasko/repos", "events_url": "https://api.github.com/users/mariosasko/events{/privacy}", "received_events_url": "https://api.github.com/users/mariosasko/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6844/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6844/timeline	null	null	true
https://api.github.com/repos/huggingface/datasets/issues/6843	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6843/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6843/comments	https://api.github.com/repos/huggingface/datasets/issues/6843/events	https://github.com/huggingface/datasets/issues/6843	2,265,432,897	I_kwDODunzps6HB8NB	6,843	IterableDataset raises exception instead of retrying	{ "login": "bauwenst", "id": 145220868, "node_id": "U_kgDOCKflBA", "avatar_url": "https://avatars.githubusercontent.com/u/145220868?v=4", "gravatar_id": "", "url": "https://api.github.com/users/bauwenst", "html_url": "https://github.com/bauwenst", "followers_url": "https://api.github.com/users/bauwenst/followers", "following_url": "https://api.github.com/users/bauwenst/following{/other_user}", "gists_url": "https://api.github.com/users/bauwenst/gists{/gist_id}", "starred_url": "https://api.github.com/users/bauwenst/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/bauwenst/subscriptions", "organizations_url": "https://api.github.com/users/bauwenst/orgs", "repos_url": "https://api.github.com/users/bauwenst/repos", "events_url": "https://api.github.com/users/bauwenst/events{/privacy}", "received_events_url": "https://api.github.com/users/bauwenst/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	open	false	null	[]	null	[ "Thanks for reporting! I've opened a PR with a fix.", "Thanks, @mariosasko! Related question (although I guess this is a feature request): could we have some kind of exponential back-off for these retries? Here's my reasoning:\r\n- If a one-time accidental error happens, you should retry immediately and will succeed immediately.\r\n- If the Hub has a small outage on the order of minutes, you don't want to retry on the order of hours. \r\n- If the Hub has a prologned outage of several hours, we don't want to keep retrying on the order of minutes.\r\n\r\nThere actually already exists an implementation for (clipped) exponential backoff in the HuggingFace suite ([here](https://github.com/huggingface/huggingface_hub/blob/61b156a4f2e5fe1a492ed8712b26803e2122bde0/src/huggingface_hub/utils/_http.py#L306)), but I don't think it is used here.\r\n\r\nThe requirements are basically that you have an initial minimum waiting time and a maximum waiting time, and with each retry, the waiting time is doubled. We don't want to overload your servers with needless retries, especially when they're down :sweat_smile:", "Oh, I've just remembered that we added retries to the `HfFileSystem` in `huggingface_hub` 0.21.0 (see [this](https://github.com/huggingface/huggingface_hub/blob/61b156a4f2e5fe1a492ed8712b26803e2122bde0/src/huggingface_hub/hf_file_system.py#L703)), so I'll close the linked PR as we don't want to retry the retries :).\r\n\r\nI agree with the exponential backoff suggestion, so I'll open another PR.", "@mariosasko The call you linked indeed points to the implementation I linked in my previous comment, yes, but it has no configurability. Arguably, you want to have this hidden backoff under the hood that catches small network disturbances on the time scale of seconds -- perhaps even with hardcoded limits as is the case currently -- but you also still want to have a separate backoff on top of that with the configurability as suggested by @lhoestq in [the comment I linked](https://github.com/huggingface/datasets/issues/6172#issuecomment-1794876229).\r\n\r\nMy particular use-case is that I'm streaming a dataset while training on a university cluster with a very long scheduling queue. This means that when the backoff runs out of retries (which happens in under 30 seconds with the call you linked), I lose my spot on the cluster and have to queue for a whole day or more. Ideally, I should be able to specify that I want to retry for 2 to 3 hours but with more and more time between requests, so that I can smooth over hours-long outages without a setback of days.", "I also have my runs crash a surprising amount due to the dataloader crashing because of the hub, some way to address this would be nice.", "@mariosasko The implementation for retries is still broken and there is still no exponential back-off.\r\n\r\nHuggingFace has a two-tiered back-off:\r\n- `huggingface_hub.utils` provides the low-level `http_backoff` function which is used for all HTTP requests. It retries first with 1 second delay, then 2, then 4, then 8, then 8, and then it crashes. This is not even half a minute of exponential backoff in total.\r\n- `datasets.utils.file_utils` provides a function `_add_retries_to_file_obj_read_method` that monkey-patches the `read` method of an `HfFileSystemFile` to have constant-time backoff on certain exceptions. The amount of retries and seconds between retries is customisable as explained by @lhoestq [here](https://github.com/huggingface/datasets/issues/6172#issuecomment-1794876229). The implementation looks like this:\r\n\r\nhttps://github.com/huggingface/datasets/blob/65f6eb54aa0e8bb44cea35deea28e0e8fecc25b9/src/datasets/utils/file_utils.py#L822-L841\r\n\r\nThis still does not catch the correct exceptions and hence no backoff happens at all which means that as soon as the hub is out for more than half a minute, processes will already start failing. Here is a stack trace of an uncaught exception:\r\n\r\n```\r\n File \"/miniconda3/envs/draft/lib/python3.11/site-packages/datasets/iterable_dataset.py\", line 268, in __iter__\r\n for key, pa_table in self.generate_tables_fn(*gen_kwags):\r\n File \"/miniconda3/envs/draft/lib/python3.11/site-packages/datasets/packaged_modules/json/json.py\", line 123, in _generate_tables\r\n batch = f.read(self.config.chunksize)\r\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\r\n File \"/miniconda3/envs/draft/lib/python3.11/site-packages/datasets/utils/file_utils.py\", line 830, in read_with_retries\r\n out = read(args, kwargs)\r\n ^^^^^^^^^^^^^^^^^^^^^\r\n File \"/miniconda3/envs/draft/lib/python3.11/site-packages/huggingface_hub/hf_file_system.py\", line 757, in read\r\n return super().read(length)\r\n ^^^^^^^^^^^^^^^^^^^^\r\n File \"/miniconda3/envs/draft/lib/python3.11/site-packages/fsspec/spec.py\", line 1856, in read\r\n out = self.cache._fetch(self.loc, self.loc + length)\r\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\r\n File \"/miniconda3/envs/draft/lib/python3.11/site-packages/fsspec/caching.py\", line 189, in _fetch\r\n self.cache = self.fetcher(start, end) # new block replaces old\r\n ^^^^^^^^^^^^^^^^^^^^^^^^\r\n File \"/miniconda3/envs/draft/lib/python3.11/site-packages/huggingface_hub/hf_file_system.py\", line 713, in _fetch_range\r\n r = http_backoff(\r\n ^^^^^^^^^^^^^\r\n File \"/miniconda3/envs/draft/lib/python3.11/site-packages/huggingface_hub/utils/_http.py\", line 326, in http_backoff\r\n raise err\r\n File \"/miniconda3/envs/draft/lib/python3.11/site-packages/huggingface_hub/utils/_http.py\", line 307, in http_backoff\r\n response = session.request(method=method, url=url, kwargs)\r\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\r\n File \"/miniconda3/envs/draft/lib/python3.11/site-packages/requests/sessions.py\", line 589, in request\r\n resp = self.send(prep, send_kwargs)\r\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\r\n File \"/miniconda3/envs/draft/lib/python3.11/site-packages/requests/sessions.py\", line 703, in send\r\n r = adapter.send(request, kwargs)\r\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\r\n File \"/miniconda3/envs/draft/lib/python3.11/site-packages/huggingface_hub/utils/_http.py\", line 93, in send\r\n return super().send(request, args, kwargs)\r\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\r\n File \"/miniconda3/envs/draft/lib/python3.11/site-packages/requests/adapters.py\", line 713, in send\r\n raise ReadTimeout(e, request=request)\r\nrequests.exceptions.ReadTimeout: (ReadTimeoutError(\"HTTPSConnectionPool(host='huggingface.co', port=443): Read timed out. (read timeout=10)\"), '(Request ID: 3d145d98-e4fa-442f-bead-6be060e60d59)')\r\n```\r\nrequests.exceptions.ReadTimeout* is not caught and hence the code fails after 0 retries.", "I merged a fix for this, thanks for reporting ! It will now retry on any `requests` Timeout error, including ReadTimeoutError: https://github.com/huggingface/datasets/pull/7256" ]	2024-04-26T10:00:43	2024-10-28T14:57:07	null	NONE	null	null	null	### Describe the bug In light of the recent server outages, I decided to look into whether I could somehow wrap my IterableDataset streams to retry rather than error out immediately. To my surprise, `datasets` [already supports retries](https://github.com/huggingface/datasets/issues/6172#issuecomment-1794876229). Since a commit by @lhoestq [last week](https://github.com/huggingface/datasets/commit/a188022dc43a76a119d90c03832d51d6e4a94d91), that code lives here: https://github.com/huggingface/datasets/blob/fe2bea6a4b09b180bd23b88fe96dfd1a11191a4f/src/datasets/utils/file_utils.py#L1097C1-L1111C19 If GitHub code snippets still aren't working, here's a copy: ```python def read_with_retries(args, kwargs): disconnect_err = None for retry in range(1, max_retries + 1): try: out = read(args, *kwargs) break except (ClientError, TimeoutError) as err: disconnect_err = err logger.warning( f"Got disconnected from remote data host. Retrying in {config.STREAMING_READ_RETRY_INTERVAL}sec [{retry}/{max_retries}]" ) time.sleep(config.STREAMING_READ_RETRY_INTERVAL) else: raise ConnectionError("Server Disconnected") from disconnect_err return out ``` With the latest outage, the end of my stack trace looked like this: ``` ... File "/miniconda3/envs/draft/lib/python3.11/site-packages/datasets/download/streaming_download_manager.py", line 342, in read_with_retries out = read(args, *kwargs) ^^^^^^^^^^^^^^^^^^^^^ File "/miniconda3/envs/draft/lib/python3.11/gzip.py", line 301, in read return self._buffer.read(size) ^^^^^^^^^^^^^^^^^^^^^^^ File "/miniconda3/envs/draft/lib/python3.11/_compression.py", line 68, in readinto data = self.read(len(byte_view)) ^^^^^^^^^^^^^^^^^^^^^^^^^ File "/miniconda3/envs/draft/lib/python3.11/gzip.py", line 505, in read buf = self._fp.read(io.DEFAULT_BUFFER_SIZE) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/miniconda3/envs/draft/lib/python3.11/gzip.py", line 88, in read return self.file.read(size) ^^^^^^^^^^^^^^^^^^^^ File "/miniconda3/envs/draft/lib/python3.11/site-packages/fsspec/spec.py", line 1856, in read out = self.cache._fetch(self.loc, self.loc + length) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/miniconda3/envs/draft/lib/python3.11/site-packages/fsspec/caching.py", line 189, in _fetch self.cache = self.fetcher(start, end) # new block replaces old ^^^^^^^^^^^^^^^^^^^^^^^^ File "/miniconda3/envs/draft/lib/python3.11/site-packages/huggingface_hub/hf_file_system.py", line 626, in _fetch_range hf_raise_for_status(r) File "/miniconda3/envs/draft/lib/python3.11/site-packages/huggingface_hub/utils/_errors.py", line 333, in hf_raise_for_status raise HfHubHTTPError(str(e), response=response) from e huggingface_hub.utils._errors.HfHubHTTPError: 504 Server Error: Gateway Time-out for url: https://huggingface.co/datasets/allenai/c4/resolve/1588ec454efa1a09f29cd18ddd04fe05fc8653a2/en/c4-train.00346-of-01024.json.gz ``` Indeed, the code for retries only catches `ClientError`s and `TimeoutError`s, and all other exceptions, including HuggingFace's own custom HTTP error class, are not caught. Nothing is retried,* and instead the exception is propagated upwards immediately. ### Steps to reproduce the bug Not sure how you reproduce this. Maybe unplug your Ethernet cable while streaming a dataset; the issue is pretty clear from the stack trace. ### Expected behavior All HTTP errors while iterating a streamable dataset should cause retries. ### Environment info Output from `datasets-cli env`: - `datasets` version: 2.18.0 - Platform: Linux-4.18.0-513.24.1.el8_9.x86_64-x86_64-with-glibc2.28 - Python version: 3.11.7 - `huggingface_hub` version: 0.20.3 - PyArrow version: 15.0.0 - Pandas version: 2.2.0 - `fsspec` version: 2023.10.0	null	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6843/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6843/timeline	null	null	false
https://api.github.com/repos/huggingface/datasets/issues/6842	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6842/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6842/comments	https://api.github.com/repos/huggingface/datasets/issues/6842/events	https://github.com/huggingface/datasets/issues/6842	2,264,692,159	I_kwDODunzps6G_HW_	6,842	Datasets with files with colon : in filenames cannot be used on Windows	{ "login": "jacobjennings", "id": 1038927, "node_id": "MDQ6VXNlcjEwMzg5Mjc=", "avatar_url": "https://avatars.githubusercontent.com/u/1038927?v=4", "gravatar_id": "", "url": "https://api.github.com/users/jacobjennings", "html_url": "https://github.com/jacobjennings", "followers_url": "https://api.github.com/users/jacobjennings/followers", "following_url": "https://api.github.com/users/jacobjennings/following{/other_user}", "gists_url": "https://api.github.com/users/jacobjennings/gists{/gist_id}", "starred_url": "https://api.github.com/users/jacobjennings/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/jacobjennings/subscriptions", "organizations_url": "https://api.github.com/users/jacobjennings/orgs", "repos_url": "https://api.github.com/users/jacobjennings/repos", "events_url": "https://api.github.com/users/jacobjennings/events{/privacy}", "received_events_url": "https://api.github.com/users/jacobjennings/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	open	false	null	[]	null	[]	2024-04-26T00:14:16	2024-04-26T00:14:16	null	NONE	null	null	null	### Describe the bug Datasets (such as https://huggingface.co/datasets/MLCommons/peoples_speech) cannot be used on Windows due to the fact that windows does not allow colons ":" in filenames. These should be converted into alternative strings. ### Steps to reproduce the bug 1. Attempt to run load_dataset on MLCommons/peoples_speech ### Expected behavior Does not crash during extraction ### Environment info Windows 11, NTFS filesystem, Python 3.12	null	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6842/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6842/timeline	null	null	false
https://api.github.com/repos/huggingface/datasets/issues/6841	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6841/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6841/comments	https://api.github.com/repos/huggingface/datasets/issues/6841/events	https://github.com/huggingface/datasets/issues/6841	2,264,687,683	I_kwDODunzps6G_GRD	6,841	Unable to load wiki_auto_asset_turk from GEM	{ "login": "abhinavsethy", "id": 23074600, "node_id": "MDQ6VXNlcjIzMDc0NjAw", "avatar_url": "https://avatars.githubusercontent.com/u/23074600?v=4", "gravatar_id": "", "url": "https://api.github.com/users/abhinavsethy", "html_url": "https://github.com/abhinavsethy", "followers_url": "https://api.github.com/users/abhinavsethy/followers", "following_url": "https://api.github.com/users/abhinavsethy/following{/other_user}", "gists_url": "https://api.github.com/users/abhinavsethy/gists{/gist_id}", "starred_url": "https://api.github.com/users/abhinavsethy/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/abhinavsethy/subscriptions", "organizations_url": "https://api.github.com/users/abhinavsethy/orgs", "repos_url": "https://api.github.com/users/abhinavsethy/repos", "events_url": "https://api.github.com/users/abhinavsethy/events{/privacy}", "received_events_url": "https://api.github.com/users/abhinavsethy/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	null	[]	null	[ "Hi! I've opened a [PR](https://huggingface.co/datasets/GEM/wiki_auto_asset_turk/discussions/5) with a fix. While waiting for it to be merged, you can load the dataset from the PR branch with `datasets.load_dataset(\"GEM/wiki_auto_asset_turk\", revision=\"refs/pr/5\")`", "Thanks Mario. Still getting the same issue though with the suggested fix\r\n\r\n#cat gem_sari.py\r\nimport datasets\r\nprint (datasets.__version__)\r\ndataset =datasets.load_dataset(\"GEM/wiki_auto_asset_turk\", revision=\"refs/pr/5\")\r\n\r\nEnd up with \r\n File \"/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/datasets/load.py\", line 2582, in load_dataset\r\n builder_instance.download_and_prepare(\r\n File \"/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/datasets/builder.py\", line 1005, in download_and_prepare\r\n self._download_and_prepare(\r\n File \"/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/datasets/builder.py\", line 1767, in _download_and_prepare\r\n super()._download_and_prepare(\r\n File \"/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/datasets/builder.py\", line 1100, in _download_and_prepare\r\n self._prepare_split(split_generator, **prepare_split_kwargs)\r\n File \"/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/datasets/builder.py\", line 1565, in _prepare_split\r\n split_info = self.info.splits[split_generator.name]\r\n ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^\r\n File \"/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/datasets/splits.py\", line 532, in __getitem__\r\n instructions = make_file_instructions(\r\n ^^^^^^^^^^^^^^^^^^^^^^^\r\n File \"/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/datasets/arrow_reader.py\", line 121, in make_file_instructions\r\n info.name: filenames_for_dataset_split(\r\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\r\n File \"/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/datasets/naming.py\", line 72, in filenames_for_dataset_split\r\n prefix = os.path.join(path, prefix)\r\n ^^^^^^^^^^^^^^^^^^^^^^^^^^\r\n File \"<frozen posixpath>\", line 76, in join\r\nTypeError: expected str, bytes or os.PathLike object, not NoneType", "Hmm, that's weird. Maybe try deleting the cache with `!rm -rf ~/.cache/huggingface/datasets` and then re-download.", "Tried that a couple of time. It does download the data fresh but end up with same error. Is there a way to see if its using the right version ?", "You can check the version with `python -c \"import datasets; print(datasets.__version__)\"`", "the datasets version is 2.18. \r\n\r\nI wanted to see if the command datasets.load_dataset(\"GEM/wiki_auto_asset_turk\", revision=\"refs/pr/5\") is using the right revision (refs/pr/5). \r\n\r\n\r\n\r\n\r\n\r\n ", "Still have this problem", "The issue is fixed once the fixing PR has been merged and the dataset has been converted to Parquet.\r\n\r\nIf the problem persists on your side, you should update your `datasets` library:\r\n```shell\r\npip install -U datasets\r\n```\r\nAnd if you have already the latest version of `datasets`, then you need to delete the old version of this dataset in your cache:\r\n```shell\r\nrm -fr ~/.cache/huggingface/datasets/GEM___wiki_auto_asset_turk\r\nrm -fr ~/.cache/huggingface/modules/datasets_modules/datasets/GEM--wiki_auto_asset_turk\r\n```" ]	2024-04-26T00:08:47	2024-05-29T13:54:03	2024-04-26T16:12:29	NONE	null	null	null	### Describe the bug I am unable to load the wiki_auto_asset_turk dataset. I get a fatal error while trying to access wiki_auto_asset_turk and load it with datasets.load_dataset. The error (TypeError: expected str, bytes or os.PathLike object, not NoneType) is from filenames_for_dataset_split in a os.path.join call >>import datasets >>print (datasets.__version__) >>dataset = datasets.load_dataset("GEM/wiki_auto_asset_turk") System output: Generating train split: 100%\|█\| 483801/483801 [00:03<00:00, 127164.26 examples/s Generating validation split: 100%\|█\| 20000/20000 [00:00<00:00, 116052.94 example Generating test_asset split: 100%\|██\| 359/359 [00:00<00:00, 76155.93 examples/s] Generating test_turk split: 100%\|███\| 359/359 [00:00<00:00, 87691.76 examples/s] Traceback (most recent call last): File "/Users/abhinav.sethy/Code/openai_evals/evals/evals/grammarly_tasks/gem_sari.py", line 3, in <module> dataset = datasets.load_dataset("GEM/wiki_auto_asset_turk") ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/datasets/load.py", line 2582, in load_dataset builder_instance.download_and_prepare( File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/datasets/builder.py", line 1005, in download_and_prepare self._download_and_prepare( File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/datasets/builder.py", line 1767, in _download_and_prepare super()._download_and_prepare( File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/datasets/builder.py", line 1100, in _download_and_prepare self._prepare_split(split_generator, **prepare_split_kwargs) File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/datasets/builder.py", line 1565, in _prepare_split split_info = self.info.splits[split_generator.name] ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^ File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/datasets/splits.py", line 532, in __getitem__ instructions = make_file_instructions( ^^^^^^^^^^^^^^^^^^^^^^^ File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/datasets/arrow_reader.py", line 121, in make_file_instructions info.name: filenames_for_dataset_split( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/Library/Frameworks/Python.framework/Versions/3.12/lib/python3.12/site-packages/datasets/naming.py", line 72, in filenames_for_dataset_split prefix = os.path.join(path, prefix) ^^^^^^^^^^^^^^^^^^^^^^^^^^ File "<frozen posixpath>", line 76, in join TypeError: expected str, bytes or os.PathLike object, not NoneType ### Steps to reproduce the bug import datasets print (datasets.__version__) dataset = datasets.load_dataset("GEM/wiki_auto_asset_turk") ### Expected behavior Should be able to load the dataset without any issues ### Environment info datasets version 2.18.0 (was able to reproduce bug with older versions 2.16 and 2.14 also) Python 3.12.0	{ "login": "mariosasko", "id": 47462742, "node_id": "MDQ6VXNlcjQ3NDYyNzQy", "avatar_url": "https://avatars.githubusercontent.com/u/47462742?v=4", "gravatar_id": "", "url": "https://api.github.com/users/mariosasko", "html_url": "https://github.com/mariosasko", "followers_url": "https://api.github.com/users/mariosasko/followers", "following_url": "https://api.github.com/users/mariosasko/following{/other_user}", "gists_url": "https://api.github.com/users/mariosasko/gists{/gist_id}", "starred_url": "https://api.github.com/users/mariosasko/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/mariosasko/subscriptions", "organizations_url": "https://api.github.com/users/mariosasko/orgs", "repos_url": "https://api.github.com/users/mariosasko/repos", "events_url": "https://api.github.com/users/mariosasko/events{/privacy}", "received_events_url": "https://api.github.com/users/mariosasko/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6841/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6841/timeline	null	completed	false
https://api.github.com/repos/huggingface/datasets/issues/6840	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6840/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6840/comments	https://api.github.com/repos/huggingface/datasets/issues/6840/events	https://github.com/huggingface/datasets/issues/6840	2,264,604,766	I_kwDODunzps6G-yBe	6,840	Delete uploaded files from the UI	{ "login": "saicharan2804", "id": 62512681, "node_id": "MDQ6VXNlcjYyNTEyNjgx", "avatar_url": "https://avatars.githubusercontent.com/u/62512681?v=4", "gravatar_id": "", "url": "https://api.github.com/users/saicharan2804", "html_url": "https://github.com/saicharan2804", "followers_url": "https://api.github.com/users/saicharan2804/followers", "following_url": "https://api.github.com/users/saicharan2804/following{/other_user}", "gists_url": "https://api.github.com/users/saicharan2804/gists{/gist_id}", "starred_url": "https://api.github.com/users/saicharan2804/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/saicharan2804/subscriptions", "organizations_url": "https://api.github.com/users/saicharan2804/orgs", "repos_url": "https://api.github.com/users/saicharan2804/repos", "events_url": "https://api.github.com/users/saicharan2804/events{/privacy}", "received_events_url": "https://api.github.com/users/saicharan2804/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[ { "id": 1935892871, "node_id": "MDU6TGFiZWwxOTM1ODkyODcx", "url": "https://api.github.com/repos/huggingface/datasets/labels/enhancement", "name": "enhancement", "color": "a2eeef", "default": true, "description": "New feature or request" } ]	open	false	null	[]	null	[]	2024-04-25T22:33:57	2024-04-25T22:33:57	null	NONE	null	null	null	### Feature request Once a file is uploaded and the commit is made, I am unable to delete individual files without completely deleting the whole dataset via the website UI. ### Motivation Would be a useful addition ### Your contribution Would love to help out with some guidance	null	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6840/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6840/timeline	null	null	false
https://api.github.com/repos/huggingface/datasets/issues/6839	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6839/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6839/comments	https://api.github.com/repos/huggingface/datasets/issues/6839/events	https://github.com/huggingface/datasets/pull/6839	2,263,761,062	PR_kwDODunzps5tvC1c	6,839	Remove token arg from CLI examples	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	null	[]	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6839). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005311 / 0.011353 (-0.006042) \| 0.003691 / 0.011008 (-0.007317) \| 0.063714 / 0.038508 (0.025206) \| 0.030875 / 0.023109 (0.007766) \| 0.251210 / 0.275898 (-0.024688) \| 0.280539 / 0.323480 (-0.042941) \| 0.004262 / 0.007986 (-0.003724) \| 0.002723 / 0.004328 (-0.001606) \| 0.049487 / 0.004250 (0.045237) \| 0.045655 / 0.037052 (0.008603) \| 0.264399 / 0.258489 (0.005910) \| 0.306613 / 0.293841 (0.012772) \| 0.028513 / 0.128546 (-0.100033) \| 0.010726 / 0.075646 (-0.064921) \| 0.210601 / 0.419271 (-0.208670) \| 0.036918 / 0.043533 (-0.006614) \| 0.257872 / 0.255139 (0.002733) \| 0.278951 / 0.283200 (-0.004249) \| 0.017900 / 0.141683 (-0.123783) \| 1.096749 / 1.452155 (-0.355406) \| 1.152603 / 1.492716 (-0.340113) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.095193 / 0.018006 (0.077187) \| 0.303919 / 0.000490 (0.303429) \| 0.000226 / 0.000200 (0.000026) \| 0.000052 / 0.000054 (-0.000002) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.018558 / 0.037411 (-0.018853) \| 0.061106 / 0.014526 (0.046580) \| 0.076233 / 0.176557 (-0.100323) \| 0.122402 / 0.737135 (-0.614734) \| 0.075579 / 0.296338 (-0.220760) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.283586 / 0.215209 (0.068377) \| 2.766179 / 2.077655 (0.688524) \| 1.481069 / 1.504120 (-0.023051) \| 1.355004 / 1.541195 (-0.186191) \| 1.392940 / 1.468490 (-0.075550) \| 0.578878 / 4.584777 (-4.005899) \| 2.432890 / 3.745712 (-1.312822) \| 2.837912 / 5.269862 (-2.431949) \| 1.762803 / 4.565676 (-2.802873) \| 0.063339 / 0.424275 (-0.360937) \| 0.005392 / 0.007607 (-0.002215) \| 0.340271 / 0.226044 (0.114227) \| 3.388371 / 2.268929 (1.119443) \| 1.862622 / 55.444624 (-53.582002) \| 1.543209 / 6.876477 (-5.333268) \| 1.569858 / 2.142072 (-0.572215) \| 0.651487 / 4.805227 (-4.153740) \| 0.119048 / 6.500664 (-6.381616) \| 0.042309 / 0.075469 (-0.033160) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.991161 / 1.841788 (-0.850627) \| 11.778857 / 8.074308 (3.704549) \| 9.586019 / 10.191392 (-0.605373) \| 0.148093 / 0.680424 (-0.532331) \| 0.014301 / 0.534201 (-0.519900) \| 0.287983 / 0.579283 (-0.291301) \| 0.266070 / 0.434364 (-0.168293) \| 0.328261 / 0.540337 (-0.212076) \| 0.417908 / 1.386936 (-0.969028) \|\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005252 / 0.011353 (-0.006100) \| 0.003740 / 0.011008 (-0.007268) \| 0.049622 / 0.038508 (0.011114) \| 0.030040 / 0.023109 (0.006931) \| 0.262224 / 0.275898 (-0.013674) \| 0.312216 / 0.323480 (-0.011264) \| 0.004213 / 0.007986 (-0.003773) \| 0.002737 / 0.004328 (-0.001592) \| 0.049159 / 0.004250 (0.044908) \| 0.041060 / 0.037052 (0.004008) \| 0.275826 / 0.258489 (0.017337) \| 0.301879 / 0.293841 (0.008038) \| 0.029364 / 0.128546 (-0.099182) \| 0.010453 / 0.075646 (-0.065193) \| 0.058095 / 0.419271 (-0.361176) \| 0.032898 / 0.043533 (-0.010635) \| 0.263876 / 0.255139 (0.008737) \| 0.281686 / 0.283200 (-0.001514) \| 0.018711 / 0.141683 (-0.122971) \| 1.126056 / 1.452155 (-0.326098) \| 1.185125 / 1.492716 (-0.307591) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.094153 / 0.018006 (0.076147) \| 0.300719 / 0.000490 (0.300229) \| 0.000207 / 0.000200 (0.000007) \| 0.000048 / 0.000054 (-0.000006) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.022610 / 0.037411 (-0.014801) \| 0.075502 / 0.014526 (0.060977) \| 0.088858 / 0.176557 (-0.087699) \| 0.129421 / 0.737135 (-0.607714) \| 0.089331 / 0.296338 (-0.207007) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.291595 / 0.215209 (0.076386) \| 2.864377 / 2.077655 (0.786722) \| 1.543387 / 1.504120 (0.039267) \| 1.404273 / 1.541195 (-0.136922) \| 1.421964 / 1.468490 (-0.046526) \| 0.579275 / 4.584777 (-4.005502) \| 0.979212 / 3.745712 (-2.766500) \| 2.822043 / 5.269862 (-2.447818) \| 1.745015 / 4.565676 (-2.820661) \| 0.064626 / 0.424275 (-0.359649) \| 0.005006 / 0.007607 (-0.002601) \| 0.345509 / 0.226044 (0.119464) \| 3.410369 / 2.268929 (1.141440) \| 1.875930 / 55.444624 (-53.568694) \| 1.600841 / 6.876477 (-5.275636) \| 1.611818 / 2.142072 (-0.530254) \| 0.662277 / 4.805227 (-4.142950) \| 0.117861 / 6.500664 (-6.382803) \| 0.041061 / 0.075469 (-0.034408) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 1.007834 / 1.841788 (-0.833954) \| 12.345653 / 8.074308 (4.271345) \| 9.775237 / 10.191392 (-0.416155) \| 0.135166 / 0.680424 (-0.545258) \| 0.016799 / 0.534201 (-0.517402) \| 0.289235 / 0.579283 (-0.290048) \| 0.126196 / 0.434364 (-0.308168) \| 0.382905 / 0.540337 (-0.157432) \| 0.435248 / 1.386936 (-0.951688) \|\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#22bf5388748611a9255d8e17218d36d2f799f182 \"CML watermark\")\n" ]	2024-04-25T14:36:58	2024-04-26T17:03:51	2024-04-26T16:57:40	MEMBER	null	false	{ "url": "https://api.github.com/repos/huggingface/datasets/pulls/6839", "html_url": "https://github.com/huggingface/datasets/pull/6839", "diff_url": "https://github.com/huggingface/datasets/pull/6839.diff", "patch_url": "https://github.com/huggingface/datasets/pull/6839.patch", "merged_at": "2024-04-26T16:57:40" }	Remove token arg from CLI examples. Fix #6838. CC: @Wauplin	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6839/reactions", "total_count": 1, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 1, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6839/timeline	null	null	true
https://api.github.com/repos/huggingface/datasets/issues/6838	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6838/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6838/comments	https://api.github.com/repos/huggingface/datasets/issues/6838/events	https://github.com/huggingface/datasets/issues/6838	2,263,674,843	I_kwDODunzps6G7O_b	6,838	Remove token arg from CLI examples	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[ { "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false } ]	null	[]	2024-04-25T14:00:38	2024-04-26T16:57:41	2024-04-26T16:57:41	MEMBER	null	null	null	As suggested by @Wauplin, see: https://github.com/huggingface/datasets/pull/6831#discussion_r1579492603 > I would not advertise the --token arg in the example as this shouldn't be the recommended way (best to login with env variable or huggingface-cli login)	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6838/reactions", "total_count": 1, "+1": 1, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6838/timeline	null	completed	false
https://api.github.com/repos/huggingface/datasets/issues/6837	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6837/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6837/comments	https://api.github.com/repos/huggingface/datasets/issues/6837/events	https://github.com/huggingface/datasets/issues/6837	2,263,273,983	I_kwDODunzps6G5tH_	6,837	Cannot use cached dataset without Internet connection (or when servers are down)	{ "login": "DionisMuzenitov", "id": 112088378, "node_id": "U_kgDOBq5VOg", "avatar_url": "https://avatars.githubusercontent.com/u/112088378?v=4", "gravatar_id": "", "url": "https://api.github.com/users/DionisMuzenitov", "html_url": "https://github.com/DionisMuzenitov", "followers_url": "https://api.github.com/users/DionisMuzenitov/followers", "following_url": "https://api.github.com/users/DionisMuzenitov/following{/other_user}", "gists_url": "https://api.github.com/users/DionisMuzenitov/gists{/gist_id}", "starred_url": "https://api.github.com/users/DionisMuzenitov/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/DionisMuzenitov/subscriptions", "organizations_url": "https://api.github.com/users/DionisMuzenitov/orgs", "repos_url": "https://api.github.com/users/DionisMuzenitov/repos", "events_url": "https://api.github.com/users/DionisMuzenitov/events{/privacy}", "received_events_url": "https://api.github.com/users/DionisMuzenitov/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	open	false	null	[]	null	[ "There are 2 workarounds, tho:\r\n1. Download datasets from web and just load them locally\r\n2. Use metadata directly (temporal solution, since metadata can change)\r\n```\r\nimport datasets\r\nfrom datasets.data_files import DataFilesDict, DataFilesList\r\n\r\ndata_files_list = DataFilesList(\r\n [\r\n \"hf://datasets/allenai/c4@1588ec454efa1a09f29cd18ddd04fe05fc8653a2/en/c4-train.00000-of-01024.json.gz\"\r\n ],\r\n [(\"allenai/c4\", \"1588ec454efa1a09f29cd18ddd04fe05fc8653a2\")],\r\n)\r\ndata_files = DataFilesDict({\"train\": data_files_list})\r\nc4_dataset = datasets.load_dataset(\r\n path=\"allenai/c4\",\r\n data_files=data_files,\r\n split=\"train\",\r\n cache_dir=\"/datesets/cache\",\r\n download_mode=\"reuse_cache_if_exists\",\r\n token=False,\r\n)\r\n```\r\nSecond solution also shows where to find the bug. I suggest that the hashing functions should always use only original parameter `data_files`, and not the one they get after connecting to the server and creating `DataFilesDict`", "Hi! You need to set the `HF_DATASETS_OFFLINE` env variable to `1` to load cached datasets offline, as explained in the docs [here](https://huggingface.co/docs/datasets/v2.19.0/en/loading#offline).", "Just tested. It doesn't work, because of the exact problem I described above: hash of dataset config is different.\r\nThe only error difference is the reason why it cannot connect to HuggingFace (now it's 'offline mode is enabled')\r\n![image](https://github.com/huggingface/datasets/assets/112088378/1a7e1720-d711-46e3-9c90-53d52c441e68)\r\n", "Met a pretty similar issue here, as I manually load the dataset into ~/.cache and try to let `load_dataset` detect it automatically, but it will always try reach hub even I set `HF_DATASETS_OFFLINE` to 1. Have you solved it? ", "same here!" ]	2024-04-25T10:48:20	2024-10-20T12:36:54	null	NONE	null	null	null	### Describe the bug I want to be able to use cached dataset from HuggingFace even when I have no Internet connection (or when HuggingFace servers are down, or my company has network issues). The problem why I can't use it: `data_files` argument from `datasets.load_dataset()` function get it updates from the server before calculating hash for caching. As a result, when I run the same code with and without Internet I get different dataset configuration directory name. ### Steps to reproduce the bug ``` import datasets c4_dataset = datasets.load_dataset( path="allenai/c4", data_files={"train": "en/c4-train.00000-of-01024.json.gz"}, split="train", cache_dir="/datesets/cache", download_mode="reuse_cache_if_exists", token=False, ) ``` 1. Run this code with the Internet. 2. Run the same code without the Internet. ### Expected behavior When running without the Internet connection, the loader should be able to get dataset from cache ### Environment info - `datasets` version: 2.19.0 - Platform: Windows-10-10.0.19044-SP0 - Python version: 3.10.13 - `huggingface_hub` version: 0.22.2 - PyArrow version: 16.0.0 - Pandas version: 1.5.3 - `fsspec` version: 2023.12.2	null	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6837/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6837/timeline	null	null	false
https://api.github.com/repos/huggingface/datasets/issues/6836	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6836/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6836/comments	https://api.github.com/repos/huggingface/datasets/issues/6836/events	https://github.com/huggingface/datasets/issues/6836	2,262,249,919	I_kwDODunzps6G1zG_	6,836	ExpectedMoreSplits error on load_dataset when upgrading to 2.19.0	{ "login": "ebsmothers", "id": 24319399, "node_id": "MDQ6VXNlcjI0MzE5Mzk5", "avatar_url": "https://avatars.githubusercontent.com/u/24319399?v=4", "gravatar_id": "", "url": "https://api.github.com/users/ebsmothers", "html_url": "https://github.com/ebsmothers", "followers_url": "https://api.github.com/users/ebsmothers/followers", "following_url": "https://api.github.com/users/ebsmothers/following{/other_user}", "gists_url": "https://api.github.com/users/ebsmothers/gists{/gist_id}", "starred_url": "https://api.github.com/users/ebsmothers/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/ebsmothers/subscriptions", "organizations_url": "https://api.github.com/users/ebsmothers/orgs", "repos_url": "https://api.github.com/users/ebsmothers/repos", "events_url": "https://api.github.com/users/ebsmothers/events{/privacy}", "received_events_url": "https://api.github.com/users/ebsmothers/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	open	false	null	[]	null	[ "Get same error on same datasets too.", "+1", "same error" ]	2024-04-24T21:52:35	2024-05-14T04:08:19	null	NONE	null	null	null	### Describe the bug Hi there, thanks for the great library! We have been using it a lot in torchtune and it's been a huge help for us. Regarding the bug: the same call to `load_dataset` errors with `ExpectedMoreSplits` in 2.19.0 after working fine in 2.18.0. Full details given in the repro below. ### Steps to reproduce the bug On 2.18.0, things work fine: ``` # First clear the locally cached dataset rm -r ~/.cache/huggingface/datasets/lvwerra___stack-exchange-paired pip install "datasets==2.18.0" python3 >>> from datasets import load_dataset >>> dataset = load_dataset('lvwerra/stack-exchange-paired', split='train', data_dir='data/rl') ``` On 2.19.0, they do not: ``` # First clear the locally cached dataset rm -r ~/.cache/huggingface/datasets/lvwerra___stack-exchange-paired pip install "datasets==2.19.0" python3 >>> from datasets import load_dataset >>> dataset = load_dataset('lvwerra/stack-exchange-paired', split='train', data_dir='data/rl') ``` The stack trace I see from the 2.19.0 version of load_dataset can be seen [here](https://gist.github.com/ebsmothers/f9b1f1949bee7030a8d7bb8a491550d2). (Maybe unsurprising but) notably if I do not delete the cache first I am able to load the dataset successfully. So based on this I suspect the cause is somewhere in the download logic. ### Expected behavior Download the dataset successfully :) ### Environment info - `datasets` version: 2.19.0 - Platform: Linux-5.12.0-0_fbk16_zion_7661_geb00762ce6d2-x86_64-with-glibc2.34 - Python version: 3.11.9 - `huggingface_hub` version: 0.22.2 - PyArrow version: 16.0.0 - Pandas version: 2.2.2 - `fsspec` version: 2024.3.1	null	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6836/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6836/timeline	null	null	false
https://api.github.com/repos/huggingface/datasets/issues/6835	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6835/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6835/comments	https://api.github.com/repos/huggingface/datasets/issues/6835/events	https://github.com/huggingface/datasets/pull/6835	2,261,079,263	PR_kwDODunzps5tl2fc	6,835	Support pyarrow LargeListType	{ "login": "Modexus", "id": 37351874, "node_id": "MDQ6VXNlcjM3MzUxODc0", "avatar_url": "https://avatars.githubusercontent.com/u/37351874?v=4", "gravatar_id": "", "url": "https://api.github.com/users/Modexus", "html_url": "https://github.com/Modexus", "followers_url": "https://api.github.com/users/Modexus/followers", "following_url": "https://api.github.com/users/Modexus/following{/other_user}", "gists_url": "https://api.github.com/users/Modexus/gists{/gist_id}", "starred_url": "https://api.github.com/users/Modexus/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/Modexus/subscriptions", "organizations_url": "https://api.github.com/users/Modexus/orgs", "repos_url": "https://api.github.com/users/Modexus/repos", "events_url": "https://api.github.com/users/Modexus/events{/privacy}", "received_events_url": "https://api.github.com/users/Modexus/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	null	[]	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6835). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "Fixed the conversion from `pyarrow` to `python` `Sequence` features. \r\n\r\nThere is still an issue that if `features` are passed the `Sequence` always forces conversion to `ListArray`.\r\nThis probably causes issues if the `LargeListArray` is actually needed.\r\n\r\nThere doesn't seem to be a great solution since this list is created solely on the `schema` for `Sequence`.\r\nOne solution would be to always use `LargeListArray` instead.\r\n", "I am retaking this PR because we would like to have this feature implemented." ]	2024-04-24T11:34:24	2024-08-12T14:43:47	2024-08-12T14:43:47	CONTRIBUTOR	null	false	{ "url": "https://api.github.com/repos/huggingface/datasets/pulls/6835", "html_url": "https://github.com/huggingface/datasets/pull/6835", "diff_url": "https://github.com/huggingface/datasets/pull/6835.diff", "patch_url": "https://github.com/huggingface/datasets/pull/6835.patch", "merged_at": null }	Fixes #6834	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6835/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6835/timeline	null	null	true
https://api.github.com/repos/huggingface/datasets/issues/6834	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6834/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6834/comments	https://api.github.com/repos/huggingface/datasets/issues/6834/events	https://github.com/huggingface/datasets/issues/6834	2,261,078,104	I_kwDODunzps6GxVBY	6,834	largelisttype not supported (.from_polars())	{ "login": "Modexus", "id": 37351874, "node_id": "MDQ6VXNlcjM3MzUxODc0", "avatar_url": "https://avatars.githubusercontent.com/u/37351874?v=4", "gravatar_id": "", "url": "https://api.github.com/users/Modexus", "html_url": "https://github.com/Modexus", "followers_url": "https://api.github.com/users/Modexus/followers", "following_url": "https://api.github.com/users/Modexus/following{/other_user}", "gists_url": "https://api.github.com/users/Modexus/gists{/gist_id}", "starred_url": "https://api.github.com/users/Modexus/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/Modexus/subscriptions", "organizations_url": "https://api.github.com/users/Modexus/orgs", "repos_url": "https://api.github.com/users/Modexus/repos", "events_url": "https://api.github.com/users/Modexus/events{/privacy}", "received_events_url": "https://api.github.com/users/Modexus/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[ { "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false } ]	null	[]	2024-04-24T11:33:43	2024-08-12T14:43:46	2024-08-12T14:43:46	CONTRIBUTOR	null	null	null	### Describe the bug The following code fails because LargeListType is not supported. This is especially a problem for .from_polars since polars uses LargeListType. ### Steps to reproduce the bug ```python import datasets import polars as pl df = pl.DataFrame({"list": [[]]}) datasets.Dataset.from_polars(df) ``` ### Expected behavior Convert LargeListType to list. ### Environment info - `datasets` version: 2.19.1.dev0 - Platform: Linux-6.8.7-200.fc39.x86_64-x86_64-with-glibc2.38 - Python version: 3.12.2 - `huggingface_hub` version: 0.22.2 - PyArrow version: 16.0.0 - Pandas version: 2.1.4 - `fsspec` version: 2024.3.1	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6834/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6834/timeline	null	completed	false
https://api.github.com/repos/huggingface/datasets/issues/6833	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6833/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6833/comments	https://api.github.com/repos/huggingface/datasets/issues/6833/events	https://github.com/huggingface/datasets/issues/6833	2,259,731,274	I_kwDODunzps6GsMNK	6,833	Super slow iteration with trivial custom transform	{ "login": "xslittlegrass", "id": 2780075, "node_id": "MDQ6VXNlcjI3ODAwNzU=", "avatar_url": "https://avatars.githubusercontent.com/u/2780075?v=4", "gravatar_id": "", "url": "https://api.github.com/users/xslittlegrass", "html_url": "https://github.com/xslittlegrass", "followers_url": "https://api.github.com/users/xslittlegrass/followers", "following_url": "https://api.github.com/users/xslittlegrass/following{/other_user}", "gists_url": "https://api.github.com/users/xslittlegrass/gists{/gist_id}", "starred_url": "https://api.github.com/users/xslittlegrass/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/xslittlegrass/subscriptions", "organizations_url": "https://api.github.com/users/xslittlegrass/orgs", "repos_url": "https://api.github.com/users/xslittlegrass/repos", "events_url": "https://api.github.com/users/xslittlegrass/events{/privacy}", "received_events_url": "https://api.github.com/users/xslittlegrass/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	open	false	null	[]	null	[ "Similar issue in text process \r\n\r\n```python\r\n\r\ntokenizer=AutoTokenizer.from_pretrained(model_dir[args.model])\r\ntrain_dataset=datasets.load_from_disk(dataset_dir[args.dataset],keep_in_memory=True)['train']\r\ntrain_dataset=train_dataset.map(partial(dname2func[args.dataset],tokenizer=tokenizer),batched=True,num_proc =50,remove_columns=train_dataset.features.keys(),desc='tokenize',keep_in_memory=True)\r\n\r\n```\r\nAfter this train_dataset will be like\r\n```python\r\nDataset({\r\n features: ['input_ids', 'labels'],\r\n num_rows: 51760\r\n})\r\n```\r\nIn which input_ids and labels are both List[int]\r\nHowever, per iter on dataset cost 7.412479639053345s ……？\r\n```python\r\nfor j in tqdm(range(len(train_dataset)),desc='first stage'):\r\n input_id,label=train_dataset['input_ids'][j],train_dataset['labels'][j]\r\n\r\n``` ", "The transform currently replaces the numpy formatting.\r\n\r\nSo you're back to copying data to long python lists which is super slow.\r\n\r\nIt would be cool for the transform to not remove the formatting in this case, but this requires a few changes in the lib", "This also (somewhat surprisingly) affects iterable datasets, making map very challenging to use for data with large arrays, unless there is some workaround?", "For iterable datasets you should be able to do this without slow downs\r\n```python\r\nds = ds.with_format(\"arrow\").map(...)\r\n```\r\n\r\nI haven't tried with \"numpy\" though, maybe there is a step that does Arrow -> List -> NumPy instead of Arrow -> NumPy directly. If it's the case it would be cool to avoid that", "Thanks! this works for me\r\n\r\nHowever, it raises an error if batched=False and map batch_size isn't explicitly set to 1 due to map's default batch_size affecting the batch size of the RebatchedArrowExamplesIterable - is this a bug?", "Thanks for the fix @alex-hh !", "opened a new issue for the numpy slowdown #7206 " ]	2024-04-23T20:40:59	2024-10-08T15:41:18	null	NONE	null	null	null	### Describe the bug Dataset is 10X slower when applying trivial transforms: ``` import time import numpy as np from datasets import Dataset, Features, Array2D a = np.zeros((800, 800)) a = np.stack([a] * 1000) features = Features({"a": Array2D(shape=(800, 800), dtype="uint8")}) ds1 = Dataset.from_dict({"a": a}, features=features).with_format('numpy') def transform(batch): return batch ds2 = ds1.with_transform(transform) %time sum(1 for _ in ds1) %time sum(1 for _ in ds2) ``` ``` CPU times: user 472 ms, sys: 319 ms, total: 791 ms Wall time: 794 ms CPU times: user 9.32 s, sys: 443 ms, total: 9.76 s Wall time: 9.78 s ``` In my real code I'm using set_transform to apply some post-processing on-the-fly for the 2d array, but it significantly slows down the dataset even if the transform itself is trivial. Related issue: https://github.com/huggingface/datasets/issues/5841 ### Steps to reproduce the bug Use code in the description to reproduce. ### Expected behavior Trivial custom transform in the example should not slowdown the dataset iteration. ### Environment info - `datasets` version: 2.18.0 - Platform: Linux-5.15.0-79-generic-x86_64-with-glibc2.35 - Python version: 3.11.4 - `huggingface_hub` version: 0.20.2 - PyArrow version: 15.0.0 - Pandas version: 1.5.3 - `fsspec` version: 2023.12.2	null	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6833/reactions", "total_count": 3, "+1": 3, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6833/timeline	null	null	false
https://api.github.com/repos/huggingface/datasets/issues/6832	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6832/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6832/comments	https://api.github.com/repos/huggingface/datasets/issues/6832/events	https://github.com/huggingface/datasets/pull/6832	2,258,761,447	PR_kwDODunzps5teFoJ	6,832	Support downloading specific splits in `load_dataset`	{ "login": "mariosasko", "id": 47462742, "node_id": "MDQ6VXNlcjQ3NDYyNzQy", "avatar_url": "https://avatars.githubusercontent.com/u/47462742?v=4", "gravatar_id": "", "url": "https://api.github.com/users/mariosasko", "html_url": "https://github.com/mariosasko", "followers_url": "https://api.github.com/users/mariosasko/followers", "following_url": "https://api.github.com/users/mariosasko/following{/other_user}", "gists_url": "https://api.github.com/users/mariosasko/gists{/gist_id}", "starred_url": "https://api.github.com/users/mariosasko/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/mariosasko/subscriptions", "organizations_url": "https://api.github.com/users/mariosasko/orgs", "repos_url": "https://api.github.com/users/mariosasko/repos", "events_url": "https://api.github.com/users/mariosasko/events{/privacy}", "received_events_url": "https://api.github.com/users/mariosasko/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	open	false	null	[]	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6832). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "Friendly ping on this! This feature would be really helpful and useful to me (and likely others with limited download speed and storage space!). Thanks so much!", "No one is working on this atm afaik :/", "No worries! I've patched the ImageNet dataset in: <https://huggingface.co/datasets/ILSVRC/imagenet-1k/blob/refs%2Fpr%2F20/imagenet-1k.py> \r\n\r\nTogether with:\r\n\r\n```python\r\ndataset = load_dataset(\r\n \"ILSVRC/imagenet-1k\",\r\n split=\"validation\",\r\n data_files={\"val\": \"data/val_images.tar.gz\"},\r\n revision=\"refs/pr/20\",\r\n trust_remote_code=True,\r\n download_config=DownloadConfig(resume_download=True),\r\n verification_mode=VerificationMode.NO_CHECKS,\r\n )\r\n```\r\n\r\nIt only downloads the validation set this way (NO_CHECKS is a bit annoying because I'd rather have md5 checks, but I guess I can't have everything) ^^' The patch is not perfect, but it does the job.\r\n\r\n" ]	2024-04-23T12:32:27	2024-08-19T15:19:38	null	COLLABORATOR	null	false	{ "url": "https://api.github.com/repos/huggingface/datasets/pulls/6832", "html_url": "https://github.com/huggingface/datasets/pull/6832", "diff_url": "https://github.com/huggingface/datasets/pull/6832.diff", "patch_url": "https://github.com/huggingface/datasets/pull/6832.patch", "merged_at": null }	This PR builds on https://github.com/huggingface/datasets/pull/6639 to support downloading only the specified splits in `load_dataset`. For this to work, a builder's `_split_generators` need to be able to accept the requested splits (as a list) via a `splits` argument to avoid processing the non-requested ones. Also, the builder has to define a `_available_splits` method that lists all the possible `splits` values. Close https://github.com/huggingface/datasets/issues/4101, close https://github.com/huggingface/datasets/issues/2538 (I'm probably missing some) Should also make it possible to address https://github.com/huggingface/datasets/issues/6793	null	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6832/reactions", "total_count": 2, "+1": 2, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6832/timeline	null	null	true
https://api.github.com/repos/huggingface/datasets/issues/6831	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6831/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6831/comments	https://api.github.com/repos/huggingface/datasets/issues/6831/events	https://github.com/huggingface/datasets/pull/6831	2,258,537,405	PR_kwDODunzps5tdTy_	6,831	Add docs about the CLI	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	null	[]	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6831). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "Concretely, the docs about convert_to_parquet are here: https://moon-ci-docs.huggingface.co/docs/datasets/pr_6831/en/cli#convert-to-parquet", "There is an issue with the example snippet when copy/pasting it: the leading shell dollar sign is also copied. I guess they will not like to fix it in the backend: currently they only support Python code snippets (with leading `>>>` or `...`), as they appear in the IPython interactive console.\r\n\r\nWhat do you suggest, @severo?" ]	2024-04-23T10:41:03	2024-04-26T16:51:09	2024-04-25T10:44:10	MEMBER	null	false	{ "url": "https://api.github.com/repos/huggingface/datasets/pulls/6831", "html_url": "https://github.com/huggingface/datasets/pull/6831", "diff_url": "https://github.com/huggingface/datasets/pull/6831.diff", "patch_url": "https://github.com/huggingface/datasets/pull/6831.patch", "merged_at": "2024-04-25T10:44:10" }	Add docs about the CLI. Close #6830. CC: @severo	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6831/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6831/timeline	null	null	true
https://api.github.com/repos/huggingface/datasets/issues/6830	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6830/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6830/comments	https://api.github.com/repos/huggingface/datasets/issues/6830/events	https://github.com/huggingface/datasets/issues/6830	2,258,433,178	I_kwDODunzps6GnPSa	6,830	Add a doc page for the convert_to_parquet CLI	{ "login": "severo", "id": 1676121, "node_id": "MDQ6VXNlcjE2NzYxMjE=", "avatar_url": "https://avatars.githubusercontent.com/u/1676121?v=4", "gravatar_id": "", "url": "https://api.github.com/users/severo", "html_url": "https://github.com/severo", "followers_url": "https://api.github.com/users/severo/followers", "following_url": "https://api.github.com/users/severo/following{/other_user}", "gists_url": "https://api.github.com/users/severo/gists{/gist_id}", "starred_url": "https://api.github.com/users/severo/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/severo/subscriptions", "organizations_url": "https://api.github.com/users/severo/orgs", "repos_url": "https://api.github.com/users/severo/repos", "events_url": "https://api.github.com/users/severo/events{/privacy}", "received_events_url": "https://api.github.com/users/severo/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[ { "id": 1935892861, "node_id": "MDU6TGFiZWwxOTM1ODkyODYx", "url": "https://api.github.com/repos/huggingface/datasets/labels/documentation", "name": "documentation", "color": "0075ca", "default": true, "description": "Improvements or additions to documentation" } ]	closed	false	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[ { "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false } ]	null	[]	2024-04-23T09:49:04	2024-04-25T10:44:11	2024-04-25T10:44:11	COLLABORATOR	null	null	null	Follow-up to https://github.com/huggingface/datasets/pull/6795. Useful for https://github.com/huggingface/dataset-viewer/issues/2742. cc @albertvillanova	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6830/reactions", "total_count": 1, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 1, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6830/timeline	null	completed	false
https://api.github.com/repos/huggingface/datasets/issues/6829	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6829/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6829/comments	https://api.github.com/repos/huggingface/datasets/issues/6829/events	https://github.com/huggingface/datasets/issues/6829	2,258,424,577	I_kwDODunzps6GnNMB	6,829	Load and save from/to disk no longer accept pathlib.Path	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[ { "id": 1935892857, "node_id": "MDU6TGFiZWwxOTM1ODkyODU3", "url": "https://api.github.com/repos/huggingface/datasets/labels/bug", "name": "bug", "color": "d73a4a", "default": true, "description": "Something isn't working" } ]	open	false	null	[]	null	[]	2024-04-23T09:44:45	2024-04-23T09:44:46	null	MEMBER	null	null	null	Reported by @vttrifonov at https://github.com/huggingface/datasets/pull/6704#issuecomment-2071168296: > This change is breaking in > https://github.com/huggingface/datasets/blob/f96e74d5c633cd5435dd526adb4a74631eb05c43/src/datasets/arrow_dataset.py#L1515 > when the input is `pathlib.Path`. The issue is that `url_to_fs` expects a `str` and cannot deal with `Path`. `get_fs_token_paths` converts to `str` so it is not a problem This change was introduced in: - #6704	null	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6829/reactions", "total_count": 1, "+1": 1, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6829/timeline	null	null	false
https://api.github.com/repos/huggingface/datasets/issues/6828	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6828/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6828/comments	https://api.github.com/repos/huggingface/datasets/issues/6828/events	https://github.com/huggingface/datasets/pull/6828	2,258,420,421	PR_kwDODunzps5tc55y	6,828	Support PathLike input in save_to_disk / load_from_disk	{ "login": "lhoestq", "id": 42851186, "node_id": "MDQ6VXNlcjQyODUxMTg2", "avatar_url": "https://avatars.githubusercontent.com/u/42851186?v=4", "gravatar_id": "", "url": "https://api.github.com/users/lhoestq", "html_url": "https://github.com/lhoestq", "followers_url": "https://api.github.com/users/lhoestq/followers", "following_url": "https://api.github.com/users/lhoestq/following{/other_user}", "gists_url": "https://api.github.com/users/lhoestq/gists{/gist_id}", "starred_url": "https://api.github.com/users/lhoestq/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/lhoestq/subscriptions", "organizations_url": "https://api.github.com/users/lhoestq/orgs", "repos_url": "https://api.github.com/users/lhoestq/repos", "events_url": "https://api.github.com/users/lhoestq/events{/privacy}", "received_events_url": "https://api.github.com/users/lhoestq/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	open	false	null	[]	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6828). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update." ]	2024-04-23T09:42:38	2024-04-23T11:05:52	null	MEMBER	null	false	{ "url": "https://api.github.com/repos/huggingface/datasets/pulls/6828", "html_url": "https://github.com/huggingface/datasets/pull/6828", "diff_url": "https://github.com/huggingface/datasets/pull/6828.diff", "patch_url": "https://github.com/huggingface/datasets/pull/6828.patch", "merged_at": null }	null	null	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6828/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6828/timeline	null	null	true
https://api.github.com/repos/huggingface/datasets/issues/6827	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6827/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6827/comments	https://api.github.com/repos/huggingface/datasets/issues/6827/events	https://github.com/huggingface/datasets/issues/6827	2,254,011,833	I_kwDODunzps6GWX25	6,827	Loading a remote dataset fails in the last release (v2.19.0)	{ "login": "zrthxn", "id": 35369637, "node_id": "MDQ6VXNlcjM1MzY5NjM3", "avatar_url": "https://avatars.githubusercontent.com/u/35369637?v=4", "gravatar_id": "", "url": "https://api.github.com/users/zrthxn", "html_url": "https://github.com/zrthxn", "followers_url": "https://api.github.com/users/zrthxn/followers", "following_url": "https://api.github.com/users/zrthxn/following{/other_user}", "gists_url": "https://api.github.com/users/zrthxn/gists{/gist_id}", "starred_url": "https://api.github.com/users/zrthxn/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/zrthxn/subscriptions", "organizations_url": "https://api.github.com/users/zrthxn/orgs", "repos_url": "https://api.github.com/users/zrthxn/repos", "events_url": "https://api.github.com/users/zrthxn/events{/privacy}", "received_events_url": "https://api.github.com/users/zrthxn/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	open	false	null	[]	null	[]	2024-04-19T21:11:58	2024-04-19T21:13:42	null	NONE	null	null	null	While loading a dataset with multiple splits I get an error saying `Couldn't find file at <URL>` I am loading the dataset like so, nothing out of the ordinary. This dataset needs a token to access it. ``` token="hf_myhftoken-sdhbdsjgkhbd" load_dataset("speechcolab/gigaspeech", "test", cache_dir=f"gigaspeech/test", token=token) ``` I get the following error ![Screenshot 2024-04-19 at 11 03 07 PM](https://github.com/huggingface/datasets/assets/35369637/8dce757f-08ff-45dd-85b5-890fced7c5bc) Now you can see that the URL that it is trying to reach has the JSON object of the dataset split appended to the base URL. I think this may be due to a newly introduced issue. I did not have this issue with the previous version of the datasets. Everything was fine for me yesterday and after the release 12 hours ago, this seems to have broken. Also, the dataset in question runs custom code and I checked and there have been no commits to the dataset on Huggingface in 6 months. ### Steps to reproduce the bug Since this happened with one particular dataset for me, I am listing steps to use that dataset. 1. Open https://huggingface.co/datasets/speechcolab/gigaspeech and fill the form to get access. 2. Create a token on your huggingface account with read access. 3. Run the following line, substituing `<your_token_here>` with your token. ``` load_dataset("speechcolab/gigaspeech", "test", cache_dir=f"gigaspeech/test", token="<your_token_here>") ``` ### Expected behavior Be able to load the dataset in question. ### Environment info datasets == 2.19.0 python == 3.10 kernel == Linux 6.1.58+	null	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6827/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6827/timeline	null	null	false
https://api.github.com/repos/huggingface/datasets/issues/6826	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6826/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6826/comments	https://api.github.com/repos/huggingface/datasets/issues/6826/events	https://github.com/huggingface/datasets/pull/6826	2,252,445,242	PR_kwDODunzps5tJMZh	6,826	Set dev version	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	null	[]	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6826). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.004893 / 0.011353 (-0.006460) \| 0.003238 / 0.011008 (-0.007771) \| 0.063143 / 0.038508 (0.024635) \| 0.029770 / 0.023109 (0.006661) \| 0.229052 / 0.275898 (-0.046846) \| 0.254534 / 0.323480 (-0.068945) \| 0.003083 / 0.007986 (-0.004903) \| 0.002615 / 0.004328 (-0.001714) \| 0.049684 / 0.004250 (0.045434) \| 0.043745 / 0.037052 (0.006693) \| 0.248985 / 0.258489 (-0.009504) \| 0.275957 / 0.293841 (-0.017884) \| 0.027323 / 0.128546 (-0.101223) \| 0.010372 / 0.075646 (-0.065275) \| 0.206494 / 0.419271 (-0.212778) \| 0.035230 / 0.043533 (-0.008303) \| 0.234235 / 0.255139 (-0.020904) \| 0.252395 / 0.283200 (-0.030805) \| 0.019442 / 0.141683 (-0.122240) \| 1.130677 / 1.452155 (-0.321478) \| 1.161721 / 1.492716 (-0.330996) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.091659 / 0.018006 (0.073653) \| 0.301323 / 0.000490 (0.300833) \| 0.000212 / 0.000200 (0.000012) \| 0.000049 / 0.000054 (-0.000005) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.018360 / 0.037411 (-0.019051) \| 0.061101 / 0.014526 (0.046575) \| 0.072383 / 0.176557 (-0.104174) \| 0.117656 / 0.737135 (-0.619479) \| 0.073903 / 0.296338 (-0.222436) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.272768 / 0.215209 (0.057558) \| 2.655714 / 2.077655 (0.578059) \| 1.446254 / 1.504120 (-0.057866) \| 1.330543 / 1.541195 (-0.210652) \| 1.352527 / 1.468490 (-0.115964) \| 0.561428 / 4.584777 (-4.023349) \| 2.368182 / 3.745712 (-1.377530) \| 2.746508 / 5.269862 (-2.523353) \| 1.713972 / 4.565676 (-2.851705) \| 0.062046 / 0.424275 (-0.362229) \| 0.005427 / 0.007607 (-0.002180) \| 0.321652 / 0.226044 (0.095607) \| 3.181812 / 2.268929 (0.912883) \| 1.766778 / 55.444624 (-53.677846) \| 1.492502 / 6.876477 (-5.383975) \| 1.534658 / 2.142072 (-0.607415) \| 0.640372 / 4.805227 (-4.164856) \| 0.118180 / 6.500664 (-6.382484) \| 0.042698 / 0.075469 (-0.032771) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.993262 / 1.841788 (-0.848525) \| 11.512827 / 8.074308 (3.438518) \| 9.602140 / 10.191392 (-0.589252) \| 0.144723 / 0.680424 (-0.535701) \| 0.014122 / 0.534201 (-0.520079) \| 0.302211 / 0.579283 (-0.277072) \| 0.268026 / 0.434364 (-0.166338) \| 0.326524 / 0.540337 (-0.213813) \| 0.423781 / 1.386936 (-0.963155) \|\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005388 / 0.011353 (-0.005965) \| 0.003535 / 0.011008 (-0.007473) \| 0.050139 / 0.038508 (0.011631) \| 0.031813 / 0.023109 (0.008704) \| 0.269501 / 0.275898 (-0.006397) \| 0.294355 / 0.323480 (-0.029125) \| 0.004128 / 0.007986 (-0.003858) \| 0.002684 / 0.004328 (-0.001644) \| 0.049295 / 0.004250 (0.045045) \| 0.040129 / 0.037052 (0.003077) \| 0.282406 / 0.258489 (0.023917) \| 0.309822 / 0.293841 (0.015981) \| 0.028506 / 0.128546 (-0.100040) \| 0.010434 / 0.075646 (-0.065213) \| 0.057890 / 0.419271 (-0.361382) \| 0.032487 / 0.043533 (-0.011046) \| 0.270631 / 0.255139 (0.015492) \| 0.288734 / 0.283200 (0.005534) \| 0.018710 / 0.141683 (-0.122973) \| 1.151571 / 1.452155 (-0.300583) \| 1.195222 / 1.492716 (-0.297494) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.090939 / 0.018006 (0.072932) \| 0.300278 / 0.000490 (0.299788) \| 0.000202 / 0.000200 (0.000002) \| 0.000052 / 0.000054 (-0.000003) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.022036 / 0.037411 (-0.015376) \| 0.075131 / 0.014526 (0.060605) \| 0.087775 / 0.176557 (-0.088782) \| 0.125719 / 0.737135 (-0.611416) \| 0.088491 / 0.296338 (-0.207848) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.300363 / 0.215209 (0.085154) \| 2.931852 / 2.077655 (0.854197) \| 1.633688 / 1.504120 (0.129568) \| 1.512641 / 1.541195 (-0.028554) \| 1.527703 / 1.468490 (0.059213) \| 0.572781 / 4.584777 (-4.011996) \| 2.445950 / 3.745712 (-1.299762) \| 2.883667 / 5.269862 (-2.386195) \| 1.761396 / 4.565676 (-2.804280) \| 0.064422 / 0.424275 (-0.359853) \| 0.005332 / 0.007607 (-0.002275) \| 0.346730 / 0.226044 (0.120686) \| 3.443815 / 2.268929 (1.174886) \| 1.988677 / 55.444624 (-53.455948) \| 1.707688 / 6.876477 (-5.168789) \| 1.694216 / 2.142072 (-0.447856) \| 0.634834 / 4.805227 (-4.170393) \| 0.115044 / 6.500664 (-6.385620) \| 0.040853 / 0.075469 (-0.034616) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 1.009382 / 1.841788 (-0.832405) \| 12.327511 / 8.074308 (4.253203) \| 10.123296 / 10.191392 (-0.068097) \| 0.130770 / 0.680424 (-0.549654) \| 0.015548 / 0.534201 (-0.518653) \| 0.286650 / 0.579283 (-0.292633) \| 0.270267 / 0.434364 (-0.164097) \| 0.333485 / 0.540337 (-0.206852) \| 0.428288 / 1.386936 (-0.958648) \|\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#f96e74d5c633cd5435dd526adb4a74631eb05c43 \"CML watermark\")\n" ]	2024-04-19T08:51:42	2024-04-19T09:05:25	2024-04-19T08:52:14	MEMBER	null	false	{ "url": "https://api.github.com/repos/huggingface/datasets/pulls/6826", "html_url": "https://github.com/huggingface/datasets/pull/6826", "diff_url": "https://github.com/huggingface/datasets/pull/6826.diff", "patch_url": "https://github.com/huggingface/datasets/pull/6826.patch", "merged_at": "2024-04-19T08:52:13" }	null	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6826/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6826/timeline	null	null	true
https://api.github.com/repos/huggingface/datasets/issues/6825	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6825/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6825/comments	https://api.github.com/repos/huggingface/datasets/issues/6825/events	https://github.com/huggingface/datasets/pull/6825	2,252,404,599	PR_kwDODunzps5tJEMw	6,825	Release: 2.19.0	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	null	[]	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6825). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.004945 / 0.011353 (-0.006407) \| 0.003290 / 0.011008 (-0.007718) \| 0.062404 / 0.038508 (0.023896) \| 0.040056 / 0.023109 (0.016946) \| 0.246574 / 0.275898 (-0.029324) \| 0.275074 / 0.323480 (-0.048406) \| 0.004118 / 0.007986 (-0.003867) \| 0.002604 / 0.004328 (-0.001724) \| 0.048618 / 0.004250 (0.044367) \| 0.044088 / 0.037052 (0.007035) \| 0.263059 / 0.258489 (0.004570) \| 0.294602 / 0.293841 (0.000761) \| 0.027425 / 0.128546 (-0.101121) \| 0.010263 / 0.075646 (-0.065383) \| 0.205925 / 0.419271 (-0.213346) \| 0.048917 / 0.043533 (0.005384) \| 0.264227 / 0.255139 (0.009088) \| 0.273339 / 0.283200 (-0.009860) \| 0.017783 / 0.141683 (-0.123900) \| 1.137526 / 1.452155 (-0.314629) \| 1.179551 / 1.492716 (-0.313165) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.096809 / 0.018006 (0.078802) \| 0.303854 / 0.000490 (0.303364) \| 0.000207 / 0.000200 (0.000007) \| 0.000042 / 0.000054 (-0.000012) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.017756 / 0.037411 (-0.019655) \| 0.061005 / 0.014526 (0.046479) \| 0.072986 / 0.176557 (-0.103571) \| 0.119851 / 0.737135 (-0.617284) \| 0.074733 / 0.296338 (-0.221605) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.278270 / 0.215209 (0.063061) \| 2.737874 / 2.077655 (0.660219) \| 1.460658 / 1.504120 (-0.043462) \| 1.337695 / 1.541195 (-0.203499) \| 1.364376 / 1.468490 (-0.104114) \| 0.565622 / 4.584777 (-4.019155) \| 2.365167 / 3.745712 (-1.380546) \| 2.694544 / 5.269862 (-2.575317) \| 1.699689 / 4.565676 (-2.865987) \| 0.062564 / 0.424275 (-0.361712) \| 0.005296 / 0.007607 (-0.002311) \| 0.340122 / 0.226044 (0.114077) \| 3.382133 / 2.268929 (1.113204) \| 1.816907 / 55.444624 (-53.627718) \| 1.530825 / 6.876477 (-5.345652) \| 1.533266 / 2.142072 (-0.608807) \| 0.638215 / 4.805227 (-4.167012) \| 0.116227 / 6.500664 (-6.384437) \| 0.041548 / 0.075469 (-0.033921) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.971031 / 1.841788 (-0.870757) \| 11.117905 / 8.074308 (3.043597) \| 9.358159 / 10.191392 (-0.833233) \| 0.127954 / 0.680424 (-0.552470) \| 0.013634 / 0.534201 (-0.520567) \| 0.285399 / 0.579283 (-0.293885) \| 0.267980 / 0.434364 (-0.166383) \| 0.320219 / 0.540337 (-0.220119) \| 0.416035 / 1.386936 (-0.970901) \|\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005177 / 0.011353 (-0.006176) \| 0.003078 / 0.011008 (-0.007930) \| 0.049650 / 0.038508 (0.011142) \| 0.030897 / 0.023109 (0.007787) \| 0.271186 / 0.275898 (-0.004712) \| 0.296050 / 0.323480 (-0.027430) \| 0.004204 / 0.007986 (-0.003781) \| 0.002755 / 0.004328 (-0.001574) \| 0.049550 / 0.004250 (0.045300) \| 0.039801 / 0.037052 (0.002749) \| 0.283243 / 0.258489 (0.024753) \| 0.310932 / 0.293841 (0.017091) \| 0.029136 / 0.128546 (-0.099410) \| 0.010278 / 0.075646 (-0.065368) \| 0.059300 / 0.419271 (-0.359971) \| 0.032965 / 0.043533 (-0.010568) \| 0.272646 / 0.255139 (0.017507) \| 0.293697 / 0.283200 (0.010497) \| 0.018330 / 0.141683 (-0.123353) \| 1.144251 / 1.452155 (-0.307904) \| 1.209660 / 1.492716 (-0.283056) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.091020 / 0.018006 (0.073014) \| 0.298294 / 0.000490 (0.297804) \| 0.000214 / 0.000200 (0.000014) \| 0.000053 / 0.000054 (-0.000002) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.021879 / 0.037411 (-0.015532) \| 0.074728 / 0.014526 (0.060202) \| 0.085499 / 0.176557 (-0.091057) \| 0.125743 / 0.737135 (-0.611392) \| 0.086130 / 0.296338 (-0.210208) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.292311 / 0.215209 (0.077102) \| 2.861240 / 2.077655 (0.783585) \| 1.590426 / 1.504120 (0.086306) \| 1.472288 / 1.541195 (-0.068907) \| 1.472901 / 1.468490 (0.004411) \| 0.574924 / 4.584777 (-4.009853) \| 2.450817 / 3.745712 (-1.294895) \| 2.781903 / 5.269862 (-2.487959) \| 1.747110 / 4.565676 (-2.818566) \| 0.064680 / 0.424275 (-0.359595) \| 0.005376 / 0.007607 (-0.002231) \| 0.356846 / 0.226044 (0.130802) \| 3.457851 / 2.268929 (1.188922) \| 1.952678 / 55.444624 (-53.491946) \| 1.670824 / 6.876477 (-5.205653) \| 1.655872 / 2.142072 (-0.486200) \| 0.655874 / 4.805227 (-4.149353) \| 0.117098 / 6.500664 (-6.383566) \| 0.040230 / 0.075469 (-0.035239) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 1.007423 / 1.841788 (-0.834365) \| 11.818228 / 8.074308 (3.743920) \| 10.153699 / 10.191392 (-0.037693) \| 0.132073 / 0.680424 (-0.548351) \| 0.015101 / 0.534201 (-0.519100) \| 0.286555 / 0.579283 (-0.292728) \| 0.281953 / 0.434364 (-0.152411) \| 0.323647 / 0.540337 (-0.216691) \| 0.418698 / 1.386936 (-0.968238) \|\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#0d3c7462bc67407c42d3ad102b7f9d5914219d9d \"CML watermark\")\n" ]	2024-04-19T08:29:02	2024-05-04T12:23:26	2024-04-19T08:44:57	MEMBER	null	false	{ "url": "https://api.github.com/repos/huggingface/datasets/pulls/6825", "html_url": "https://github.com/huggingface/datasets/pull/6825", "diff_url": "https://github.com/huggingface/datasets/pull/6825.diff", "patch_url": "https://github.com/huggingface/datasets/pull/6825.patch", "merged_at": "2024-04-19T08:44:57" }	null	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6825/reactions", "total_count": 1, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 1 }	https://api.github.com/repos/huggingface/datasets/issues/6825/timeline	null	null	true
https://api.github.com/repos/huggingface/datasets/issues/6824	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6824/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6824/comments	https://api.github.com/repos/huggingface/datasets/issues/6824/events	https://github.com/huggingface/datasets/issues/6824	2,251,076,197	I_kwDODunzps6GLLJl	6,824	Winogrande does not seem to be compatible with datasets version of 1.18.0	{ "login": "spliew", "id": 7878204, "node_id": "MDQ6VXNlcjc4NzgyMDQ=", "avatar_url": "https://avatars.githubusercontent.com/u/7878204?v=4", "gravatar_id": "", "url": "https://api.github.com/users/spliew", "html_url": "https://github.com/spliew", "followers_url": "https://api.github.com/users/spliew/followers", "following_url": "https://api.github.com/users/spliew/following{/other_user}", "gists_url": "https://api.github.com/users/spliew/gists{/gist_id}", "starred_url": "https://api.github.com/users/spliew/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/spliew/subscriptions", "organizations_url": "https://api.github.com/users/spliew/orgs", "repos_url": "https://api.github.com/users/spliew/repos", "events_url": "https://api.github.com/users/spliew/events{/privacy}", "received_events_url": "https://api.github.com/users/spliew/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	null	[]	null	[ "Hi ! Do you mean 2.18 ? Can you try to update `fsspec` and `huggingface_hub` ?\r\n\r\n```\r\npip install -U fsspec huggingface_hub\r\n```", "Yes I meant 2.18, and it works after updating `fsspec` and `huggingface_hub`. Thanks!" ]	2024-04-18T16:11:04	2024-04-19T09:53:15	2024-04-19T09:52:33	NONE	null	null	null	### Describe the bug I get the following error when simply running `load_dataset('winogrande','winogrande_xl')`. I do not have such an issue in the 1.17.0 version. ```Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/usr/local/lib/python3.10/dist-packages/datasets/load.py", line 2556, in load_dataset builder_instance = load_dataset_builder( File "/usr/local/lib/python3.10/dist-packages/datasets/load.py", line 2265, in load_dataset_builder builder_instance: DatasetBuilder = builder_cls( File "/usr/local/lib/python3.10/dist-packages/datasets/builder.py", line 371, in __init__ self.config, self.config_id = self._create_builder_config( File "/usr/local/lib/python3.10/dist-packages/datasets/builder.py", line 620, in _create_builder_config builder_config._resolve_data_files( File "/usr/local/lib/python3.10/dist-packages/datasets/builder.py", line 211, in _resolve_data_files self.data_files = self.data_files.resolve(base_path, download_config) File "/usr/local/lib/python3.10/dist-packages/datasets/data_files.py", line 799, in resolve out[key] = data_files_patterns_list.resolve(base_path, download_config) File "/usr/local/lib/python3.10/dist-packages/datasets/data_files.py", line 752, in resolve resolve_pattern( File "/usr/local/lib/python3.10/dist-packages/datasets/data_files.py", line 393, in resolve_pattern raise FileNotFoundError(error_msg) FileNotFoundError: Unable to find 'hf://datasets/winogrande@ebf71e3c7b5880d019ecf6099c0b09311b1084f5/winogrande_xl/train/0000.parquet' with any supported extension ['.csv', '.tsv', '.json', '.jsonl', '.parquet', '.geoparquet', '.gpq', '.arrow', '.txt', '.tar', '.blp', '.bmp', '.dib', '.bufr', '.cur', '.pcx', '.dcx', '.dds', '.ps', '.eps', '.fit', '.fits', '.fli', '.flc', '.ftc', '.ftu', '.gbr', '.gif', '.grib', '.h5', '.hdf', '.png', '.apng', '.jp2', '.j2k', '.jpc', '.jpf', '.jpx', '.j2c', '.icns', '.ico', '.im', '.iim', '.tif', '.tiff', '.jfif', '.jpe', '.jpg', '.jpeg', '.mpg', '.mpeg', '.msp', '.pcd', '.pxr', '.pbm', '.pgm', '.ppm', '.pnm', '.psd', '.bw', '.rgb', '.rgba', '.sgi', '.ras', '.tga', '.icb', '.vda', '.vst', '.webp', '.wmf', '.emf', '.xbm', '.xpm', '.BLP', '.BMP', '.DIB', '.BUFR', '.CUR', '.PCX', '.DCX', '.DDS', '.PS', '.EPS', '.FIT', '.FITS', '.FLI', '.FLC', '.FTC', '.FTU', '.GBR', '.GIF', '.GRIB', '.H5', '.HDF', '.PNG', '.APNG', '.JP2', '.J2K', '.JPC', '.JPF', '.JPX', '.J2C', '.ICNS', '.ICO', '.IM', '.IIM', '.TIF', '.TIFF', '.JFIF', '.JPE', '.JPG', '.JPEG', '.MPG', '.MPEG', '.MSP', '.PCD', '.PXR', '.PBM', '.PGM', '.PPM', '.PNM', '.PSD', '.BW', '.RGB', '.RGBA', '.SGI', '.RAS', '.TGA', '.ICB', '.VDA', '.VST', '.WEBP', '.WMF', '.EMF', '.XBM', '.XPM', '.aiff', '.au', '.avr', '.caf', '.flac', '.htk', '.svx', '.mat4', '.mat5', '.mpc2k', '.ogg', '.paf', '.pvf', '.raw', '.rf64', '.sd2', '.sds', '.ircam', '.voc', '.w64', '.wav', '.nist', '.wavex', '.wve', '.xi', '.mp3', '.opus', '.AIFF', '.AU', '.AVR', '.CAF', '.FLAC', '.HTK', '.SVX', '.MAT4', '.MAT5', '.MPC2K', '.OGG', '.PAF', '.PVF', '.RAW', '.RF64', '.SD2', '.SDS', '.IRCAM', '.VOC', '.W64', '.WAV', '.NIST', '.WAVEX', '.WVE', '.XI', '.MP3', '.OPUS', '.zip']``` ### Steps to reproduce the bug from datasets import load_dataset datasets = load_dataset('winogrande','winogrande_xl') ### Expected behavior ```Downloading data: 100%\|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████\| 2.06M/2.06M [00:00<00:00, 5.16MB/s] Downloading data: 100%\|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████\| 118k/118k [00:00<00:00, 360kB/s] Downloading data: 100%\|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████\| 85.9k/85.9k [00:00<00:00, 242kB/s] Generating train split: 100%\|██████████████████████████████████████████████████████████████████████████████████████████████████████\| 40398/40398 [00:00<00:00, 845491.12 examples/s] Generating test split: 100%\|█████████████████████████████████████████████████████████████████████████████████████████████████████████\| 1767/1767 [00:00<00:00, 362501.11 examples/s] Generating validation split: 100%\|███████████████████████████████████████████████████████████████████████████████████████████████████\| 1267/1267 [00:00<00:00, 318768.11 examples/s]``` ### Environment info datasets version: 1.18.0	{ "login": "spliew", "id": 7878204, "node_id": "MDQ6VXNlcjc4NzgyMDQ=", "avatar_url": "https://avatars.githubusercontent.com/u/7878204?v=4", "gravatar_id": "", "url": "https://api.github.com/users/spliew", "html_url": "https://github.com/spliew", "followers_url": "https://api.github.com/users/spliew/followers", "following_url": "https://api.github.com/users/spliew/following{/other_user}", "gists_url": "https://api.github.com/users/spliew/gists{/gist_id}", "starred_url": "https://api.github.com/users/spliew/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/spliew/subscriptions", "organizations_url": "https://api.github.com/users/spliew/orgs", "repos_url": "https://api.github.com/users/spliew/repos", "events_url": "https://api.github.com/users/spliew/events{/privacy}", "received_events_url": "https://api.github.com/users/spliew/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6824/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6824/timeline	null	completed	false
https://api.github.com/repos/huggingface/datasets/issues/6823	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6823/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6823/comments	https://api.github.com/repos/huggingface/datasets/issues/6823/events	https://github.com/huggingface/datasets/issues/6823	2,250,775,569	I_kwDODunzps6GKBwR	6,823	Loading problems of Datasets with a single shard	{ "login": "andjoer", "id": 60151338, "node_id": "MDQ6VXNlcjYwMTUxMzM4", "avatar_url": "https://avatars.githubusercontent.com/u/60151338?v=4", "gravatar_id": "", "url": "https://api.github.com/users/andjoer", "html_url": "https://github.com/andjoer", "followers_url": "https://api.github.com/users/andjoer/followers", "following_url": "https://api.github.com/users/andjoer/following{/other_user}", "gists_url": "https://api.github.com/users/andjoer/gists{/gist_id}", "starred_url": "https://api.github.com/users/andjoer/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/andjoer/subscriptions", "organizations_url": "https://api.github.com/users/andjoer/orgs", "repos_url": "https://api.github.com/users/andjoer/repos", "events_url": "https://api.github.com/users/andjoer/events{/privacy}", "received_events_url": "https://api.github.com/users/andjoer/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	open	false	null	[]	null	[ "Has there been a PR to resolve this already?" ]	2024-04-18T13:59:00	2024-08-19T19:32:37	null	NONE	null	null	null	### Describe the bug When saving a dataset on disk and it has a single shard it is not loaded as when it is saved in multiple shards. I installed the latest version of datasets via pip. ### Steps to reproduce the bug The code below reproduces the behavior. All works well when the range of the loop is 10000 but it fails when it is 1000. ``` from PIL import Image import numpy as np from datasets import Dataset, DatasetDict, load_dataset def load_image(): # Generate random noise image noise = np.random.randint(0, 256, (256, 256, 3), dtype=np.uint8) return Image.fromarray(noise) def create_dataset(): input_images = [] output_images = [] text_prompts = [] for _ in range(10000): # this is the problematic parameter input_images.append(load_image()) output_images.append(load_image()) text_prompts.append('test prompt') data = {'input_image': input_images, 'output_image': output_images, 'text_prompt': text_prompts} dataset = Dataset.from_dict(data) return DatasetDict({'train': dataset}) dataset = create_dataset() print('dataset before saving') print(dataset) print(dataset['train'].column_names) dataset.save_to_disk('test_ds') print('dataset after loading') dataset_loaded = load_dataset('test_ds') print(dataset_loaded) print(dataset_loaded['train'].column_names) ``` The output for 1000 iterations is: ``` dataset before saving DatasetDict({ train: Dataset({ features: ['input_image', 'output_image', 'text_prompt'], num_rows: 1000 }) }) ['input_image', 'output_image', 'text_prompt'] Saving the dataset (1/1 shards): 100%\|█\| 1000/1000 [00:00<00:00, 5156.00 example dataset after loading Generating train split: 1 examples [00:00, 230.52 examples/s] DatasetDict({ train: Dataset({ features: ['_data_files', '_fingerprint', '_format_columns', '_format_kwargs', '_format_type', '_output_all_columns', '_split'], num_rows: 1 }) }) ['_data_files', '_fingerprint', '_format_columns', '_format_kwargs', '_format_type', '_output_all_columns', '_split'] ``` For 10000 iteration (8 shards) it is correct: ``` dataset before saving DatasetDict({ train: Dataset({ features: ['input_image', 'output_image', 'text_prompt'], num_rows: 10000 }) }) ['input_image', 'output_image', 'text_prompt'] Saving the dataset (8/8 shards): 100%\|█\| 10000/10000 [00:01<00:00, 6237.68 examp dataset after loading Generating train split: 10000 examples [00:00, 10773.16 examples/s] DatasetDict({ train: Dataset({ features: ['input_image', 'output_image', 'text_prompt'], num_rows: 10000 }) }) ['input_image', 'output_image', 'text_prompt'] ``` ### Expected behavior The procedure should work for a dataset with one shrad the same as for one with multiple shards ### Environment info - `datasets` version: 2.18.0 - Platform: macOS-14.1-arm64-arm-64bit - Python version: 3.11.8 - `huggingface_hub` version: 0.22.2 - PyArrow version: 15.0.2 - Pandas version: 2.2.2 - `fsspec` version: 2024.2.0 Edit: I looked in the source code of load.py in datasets. I should have used "load_from_disk" and it indeed works that way. But ideally load_dataset would have raisen an error the same way as if I call a path: ``` if Path(path, config.DATASET_STATE_JSON_FILENAME).exists(): raise ValueError( "You are trying to load a dataset that was saved using `save_to_disk`. " "Please use `load_from_disk` instead." ) ``` nevertheless I find it interesting that it works just well and without a warning if there are multiple shards.	null	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6823/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6823/timeline	null	null	false
https://api.github.com/repos/huggingface/datasets/issues/6822	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6822/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6822/comments	https://api.github.com/repos/huggingface/datasets/issues/6822/events	https://github.com/huggingface/datasets/pull/6822	2,250,316,258	PR_kwDODunzps5tB8aD	6,822	Fix parquet export infos	{ "login": "lhoestq", "id": 42851186, "node_id": "MDQ6VXNlcjQyODUxMTg2", "avatar_url": "https://avatars.githubusercontent.com/u/42851186?v=4", "gravatar_id": "", "url": "https://api.github.com/users/lhoestq", "html_url": "https://github.com/lhoestq", "followers_url": "https://api.github.com/users/lhoestq/followers", "following_url": "https://api.github.com/users/lhoestq/following{/other_user}", "gists_url": "https://api.github.com/users/lhoestq/gists{/gist_id}", "starred_url": "https://api.github.com/users/lhoestq/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/lhoestq/subscriptions", "organizations_url": "https://api.github.com/users/lhoestq/orgs", "repos_url": "https://api.github.com/users/lhoestq/repos", "events_url": "https://api.github.com/users/lhoestq/events{/privacy}", "received_events_url": "https://api.github.com/users/lhoestq/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	null	[]	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6822). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005084 / 0.011353 (-0.006269) \| 0.003658 / 0.011008 (-0.007351) \| 0.063369 / 0.038508 (0.024860) \| 0.030739 / 0.023109 (0.007630) \| 0.244335 / 0.275898 (-0.031564) \| 0.271731 / 0.323480 (-0.051749) \| 0.004133 / 0.007986 (-0.003853) \| 0.002798 / 0.004328 (-0.001530) \| 0.048790 / 0.004250 (0.044540) \| 0.044054 / 0.037052 (0.007002) \| 0.261514 / 0.258489 (0.003025) \| 0.292155 / 0.293841 (-0.001686) \| 0.027971 / 0.128546 (-0.100575) \| 0.010723 / 0.075646 (-0.064923) \| 0.207328 / 0.419271 (-0.211944) \| 0.035928 / 0.043533 (-0.007605) \| 0.245320 / 0.255139 (-0.009819) \| 0.268774 / 0.283200 (-0.014426) \| 0.017119 / 0.141683 (-0.124564) \| 1.107052 / 1.452155 (-0.345103) \| 1.151752 / 1.492716 (-0.340965) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.089941 / 0.018006 (0.071935) \| 0.299788 / 0.000490 (0.299298) \| 0.000211 / 0.000200 (0.000012) \| 0.000043 / 0.000054 (-0.000011) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.018159 / 0.037411 (-0.019252) \| 0.061876 / 0.014526 (0.047350) \| 0.074733 / 0.176557 (-0.101824) \| 0.122070 / 0.737135 (-0.615065) \| 0.076100 / 0.296338 (-0.220238) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.282209 / 0.215209 (0.067000) \| 2.758098 / 2.077655 (0.680444) \| 1.482454 / 1.504120 (-0.021666) \| 1.372649 / 1.541195 (-0.168546) \| 1.373171 / 1.468490 (-0.095319) \| 0.563606 / 4.584777 (-4.021171) \| 2.406760 / 3.745712 (-1.338952) \| 2.796322 / 5.269862 (-2.473540) \| 1.732327 / 4.565676 (-2.833350) \| 0.063623 / 0.424275 (-0.360652) \| 0.005338 / 0.007607 (-0.002269) \| 0.337562 / 0.226044 (0.111518) \| 3.345225 / 2.268929 (1.076296) \| 1.844353 / 55.444624 (-53.600271) \| 1.551003 / 6.876477 (-5.325474) \| 1.570623 / 2.142072 (-0.571449) \| 0.644843 / 4.805227 (-4.160385) \| 0.118811 / 6.500664 (-6.381853) \| 0.041731 / 0.075469 (-0.033738) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.970469 / 1.841788 (-0.871319) \| 11.775531 / 8.074308 (3.701222) \| 9.757852 / 10.191392 (-0.433540) \| 0.130187 / 0.680424 (-0.550237) \| 0.013654 / 0.534201 (-0.520547) \| 0.328387 / 0.579283 (-0.250896) \| 0.268181 / 0.434364 (-0.166183) \| 0.325230 / 0.540337 (-0.215107) \| 0.421055 / 1.386936 (-0.965881) \|\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005846 / 0.011353 (-0.005507) \| 0.003606 / 0.011008 (-0.007402) \| 0.050787 / 0.038508 (0.012279) \| 0.031635 / 0.023109 (0.008526) \| 0.277040 / 0.275898 (0.001142) \| 0.300544 / 0.323480 (-0.022936) \| 0.004200 / 0.007986 (-0.003786) \| 0.002749 / 0.004328 (-0.001580) \| 0.049449 / 0.004250 (0.045198) \| 0.041616 / 0.037052 (0.004564) \| 0.289570 / 0.258489 (0.031081) \| 0.316138 / 0.293841 (0.022297) \| 0.029578 / 0.128546 (-0.098969) \| 0.010582 / 0.075646 (-0.065064) \| 0.058284 / 0.419271 (-0.360988) \| 0.033078 / 0.043533 (-0.010455) \| 0.277964 / 0.255139 (0.022825) \| 0.295008 / 0.283200 (0.011808) \| 0.017753 / 0.141683 (-0.123930) \| 1.128635 / 1.452155 (-0.323519) \| 1.190142 / 1.492716 (-0.302575) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.091504 / 0.018006 (0.073498) \| 0.303875 / 0.000490 (0.303385) \| 0.000221 / 0.000200 (0.000021) \| 0.000052 / 0.000054 (-0.000003) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.021413 / 0.037411 (-0.015998) \| 0.074825 / 0.014526 (0.060299) \| 0.086329 / 0.176557 (-0.090228) \| 0.125632 / 0.737135 (-0.611503) \| 0.087918 / 0.296338 (-0.208420) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.297914 / 0.215209 (0.082705) \| 2.922885 / 2.077655 (0.845230) \| 1.625758 / 1.504120 (0.121638) \| 1.500174 / 1.541195 (-0.041021) \| 1.517162 / 1.468490 (0.048672) \| 0.576885 / 4.584777 (-4.007892) \| 2.458723 / 3.745712 (-1.286989) \| 2.798471 / 5.269862 (-2.471391) \| 1.762499 / 4.565676 (-2.803178) \| 0.064736 / 0.424275 (-0.359539) \| 0.005325 / 0.007607 (-0.002282) \| 0.351697 / 0.226044 (0.125652) \| 3.496223 / 2.268929 (1.227294) \| 1.977535 / 55.444624 (-53.467090) \| 1.695223 / 6.876477 (-5.181254) \| 1.689692 / 2.142072 (-0.452381) \| 0.656404 / 4.805227 (-4.148823) \| 0.123106 / 6.500664 (-6.377558) \| 0.040980 / 0.075469 (-0.034489) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 1.036972 / 1.841788 (-0.804816) \| 12.163931 / 8.074308 (4.089623) \| 10.297927 / 10.191392 (0.106535) \| 0.144087 / 0.680424 (-0.536337) \| 0.015553 / 0.534201 (-0.518648) \| 0.286225 / 0.579283 (-0.293058) \| 0.275567 / 0.434364 (-0.158797) \| 0.332717 / 0.540337 (-0.207620) \| 0.423804 / 1.386936 (-0.963132) \|\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#0bc709af303c8dc64c973a17016bd5aa5db2f3d5 \"CML watermark\")\n" ]	2024-04-18T10:21:41	2024-04-18T11:15:41	2024-04-18T11:09:13	MEMBER	null	false	{ "url": "https://api.github.com/repos/huggingface/datasets/pulls/6822", "html_url": "https://github.com/huggingface/datasets/pull/6822", "diff_url": "https://github.com/huggingface/datasets/pull/6822.diff", "patch_url": "https://github.com/huggingface/datasets/pull/6822.patch", "merged_at": "2024-04-18T11:09:13" }	Don't use the parquet export infos when USE_PARQUET_EXPORT is False. Otherwise the `datasets-server` might reuse erroneous data when re-running a job this follows https://github.com/huggingface/datasets/pull/6714	{ "login": "lhoestq", "id": 42851186, "node_id": "MDQ6VXNlcjQyODUxMTg2", "avatar_url": "https://avatars.githubusercontent.com/u/42851186?v=4", "gravatar_id": "", "url": "https://api.github.com/users/lhoestq", "html_url": "https://github.com/lhoestq", "followers_url": "https://api.github.com/users/lhoestq/followers", "following_url": "https://api.github.com/users/lhoestq/following{/other_user}", "gists_url": "https://api.github.com/users/lhoestq/gists{/gist_id}", "starred_url": "https://api.github.com/users/lhoestq/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/lhoestq/subscriptions", "organizations_url": "https://api.github.com/users/lhoestq/orgs", "repos_url": "https://api.github.com/users/lhoestq/repos", "events_url": "https://api.github.com/users/lhoestq/events{/privacy}", "received_events_url": "https://api.github.com/users/lhoestq/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6822/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6822/timeline	null	null	true
https://api.github.com/repos/huggingface/datasets/issues/6820	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6820/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6820/comments	https://api.github.com/repos/huggingface/datasets/issues/6820/events	https://github.com/huggingface/datasets/pull/6820	2,248,471,673	PR_kwDODunzps5s7sgy	6,820	Allow deleting a subset/config from a no-script dataset	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	null	[]	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6820). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "This is ready for review, @huggingface/datasets.", "I am adding a test...", "@lhoestq I am getting an error in the test and I think it happens because the CI endpoint does not have the /preupload functionality:\r\n```\r\nhuggingface_hub.utils._errors.RepositoryNotFoundError: 401 Client Error. (Request ID: Root=1-662a4de9-7134df595e29e4c073ac1298;332ff6e3-597a-4dfc-89df-4e9ac64215ad)\r\n\r\nRepository Not Found for url: https://hub-ci.huggingface.co/api/datasets/__DUMMY_TRANSFORMERS_USER__/test-dataset-6c54e2-17140484441915/preupload/main?create_pr=1.\r\nPlease make sure you specified the correct `repo_id` and `repo_type`.\r\nIf you are trying to access a private or gated repo, make sure you are authenticated.\r\nInvalid username or password.\r\nNote: Creating a commit assumes that the repo already exists on the Huggingface Hub. Please use `create_repo` if it's not the case.\r\n```", "@lhoestq, finally, I implemented the test with a mock of the call to `HfApi.create_commit`.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.004958 / 0.011353 (-0.006395) \| 0.004065 / 0.011008 (-0.006943) \| 0.063499 / 0.038508 (0.024991) \| 0.030260 / 0.023109 (0.007151) \| 0.250910 / 0.275898 (-0.024988) \| 0.276632 / 0.323480 (-0.046848) \| 0.004038 / 0.007986 (-0.003948) \| 0.002721 / 0.004328 (-0.001608) \| 0.049098 / 0.004250 (0.044848) \| 0.044418 / 0.037052 (0.007366) \| 0.262189 / 0.258489 (0.003700) \| 0.292426 / 0.293841 (-0.001415) \| 0.027268 / 0.128546 (-0.101279) \| 0.010601 / 0.075646 (-0.065045) \| 0.207332 / 0.419271 (-0.211940) \| 0.036102 / 0.043533 (-0.007430) \| 0.252425 / 0.255139 (-0.002714) \| 0.269421 / 0.283200 (-0.013779) \| 0.018534 / 0.141683 (-0.123149) \| 1.127869 / 1.452155 (-0.324286) \| 1.179660 / 1.492716 (-0.313056) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.092686 / 0.018006 (0.074680) \| 0.299492 / 0.000490 (0.299002) \| 0.000211 / 0.000200 (0.000011) \| 0.000044 / 0.000054 (-0.000010) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.018385 / 0.037411 (-0.019026) \| 0.060979 / 0.014526 (0.046453) \| 0.073351 / 0.176557 (-0.103205) \| 0.120145 / 0.737135 (-0.616990) \| 0.073653 / 0.296338 (-0.222686) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.286175 / 0.215209 (0.070966) \| 2.792698 / 2.077655 (0.715043) \| 1.507442 / 1.504120 (0.003322) \| 1.392531 / 1.541195 (-0.148664) \| 1.387253 / 1.468490 (-0.081237) \| 0.568435 / 4.584777 (-4.016342) \| 2.387392 / 3.745712 (-1.358321) \| 2.813695 / 5.269862 (-2.456167) \| 1.747392 / 4.565676 (-2.818284) \| 0.062948 / 0.424275 (-0.361328) \| 0.005596 / 0.007607 (-0.002011) \| 0.334357 / 0.226044 (0.108313) \| 3.263289 / 2.268929 (0.994360) \| 1.829553 / 55.444624 (-53.615071) \| 1.552510 / 6.876477 (-5.323967) \| 1.579975 / 2.142072 (-0.562098) \| 0.633982 / 4.805227 (-4.171246) \| 0.118752 / 6.500664 (-6.381912) \| 0.042445 / 0.075469 (-0.033024) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.988062 / 1.841788 (-0.853725) \| 11.615693 / 8.074308 (3.541385) \| 9.728103 / 10.191392 (-0.463289) \| 0.131561 / 0.680424 (-0.548862) \| 0.015330 / 0.534201 (-0.518871) \| 0.289617 / 0.579283 (-0.289666) \| 0.265717 / 0.434364 (-0.168646) \| 0.323974 / 0.540337 (-0.216363) \| 0.419523 / 1.386936 (-0.967413) \|\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005385 / 0.011353 (-0.005968) \| 0.003753 / 0.011008 (-0.007255) \| 0.049821 / 0.038508 (0.011313) \| 0.030490 / 0.023109 (0.007381) \| 0.260550 / 0.275898 (-0.015348) \| 0.284598 / 0.323480 (-0.038881) \| 0.004165 / 0.007986 (-0.003821) \| 0.002741 / 0.004328 (-0.001588) \| 0.048567 / 0.004250 (0.044317) \| 0.045185 / 0.037052 (0.008133) \| 0.273164 / 0.258489 (0.014674) \| 0.301995 / 0.293841 (0.008155) \| 0.028802 / 0.128546 (-0.099744) \| 0.010539 / 0.075646 (-0.065108) \| 0.057967 / 0.419271 (-0.361305) \| 0.032826 / 0.043533 (-0.010706) \| 0.260425 / 0.255139 (0.005286) \| 0.280175 / 0.283200 (-0.003024) \| 0.017202 / 0.141683 (-0.124481) \| 1.129588 / 1.452155 (-0.322567) \| 1.199565 / 1.492716 (-0.293152) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.091234 / 0.018006 (0.073228) \| 0.299313 / 0.000490 (0.298824) \| 0.000203 / 0.000200 (0.000003) \| 0.000044 / 0.000054 (-0.000010) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.022519 / 0.037411 (-0.014892) \| 0.075915 / 0.014526 (0.061389) \| 0.088636 / 0.176557 (-0.087920) \| 0.128234 / 0.737135 (-0.608902) \| 0.089782 / 0.296338 (-0.206556) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.291936 / 0.215209 (0.076727) \| 2.864589 / 2.077655 (0.786935) \| 1.575649 / 1.504120 (0.071529) \| 1.452797 / 1.541195 (-0.088398) \| 1.476245 / 1.468490 (0.007754) \| 0.593972 / 4.584777 (-3.990804) \| 0.962315 / 3.745712 (-2.783397) \| 2.836496 / 5.269862 (-2.433366) \| 1.758639 / 4.565676 (-2.807038) \| 0.064842 / 0.424275 (-0.359433) \| 0.005076 / 0.007607 (-0.002531) \| 0.342568 / 0.226044 (0.116524) \| 3.392753 / 2.268929 (1.123825) \| 1.908305 / 55.444624 (-53.536319) \| 1.632140 / 6.876477 (-5.244337) \| 1.653048 / 2.142072 (-0.489024) \| 0.662068 / 4.805227 (-4.143159) \| 0.118326 / 6.500664 (-6.382338) \| 0.041222 / 0.075469 (-0.034247) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 1.005119 / 1.841788 (-0.836669) \| 12.250922 / 8.074308 (4.176614) \| 9.775600 / 10.191392 (-0.415792) \| 0.146230 / 0.680424 (-0.534194) \| 0.015883 / 0.534201 (-0.518318) \| 0.290807 / 0.579283 (-0.288476) \| 0.126002 / 0.434364 (-0.308362) \| 0.392332 / 0.540337 (-0.148005) \| 0.435513 / 1.386936 (-0.951423) \|\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#ceb25e118f21f54b5b5c5e9c223713f14a798eb5 \"CML watermark\")\n" ]	2024-04-17T14:41:12	2024-05-02T07:31:03	2024-04-30T09:44:24	MEMBER	null	false	{ "url": "https://api.github.com/repos/huggingface/datasets/pulls/6820", "html_url": "https://github.com/huggingface/datasets/pull/6820", "diff_url": "https://github.com/huggingface/datasets/pull/6820.diff", "patch_url": "https://github.com/huggingface/datasets/pull/6820.patch", "merged_at": "2024-04-30T09:44:24" }	TODO: - [x] Add docs - [x] Delete token arg from CLI example - See: #6839 Close #6810.	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6820/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6820/timeline	null	null	true
https://api.github.com/repos/huggingface/datasets/issues/6819	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6819/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6819/comments	https://api.github.com/repos/huggingface/datasets/issues/6819/events	https://github.com/huggingface/datasets/issues/6819	2,248,043,797	I_kwDODunzps6F_m0V	6,819	Give more details in `DataFilesNotFoundError` when getting the config names	{ "login": "severo", "id": 1676121, "node_id": "MDQ6VXNlcjE2NzYxMjE=", "avatar_url": "https://avatars.githubusercontent.com/u/1676121?v=4", "gravatar_id": "", "url": "https://api.github.com/users/severo", "html_url": "https://github.com/severo", "followers_url": "https://api.github.com/users/severo/followers", "following_url": "https://api.github.com/users/severo/following{/other_user}", "gists_url": "https://api.github.com/users/severo/gists{/gist_id}", "starred_url": "https://api.github.com/users/severo/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/severo/subscriptions", "organizations_url": "https://api.github.com/users/severo/orgs", "repos_url": "https://api.github.com/users/severo/repos", "events_url": "https://api.github.com/users/severo/events{/privacy}", "received_events_url": "https://api.github.com/users/severo/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[ { "id": 1935892871, "node_id": "MDU6TGFiZWwxOTM1ODkyODcx", "url": "https://api.github.com/repos/huggingface/datasets/labels/enhancement", "name": "enhancement", "color": "a2eeef", "default": true, "description": "New feature or request" } ]	open	false	null	[]	null	[]	2024-04-17T11:19:47	2024-04-17T11:19:47	null	COLLABORATOR	null	null	null	### Feature request After https://huggingface.co/datasets/cis-lmu/Glot500/commit/39060e01272ff228cc0ce1d31ae53789cacae8c3, the dataset viewer gives the following error: ``` { "error": "Cannot get the config names for the dataset.", "cause_exception": "DataFilesNotFoundError", "cause_message": "No (supported) data files found in cis-lmu/Glot500", "cause_traceback": [ "Traceback (most recent call last):\n", " File \"/src/services/worker/src/worker/job_runners/dataset/config_names.py\", line 73, in compute_config_names_response\n config_names = get_dataset_config_names(\n", " File \"/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py\", line 347, in get_dataset_config_names\n dataset_module = dataset_module_factory(\n", " File \"/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py\", line 1873, in dataset_module_factory\n raise e1 from None\n", " File \"/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py\", line 1854, in dataset_module_factory\n return HubDatasetModuleFactoryWithoutScript(\n", " File \"/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py\", line 1245, in get_module\n module_name, default_builder_kwargs = infer_module_for_data_files(\n", " File \"/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py\", line 595, in infer_module_for_data_files\n raise DataFilesNotFoundError(\"No (supported) data files found\" + (f\" in {path}\" if path else \"\"))\n", "datasets.exceptions.DataFilesNotFoundError: No (supported) data files found in cis-lmu/Glot500\n" ] } ``` because the deleted files were still listed in the README, see https://huggingface.co/datasets/cis-lmu/Glot500/discussions/4 Ideally, the error message would include the name of the first configuration with missing files, to help the user understand how to fix it. Here, it would tell that configuration `aze_Ethi` has no supported data files, instead of telling that the `cis-lmu/Glot500` dataset has no supported data files (which is not true). ### Motivation Giving more detail in the error would help the Datasets Hub users to debug why the dataset viewer does not work. ### Your contribution Not sure how to best fix this, as there are a lot of loops on the dataset configs in the traceback methods. "maybe" it would be easier to handle if the code was completely isolating each config.	null	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6819/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6819/timeline	null	null	false
https://api.github.com/repos/huggingface/datasets/issues/6817	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6817/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6817/comments	https://api.github.com/repos/huggingface/datasets/issues/6817/events	https://github.com/huggingface/datasets/pull/6817	2,246,578,480	PR_kwDODunzps5s1RAN	6,817	Support indexable objects in `Dataset.__getitem__`	{ "login": "mariosasko", "id": 47462742, "node_id": "MDQ6VXNlcjQ3NDYyNzQy", "avatar_url": "https://avatars.githubusercontent.com/u/47462742?v=4", "gravatar_id": "", "url": "https://api.github.com/users/mariosasko", "html_url": "https://github.com/mariosasko", "followers_url": "https://api.github.com/users/mariosasko/followers", "following_url": "https://api.github.com/users/mariosasko/following{/other_user}", "gists_url": "https://api.github.com/users/mariosasko/gists{/gist_id}", "starred_url": "https://api.github.com/users/mariosasko/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/mariosasko/subscriptions", "organizations_url": "https://api.github.com/users/mariosasko/orgs", "repos_url": "https://api.github.com/users/mariosasko/repos", "events_url": "https://api.github.com/users/mariosasko/events{/privacy}", "received_events_url": "https://api.github.com/users/mariosasko/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	null	[]	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6817). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005464 / 0.011353 (-0.005889) \| 0.004174 / 0.011008 (-0.006834) \| 0.064252 / 0.038508 (0.025744) \| 0.033305 / 0.023109 (0.010196) \| 0.245831 / 0.275898 (-0.030067) \| 0.275575 / 0.323480 (-0.047905) \| 0.003359 / 0.007986 (-0.004626) \| 0.004196 / 0.004328 (-0.000132) \| 0.049961 / 0.004250 (0.045710) \| 0.048940 / 0.037052 (0.011888) \| 0.261037 / 0.258489 (0.002548) \| 0.295329 / 0.293841 (0.001488) \| 0.028570 / 0.128546 (-0.099976) \| 0.010747 / 0.075646 (-0.064900) \| 0.216021 / 0.419271 (-0.203251) \| 0.036885 / 0.043533 (-0.006648) \| 0.251169 / 0.255139 (-0.003970) \| 0.286233 / 0.283200 (0.003034) \| 0.021253 / 0.141683 (-0.120429) \| 1.150669 / 1.452155 (-0.301485) \| 1.187577 / 1.492716 (-0.305140) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.094443 / 0.018006 (0.076436) \| 0.304410 / 0.000490 (0.303920) \| 0.000213 / 0.000200 (0.000013) \| 0.000041 / 0.000054 (-0.000013) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.019568 / 0.037411 (-0.017844) \| 0.065734 / 0.014526 (0.051208) \| 0.076042 / 0.176557 (-0.100515) \| 0.123624 / 0.737135 (-0.613511) \| 0.078047 / 0.296338 (-0.218291) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.295725 / 0.215209 (0.080515) \| 2.752501 / 2.077655 (0.674846) \| 1.461856 / 1.504120 (-0.042264) \| 1.353692 / 1.541195 (-0.187503) \| 1.391777 / 1.468490 (-0.076713) \| 0.563423 / 4.584777 (-4.021354) \| 2.384620 / 3.745712 (-1.361092) \| 2.876092 / 5.269862 (-2.393769) \| 1.803913 / 4.565676 (-2.761763) \| 0.062678 / 0.424275 (-0.361597) \| 0.005428 / 0.007607 (-0.002179) \| 0.333797 / 0.226044 (0.107753) \| 3.304458 / 2.268929 (1.035530) \| 1.801768 / 55.444624 (-53.642856) \| 1.569406 / 6.876477 (-5.307070) \| 1.614535 / 2.142072 (-0.527538) \| 0.650178 / 4.805227 (-4.155049) \| 0.119693 / 6.500664 (-6.380971) \| 0.042832 / 0.075469 (-0.032637) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.982035 / 1.841788 (-0.859753) \| 12.390006 / 8.074308 (4.315698) \| 10.127018 / 10.191392 (-0.064374) \| 0.131963 / 0.680424 (-0.548461) \| 0.013926 / 0.534201 (-0.520275) \| 0.289587 / 0.579283 (-0.289696) \| 0.270302 / 0.434364 (-0.164062) \| 0.327231 / 0.540337 (-0.213107) \| 0.422522 / 1.386936 (-0.964414) \|\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005666 / 0.011353 (-0.005687) \| 0.003914 / 0.011008 (-0.007094) \| 0.050315 / 0.038508 (0.011807) \| 0.032367 / 0.023109 (0.009257) \| 0.271732 / 0.275898 (-0.004166) \| 0.297248 / 0.323480 (-0.026231) \| 0.005101 / 0.007986 (-0.002884) \| 0.002882 / 0.004328 (-0.001447) \| 0.049651 / 0.004250 (0.045401) \| 0.043773 / 0.037052 (0.006721) \| 0.288011 / 0.258489 (0.029522) \| 0.311863 / 0.293841 (0.018023) \| 0.029147 / 0.128546 (-0.099399) \| 0.010722 / 0.075646 (-0.064925) \| 0.058832 / 0.419271 (-0.360440) \| 0.033092 / 0.043533 (-0.010441) \| 0.274686 / 0.255139 (0.019547) \| 0.294174 / 0.283200 (0.010975) \| 0.019196 / 0.141683 (-0.122486) \| 1.126615 / 1.452155 (-0.325540) \| 1.193107 / 1.492716 (-0.299609) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.097547 / 0.018006 (0.079541) \| 0.316018 / 0.000490 (0.315529) \| 0.000330 / 0.000200 (0.000130) \| 0.000073 / 0.000054 (0.000019) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.022336 / 0.037411 (-0.015076) \| 0.077092 / 0.014526 (0.062566) \| 0.088873 / 0.176557 (-0.087684) \| 0.128517 / 0.737135 (-0.608619) \| 0.094061 / 0.296338 (-0.202278) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.300100 / 0.215209 (0.084891) \| 2.893114 / 2.077655 (0.815460) \| 1.570541 / 1.504120 (0.066421) \| 1.453538 / 1.541195 (-0.087657) \| 1.505325 / 1.468490 (0.036835) \| 0.567955 / 4.584777 (-4.016822) \| 2.458547 / 3.745712 (-1.287166) \| 2.969181 / 5.269862 (-2.300680) \| 1.850082 / 4.565676 (-2.715594) \| 0.063811 / 0.424275 (-0.360464) \| 0.005378 / 0.007607 (-0.002229) \| 0.348219 / 0.226044 (0.122175) \| 3.443986 / 2.268929 (1.175057) \| 1.943005 / 55.444624 (-53.501620) \| 1.686541 / 6.876477 (-5.189935) \| 1.715552 / 2.142072 (-0.426520) \| 0.641361 / 4.805227 (-4.163866) \| 0.116652 / 6.500664 (-6.384012) \| 0.042216 / 0.075469 (-0.033253) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 1.020102 / 1.841788 (-0.821686) \| 12.966127 / 8.074308 (4.891819) \| 10.748397 / 10.191392 (0.557005) \| 0.132601 / 0.680424 (-0.547823) \| 0.016643 / 0.534201 (-0.517558) \| 0.289422 / 0.579283 (-0.289861) \| 0.275524 / 0.434364 (-0.158840) \| 0.332835 / 0.540337 (-0.207503) \| 0.427867 / 1.386936 (-0.959069) \|\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#5eb93f61f9f6e7fefba5d800defe21e50ddf8c58 \"CML watermark\")\n" ]	2024-04-16T17:41:27	2024-04-16T18:27:44	2024-04-16T18:17:29	COLLABORATOR	null	false	{ "url": "https://api.github.com/repos/huggingface/datasets/pulls/6817", "html_url": "https://github.com/huggingface/datasets/pull/6817", "diff_url": "https://github.com/huggingface/datasets/pull/6817.diff", "patch_url": "https://github.com/huggingface/datasets/pull/6817.patch", "merged_at": "2024-04-16T18:17:29" }	As discussed in https://github.com/huggingface/datasets/pull/6816, this is needed to support objects that implement `__index__` such as `np.int64` in `Dataset.__getitem__`.	{ "login": "mariosasko", "id": 47462742, "node_id": "MDQ6VXNlcjQ3NDYyNzQy", "avatar_url": "https://avatars.githubusercontent.com/u/47462742?v=4", "gravatar_id": "", "url": "https://api.github.com/users/mariosasko", "html_url": "https://github.com/mariosasko", "followers_url": "https://api.github.com/users/mariosasko/followers", "following_url": "https://api.github.com/users/mariosasko/following{/other_user}", "gists_url": "https://api.github.com/users/mariosasko/gists{/gist_id}", "starred_url": "https://api.github.com/users/mariosasko/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/mariosasko/subscriptions", "organizations_url": "https://api.github.com/users/mariosasko/orgs", "repos_url": "https://api.github.com/users/mariosasko/repos", "events_url": "https://api.github.com/users/mariosasko/events{/privacy}", "received_events_url": "https://api.github.com/users/mariosasko/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6817/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6817/timeline	null	null	true
https://api.github.com/repos/huggingface/datasets/issues/6816	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6816/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6816/comments	https://api.github.com/repos/huggingface/datasets/issues/6816/events	https://github.com/huggingface/datasets/pull/6816	2,246,264,911	PR_kwDODunzps5s0MYO	6,816	Improve typing of Dataset.search, matching definition	{ "login": "Dref360", "id": 8976546, "node_id": "MDQ6VXNlcjg5NzY1NDY=", "avatar_url": "https://avatars.githubusercontent.com/u/8976546?v=4", "gravatar_id": "", "url": "https://api.github.com/users/Dref360", "html_url": "https://github.com/Dref360", "followers_url": "https://api.github.com/users/Dref360/followers", "following_url": "https://api.github.com/users/Dref360/following{/other_user}", "gists_url": "https://api.github.com/users/Dref360/gists{/gist_id}", "starred_url": "https://api.github.com/users/Dref360/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/Dref360/subscriptions", "organizations_url": "https://api.github.com/users/Dref360/orgs", "repos_url": "https://api.github.com/users/Dref360/repos", "events_url": "https://api.github.com/users/Dref360/events{/privacy}", "received_events_url": "https://api.github.com/users/Dref360/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	null	[]	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6816). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "Hi! This is a breaking change. A better solution is to check for \"indexable\" types in `__getitem__` to support keys such as `np.int64`:\r\n```python\r\nimport operator\r\n\r\ndef _query_table_with_indices_mapping(...): # or _query_table\r\n ...\r\n try:\r\n operator.index(key)\r\n except TypeError:\r\n pass\r\n \r\n _raise_bad_key_type(key)\r\n```", "Sounds good! We should still update type annotations for SearchResult in my opinion." ]	2024-04-16T14:53:39	2024-04-16T15:54:10	2024-04-16T15:54:10	CONTRIBUTOR	null	false	{ "url": "https://api.github.com/repos/huggingface/datasets/pulls/6816", "html_url": "https://github.com/huggingface/datasets/pull/6816", "diff_url": "https://github.com/huggingface/datasets/pull/6816.diff", "patch_url": "https://github.com/huggingface/datasets/pull/6816.patch", "merged_at": null }	Previously, the output of `score, indices = Dataset.search(...)` would be numpy arrays. The definition in `SearchResult` is a `List[int]` so this PR now matched the expected type. The previous behavior is a bit annoying as `Dataset.__getitem__` doesn't support `numpy.int64` which forced me to convert `indices` to int eg: ```python score, indices = ds.search(...) item = ds[int(indices[0])] ```	{ "login": "Dref360", "id": 8976546, "node_id": "MDQ6VXNlcjg5NzY1NDY=", "avatar_url": "https://avatars.githubusercontent.com/u/8976546?v=4", "gravatar_id": "", "url": "https://api.github.com/users/Dref360", "html_url": "https://github.com/Dref360", "followers_url": "https://api.github.com/users/Dref360/followers", "following_url": "https://api.github.com/users/Dref360/following{/other_user}", "gists_url": "https://api.github.com/users/Dref360/gists{/gist_id}", "starred_url": "https://api.github.com/users/Dref360/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/Dref360/subscriptions", "organizations_url": "https://api.github.com/users/Dref360/orgs", "repos_url": "https://api.github.com/users/Dref360/repos", "events_url": "https://api.github.com/users/Dref360/events{/privacy}", "received_events_url": "https://api.github.com/users/Dref360/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6816/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6816/timeline	null	null	true
https://api.github.com/repos/huggingface/datasets/issues/6815	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6815/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6815/comments	https://api.github.com/repos/huggingface/datasets/issues/6815/events	https://github.com/huggingface/datasets/pull/6815	2,246,197,070	PR_kwDODunzps5sz9eC	6,815	Remove `os.path.relpath` in `resolve_patterns`	{ "login": "mariosasko", "id": 47462742, "node_id": "MDQ6VXNlcjQ3NDYyNzQy", "avatar_url": "https://avatars.githubusercontent.com/u/47462742?v=4", "gravatar_id": "", "url": "https://api.github.com/users/mariosasko", "html_url": "https://github.com/mariosasko", "followers_url": "https://api.github.com/users/mariosasko/followers", "following_url": "https://api.github.com/users/mariosasko/following{/other_user}", "gists_url": "https://api.github.com/users/mariosasko/gists{/gist_id}", "starred_url": "https://api.github.com/users/mariosasko/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/mariosasko/subscriptions", "organizations_url": "https://api.github.com/users/mariosasko/orgs", "repos_url": "https://api.github.com/users/mariosasko/repos", "events_url": "https://api.github.com/users/mariosasko/events{/privacy}", "received_events_url": "https://api.github.com/users/mariosasko/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	null	[]	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6815). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005101 / 0.011353 (-0.006252) \| 0.003478 / 0.011008 (-0.007531) \| 0.063634 / 0.038508 (0.025126) \| 0.030670 / 0.023109 (0.007561) \| 0.240057 / 0.275898 (-0.035841) \| 0.258726 / 0.323480 (-0.064754) \| 0.004136 / 0.007986 (-0.003849) \| 0.002667 / 0.004328 (-0.001662) \| 0.048968 / 0.004250 (0.044718) \| 0.043125 / 0.037052 (0.006073) \| 0.249033 / 0.258489 (-0.009456) \| 0.282630 / 0.293841 (-0.011211) \| 0.027528 / 0.128546 (-0.101018) \| 0.009987 / 0.075646 (-0.065660) \| 0.210614 / 0.419271 (-0.208657) \| 0.034965 / 0.043533 (-0.008567) \| 0.239199 / 0.255139 (-0.015940) \| 0.276891 / 0.283200 (-0.006309) \| 0.017781 / 0.141683 (-0.123902) \| 1.142795 / 1.452155 (-0.309360) \| 1.184171 / 1.492716 (-0.308545) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.092075 / 0.018006 (0.074068) \| 0.300709 / 0.000490 (0.300220) \| 0.000217 / 0.000200 (0.000017) \| 0.000046 / 0.000054 (-0.000008) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.017887 / 0.037411 (-0.019525) \| 0.061134 / 0.014526 (0.046608) \| 0.077075 / 0.176557 (-0.099482) \| 0.118808 / 0.737135 (-0.618327) \| 0.074961 / 0.296338 (-0.221377) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.280404 / 0.215209 (0.065194) \| 2.759453 / 2.077655 (0.681798) \| 1.437552 / 1.504120 (-0.066568) \| 1.318703 / 1.541195 (-0.222492) \| 1.313075 / 1.468490 (-0.155416) \| 0.564876 / 4.584777 (-4.019901) \| 2.381595 / 3.745712 (-1.364118) \| 2.759171 / 5.269862 (-2.510691) \| 1.725878 / 4.565676 (-2.839799) \| 0.062627 / 0.424275 (-0.361648) \| 0.005295 / 0.007607 (-0.002312) \| 0.335245 / 0.226044 (0.109201) \| 3.276266 / 2.268929 (1.007337) \| 1.843272 / 55.444624 (-53.601353) \| 1.519948 / 6.876477 (-5.356529) \| 1.519626 / 2.142072 (-0.622447) \| 0.637891 / 4.805227 (-4.167336) \| 0.116260 / 6.500664 (-6.384404) \| 0.041768 / 0.075469 (-0.033701) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.981739 / 1.841788 (-0.860049) \| 11.354768 / 8.074308 (3.280460) \| 9.900585 / 10.191392 (-0.290807) \| 0.130683 / 0.680424 (-0.549741) \| 0.014122 / 0.534201 (-0.520079) \| 0.297451 / 0.579283 (-0.281832) \| 0.264786 / 0.434364 (-0.169577) \| 0.337559 / 0.540337 (-0.202778) \| 0.425131 / 1.386936 (-0.961805) \|\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005182 / 0.011353 (-0.006171) \| 0.003355 / 0.011008 (-0.007653) \| 0.049842 / 0.038508 (0.011334) \| 0.031094 / 0.023109 (0.007985) \| 0.270080 / 0.275898 (-0.005818) \| 0.291602 / 0.323480 (-0.031878) \| 0.004210 / 0.007986 (-0.003776) \| 0.002720 / 0.004328 (-0.001608) \| 0.048986 / 0.004250 (0.044736) \| 0.055187 / 0.037052 (0.018135) \| 0.280085 / 0.258489 (0.021595) \| 0.308148 / 0.293841 (0.014308) \| 0.029300 / 0.128546 (-0.099246) \| 0.009976 / 0.075646 (-0.065670) \| 0.057930 / 0.419271 (-0.361341) \| 0.032543 / 0.043533 (-0.010990) \| 0.277485 / 0.255139 (0.022346) \| 0.289345 / 0.283200 (0.006145) \| 0.018070 / 0.141683 (-0.123613) \| 1.140977 / 1.452155 (-0.311178) \| 1.190543 / 1.492716 (-0.302173) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.093416 / 0.018006 (0.075410) \| 0.298732 / 0.000490 (0.298242) \| 0.000224 / 0.000200 (0.000024) \| 0.000051 / 0.000054 (-0.000004) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.022167 / 0.037411 (-0.015244) \| 0.074970 / 0.014526 (0.060444) \| 0.086047 / 0.176557 (-0.090509) \| 0.125228 / 0.737135 (-0.611907) \| 0.088330 / 0.296338 (-0.208008) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.292016 / 0.215209 (0.076807) \| 2.845712 / 2.077655 (0.768057) \| 1.576951 / 1.504120 (0.072831) \| 1.452298 / 1.541195 (-0.088897) \| 1.456918 / 1.468490 (-0.011572) \| 0.560529 / 4.584777 (-4.024248) \| 2.425333 / 3.745712 (-1.320379) \| 2.739416 / 5.269862 (-2.530445) \| 1.715779 / 4.565676 (-2.849898) \| 0.062568 / 0.424275 (-0.361707) \| 0.005327 / 0.007607 (-0.002280) \| 0.351376 / 0.226044 (0.125332) \| 3.401855 / 2.268929 (1.132927) \| 1.921844 / 55.444624 (-53.522780) \| 1.648423 / 6.876477 (-5.228054) \| 1.642003 / 2.142072 (-0.500069) \| 0.640789 / 4.805227 (-4.164438) \| 0.114699 / 6.500664 (-6.385965) \| 0.040451 / 0.075469 (-0.035018) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 1.004186 / 1.841788 (-0.837602) \| 11.879918 / 8.074308 (3.805609) \| 9.981852 / 10.191392 (-0.209540) \| 0.141298 / 0.680424 (-0.539126) \| 0.015005 / 0.534201 (-0.519196) \| 0.291537 / 0.579283 (-0.287746) \| 0.272093 / 0.434364 (-0.162271) \| 0.331361 / 0.540337 (-0.208977) \| 0.422940 / 1.386936 (-0.963996) \|\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#ed8860faef3e751f3b77c08e09ce723a74d2c2e5 \"CML watermark\")\n" ]	2024-04-16T14:23:13	2024-04-16T16:06:48	2024-04-16T15:58:22	COLLABORATOR	null	false	{ "url": "https://api.github.com/repos/huggingface/datasets/pulls/6815", "html_url": "https://github.com/huggingface/datasets/pull/6815", "diff_url": "https://github.com/huggingface/datasets/pull/6815.diff", "patch_url": "https://github.com/huggingface/datasets/pull/6815.patch", "merged_at": "2024-04-16T15:58:22" }	... to save a few seconds when resolving repos with many data files.	{ "login": "mariosasko", "id": 47462742, "node_id": "MDQ6VXNlcjQ3NDYyNzQy", "avatar_url": "https://avatars.githubusercontent.com/u/47462742?v=4", "gravatar_id": "", "url": "https://api.github.com/users/mariosasko", "html_url": "https://github.com/mariosasko", "followers_url": "https://api.github.com/users/mariosasko/followers", "following_url": "https://api.github.com/users/mariosasko/following{/other_user}", "gists_url": "https://api.github.com/users/mariosasko/gists{/gist_id}", "starred_url": "https://api.github.com/users/mariosasko/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/mariosasko/subscriptions", "organizations_url": "https://api.github.com/users/mariosasko/orgs", "repos_url": "https://api.github.com/users/mariosasko/repos", "events_url": "https://api.github.com/users/mariosasko/events{/privacy}", "received_events_url": "https://api.github.com/users/mariosasko/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6815/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6815/timeline	null	null	true
https://api.github.com/repos/huggingface/datasets/issues/6814	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6814/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6814/comments	https://api.github.com/repos/huggingface/datasets/issues/6814/events	https://github.com/huggingface/datasets/issues/6814	2,245,857,902	I_kwDODunzps6F3RJu	6,814	`map` with `num_proc` > 1 leads to OOM	{ "login": "bhavitvyamalik", "id": 19718818, "node_id": "MDQ6VXNlcjE5NzE4ODE4", "avatar_url": "https://avatars.githubusercontent.com/u/19718818?v=4", "gravatar_id": "", "url": "https://api.github.com/users/bhavitvyamalik", "html_url": "https://github.com/bhavitvyamalik", "followers_url": "https://api.github.com/users/bhavitvyamalik/followers", "following_url": "https://api.github.com/users/bhavitvyamalik/following{/other_user}", "gists_url": "https://api.github.com/users/bhavitvyamalik/gists{/gist_id}", "starred_url": "https://api.github.com/users/bhavitvyamalik/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/bhavitvyamalik/subscriptions", "organizations_url": "https://api.github.com/users/bhavitvyamalik/orgs", "repos_url": "https://api.github.com/users/bhavitvyamalik/repos", "events_url": "https://api.github.com/users/bhavitvyamalik/events{/privacy}", "received_events_url": "https://api.github.com/users/bhavitvyamalik/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	open	false	null	[]	null	[ "Hi ! You can try to reduce `writer_batch_size`. It corresponds to the number of samples that stay in RAM before being flushed to disk" ]	2024-04-16T11:56:03	2024-04-19T11:53:41	null	CONTRIBUTOR	null	null	null	### Describe the bug When running `map` on parquet dataset loaded from local machine, the RAM usage increases linearly eventually leading to OOM. I was wondering if I should I save the `cache_file` after every n steps in order to prevent this? ### Steps to reproduce the bug ``` ds = load_dataset("parquet", data_files=dataset_path, split="train") ds = ds.shard(num_shards=4, index=0) ds = ds.cast_column("audio", datasets.features.Audio(sampling_rate=16_000)) ds = ds.map(prepare_dataset, num_proc=32, writer_batch_size=1000, keep_in_memory=False, desc="preprocess dataset") ``` ``` def prepare_dataset(batch): # load audio sample = batch["audio"] inputs = feature_extractor(sample["array"], sampling_rate=16000) batch["input_values"] = inputs.input_values[0] batch["input_length"] = len(sample["array"].squeeze()) return batch ``` ### Expected behavior It shouldn't run into OOM problem. ### Environment info - `datasets` version: 2.18.0 - Platform: Linux-5.4.0-91-generic-x86_64-with-glibc2.17 - Python version: 3.8.19 - `huggingface_hub` version: 0.22.2 - PyArrow version: 15.0.2 - Pandas version: 2.0.3 - `fsspec` version: 2024.2.0	null	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6814/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6814/timeline	null	null	false
https://api.github.com/repos/huggingface/datasets/issues/6813	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6813/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6813/comments	https://api.github.com/repos/huggingface/datasets/issues/6813/events	https://github.com/huggingface/datasets/pull/6813	2,245,626,870	PR_kwDODunzps5sx-9V	6,813	Add Dataset.take and Dataset.skip	{ "login": "lhoestq", "id": 42851186, "node_id": "MDQ6VXNlcjQyODUxMTg2", "avatar_url": "https://avatars.githubusercontent.com/u/42851186?v=4", "gravatar_id": "", "url": "https://api.github.com/users/lhoestq", "html_url": "https://github.com/lhoestq", "followers_url": "https://api.github.com/users/lhoestq/followers", "following_url": "https://api.github.com/users/lhoestq/following{/other_user}", "gists_url": "https://api.github.com/users/lhoestq/gists{/gist_id}", "starred_url": "https://api.github.com/users/lhoestq/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/lhoestq/subscriptions", "organizations_url": "https://api.github.com/users/lhoestq/orgs", "repos_url": "https://api.github.com/users/lhoestq/repos", "events_url": "https://api.github.com/users/lhoestq/events{/privacy}", "received_events_url": "https://api.github.com/users/lhoestq/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	null	[]	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6813). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005153 / 0.011353 (-0.006200) \| 0.003560 / 0.011008 (-0.007448) \| 0.063142 / 0.038508 (0.024634) \| 0.030799 / 0.023109 (0.007690) \| 0.241754 / 0.275898 (-0.034144) \| 0.264874 / 0.323480 (-0.058606) \| 0.003099 / 0.007986 (-0.004887) \| 0.002629 / 0.004328 (-0.001700) \| 0.049006 / 0.004250 (0.044756) \| 0.044831 / 0.037052 (0.007779) \| 0.258961 / 0.258489 (0.000472) \| 0.286939 / 0.293841 (-0.006902) \| 0.026756 / 0.128546 (-0.101791) \| 0.010443 / 0.075646 (-0.065204) \| 0.207264 / 0.419271 (-0.212007) \| 0.035242 / 0.043533 (-0.008291) \| 0.250440 / 0.255139 (-0.004699) \| 0.265405 / 0.283200 (-0.017794) \| 0.018924 / 0.141683 (-0.122759) \| 1.138607 / 1.452155 (-0.313547) \| 1.203017 / 1.492716 (-0.289700) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.091293 / 0.018006 (0.073286) \| 0.303937 / 0.000490 (0.303447) \| 0.000266 / 0.000200 (0.000066) \| 0.000056 / 0.000054 (0.000002) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.018667 / 0.037411 (-0.018744) \| 0.061310 / 0.014526 (0.046784) \| 0.073565 / 0.176557 (-0.102991) \| 0.119044 / 0.737135 (-0.618091) \| 0.074484 / 0.296338 (-0.221854) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.286324 / 0.215209 (0.071114) \| 2.836637 / 2.077655 (0.758982) \| 1.458531 / 1.504120 (-0.045589) \| 1.333081 / 1.541195 (-0.208114) \| 1.328398 / 1.468490 (-0.140092) \| 0.571467 / 4.584777 (-4.013310) \| 2.409869 / 3.745712 (-1.335843) \| 2.760241 / 5.269862 (-2.509621) \| 1.728153 / 4.565676 (-2.837523) \| 0.063008 / 0.424275 (-0.361267) \| 0.005375 / 0.007607 (-0.002232) \| 0.338574 / 0.226044 (0.112530) \| 3.355485 / 2.268929 (1.086556) \| 1.812741 / 55.444624 (-53.631884) \| 1.507435 / 6.876477 (-5.369041) \| 1.516957 / 2.142072 (-0.625116) \| 0.643790 / 4.805227 (-4.161437) \| 0.117465 / 6.500664 (-6.383199) \| 0.041960 / 0.075469 (-0.033509) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.993787 / 1.841788 (-0.848001) \| 11.439076 / 8.074308 (3.364768) \| 9.636815 / 10.191392 (-0.554577) \| 0.131292 / 0.680424 (-0.549132) \| 0.014916 / 0.534201 (-0.519285) \| 0.287309 / 0.579283 (-0.291974) \| 0.261971 / 0.434364 (-0.172392) \| 0.324453 / 0.540337 (-0.215885) \| 0.420306 / 1.386936 (-0.966630) \|\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005138 / 0.011353 (-0.006215) \| 0.003719 / 0.011008 (-0.007289) \| 0.050411 / 0.038508 (0.011903) \| 0.031334 / 0.023109 (0.008225) \| 0.281752 / 0.275898 (0.005854) \| 0.299445 / 0.323480 (-0.024035) \| 0.004194 / 0.007986 (-0.003792) \| 0.002737 / 0.004328 (-0.001591) \| 0.048527 / 0.004250 (0.044277) \| 0.040294 / 0.037052 (0.003242) \| 0.291763 / 0.258489 (0.033274) \| 0.317597 / 0.293841 (0.023757) \| 0.029014 / 0.128546 (-0.099532) \| 0.010372 / 0.075646 (-0.065274) \| 0.058704 / 0.419271 (-0.360568) \| 0.033259 / 0.043533 (-0.010273) \| 0.278109 / 0.255139 (0.022970) \| 0.299593 / 0.283200 (0.016393) \| 0.018048 / 0.141683 (-0.123635) \| 1.185558 / 1.452155 (-0.266597) \| 1.203481 / 1.492716 (-0.289236) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.091149 / 0.018006 (0.073143) \| 0.306152 / 0.000490 (0.305662) \| 0.000246 / 0.000200 (0.000046) \| 0.000052 / 0.000054 (-0.000003) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.022082 / 0.037411 (-0.015330) \| 0.074487 / 0.014526 (0.059961) \| 0.086112 / 0.176557 (-0.090444) \| 0.124303 / 0.737135 (-0.612832) \| 0.088831 / 0.296338 (-0.207508) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.291745 / 0.215209 (0.076536) \| 2.878397 / 2.077655 (0.800742) \| 1.606920 / 1.504120 (0.102801) \| 1.492352 / 1.541195 (-0.048843) \| 1.509725 / 1.468490 (0.041235) \| 0.567087 / 4.584777 (-4.017690) \| 2.436423 / 3.745712 (-1.309290) \| 2.793930 / 5.269862 (-2.475932) \| 1.748329 / 4.565676 (-2.817347) \| 0.063424 / 0.424275 (-0.360851) \| 0.005476 / 0.007607 (-0.002131) \| 0.346211 / 0.226044 (0.120167) \| 3.461288 / 2.268929 (1.192360) \| 1.979362 / 55.444624 (-53.465262) \| 1.702877 / 6.876477 (-5.173600) \| 1.699087 / 2.142072 (-0.442985) \| 0.645116 / 4.805227 (-4.160112) \| 0.116186 / 6.500664 (-6.384478) \| 0.041246 / 0.075469 (-0.034223) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 1.017540 / 1.841788 (-0.824248) \| 12.016640 / 8.074308 (3.942332) \| 10.234085 / 10.191392 (0.042693) \| 0.147558 / 0.680424 (-0.532866) \| 0.015096 / 0.534201 (-0.519105) \| 0.288077 / 0.579283 (-0.291206) \| 0.274629 / 0.434364 (-0.159735) \| 0.334097 / 0.540337 (-0.206241) \| 0.425476 / 1.386936 (-0.961460) \|\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#55eb1d9a34a91dbf2418166f9f1d92f7181e778b \"CML watermark\")\n" ]	2024-04-16T09:53:42	2024-04-16T14:12:14	2024-04-16T14:06:07	MEMBER	null	false	{ "url": "https://api.github.com/repos/huggingface/datasets/pulls/6813", "html_url": "https://github.com/huggingface/datasets/pull/6813", "diff_url": "https://github.com/huggingface/datasets/pull/6813.diff", "patch_url": "https://github.com/huggingface/datasets/pull/6813.patch", "merged_at": "2024-04-16T14:06:07" }	...to be aligned with IterableDataset.take and IterableDataset.skip	{ "login": "lhoestq", "id": 42851186, "node_id": "MDQ6VXNlcjQyODUxMTg2", "avatar_url": "https://avatars.githubusercontent.com/u/42851186?v=4", "gravatar_id": "", "url": "https://api.github.com/users/lhoestq", "html_url": "https://github.com/lhoestq", "followers_url": "https://api.github.com/users/lhoestq/followers", "following_url": "https://api.github.com/users/lhoestq/following{/other_user}", "gists_url": "https://api.github.com/users/lhoestq/gists{/gist_id}", "starred_url": "https://api.github.com/users/lhoestq/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/lhoestq/subscriptions", "organizations_url": "https://api.github.com/users/lhoestq/orgs", "repos_url": "https://api.github.com/users/lhoestq/repos", "events_url": "https://api.github.com/users/lhoestq/events{/privacy}", "received_events_url": "https://api.github.com/users/lhoestq/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6813/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6813/timeline	null	null	true
https://api.github.com/repos/huggingface/datasets/issues/6812	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6812/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6812/comments	https://api.github.com/repos/huggingface/datasets/issues/6812/events	https://github.com/huggingface/datasets/pull/6812	2,244,898,824	PR_kwDODunzps5svgoq	6,812	Run CI	{ "login": "charliermarsh", "id": 1309177, "node_id": "MDQ6VXNlcjEzMDkxNzc=", "avatar_url": "https://avatars.githubusercontent.com/u/1309177?v=4", "gravatar_id": "", "url": "https://api.github.com/users/charliermarsh", "html_url": "https://github.com/charliermarsh", "followers_url": "https://api.github.com/users/charliermarsh/followers", "following_url": "https://api.github.com/users/charliermarsh/following{/other_user}", "gists_url": "https://api.github.com/users/charliermarsh/gists{/gist_id}", "starred_url": "https://api.github.com/users/charliermarsh/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/charliermarsh/subscriptions", "organizations_url": "https://api.github.com/users/charliermarsh/orgs", "repos_url": "https://api.github.com/users/charliermarsh/repos", "events_url": "https://api.github.com/users/charliermarsh/events{/privacy}", "received_events_url": "https://api.github.com/users/charliermarsh/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	null	[]	null	[ "(Sorry, meant to open this against my own fork. I'm attempting to debug this issue (https://github.com/astral-sh/uv/issues/1921#issuecomment-2058056192) reported by `huggingface/datasets` on the uv repo.)" ]	2024-04-16T01:12:36	2024-04-16T01:14:16	2024-04-16T01:12:41	NONE	null	false	{ "url": "https://api.github.com/repos/huggingface/datasets/pulls/6812", "html_url": "https://github.com/huggingface/datasets/pull/6812", "diff_url": "https://github.com/huggingface/datasets/pull/6812.diff", "patch_url": "https://github.com/huggingface/datasets/pull/6812.patch", "merged_at": null }	null	{ "login": "charliermarsh", "id": 1309177, "node_id": "MDQ6VXNlcjEzMDkxNzc=", "avatar_url": "https://avatars.githubusercontent.com/u/1309177?v=4", "gravatar_id": "", "url": "https://api.github.com/users/charliermarsh", "html_url": "https://github.com/charliermarsh", "followers_url": "https://api.github.com/users/charliermarsh/followers", "following_url": "https://api.github.com/users/charliermarsh/following{/other_user}", "gists_url": "https://api.github.com/users/charliermarsh/gists{/gist_id}", "starred_url": "https://api.github.com/users/charliermarsh/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/charliermarsh/subscriptions", "organizations_url": "https://api.github.com/users/charliermarsh/orgs", "repos_url": "https://api.github.com/users/charliermarsh/repos", "events_url": "https://api.github.com/users/charliermarsh/events{/privacy}", "received_events_url": "https://api.github.com/users/charliermarsh/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6812/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6812/timeline	null	null	true
https://api.github.com/repos/huggingface/datasets/issues/6811	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6811/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6811/comments	https://api.github.com/repos/huggingface/datasets/issues/6811/events	https://github.com/huggingface/datasets/pull/6811	2,243,656,096	PR_kwDODunzps5srOtR	6,811	add allow_primitive_to_str and allow_decimal_to_str instead of allow_number_to_str	{ "login": "Modexus", "id": 37351874, "node_id": "MDQ6VXNlcjM3MzUxODc0", "avatar_url": "https://avatars.githubusercontent.com/u/37351874?v=4", "gravatar_id": "", "url": "https://api.github.com/users/Modexus", "html_url": "https://github.com/Modexus", "followers_url": "https://api.github.com/users/Modexus/followers", "following_url": "https://api.github.com/users/Modexus/following{/other_user}", "gists_url": "https://api.github.com/users/Modexus/gists{/gist_id}", "starred_url": "https://api.github.com/users/Modexus/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/Modexus/subscriptions", "organizations_url": "https://api.github.com/users/Modexus/orgs", "repos_url": "https://api.github.com/users/Modexus/repos", "events_url": "https://api.github.com/users/Modexus/events{/privacy}", "received_events_url": "https://api.github.com/users/Modexus/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	null	[]	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6811). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "@mariosasko pytest seems to be missing on windows?", "CI is not behaving well today 🙂 ", "I couldn't find an instance of the `allow_number_to_str` parameter (or `array_cast`/`cast_array_to_feature` more generally) being used in the wild. So, I think simply removing `allow_number_to_str` instead of deprecating it should be fine, considering `array_cast`/`cast_array_to_feature` are somewhat hidden. Do you agree @lhoestq? ", "Yup we can remove without any deprecation cycle", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005253 / 0.011353 (-0.006100) \| 0.003767 / 0.011008 (-0.007241) \| 0.064599 / 0.038508 (0.026091) \| 0.030758 / 0.023109 (0.007649) \| 0.237437 / 0.275898 (-0.038461) \| 0.277580 / 0.323480 (-0.045900) \| 0.004220 / 0.007986 (-0.003766) \| 0.002738 / 0.004328 (-0.001591) \| 0.049393 / 0.004250 (0.045143) \| 0.045283 / 0.037052 (0.008231) \| 0.249907 / 0.258489 (-0.008582) \| 0.283301 / 0.293841 (-0.010540) \| 0.027722 / 0.128546 (-0.100825) \| 0.010842 / 0.075646 (-0.064804) \| 0.219197 / 0.419271 (-0.200074) \| 0.036449 / 0.043533 (-0.007084) \| 0.237774 / 0.255139 (-0.017365) \| 0.257981 / 0.283200 (-0.025218) \| 0.018098 / 0.141683 (-0.123585) \| 1.161778 / 1.452155 (-0.290376) \| 1.212707 / 1.492716 (-0.280010) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.096462 / 0.018006 (0.078456) \| 0.305322 / 0.000490 (0.304832) \| 0.000218 / 0.000200 (0.000018) \| 0.000048 / 0.000054 (-0.000006) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.018438 / 0.037411 (-0.018973) \| 0.061633 / 0.014526 (0.047107) \| 0.073678 / 0.176557 (-0.102879) \| 0.122033 / 0.737135 (-0.615103) \| 0.074846 / 0.296338 (-0.221493) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.279564 / 0.215209 (0.064355) \| 2.756984 / 2.077655 (0.679330) \| 1.486525 / 1.504120 (-0.017595) \| 1.366474 / 1.541195 (-0.174721) \| 1.370192 / 1.468490 (-0.098298) \| 0.576940 / 4.584777 (-4.007837) \| 2.414088 / 3.745712 (-1.331624) \| 2.788423 / 5.269862 (-2.481439) \| 1.738695 / 4.565676 (-2.826982) \| 0.064456 / 0.424275 (-0.359819) \| 0.005536 / 0.007607 (-0.002071) \| 0.337266 / 0.226044 (0.111222) \| 3.327140 / 2.268929 (1.058212) \| 1.837553 / 55.444624 (-53.607072) \| 1.538955 / 6.876477 (-5.337521) \| 1.575624 / 2.142072 (-0.566448) \| 0.639960 / 4.805227 (-4.165267) \| 0.117607 / 6.500664 (-6.383057) \| 0.042077 / 0.075469 (-0.033393) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.960488 / 1.841788 (-0.881300) \| 11.565280 / 8.074308 (3.490972) \| 9.702633 / 10.191392 (-0.488759) \| 0.139106 / 0.680424 (-0.541318) \| 0.013601 / 0.534201 (-0.520600) \| 0.291499 / 0.579283 (-0.287784) \| 0.277433 / 0.434364 (-0.156930) \| 0.325700 / 0.540337 (-0.214637) \| 0.421036 / 1.386936 (-0.965900) \|\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005405 / 0.011353 (-0.005948) \| 0.003816 / 0.011008 (-0.007192) \| 0.050422 / 0.038508 (0.011914) \| 0.030473 / 0.023109 (0.007364) \| 0.275975 / 0.275898 (0.000077) \| 0.298002 / 0.323480 (-0.025478) \| 0.004280 / 0.007986 (-0.003706) \| 0.002746 / 0.004328 (-0.001583) \| 0.049649 / 0.004250 (0.045398) \| 0.040675 / 0.037052 (0.003623) \| 0.287496 / 0.258489 (0.029007) \| 0.315140 / 0.293841 (0.021299) \| 0.029835 / 0.128546 (-0.098711) \| 0.010443 / 0.075646 (-0.065204) \| 0.058299 / 0.419271 (-0.360972) \| 0.032944 / 0.043533 (-0.010588) \| 0.279468 / 0.255139 (0.024329) \| 0.296336 / 0.283200 (0.013136) \| 0.018572 / 0.141683 (-0.123111) \| 1.177622 / 1.452155 (-0.274532) \| 1.238240 / 1.492716 (-0.254477) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.091867 / 0.018006 (0.073861) \| 0.299982 / 0.000490 (0.299492) \| 0.000217 / 0.000200 (0.000017) \| 0.000043 / 0.000054 (-0.000011) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.022649 / 0.037411 (-0.014762) \| 0.074948 / 0.014526 (0.060422) \| 0.087949 / 0.176557 (-0.088607) \| 0.125875 / 0.737135 (-0.611261) \| 0.089295 / 0.296338 (-0.207044) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.290387 / 0.215209 (0.075178) \| 2.820969 / 2.077655 (0.743315) \| 1.614607 / 1.504120 (0.110487) \| 1.496959 / 1.541195 (-0.044236) \| 1.526475 / 1.468490 (0.057985) \| 0.570087 / 4.584777 (-4.014690) \| 2.423106 / 3.745712 (-1.322606) \| 2.825321 / 5.269862 (-2.444540) \| 1.765580 / 4.565676 (-2.800097) \| 0.063289 / 0.424275 (-0.360986) \| 0.005456 / 0.007607 (-0.002151) \| 0.344100 / 0.226044 (0.118055) \| 3.395733 / 2.268929 (1.126804) \| 1.951794 / 55.444624 (-53.492830) \| 1.677689 / 6.876477 (-5.198787) \| 1.684448 / 2.142072 (-0.457624) \| 0.644343 / 4.805227 (-4.160885) \| 0.115796 / 6.500664 (-6.384868) \| 0.041052 / 0.075469 (-0.034417) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 1.031487 / 1.841788 (-0.810301) \| 12.116156 / 8.074308 (4.041848) \| 10.472247 / 10.191392 (0.280855) \| 0.142934 / 0.680424 (-0.537490) \| 0.015470 / 0.534201 (-0.518731) \| 0.290402 / 0.579283 (-0.288882) \| 0.272594 / 0.434364 (-0.161770) \| 0.328311 / 0.540337 (-0.212027) \| 0.424694 / 1.386936 (-0.962242) \|\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#8983a3b4dec315bf25331a6065cb74de9017f0e8 \"CML watermark\")\n" ]	2024-04-15T13:14:38	2024-07-03T14:59:42	2024-04-16T17:03:17	CONTRIBUTOR	null	false	{ "url": "https://api.github.com/repos/huggingface/datasets/pulls/6811", "html_url": "https://github.com/huggingface/datasets/pull/6811", "diff_url": "https://github.com/huggingface/datasets/pull/6811.diff", "patch_url": "https://github.com/huggingface/datasets/pull/6811.patch", "merged_at": "2024-04-16T17:03:17" }	Fix #6805	{ "login": "lhoestq", "id": 42851186, "node_id": "MDQ6VXNlcjQyODUxMTg2", "avatar_url": "https://avatars.githubusercontent.com/u/42851186?v=4", "gravatar_id": "", "url": "https://api.github.com/users/lhoestq", "html_url": "https://github.com/lhoestq", "followers_url": "https://api.github.com/users/lhoestq/followers", "following_url": "https://api.github.com/users/lhoestq/following{/other_user}", "gists_url": "https://api.github.com/users/lhoestq/gists{/gist_id}", "starred_url": "https://api.github.com/users/lhoestq/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/lhoestq/subscriptions", "organizations_url": "https://api.github.com/users/lhoestq/orgs", "repos_url": "https://api.github.com/users/lhoestq/repos", "events_url": "https://api.github.com/users/lhoestq/events{/privacy}", "received_events_url": "https://api.github.com/users/lhoestq/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6811/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6811/timeline	null	null	true
https://api.github.com/repos/huggingface/datasets/issues/6810	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6810/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6810/comments	https://api.github.com/repos/huggingface/datasets/issues/6810/events	https://github.com/huggingface/datasets/issues/6810	2,242,968,745	I_kwDODunzps6FsPyp	6,810	Allow deleting a subset/config from a no-script dataset	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[ { "id": 1935892871, "node_id": "MDU6TGFiZWwxOTM1ODkyODcx", "url": "https://api.github.com/repos/huggingface/datasets/labels/enhancement", "name": "enhancement", "color": "a2eeef", "default": true, "description": "New feature or request" } ]	closed	false	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[ { "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false } ]	null	[ "Probably best to implement this as a CLI command?", "Thanks for your comment, @mariosasko. Or maybe both (in Python and as CLI command)? The Python command would be just the reverse of `push_to_hub`...\r\n\r\nI am working on a draft implementation, so we can discuss about the API and UX." ]	2024-04-15T07:53:26	2024-04-30T09:44:25	2024-04-30T09:44:25	MEMBER	null	null	null	As proposed by @BramVanroy, it would be neat to have this functionality through the API.	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6810/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6810/timeline	null	completed	false
https://api.github.com/repos/huggingface/datasets/issues/6809	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6809/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6809/comments	https://api.github.com/repos/huggingface/datasets/issues/6809/events	https://github.com/huggingface/datasets/pull/6809	2,242,956,297	PR_kwDODunzps5so0e2	6,809	Make convert_to_parquet CLI command create script branch	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	null	[]	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6809). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "@huggingface/datasets once this PR is merged, I would suggest making a release. Do you agree?\r\n- This PR is a follow-up of #6795", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.004963 / 0.011353 (-0.006390) \| 0.003121 / 0.011008 (-0.007888) \| 0.063421 / 0.038508 (0.024913) \| 0.030727 / 0.023109 (0.007618) \| 0.237698 / 0.275898 (-0.038200) \| 0.266613 / 0.323480 (-0.056867) \| 0.004237 / 0.007986 (-0.003749) \| 0.002715 / 0.004328 (-0.001614) \| 0.049503 / 0.004250 (0.045253) \| 0.043705 / 0.037052 (0.006653) \| 0.247818 / 0.258489 (-0.010671) \| 0.287545 / 0.293841 (-0.006296) \| 0.027232 / 0.128546 (-0.101314) \| 0.009952 / 0.075646 (-0.065695) \| 0.208678 / 0.419271 (-0.210593) \| 0.035494 / 0.043533 (-0.008039) \| 0.260900 / 0.255139 (0.005761) \| 0.264738 / 0.283200 (-0.018461) \| 0.018093 / 0.141683 (-0.123590) \| 1.130924 / 1.452155 (-0.321231) \| 1.178982 / 1.492716 (-0.313734) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.094610 / 0.018006 (0.076604) \| 0.304674 / 0.000490 (0.304184) \| 0.000215 / 0.000200 (0.000015) \| 0.000048 / 0.000054 (-0.000007) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.018168 / 0.037411 (-0.019243) \| 0.062040 / 0.014526 (0.047514) \| 0.075634 / 0.176557 (-0.100922) \| 0.119488 / 0.737135 (-0.617647) \| 0.074790 / 0.296338 (-0.221548) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.282449 / 0.215209 (0.067240) \| 2.773231 / 2.077655 (0.695576) \| 1.455156 / 1.504120 (-0.048964) \| 1.332652 / 1.541195 (-0.208543) \| 1.340795 / 1.468490 (-0.127695) \| 0.576588 / 4.584777 (-4.008189) \| 2.415513 / 3.745712 (-1.330199) \| 2.801569 / 5.269862 (-2.468292) \| 1.741039 / 4.565676 (-2.824637) \| 0.064386 / 0.424275 (-0.359890) \| 0.005293 / 0.007607 (-0.002314) \| 0.329732 / 0.226044 (0.103688) \| 3.227275 / 2.268929 (0.958347) \| 1.793121 / 55.444624 (-53.651503) \| 1.515115 / 6.876477 (-5.361362) \| 1.518738 / 2.142072 (-0.623335) \| 0.664465 / 4.805227 (-4.140762) \| 0.118813 / 6.500664 (-6.381851) \| 0.041715 / 0.075469 (-0.033754) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.974371 / 1.841788 (-0.867416) \| 11.432869 / 8.074308 (3.358561) \| 9.607939 / 10.191392 (-0.583453) \| 0.143996 / 0.680424 (-0.536427) \| 0.014624 / 0.534201 (-0.519577) \| 0.286899 / 0.579283 (-0.292384) \| 0.265965 / 0.434364 (-0.168399) \| 0.324727 / 0.540337 (-0.215611) \| 0.420917 / 1.386936 (-0.966019) \|\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005145 / 0.011353 (-0.006207) \| 0.003723 / 0.011008 (-0.007286) \| 0.050387 / 0.038508 (0.011879) \| 0.030734 / 0.023109 (0.007625) \| 0.274331 / 0.275898 (-0.001567) \| 0.295045 / 0.323480 (-0.028435) \| 0.004187 / 0.007986 (-0.003799) \| 0.002781 / 0.004328 (-0.001547) \| 0.049698 / 0.004250 (0.045448) \| 0.040049 / 0.037052 (0.002996) \| 0.284016 / 0.258489 (0.025527) \| 0.309908 / 0.293841 (0.016067) \| 0.028994 / 0.128546 (-0.099552) \| 0.010625 / 0.075646 (-0.065021) \| 0.059305 / 0.419271 (-0.359967) \| 0.032982 / 0.043533 (-0.010551) \| 0.273342 / 0.255139 (0.018203) \| 0.291726 / 0.283200 (0.008527) \| 0.018084 / 0.141683 (-0.123599) \| 1.136864 / 1.452155 (-0.315290) \| 1.163656 / 1.492716 (-0.329061) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.094868 / 0.018006 (0.076862) \| 0.302900 / 0.000490 (0.302410) \| 0.000226 / 0.000200 (0.000026) \| 0.000053 / 0.000054 (-0.000002) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.022142 / 0.037411 (-0.015269) \| 0.077457 / 0.014526 (0.062932) \| 0.087989 / 0.176557 (-0.088568) \| 0.127354 / 0.737135 (-0.609781) \| 0.092027 / 0.296338 (-0.204312) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.291196 / 0.215209 (0.075987) \| 2.840386 / 2.077655 (0.762731) \| 1.571201 / 1.504120 (0.067081) \| 1.449429 / 1.541195 (-0.091765) \| 1.467189 / 1.468490 (-0.001301) \| 0.580991 / 4.584777 (-4.003786) \| 2.422566 / 3.745712 (-1.323146) \| 2.839621 / 5.269862 (-2.430240) \| 1.782987 / 4.565676 (-2.782689) \| 0.064765 / 0.424275 (-0.359510) \| 0.005338 / 0.007607 (-0.002269) \| 0.349148 / 0.226044 (0.123104) \| 3.421283 / 2.268929 (1.152355) \| 1.943503 / 55.444624 (-53.501122) \| 1.653881 / 6.876477 (-5.222596) \| 1.698141 / 2.142072 (-0.443931) \| 0.667628 / 4.805227 (-4.137599) \| 0.118469 / 6.500664 (-6.382195) \| 0.041693 / 0.075469 (-0.033776) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 1.026385 / 1.841788 (-0.815403) \| 12.225049 / 8.074308 (4.150741) \| 10.363072 / 10.191392 (0.171680) \| 0.142682 / 0.680424 (-0.537742) \| 0.015698 / 0.534201 (-0.518502) \| 0.288148 / 0.579283 (-0.291135) \| 0.272639 / 0.434364 (-0.161724) \| 0.325305 / 0.540337 (-0.215032) \| 0.421395 / 1.386936 (-0.965541) \|\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#2a14271263da2fda9f966af41c7bd885bfa42256 \"CML watermark\")\n" ]	2024-04-15T07:47:26	2024-04-17T08:44:26	2024-04-17T08:38:18	MEMBER	null	false	{ "url": "https://api.github.com/repos/huggingface/datasets/pulls/6809", "html_url": "https://github.com/huggingface/datasets/pull/6809", "diff_url": "https://github.com/huggingface/datasets/pull/6809.diff", "patch_url": "https://github.com/huggingface/datasets/pull/6809.patch", "merged_at": "2024-04-17T08:38:18" }	Make convert_to_parquet CLI command create a "script" branch and keep the script file on it. This PR proposes the simplest UX approach: whenever `--revision` is not explicitly passed (i.e., when the script is in the main branch), try to create a "script" branch from the "main" branch; if the "script" branch exists already, then do nothing. Follow-up of: - #6795 Close #6808. CC: @severo	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6809/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6809/timeline	null	null	true
https://api.github.com/repos/huggingface/datasets/issues/6808	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6808/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6808/comments	https://api.github.com/repos/huggingface/datasets/issues/6808/events	https://github.com/huggingface/datasets/issues/6808	2,242,843,611	I_kwDODunzps6FrxPb	6,808	Make convert_to_parquet CLI command create script branch	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[ { "id": 1935892871, "node_id": "MDU6TGFiZWwxOTM1ODkyODcx", "url": "https://api.github.com/repos/huggingface/datasets/labels/enhancement", "name": "enhancement", "color": "a2eeef", "default": true, "description": "New feature or request" } ]	closed	false	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[ { "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false } ]	null	[]	2024-04-15T06:46:07	2024-04-17T08:38:19	2024-04-17T08:38:19	MEMBER	null	null	null	As proposed by @severo, maybe we should add this functionality as well to the CLI command to convert a script-dataset to Parquet. See: https://github.com/huggingface/datasets/pull/6795#discussion_r1562819168 > When providing support, we sometimes suggest that users store their script in a script branch. What do you think of this alternative to deleting the files?	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6808/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6808/timeline	null	completed	false
https://api.github.com/repos/huggingface/datasets/issues/6806	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6806/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6806/comments	https://api.github.com/repos/huggingface/datasets/issues/6806/events	https://github.com/huggingface/datasets/pull/6806	2,239,435,074	PR_kwDODunzps5sc8Mb	6,806	Fix hf-internal-testing/dataset_with_script commit SHA in CI test	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	null	[]	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6806). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005068 / 0.011353 (-0.006285) \| 0.003613 / 0.011008 (-0.007395) \| 0.063226 / 0.038508 (0.024718) \| 0.030653 / 0.023109 (0.007544) \| 0.243981 / 0.275898 (-0.031918) \| 0.268596 / 0.323480 (-0.054884) \| 0.003109 / 0.007986 (-0.004876) \| 0.003292 / 0.004328 (-0.001036) \| 0.048857 / 0.004250 (0.044606) \| 0.043929 / 0.037052 (0.006876) \| 0.264002 / 0.258489 (0.005513) \| 0.289028 / 0.293841 (-0.004813) \| 0.028053 / 0.128546 (-0.100493) \| 0.010837 / 0.075646 (-0.064809) \| 0.208084 / 0.419271 (-0.211188) \| 0.035592 / 0.043533 (-0.007941) \| 0.252639 / 0.255139 (-0.002500) \| 0.267599 / 0.283200 (-0.015600) \| 0.018097 / 0.141683 (-0.123585) \| 1.150811 / 1.452155 (-0.301344) \| 1.219449 / 1.492716 (-0.273267) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.095427 / 0.018006 (0.077421) \| 0.307270 / 0.000490 (0.306781) \| 0.000218 / 0.000200 (0.000018) \| 0.000043 / 0.000054 (-0.000011) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.018713 / 0.037411 (-0.018698) \| 0.065238 / 0.014526 (0.050712) \| 0.074650 / 0.176557 (-0.101906) \| 0.120130 / 0.737135 (-0.617005) \| 0.078457 / 0.296338 (-0.217882) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.283666 / 0.215209 (0.068457) \| 2.852818 / 2.077655 (0.775163) \| 1.459790 / 1.504120 (-0.044330) \| 1.326732 / 1.541195 (-0.214463) \| 1.373530 / 1.468490 (-0.094960) \| 0.579136 / 4.584777 (-4.005641) \| 2.388369 / 3.745712 (-1.357343) \| 2.813786 / 5.269862 (-2.456075) \| 1.730079 / 4.565676 (-2.835597) \| 0.063445 / 0.424275 (-0.360831) \| 0.005355 / 0.007607 (-0.002252) \| 0.340169 / 0.226044 (0.114124) \| 3.391220 / 2.268929 (1.122291) \| 1.838003 / 55.444624 (-53.606621) \| 1.523518 / 6.876477 (-5.352959) \| 1.574007 / 2.142072 (-0.568065) \| 0.650265 / 4.805227 (-4.154962) \| 0.117114 / 6.500664 (-6.383550) \| 0.042430 / 0.075469 (-0.033039) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.955596 / 1.841788 (-0.886191) \| 11.546544 / 8.074308 (3.472236) \| 9.593613 / 10.191392 (-0.597779) \| 0.141502 / 0.680424 (-0.538922) \| 0.014251 / 0.534201 (-0.519950) \| 0.293825 / 0.579283 (-0.285458) \| 0.263088 / 0.434364 (-0.171276) \| 0.325035 / 0.540337 (-0.215302) \| 0.419372 / 1.386936 (-0.967564) \|\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005567 / 0.011353 (-0.005785) \| 0.003670 / 0.011008 (-0.007338) \| 0.050338 / 0.038508 (0.011830) \| 0.031730 / 0.023109 (0.008621) \| 0.278307 / 0.275898 (0.002409) \| 0.303170 / 0.323480 (-0.020310) \| 0.004276 / 0.007986 (-0.003709) \| 0.002720 / 0.004328 (-0.001609) \| 0.048675 / 0.004250 (0.044425) \| 0.041026 / 0.037052 (0.003974) \| 0.291353 / 0.258489 (0.032864) \| 0.318487 / 0.293841 (0.024646) \| 0.029676 / 0.128546 (-0.098870) \| 0.010428 / 0.075646 (-0.065218) \| 0.057443 / 0.419271 (-0.361828) \| 0.032735 / 0.043533 (-0.010798) \| 0.282900 / 0.255139 (0.027761) \| 0.297539 / 0.283200 (0.014339) \| 0.018237 / 0.141683 (-0.123446) \| 1.188047 / 1.452155 (-0.264107) \| 1.223283 / 1.492716 (-0.269433) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.090629 / 0.018006 (0.072623) \| 0.300898 / 0.000490 (0.300408) \| 0.000212 / 0.000200 (0.000012) \| 0.000133 / 0.000054 (0.000078) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.022200 / 0.037411 (-0.015211) \| 0.075310 / 0.014526 (0.060784) \| 0.086790 / 0.176557 (-0.089766) \| 0.127392 / 0.737135 (-0.609744) \| 0.088435 / 0.296338 (-0.207903) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.301308 / 0.215209 (0.086099) \| 2.963126 / 2.077655 (0.885471) \| 1.639604 / 1.504120 (0.135484) \| 1.508776 / 1.541195 (-0.032419) \| 1.553280 / 1.468490 (0.084789) \| 0.567256 / 4.584777 (-4.017520) \| 2.445231 / 3.745712 (-1.300482) \| 2.884071 / 5.269862 (-2.385791) \| 1.777321 / 4.565676 (-2.788355) \| 0.063659 / 0.424275 (-0.360616) \| 0.005435 / 0.007607 (-0.002172) \| 0.361786 / 0.226044 (0.135742) \| 3.624264 / 2.268929 (1.355335) \| 2.022661 / 55.444624 (-53.421963) \| 1.740581 / 6.876477 (-5.135896) \| 1.748503 / 2.142072 (-0.393570) \| 0.660783 / 4.805227 (-4.144444) \| 0.118045 / 6.500664 (-6.382619) \| 0.040940 / 0.075469 (-0.034529) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 1.015614 / 1.841788 (-0.826174) \| 12.094985 / 8.074308 (4.020677) \| 10.435581 / 10.191392 (0.244189) \| 0.140239 / 0.680424 (-0.540185) \| 0.014992 / 0.534201 (-0.519209) \| 0.290549 / 0.579283 (-0.288735) \| 0.274718 / 0.434364 (-0.159645) \| 0.334783 / 0.540337 (-0.205554) \| 0.426540 / 1.386936 (-0.960396) \|\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#828aff908450ac7af3a1820bb2eb7b438f2692f5 \"CML watermark\")\n" ]	2024-04-12T08:47:50	2024-04-12T09:08:23	2024-04-12T09:02:12	MEMBER	null	false	{ "url": "https://api.github.com/repos/huggingface/datasets/pulls/6806", "html_url": "https://github.com/huggingface/datasets/pull/6806", "diff_url": "https://github.com/huggingface/datasets/pull/6806.diff", "patch_url": "https://github.com/huggingface/datasets/pull/6806.patch", "merged_at": "2024-04-12T09:02:12" }	Fix test using latest commit SHA in hf-internal-testing/dataset_with_script dataset: https://huggingface.co/datasets/hf-internal-testing/dataset_with_script/commits/refs%2Fconvert%2Fparquet Fix #6796.	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6806/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6806/timeline	null	null	true
https://api.github.com/repos/huggingface/datasets/issues/6805	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6805/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6805/comments	https://api.github.com/repos/huggingface/datasets/issues/6805/events	https://github.com/huggingface/datasets/issues/6805	2,239,034,951	I_kwDODunzps6FdPZH	6,805	Batched mapping of existing string column casts boolean to string	{ "login": "starmpcc", "id": 46891489, "node_id": "MDQ6VXNlcjQ2ODkxNDg5", "avatar_url": "https://avatars.githubusercontent.com/u/46891489?v=4", "gravatar_id": "", "url": "https://api.github.com/users/starmpcc", "html_url": "https://github.com/starmpcc", "followers_url": "https://api.github.com/users/starmpcc/followers", "following_url": "https://api.github.com/users/starmpcc/following{/other_user}", "gists_url": "https://api.github.com/users/starmpcc/gists{/gist_id}", "starred_url": "https://api.github.com/users/starmpcc/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/starmpcc/subscriptions", "organizations_url": "https://api.github.com/users/starmpcc/orgs", "repos_url": "https://api.github.com/users/starmpcc/repos", "events_url": "https://api.github.com/users/starmpcc/events{/privacy}", "received_events_url": "https://api.github.com/users/starmpcc/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	null	[]	null	[ "This seems to be hardcoded behavior in table.py `array_cast`.\r\n```python\r\nif (\r\n not allow_number_to_str\r\n and pa.types.is_string(pa_type)\r\n and (pa.types.is_floating(array.type) or pa.types.is_integer(array.type))\r\n ):\r\n raise TypeError(\r\n f\"Couldn't cast array of type {array.type} to {pa_type} since allow_number_to_str is set to {allow_number_to_str}\"\r\n )\r\n if pa.types.is_null(pa_type) and not pa.types.is_null(array.type):\r\n raise TypeError(f\"Couldn't cast array of type {array.type} to {pa_type}\")\r\n return array.cast(pa_type)\r\n```\r\nwhere floats and integers are not cast to string but booleans are.\r\nMaybe this should be extended to booleans?", "Thanks for reporting! @Modexus Do you want to open a PR with the suggested fix?", "I'll gladly create a PR but not sure what the behavior should be.\r\n\r\nShould a value returned from map be cast to the current feature?\r\nAt the moment this seems very inconsistent since `datetime `is also cast (this would only fix `boolean`) but nested structures are not.\r\n\r\n```python\r\ndset = Dataset.from_dict({\"a\": [\"Hello world!\"]})\r\ndset = dset.map(lambda x: {\"a\": date(2021, 1, 1)})\r\n# dset[0][\"a\"] == '2021-01-01'\r\n```\r\n```python\r\ndset = Dataset.from_dict({\"a\": [\"Hello world!\"]})\r\ndset = dset.map(lambda x: {\"a\": [True]})\r\n# dset[0][\"a\"] == [True]\r\n```\r\n\r\nIs there are reason to cast the value if the user doesn't specify it explicitly?\r\nSeems tricky that some things are cast and some are not.", "Indeed, it also makes sense to raise a `TypeError` for temporal and decimal types.\r\n\r\n> Is there are reason to cast the value if the user doesn't specify it explicitly?\r\n\r\nThis is how PyArrow's built-in `cast` behaves - it allows casting from primitive types to strings. Hence, we need `allow_number_to_str` to disallow such casts (e.g., in the [scenario](https://github.com/huggingface/datasets/blob/a3bc89d8bfd47c2a175c3ce16d92b7307cdeafd6/src/datasets/arrow_writer.py#L208) when we are \"trying a type\" to preserve the original type if there is a column in the output dataset with the same name as in the input one).\r\n\r\nPS: In the PR, we can introduce `allow_numeric_to_str` (for floats, integers, decimals, booleans) and `allow_temporal_to_str` (for dates, timestamps, ...) and deprecate `allow_number_to_str` to make it clear what each parameter does.", "Would just `allow_primitive_to_str` work?\r\nThis should include all `numeric`, `boolean `and `temporal`formats.\r\n\r\nNote that at least in the [ C++ implementation](https://arrow.apache.org/docs/cpp/api/utilities.html#_CPPv410is_numericRK8DataType) `numeric `seems to exclude `boolean`.\r\n[](https://arrow.apache.org/docs/cpp/api/utilities.html#_CPPv410is_numericRK8DataType)", "Indeed, `allow_primitive_to_str` sounds better.\r\n\r\nPS: PyArrow's `pa.types.is_primitive` returns `False` for decimal types, but I think is okay for us to treat decimals as primitive types (or we can have `allow_decimal_to_str` to be fully consistent with PyArrow)", "Fixed by:\r\n- #6811" ]	2024-04-12T04:21:41	2024-07-03T15:00:07	2024-07-03T15:00:07	NONE	null	null	null	### Describe the bug Let the dataset contain a column named 'a', which is of the string type. If 'a' is converted to a boolean using batched mapping, the mapper automatically casts the boolean to a string (e.g., True -> 'true'). It only happens when the original column and the mapped column name are identical. Thank you! ### Steps to reproduce the bug ```python from datasets import Dataset dset = Dataset.from_dict({'a': ['11', '22']}) dset = dset.map(lambda x: {'a': [True for _ in x['a']]}, batched=True) print(dset['a']) ``` ``` > ['true', 'true'] ``` ### Expected behavior [True, True] ### Environment info - `datasets` version: 2.18.0 - Platform: Linux-5.4.0-148-generic-x86_64-with-glibc2.31 - Python version: 3.10.13 - `huggingface_hub` version: 0.21.4 - PyArrow version: 15.0.2 - Pandas version: 2.2.1 - `fsspec` version: 2023.12.2	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6805/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6805/timeline	null	completed	false
https://api.github.com/repos/huggingface/datasets/issues/6804	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6804/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6804/comments	https://api.github.com/repos/huggingface/datasets/issues/6804/events	https://github.com/huggingface/datasets/pull/6804	2,238,035,124	PR_kwDODunzps5sYJFF	6,804	Fix --repo-type order in cli upload docs	{ "login": "lhoestq", "id": 42851186, "node_id": "MDQ6VXNlcjQyODUxMTg2", "avatar_url": "https://avatars.githubusercontent.com/u/42851186?v=4", "gravatar_id": "", "url": "https://api.github.com/users/lhoestq", "html_url": "https://github.com/lhoestq", "followers_url": "https://api.github.com/users/lhoestq/followers", "following_url": "https://api.github.com/users/lhoestq/following{/other_user}", "gists_url": "https://api.github.com/users/lhoestq/gists{/gist_id}", "starred_url": "https://api.github.com/users/lhoestq/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/lhoestq/subscriptions", "organizations_url": "https://api.github.com/users/lhoestq/orgs", "repos_url": "https://api.github.com/users/lhoestq/repos", "events_url": "https://api.github.com/users/lhoestq/events{/privacy}", "received_events_url": "https://api.github.com/users/lhoestq/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	null	[]	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6804). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005222 / 0.011353 (-0.006131) \| 0.003306 / 0.011008 (-0.007702) \| 0.063326 / 0.038508 (0.024818) \| 0.031371 / 0.023109 (0.008261) \| 0.244947 / 0.275898 (-0.030951) \| 0.264141 / 0.323480 (-0.059339) \| 0.004186 / 0.007986 (-0.003800) \| 0.002676 / 0.004328 (-0.001653) \| 0.048690 / 0.004250 (0.044440) \| 0.045172 / 0.037052 (0.008120) \| 0.256597 / 0.258489 (-0.001892) \| 0.284348 / 0.293841 (-0.009493) \| 0.026855 / 0.128546 (-0.101691) \| 0.009947 / 0.075646 (-0.065699) \| 0.206311 / 0.419271 (-0.212961) \| 0.035178 / 0.043533 (-0.008355) \| 0.251501 / 0.255139 (-0.003638) \| 0.261314 / 0.283200 (-0.021886) \| 0.018000 / 0.141683 (-0.123683) \| 1.144588 / 1.452155 (-0.307566) \| 1.193627 / 1.492716 (-0.299089) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.091629 / 0.018006 (0.073623) \| 0.298959 / 0.000490 (0.298469) \| 0.000207 / 0.000200 (0.000007) \| 0.000042 / 0.000054 (-0.000012) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.018053 / 0.037411 (-0.019358) \| 0.061280 / 0.014526 (0.046754) \| 0.074138 / 0.176557 (-0.102419) \| 0.119048 / 0.737135 (-0.618088) \| 0.074572 / 0.296338 (-0.221767) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.282440 / 0.215209 (0.067231) \| 2.762017 / 2.077655 (0.684362) \| 1.474452 / 1.504120 (-0.029668) \| 1.361489 / 1.541195 (-0.179706) \| 1.359696 / 1.468490 (-0.108795) \| 0.569640 / 4.584777 (-4.015137) \| 2.398098 / 3.745712 (-1.347614) \| 2.731399 / 5.269862 (-2.538462) \| 1.697432 / 4.565676 (-2.868245) \| 0.063330 / 0.424275 (-0.360945) \| 0.005416 / 0.007607 (-0.002191) \| 0.346510 / 0.226044 (0.120465) \| 3.276473 / 2.268929 (1.007544) \| 1.837605 / 55.444624 (-53.607019) \| 1.538654 / 6.876477 (-5.337822) \| 1.553943 / 2.142072 (-0.588129) \| 0.640571 / 4.805227 (-4.164657) \| 0.116736 / 6.500664 (-6.383928) \| 0.041701 / 0.075469 (-0.033768) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.975846 / 1.841788 (-0.865942) \| 11.151727 / 8.074308 (3.077419) \| 9.436281 / 10.191392 (-0.755111) \| 0.141027 / 0.680424 (-0.539397) \| 0.014389 / 0.534201 (-0.519812) \| 0.285575 / 0.579283 (-0.293708) \| 0.263753 / 0.434364 (-0.170610) \| 0.321893 / 0.540337 (-0.218444) \| 0.420280 / 1.386936 (-0.966656) \|\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005148 / 0.011353 (-0.006205) \| 0.003264 / 0.011008 (-0.007744) \| 0.049828 / 0.038508 (0.011320) \| 0.031234 / 0.023109 (0.008125) \| 0.271079 / 0.275898 (-0.004819) \| 0.295256 / 0.323480 (-0.028224) \| 0.004128 / 0.007986 (-0.003857) \| 0.002637 / 0.004328 (-0.001692) \| 0.048145 / 0.004250 (0.043895) \| 0.039691 / 0.037052 (0.002638) \| 0.287229 / 0.258489 (0.028740) \| 0.310477 / 0.293841 (0.016636) \| 0.028936 / 0.128546 (-0.099610) \| 0.010392 / 0.075646 (-0.065254) \| 0.057774 / 0.419271 (-0.361497) \| 0.032557 / 0.043533 (-0.010975) \| 0.275146 / 0.255139 (0.020007) \| 0.291283 / 0.283200 (0.008084) \| 0.017724 / 0.141683 (-0.123958) \| 1.186831 / 1.452155 (-0.265324) \| 1.220086 / 1.492716 (-0.272630) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.093575 / 0.018006 (0.075569) \| 0.297198 / 0.000490 (0.296709) \| 0.000216 / 0.000200 (0.000016) \| 0.000044 / 0.000054 (-0.000010) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.021683 / 0.037411 (-0.015728) \| 0.075347 / 0.014526 (0.060821) \| 0.085453 / 0.176557 (-0.091103) \| 0.125422 / 0.737135 (-0.611713) \| 0.087185 / 0.296338 (-0.209153) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.301520 / 0.215209 (0.086311) \| 2.951614 / 2.077655 (0.873959) \| 1.659897 / 1.504120 (0.155777) \| 1.528097 / 1.541195 (-0.013097) \| 1.552031 / 1.468490 (0.083541) \| 0.576297 / 4.584777 (-4.008480) \| 2.492349 / 3.745712 (-1.253363) \| 2.805999 / 5.269862 (-2.463862) \| 1.757556 / 4.565676 (-2.808121) \| 0.064940 / 0.424275 (-0.359335) \| 0.005314 / 0.007607 (-0.002293) \| 0.358838 / 0.226044 (0.132793) \| 3.576890 / 2.268929 (1.307961) \| 2.030788 / 55.444624 (-53.413837) \| 1.743650 / 6.876477 (-5.132826) \| 1.745229 / 2.142072 (-0.396844) \| 0.647840 / 4.805227 (-4.157387) \| 0.116637 / 6.500664 (-6.384027) \| 0.040555 / 0.075469 (-0.034915) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 1.009130 / 1.841788 (-0.832657) \| 11.951145 / 8.074308 (3.876836) \| 9.968355 / 10.191392 (-0.223037) \| 0.139959 / 0.680424 (-0.540465) \| 0.015985 / 0.534201 (-0.518216) \| 0.286594 / 0.579283 (-0.292689) \| 0.275805 / 0.434364 (-0.158559) \| 0.328484 / 0.540337 (-0.211854) \| 0.419818 / 1.386936 (-0.967118) \|\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#89a58cdfc59ecc83662a47b638cf82a5b99f4a48 \"CML watermark\")\n" ]	2024-04-11T15:39:09	2024-04-11T16:24:57	2024-04-11T16:18:47	MEMBER	null	false	{ "url": "https://api.github.com/repos/huggingface/datasets/pulls/6804", "html_url": "https://github.com/huggingface/datasets/pull/6804", "diff_url": "https://github.com/huggingface/datasets/pull/6804.diff", "patch_url": "https://github.com/huggingface/datasets/pull/6804.patch", "merged_at": "2024-04-11T16:18:47" }	null	{ "login": "lhoestq", "id": 42851186, "node_id": "MDQ6VXNlcjQyODUxMTg2", "avatar_url": "https://avatars.githubusercontent.com/u/42851186?v=4", "gravatar_id": "", "url": "https://api.github.com/users/lhoestq", "html_url": "https://github.com/lhoestq", "followers_url": "https://api.github.com/users/lhoestq/followers", "following_url": "https://api.github.com/users/lhoestq/following{/other_user}", "gists_url": "https://api.github.com/users/lhoestq/gists{/gist_id}", "starred_url": "https://api.github.com/users/lhoestq/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/lhoestq/subscriptions", "organizations_url": "https://api.github.com/users/lhoestq/orgs", "repos_url": "https://api.github.com/users/lhoestq/repos", "events_url": "https://api.github.com/users/lhoestq/events{/privacy}", "received_events_url": "https://api.github.com/users/lhoestq/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6804/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6804/timeline	null	null	true
https://api.github.com/repos/huggingface/datasets/issues/6803	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6803/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6803/comments	https://api.github.com/repos/huggingface/datasets/issues/6803/events	https://github.com/huggingface/datasets/pull/6803	2,237,933,090	PR_kwDODunzps5sXyct	6,803	#6791 Improve type checking around FAISS	{ "login": "Dref360", "id": 8976546, "node_id": "MDQ6VXNlcjg5NzY1NDY=", "avatar_url": "https://avatars.githubusercontent.com/u/8976546?v=4", "gravatar_id": "", "url": "https://api.github.com/users/Dref360", "html_url": "https://github.com/Dref360", "followers_url": "https://api.github.com/users/Dref360/followers", "following_url": "https://api.github.com/users/Dref360/following{/other_user}", "gists_url": "https://api.github.com/users/Dref360/gists{/gist_id}", "starred_url": "https://api.github.com/users/Dref360/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/Dref360/subscriptions", "organizations_url": "https://api.github.com/users/Dref360/orgs", "repos_url": "https://api.github.com/users/Dref360/repos", "events_url": "https://api.github.com/users/Dref360/events{/privacy}", "received_events_url": "https://api.github.com/users/Dref360/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	null	[]	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6803). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "CI failures are unrelated.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005063 / 0.011353 (-0.006290) \| 0.003598 / 0.011008 (-0.007410) \| 0.062929 / 0.038508 (0.024421) \| 0.031723 / 0.023109 (0.008614) \| 0.246503 / 0.275898 (-0.029395) \| 0.268742 / 0.323480 (-0.054738) \| 0.003249 / 0.007986 (-0.004737) \| 0.002613 / 0.004328 (-0.001715) \| 0.049001 / 0.004250 (0.044751) \| 0.045740 / 0.037052 (0.008687) \| 0.261182 / 0.258489 (0.002693) \| 0.297328 / 0.293841 (0.003487) \| 0.026925 / 0.128546 (-0.101621) \| 0.010588 / 0.075646 (-0.065059) \| 0.208954 / 0.419271 (-0.210317) \| 0.035286 / 0.043533 (-0.008246) \| 0.277678 / 0.255139 (0.022539) \| 0.269313 / 0.283200 (-0.013887) \| 0.019865 / 0.141683 (-0.121818) \| 1.145883 / 1.452155 (-0.306272) \| 1.196766 / 1.492716 (-0.295950) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.093886 / 0.018006 (0.075879) \| 0.305118 / 0.000490 (0.304629) \| 0.000207 / 0.000200 (0.000008) \| 0.000048 / 0.000054 (-0.000006) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.018473 / 0.037411 (-0.018938) \| 0.061719 / 0.014526 (0.047193) \| 0.074980 / 0.176557 (-0.101577) \| 0.122354 / 0.737135 (-0.614781) \| 0.076111 / 0.296338 (-0.220227) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.280222 / 0.215209 (0.065013) \| 2.692820 / 2.077655 (0.615165) \| 1.440897 / 1.504120 (-0.063223) \| 1.313829 / 1.541195 (-0.227366) \| 1.324392 / 1.468490 (-0.144098) \| 0.570114 / 4.584777 (-4.014662) \| 2.373946 / 3.745712 (-1.371766) \| 2.804485 / 5.269862 (-2.465377) \| 1.753595 / 4.565676 (-2.812081) \| 0.062660 / 0.424275 (-0.361615) \| 0.005267 / 0.007607 (-0.002340) \| 0.323108 / 0.226044 (0.097063) \| 3.257302 / 2.268929 (0.988373) \| 1.802613 / 55.444624 (-53.642011) \| 1.510590 / 6.876477 (-5.365886) \| 1.567452 / 2.142072 (-0.574621) \| 0.649872 / 4.805227 (-4.155355) \| 0.117245 / 6.500664 (-6.383419) \| 0.042260 / 0.075469 (-0.033209) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.976068 / 1.841788 (-0.865720) \| 11.565981 / 8.074308 (3.491672) \| 9.598650 / 10.191392 (-0.592742) \| 0.129903 / 0.680424 (-0.550520) \| 0.014925 / 0.534201 (-0.519276) \| 0.290732 / 0.579283 (-0.288551) \| 0.271236 / 0.434364 (-0.163128) \| 0.325450 / 0.540337 (-0.214888) \| 0.420218 / 1.386936 (-0.966718) \|\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005404 / 0.011353 (-0.005949) \| 0.003710 / 0.011008 (-0.007298) \| 0.050982 / 0.038508 (0.012474) \| 0.031340 / 0.023109 (0.008231) \| 0.279221 / 0.275898 (0.003323) \| 0.300936 / 0.323480 (-0.022544) \| 0.004251 / 0.007986 (-0.003735) \| 0.002697 / 0.004328 (-0.001631) \| 0.049335 / 0.004250 (0.045085) \| 0.040979 / 0.037052 (0.003926) \| 0.287121 / 0.258489 (0.028632) \| 0.315100 / 0.293841 (0.021259) \| 0.029093 / 0.128546 (-0.099454) \| 0.010618 / 0.075646 (-0.065028) \| 0.059095 / 0.419271 (-0.360177) \| 0.032953 / 0.043533 (-0.010580) \| 0.274861 / 0.255139 (0.019722) \| 0.292284 / 0.283200 (0.009085) \| 0.017882 / 0.141683 (-0.123801) \| 1.150590 / 1.452155 (-0.301565) \| 1.203501 / 1.492716 (-0.289215) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.096868 / 0.018006 (0.078862) \| 0.306460 / 0.000490 (0.305971) \| 0.000230 / 0.000200 (0.000030) \| 0.000058 / 0.000054 (0.000003) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.022031 / 0.037411 (-0.015381) \| 0.074847 / 0.014526 (0.060321) \| 0.086951 / 0.176557 (-0.089606) \| 0.125706 / 0.737135 (-0.611429) \| 0.088244 / 0.296338 (-0.208094) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.297861 / 0.215209 (0.082652) \| 2.923172 / 2.077655 (0.845518) \| 1.628511 / 1.504120 (0.124391) \| 1.499907 / 1.541195 (-0.041288) \| 1.490060 / 1.468490 (0.021570) \| 0.564087 / 4.584777 (-4.020690) \| 2.441201 / 3.745712 (-1.304511) \| 2.805283 / 5.269862 (-2.464578) \| 1.762703 / 4.565676 (-2.802974) \| 0.063038 / 0.424275 (-0.361237) \| 0.005276 / 0.007607 (-0.002331) \| 0.343413 / 0.226044 (0.117369) \| 3.400858 / 2.268929 (1.131930) \| 2.039937 / 55.444624 (-53.404687) \| 1.674622 / 6.876477 (-5.201855) \| 1.688371 / 2.142072 (-0.453702) \| 0.635321 / 4.805227 (-4.169907) \| 0.120235 / 6.500664 (-6.380429) \| 0.041106 / 0.075469 (-0.034363) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 1.017469 / 1.841788 (-0.824319) \| 12.383734 / 8.074308 (4.309426) \| 10.352393 / 10.191392 (0.161001) \| 0.131981 / 0.680424 (-0.548443) \| 0.015204 / 0.534201 (-0.518997) \| 0.286157 / 0.579283 (-0.293126) \| 0.278270 / 0.434364 (-0.156094) \| 0.325105 / 0.540337 (-0.215233) \| 0.422301 / 1.386936 (-0.964635) \|\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#9323521505b7fab098fbe2a304389ee2d59783ff \"CML watermark\")\n" ]	2024-04-11T14:54:30	2024-04-11T15:44:09	2024-04-11T15:38:04	CONTRIBUTOR	null	false	{ "url": "https://api.github.com/repos/huggingface/datasets/pulls/6803", "html_url": "https://github.com/huggingface/datasets/pull/6803", "diff_url": "https://github.com/huggingface/datasets/pull/6803.diff", "patch_url": "https://github.com/huggingface/datasets/pull/6803.patch", "merged_at": "2024-04-11T15:38:04" }	Fixes #6791 Small PR to raise a better error when a dataset is not embedded properly.	{ "login": "mariosasko", "id": 47462742, "node_id": "MDQ6VXNlcjQ3NDYyNzQy", "avatar_url": "https://avatars.githubusercontent.com/u/47462742?v=4", "gravatar_id": "", "url": "https://api.github.com/users/mariosasko", "html_url": "https://github.com/mariosasko", "followers_url": "https://api.github.com/users/mariosasko/followers", "following_url": "https://api.github.com/users/mariosasko/following{/other_user}", "gists_url": "https://api.github.com/users/mariosasko/gists{/gist_id}", "starred_url": "https://api.github.com/users/mariosasko/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/mariosasko/subscriptions", "organizations_url": "https://api.github.com/users/mariosasko/orgs", "repos_url": "https://api.github.com/users/mariosasko/repos", "events_url": "https://api.github.com/users/mariosasko/events{/privacy}", "received_events_url": "https://api.github.com/users/mariosasko/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6803/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6803/timeline	null	null	true
https://api.github.com/repos/huggingface/datasets/issues/6802	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6802/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6802/comments	https://api.github.com/repos/huggingface/datasets/issues/6802/events	https://github.com/huggingface/datasets/pull/6802	2,237,365,489	PR_kwDODunzps5sV0m8	6,802	Fix typo in docs (upload CLI)	{ "login": "Wauplin", "id": 11801849, "node_id": "MDQ6VXNlcjExODAxODQ5", "avatar_url": "https://avatars.githubusercontent.com/u/11801849?v=4", "gravatar_id": "", "url": "https://api.github.com/users/Wauplin", "html_url": "https://github.com/Wauplin", "followers_url": "https://api.github.com/users/Wauplin/followers", "following_url": "https://api.github.com/users/Wauplin/following{/other_user}", "gists_url": "https://api.github.com/users/Wauplin/gists{/gist_id}", "starred_url": "https://api.github.com/users/Wauplin/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/Wauplin/subscriptions", "organizations_url": "https://api.github.com/users/Wauplin/orgs", "repos_url": "https://api.github.com/users/Wauplin/repos", "events_url": "https://api.github.com/users/Wauplin/events{/privacy}", "received_events_url": "https://api.github.com/users/Wauplin/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	null	[]	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6802). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.004991 / 0.011353 (-0.006362) \| 0.003574 / 0.011008 (-0.007434) \| 0.062369 / 0.038508 (0.023861) \| 0.029966 / 0.023109 (0.006857) \| 0.256140 / 0.275898 (-0.019758) \| 0.283705 / 0.323480 (-0.039775) \| 0.003170 / 0.007986 (-0.004816) \| 0.002732 / 0.004328 (-0.001597) \| 0.048048 / 0.004250 (0.043798) \| 0.044497 / 0.037052 (0.007445) \| 0.273206 / 0.258489 (0.014717) \| 0.294593 / 0.293841 (0.000752) \| 0.027251 / 0.128546 (-0.101295) \| 0.010205 / 0.075646 (-0.065441) \| 0.205979 / 0.419271 (-0.213293) \| 0.035416 / 0.043533 (-0.008117) \| 0.256260 / 0.255139 (0.001121) \| 0.270580 / 0.283200 (-0.012620) \| 0.019659 / 0.141683 (-0.122024) \| 1.138722 / 1.452155 (-0.313432) \| 1.170535 / 1.492716 (-0.322182) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.091588 / 0.018006 (0.073582) \| 0.301280 / 0.000490 (0.300791) \| 0.000209 / 0.000200 (0.000009) \| 0.000048 / 0.000054 (-0.000006) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.019684 / 0.037411 (-0.017727) \| 0.061166 / 0.014526 (0.046640) \| 0.072999 / 0.176557 (-0.103558) \| 0.119264 / 0.737135 (-0.617871) \| 0.074555 / 0.296338 (-0.221784) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.283210 / 0.215209 (0.068001) \| 2.762284 / 2.077655 (0.684629) \| 1.472700 / 1.504120 (-0.031420) \| 1.352734 / 1.541195 (-0.188461) \| 1.363287 / 1.468490 (-0.105203) \| 0.558175 / 4.584777 (-4.026602) \| 2.391648 / 3.745712 (-1.354064) \| 2.787109 / 5.269862 (-2.482752) \| 1.725635 / 4.565676 (-2.840042) \| 0.061827 / 0.424275 (-0.362448) \| 0.005351 / 0.007607 (-0.002256) \| 0.337540 / 0.226044 (0.111496) \| 3.353181 / 2.268929 (1.084252) \| 1.829599 / 55.444624 (-53.615026) \| 1.567691 / 6.876477 (-5.308786) \| 1.605680 / 2.142072 (-0.536393) \| 0.642182 / 4.805227 (-4.163045) \| 0.117321 / 6.500664 (-6.383343) \| 0.042555 / 0.075469 (-0.032915) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.991099 / 1.841788 (-0.850689) \| 11.545219 / 8.074308 (3.470911) \| 9.777574 / 10.191392 (-0.413818) \| 0.130237 / 0.680424 (-0.550186) \| 0.015068 / 0.534201 (-0.519133) \| 0.286029 / 0.579283 (-0.293254) \| 0.266778 / 0.434364 (-0.167586) \| 0.321468 / 0.540337 (-0.218869) \| 0.425371 / 1.386936 (-0.961565) \|\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005144 / 0.011353 (-0.006208) \| 0.004046 / 0.011008 (-0.006962) \| 0.050552 / 0.038508 (0.012043) \| 0.030716 / 0.023109 (0.007607) \| 0.273462 / 0.275898 (-0.002436) \| 0.290649 / 0.323480 (-0.032831) \| 0.004093 / 0.007986 (-0.003893) \| 0.002700 / 0.004328 (-0.001628) \| 0.048833 / 0.004250 (0.044582) \| 0.040059 / 0.037052 (0.003007) \| 0.282496 / 0.258489 (0.024007) \| 0.309176 / 0.293841 (0.015335) \| 0.029207 / 0.128546 (-0.099339) \| 0.010740 / 0.075646 (-0.064907) \| 0.057692 / 0.419271 (-0.361580) \| 0.032570 / 0.043533 (-0.010963) \| 0.269048 / 0.255139 (0.013909) \| 0.287351 / 0.283200 (0.004151) \| 0.017565 / 0.141683 (-0.124118) \| 1.161628 / 1.452155 (-0.290526) \| 1.187236 / 1.492716 (-0.305480) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.095552 / 0.018006 (0.077546) \| 0.312449 / 0.000490 (0.311959) \| 0.000219 / 0.000200 (0.000019) \| 0.000052 / 0.000054 (-0.000003) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.022425 / 0.037411 (-0.014986) \| 0.074941 / 0.014526 (0.060416) \| 0.086784 / 0.176557 (-0.089772) \| 0.125630 / 0.737135 (-0.611506) \| 0.088632 / 0.296338 (-0.207706) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.293003 / 0.215209 (0.077794) \| 2.881826 / 2.077655 (0.804172) \| 1.612840 / 1.504120 (0.108720) \| 1.492727 / 1.541195 (-0.048468) \| 1.520023 / 1.468490 (0.051532) \| 0.558715 / 4.584777 (-4.026062) \| 2.431093 / 3.745712 (-1.314619) \| 2.782672 / 5.269862 (-2.487189) \| 1.721611 / 4.565676 (-2.844065) \| 0.063466 / 0.424275 (-0.360809) \| 0.005221 / 0.007607 (-0.002386) \| 0.352917 / 0.226044 (0.126873) \| 3.443742 / 2.268929 (1.174814) \| 1.981190 / 55.444624 (-53.463435) \| 1.695396 / 6.876477 (-5.181081) \| 1.709959 / 2.142072 (-0.432113) \| 0.649267 / 4.805227 (-4.155960) \| 0.116604 / 6.500664 (-6.384060) \| 0.040688 / 0.075469 (-0.034781) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 1.023182 / 1.841788 (-0.818605) \| 12.046760 / 8.074308 (3.972452) \| 10.294706 / 10.191392 (0.103314) \| 0.132323 / 0.680424 (-0.548101) \| 0.016141 / 0.534201 (-0.518060) \| 0.286620 / 0.579283 (-0.292663) \| 0.272299 / 0.434364 (-0.162065) \| 0.320995 / 0.540337 (-0.219343) \| 0.424138 / 1.386936 (-0.962798) \|\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#873b7c8e354bfbd1873272a03d1392550d2cac39 \"CML watermark\")\n", "> Should it also be applied to this example a few lines later ?\r\n\r\nYes!", "done in https://github.com/huggingface/datasets/pull/6804" ]	2024-04-11T10:05:05	2024-04-11T16:19:00	2024-04-11T13:19:43	CONTRIBUTOR	null	false	{ "url": "https://api.github.com/repos/huggingface/datasets/pulls/6802", "html_url": "https://github.com/huggingface/datasets/pull/6802", "diff_url": "https://github.com/huggingface/datasets/pull/6802.diff", "patch_url": "https://github.com/huggingface/datasets/pull/6802.patch", "merged_at": "2024-04-11T13:19:43" }	Related to https://huggingface.slack.com/archives/C04RG8YRVB8/p1712643948574129 (interal) Positional args must be placed before optional args. Feel free to merge whenever it's ready.	{ "login": "lhoestq", "id": 42851186, "node_id": "MDQ6VXNlcjQyODUxMTg2", "avatar_url": "https://avatars.githubusercontent.com/u/42851186?v=4", "gravatar_id": "", "url": "https://api.github.com/users/lhoestq", "html_url": "https://github.com/lhoestq", "followers_url": "https://api.github.com/users/lhoestq/followers", "following_url": "https://api.github.com/users/lhoestq/following{/other_user}", "gists_url": "https://api.github.com/users/lhoestq/gists{/gist_id}", "starred_url": "https://api.github.com/users/lhoestq/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/lhoestq/subscriptions", "organizations_url": "https://api.github.com/users/lhoestq/orgs", "repos_url": "https://api.github.com/users/lhoestq/repos", "events_url": "https://api.github.com/users/lhoestq/events{/privacy}", "received_events_url": "https://api.github.com/users/lhoestq/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6802/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6802/timeline	null	null	true
https://api.github.com/repos/huggingface/datasets/issues/6801	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6801/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6801/comments	https://api.github.com/repos/huggingface/datasets/issues/6801/events	https://github.com/huggingface/datasets/issues/6801	2,236,911,556	I_kwDODunzps6FVI_E	6,801	got fileNotFound	{ "login": "laoniandisko", "id": 93729155, "node_id": "U_kgDOBZYxgw", "avatar_url": "https://avatars.githubusercontent.com/u/93729155?v=4", "gravatar_id": "", "url": "https://api.github.com/users/laoniandisko", "html_url": "https://github.com/laoniandisko", "followers_url": "https://api.github.com/users/laoniandisko/followers", "following_url": "https://api.github.com/users/laoniandisko/following{/other_user}", "gists_url": "https://api.github.com/users/laoniandisko/gists{/gist_id}", "starred_url": "https://api.github.com/users/laoniandisko/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/laoniandisko/subscriptions", "organizations_url": "https://api.github.com/users/laoniandisko/orgs", "repos_url": "https://api.github.com/users/laoniandisko/repos", "events_url": "https://api.github.com/users/laoniandisko/events{/privacy}", "received_events_url": "https://api.github.com/users/laoniandisko/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	null	[]	null	[ "Hi! I'll open a PR on the Hub to fix this, but please use the Hub's [Community tab](https://huggingface.co/datasets/nyanko7/danbooru2023/discussions) to report such issues in the future.", "I've opened a [PR](https://huggingface.co/datasets/nyanko7/danbooru2023/discussions/8) in the repo, so let's continue the discussion there" ]	2024-04-11T04:57:41	2024-04-12T16:47:43	2024-04-12T16:47:43	NONE	null	null	null	### Describe the bug When I use load_dataset to load the nyanko7/danbooru2023 data set, the cache is read in the form of a symlink. There may be a problem with the arrow_dataset initialization process and I get FileNotFoundError: [Errno 2] No such file or directory: '2945000.jpg' ### Steps to reproduce the bug #code show as below from datasets import load_dataset data = load_dataset("nyanko7/danbooru2023",cache_dir=<symlink>) data["train"][0] ### Expected behavior I should get this result: {'image': <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=365x256 at 0x7FB730CB4070>, 'label': 0} ### Environment info datasets==2.12.0 python==3.10.14	{ "login": "mariosasko", "id": 47462742, "node_id": "MDQ6VXNlcjQ3NDYyNzQy", "avatar_url": "https://avatars.githubusercontent.com/u/47462742?v=4", "gravatar_id": "", "url": "https://api.github.com/users/mariosasko", "html_url": "https://github.com/mariosasko", "followers_url": "https://api.github.com/users/mariosasko/followers", "following_url": "https://api.github.com/users/mariosasko/following{/other_user}", "gists_url": "https://api.github.com/users/mariosasko/gists{/gist_id}", "starred_url": "https://api.github.com/users/mariosasko/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/mariosasko/subscriptions", "organizations_url": "https://api.github.com/users/mariosasko/orgs", "repos_url": "https://api.github.com/users/mariosasko/repos", "events_url": "https://api.github.com/users/mariosasko/events{/privacy}", "received_events_url": "https://api.github.com/users/mariosasko/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6801/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6801/timeline	null	completed	false
https://api.github.com/repos/huggingface/datasets/issues/6800	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6800/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6800/comments	https://api.github.com/repos/huggingface/datasets/issues/6800/events	https://github.com/huggingface/datasets/issues/6800	2,236,431,288	I_kwDODunzps6FTTu4	6,800	High overhead when loading lots of subsets from the same dataset	{ "login": "loicmagne", "id": 53355258, "node_id": "MDQ6VXNlcjUzMzU1MjU4", "avatar_url": "https://avatars.githubusercontent.com/u/53355258?v=4", "gravatar_id": "", "url": "https://api.github.com/users/loicmagne", "html_url": "https://github.com/loicmagne", "followers_url": "https://api.github.com/users/loicmagne/followers", "following_url": "https://api.github.com/users/loicmagne/following{/other_user}", "gists_url": "https://api.github.com/users/loicmagne/gists{/gist_id}", "starred_url": "https://api.github.com/users/loicmagne/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/loicmagne/subscriptions", "organizations_url": "https://api.github.com/users/loicmagne/orgs", "repos_url": "https://api.github.com/users/loicmagne/repos", "events_url": "https://api.github.com/users/loicmagne/events{/privacy}", "received_events_url": "https://api.github.com/users/loicmagne/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	open	false	null	[]	null	[ "Hi !\r\n\r\nIt's possible to multiple files at once:\r\n\r\n```python\r\ndata_files = \"data/.jsonl\"\r\n# Or pass a list of files\r\nlangs = ['ka-ml', 'br-sr', 'ka-pt', 'id-ko', ..., 'fi-ze_zh', 'he-kk', 'ka-tr']\r\ndata_files = [f\"data/{lang}.jsonl\" for lang in langs]\r\nds = load_dataset(\"loicmagne/open-subtitles-250-bitext-mining\", data_files=data_files, split=\"train\")\r\n```\r\n\r\nAlso maybe you can add a subset called \"all\" for people that want to load all the data without having to list all the languages ?\r\n\r\n```yaml\r\n - config_name: all\r\n data_files: data/.jsonl\r\n```\r\n", "Thanks for your reply, it is indeed much faster, however the result is a dataset where all the subsets are \"merged\" together, the language pair is lost:\r\n```\r\nDatasetDict({\r\n train: Dataset({\r\n features: ['sentence1', 'sentence2'],\r\n num_rows: 247809\r\n })\r\n})\r\n```\r\nI guess I could add a 'lang' feature for each row in the dataset, is there a better way to do it ?", "Hi @lhoestq over at https://github.com/embeddings-benchmark/mteb/issues/530 we have started examining these issues and would love to make a PR for datasets if we believe there is a way to improve the speed. As I assume you have a better overview than me @lhoestq, would you be interested in a PR, and might you have an idea about where we would start working on it?\r\n\r\nWe see a speed comparison of \r\n1. 15 minutes (for ~20% of the languages) when loaded using a for loop\r\n2. 17 minutes using the your suggestion\r\n3. ~30 seconds when using @loicmagne \"merged\" method.\r\n\r\nWorth mentioning is that solution 2 looses the language information.", "Can you retry using `datasets` 2.19 ? We improved a lot the speed of downloading datasets with tons of small files.\r\n\r\n```\r\npip install -U datasets\r\n```\r\n\r\nNow this takes 17sec on my side instead of the 17min minutes @loicmagne mentioned :)\r\n\r\n```python\r\n>>> %time ds = load_dataset(\"loicmagne/open-subtitles-250-bitext-mining\", data_files=\"data/.jsonl\")\r\nDownloading readme: 100%\|█████████████████████████████████\| 13.7k/13.7k [00:00<00:00, 5.47MB/s]\r\nResolving data files: 100%\|█████████████████████████████████\| 250/250 [00:00<00:00, 612.51it/s]\r\nDownloading data: 100%\|██████████████████████████████████\| 250/250 [00:12<00:00, 19.68files/s]\r\nGenerating train split: 247809 examples [00:00, 1057071.08 examples/s]\r\nCPU times: user 4.95 s, sys: 3.1 s, total: 8.05 s\r\nWall time: 17.4 s\r\n```", "> Can you retry using `datasets` 2.19 ? We improved a lot the speed of downloading datasets with tons of small files.\r\n> \r\n> ```\r\n> pip install -U datasets\r\n> ```\r\n> \r\n> Now this takes 17sec on my side instead of the 17min minutes @loicmagne mentioned :)\r\n> \r\n> ```python\r\n> >>> %time ds = load_dataset(\"loicmagne/open-subtitles-250-bitext-mining\", data_files=\"data/.jsonl\")\r\n> Downloading readme: 100%\|█████████████████████████████████\| 13.7k/13.7k [00:00<00:00, 5.47MB/s]\r\n> Resolving data files: 100%\|█████████████████████████████████\| 250/250 [00:00<00:00, 612.51it/s]\r\n> Downloading data: 100%\|██████████████████████████████████\| 250/250 [00:12<00:00, 19.68files/s]\r\n> Generating train split: 247809 examples [00:00, 1057071.08 examples/s]\r\n> CPU times: user 4.95 s, sys: 3.1 s, total: 8.05 s\r\n> Wall time: 17.4 s\r\n> ```\r\n\r\nI was actually just noticing that, I bumped from 2.18 to 2.19 and got a massive speedup, amazing!\r\n\r\nAbout the fact that subset names are lost when loading all files at once, currently my solution is to add a 'lang' feature to each rows, convert to polars and use:\r\n\r\n```python\r\nds_split = ds.to_polars().group_by('lang')\r\n```\r\n\r\nIt's fast so I think it's an acceptable solution, but is there a better way to do it ?", "It's the fastest way I think :)\r\n\r\nAlternatively you can download the dataset repository locally using [huggingface_hub](https://huggingface.co/docs/huggingface_hub/guides/download) (either via CLI or in python) and load the subsets one by one locally using a for loop as you were doing before (just pass the directory path to load_dataset instead of the dataset_id). " ]	2024-04-10T21:08:57	2024-04-24T13:48:05	null	NONE	null	null	null	### Describe the bug I have a multilingual dataset that contains a lot of subsets. Each subset corresponds to a pair of languages, you can see here an example with 250 subsets: [https://hf.co/datasets/loicmagne/open-subtitles-250-bitext-mining](). As part of the MTEB benchmark, we may need to load all the subsets of the dataset. The dataset is relatively small and contains only ~45MB of data, but when I try to load every subset, it takes 15 minutes from the HF hub and 13 minutes from the cache This issue https://github.com/huggingface/datasets/issues/5499 also referenced this overhead, but I'm wondering if there is anything I can do to speedup loading different subsets of the same dataset, both when loading from disk and from the HF hub? Currently each subset is stored in a jsonl file ### Steps to reproduce the bug ``` from datasets import load_dataset for subset in ['ka-ml', 'br-sr', 'bg-br', 'kk-lv', 'br-sk', 'br-fi', 'eu-ze_zh', 'kk-nl', 'kk-vi', 'ja-kk', 'br-sv', 'kk-zh_cn', 'kk-ms', 'br-et', 'br-hu', 'eo-kk', 'br-tr', 'ko-tl', 'te-zh_tw', 'br-hr', 'br-nl', 'ka-si', 'br-cs', 'br-is', 'br-ro', 'br-de', 'et-kk', 'fr-hy', 'br-no', 'is-ko', 'br-da', 'br-en', 'eo-lt', 'is-ze_zh', 'eu-ko', 'br-it', 'br-id', 'eu-zh_cn', 'is-ja', 'br-sl', 'br-gl', 'br-pt_br', 'br-es', 'br-pt', 'is-th', 'fa-is', 'br-ca', 'eu-ka', 'is-zh_cn', 'eu-ur', 'id-kk', 'br-sq', 'eu-ja', 'uk-ur', 'is-zh_tw', 'ka-ko', 'eu-zh_tw', 'eu-th', 'eu-is', 'is-tl', 'br-eo', 'eo-ze_zh', 'eu-te', 'ar-kk', 'eo-lv', 'ko-ze_zh', 'ml-ze_zh', 'is-lt', 'br-fr', 'ko-te', 'kk-sl', 'eu-fa', 'eo-ko', 'ka-ze_en', 'eo-eu', 'ta-zh_tw', 'eu-lv', 'ko-lv', 'lt-tl', 'eu-si', 'hy-ru', 'ar-is', 'eu-lt', 'eu-tl', 'eu-uk', 'ka-ze_zh', 'si-ze_zh', 'el-is', 'bn-is', 'ko-ze_en', 'eo-si', 'cs-kk', 'is-uk', 'eu-ze_en', 'ta-ze_zh', 'is-pl', 'is-mk', 'eu-ta', 'ko-lt', 'is-lv', 'fa-ko', 'bn-ko', 'hi-is', 'bn-ze_zh', 'bn-eu', 'bn-ja', 'is-ml', 'eu-ru', 'ko-ta', 'is-vi', 'ja-tl', 'eu-mk', 'eu-he', 'ka-zh_tw', 'ka-zh_cn', 'si-tl', 'is-kk', 'eu-fi', 'fi-ko', 'is-ur', 'ka-th', 'ko-ur', 'eo-ja', 'he-is', 'is-tr', 'ka-ur', 'et-ko', 'eu-vi', 'is-sk', 'gl-is', 'fr-is', 'is-sq', 'hu-is', 'fr-kk', 'eu-sq', 'is-ru', 'ja-ka', 'fi-tl', 'ka-lv', 'fi-is', 'is-si', 'ar-ko', 'ko-sl', 'ar-eu', 'ko-si', 'bg-is', 'eu-hu', 'ko-sv', 'bn-hu', 'kk-ro', 'eu-hi', 'ka-ms', 'ko-th', 'ko-sr', 'ko-mk', 'fi-kk', 'ka-vi', 'eu-ml', 'ko-ml', 'de-ko', 'fa-ze_zh', 'eu-sk', 'is-sl', 'et-is', 'eo-is', 'is-sr', 'is-ze_en', 'kk-pt_br', 'hr-hy', 'kk-pl', 'ja-ta', 'is-ms', 'hi-ze_en', 'is-ro', 'ko-zh_cn', 'el-eu', 'ka-pl', 'ka-sq', 'eu-sl', 'fa-ka', 'ko-no', 'si-ze_en', 'ko-uk', 'ja-ze_zh', 'hu-ko', 'kk-no', 'eu-pl', 'is-pt_br', 'bn-lv', 'tl-zh_cn', 'is-nl', 'he-ko', 'ko-sq', 'ta-th', 'lt-ta', 'da-ko', 'ca-is', 'is-ta', 'bn-fi', 'ja-ml', 'lv-si', 'eu-sv', 'ja-te', 'bn-ur', 'bn-ca', 'bs-ko', 'bs-is', 'eu-sr', 'ko-vi', 'ko-zh_tw', 'et-tl', 'kk-tr', 'eo-vi', 'is-it', 'ja-ko', 'eo-et', 'id-is', 'bn-et', 'bs-eu', 'bn-lt', 'tl-uk', 'bn-zh_tw', 'da-eu', 'el-ko', 'no-tl', 'ko-sk', 'is-pt', 'hu-kk', 'si-zh_tw', 'si-te', 'ka-ru', 'lt-ml', 'af-ja', 'bg-eu', 'eo-th', 'cs-is', 'pl-ze_zh', 'el-kk', 'kk-sv', 'ka-nl', 'ko-pl', 'bg-ko', 'ka-pt_br', 'et-eu', 'tl-zh_tw', 'ka-pt', 'id-ko', 'fi-ze_zh', 'he-kk', 'ka-tr']: load_dataset('loicmagne/open-subtitles-250-bitext-mining', subset) ``` ### Expected behavior Faster loading? ### Environment info Copy-and-paste the text below in your GitHub issue. - `datasets` version: 2.18.0 - Platform: Linux-6.5.0-27-generic-x86_64-with-glibc2.35 - Python version: 3.10.12 - `huggingface_hub` version: 0.22.2 - PyArrow version: 15.0.2 - Pandas version: 2.2.2 - `fsspec` version: 2023.5.0	null	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6800/reactions", "total_count": 1, "+1": 1, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6800/timeline	null	null	false
https://api.github.com/repos/huggingface/datasets/issues/6799	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6799/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6799/comments	https://api.github.com/repos/huggingface/datasets/issues/6799/events	https://github.com/huggingface/datasets/pull/6799	2,236,124,531	PR_kwDODunzps5sRk_r	6,799	fix `DatasetBuilder._split_generators` incomplete type annotation	{ "login": "JonasLoos", "id": 33965649, "node_id": "MDQ6VXNlcjMzOTY1NjQ5", "avatar_url": "https://avatars.githubusercontent.com/u/33965649?v=4", "gravatar_id": "", "url": "https://api.github.com/users/JonasLoos", "html_url": "https://github.com/JonasLoos", "followers_url": "https://api.github.com/users/JonasLoos/followers", "following_url": "https://api.github.com/users/JonasLoos/following{/other_user}", "gists_url": "https://api.github.com/users/JonasLoos/gists{/gist_id}", "starred_url": "https://api.github.com/users/JonasLoos/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/JonasLoos/subscriptions", "organizations_url": "https://api.github.com/users/JonasLoos/orgs", "repos_url": "https://api.github.com/users/JonasLoos/repos", "events_url": "https://api.github.com/users/JonasLoos/events{/privacy}", "received_events_url": "https://api.github.com/users/JonasLoos/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	null	[]	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6799). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "The CI failures are unrelated to the changes", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.004974 / 0.011353 (-0.006378) \| 0.003153 / 0.011008 (-0.007856) \| 0.062785 / 0.038508 (0.024277) \| 0.029504 / 0.023109 (0.006395) \| 0.245558 / 0.275898 (-0.030340) \| 0.274022 / 0.323480 (-0.049457) \| 0.003173 / 0.007986 (-0.004813) \| 0.002643 / 0.004328 (-0.001686) \| 0.048917 / 0.004250 (0.044667) \| 0.042965 / 0.037052 (0.005912) \| 0.261266 / 0.258489 (0.002777) \| 0.291546 / 0.293841 (-0.002295) \| 0.027860 / 0.128546 (-0.100686) \| 0.010397 / 0.075646 (-0.065249) \| 0.205981 / 0.419271 (-0.213290) \| 0.035663 / 0.043533 (-0.007870) \| 0.250466 / 0.255139 (-0.004673) \| 0.273947 / 0.283200 (-0.009253) \| 0.016659 / 0.141683 (-0.125023) \| 1.147884 / 1.452155 (-0.304270) \| 1.187609 / 1.492716 (-0.305107) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.095564 / 0.018006 (0.077558) \| 0.300086 / 0.000490 (0.299597) \| 0.000212 / 0.000200 (0.000012) \| 0.000049 / 0.000054 (-0.000005) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.018100 / 0.037411 (-0.019311) \| 0.061342 / 0.014526 (0.046816) \| 0.073747 / 0.176557 (-0.102810) \| 0.120577 / 0.737135 (-0.616559) \| 0.075797 / 0.296338 (-0.220541) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.288766 / 0.215209 (0.073557) \| 2.835274 / 2.077655 (0.757620) \| 1.515288 / 1.504120 (0.011168) \| 1.396097 / 1.541195 (-0.145098) \| 1.424293 / 1.468490 (-0.044197) \| 0.568356 / 4.584777 (-4.016421) \| 2.393171 / 3.745712 (-1.352541) \| 2.756219 / 5.269862 (-2.513642) \| 1.731343 / 4.565676 (-2.834334) \| 0.062542 / 0.424275 (-0.361733) \| 0.005385 / 0.007607 (-0.002223) \| 0.340876 / 0.226044 (0.114832) \| 3.376649 / 2.268929 (1.107720) \| 1.856135 / 55.444624 (-53.588490) \| 1.581802 / 6.876477 (-5.294675) \| 1.591081 / 2.142072 (-0.550992) \| 0.647963 / 4.805227 (-4.157264) \| 0.119218 / 6.500664 (-6.381446) \| 0.042660 / 0.075469 (-0.032809) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 1.005017 / 1.841788 (-0.836770) \| 11.670779 / 8.074308 (3.596471) \| 9.533790 / 10.191392 (-0.657602) \| 0.141571 / 0.680424 (-0.538853) \| 0.013987 / 0.534201 (-0.520214) \| 0.286598 / 0.579283 (-0.292685) \| 0.260123 / 0.434364 (-0.174240) \| 0.324186 / 0.540337 (-0.216151) \| 0.421246 / 1.386936 (-0.965690) \|\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005196 / 0.011353 (-0.006157) \| 0.003697 / 0.011008 (-0.007311) \| 0.049530 / 0.038508 (0.011022) \| 0.030892 / 0.023109 (0.007783) \| 0.284787 / 0.275898 (0.008889) \| 0.302833 / 0.323480 (-0.020647) \| 0.004203 / 0.007986 (-0.003783) \| 0.002736 / 0.004328 (-0.001592) \| 0.050203 / 0.004250 (0.045953) \| 0.040335 / 0.037052 (0.003283) \| 0.292508 / 0.258489 (0.034019) \| 0.317918 / 0.293841 (0.024077) \| 0.029144 / 0.128546 (-0.099403) \| 0.010171 / 0.075646 (-0.065475) \| 0.058130 / 0.419271 (-0.361141) \| 0.032743 / 0.043533 (-0.010790) \| 0.281354 / 0.255139 (0.026215) \| 0.296951 / 0.283200 (0.013751) \| 0.018399 / 0.141683 (-0.123284) \| 1.158852 / 1.452155 (-0.293303) \| 1.189750 / 1.492716 (-0.302966) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.093073 / 0.018006 (0.075066) \| 0.301779 / 0.000490 (0.301290) \| 0.000209 / 0.000200 (0.000009) \| 0.000051 / 0.000054 (-0.000003) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.021565 / 0.037411 (-0.015846) \| 0.075237 / 0.014526 (0.060711) \| 0.087368 / 0.176557 (-0.089188) \| 0.126955 / 0.737135 (-0.610180) \| 0.088456 / 0.296338 (-0.207883) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.291225 / 0.215209 (0.076016) \| 2.863220 / 2.077655 (0.785565) \| 1.616936 / 1.504120 (0.112817) \| 1.500553 / 1.541195 (-0.040641) \| 1.501693 / 1.468490 (0.033203) \| 0.560118 / 4.584777 (-4.024659) \| 2.439241 / 3.745712 (-1.306472) \| 2.786804 / 5.269862 (-2.483058) \| 1.737772 / 4.565676 (-2.827905) \| 0.063668 / 0.424275 (-0.360607) \| 0.005320 / 0.007607 (-0.002287) \| 0.344539 / 0.226044 (0.118495) \| 3.418803 / 2.268929 (1.149874) \| 1.981791 / 55.444624 (-53.462834) \| 1.698484 / 6.876477 (-5.177993) \| 1.686815 / 2.142072 (-0.455258) \| 0.646911 / 4.805227 (-4.158316) \| 0.116969 / 6.500664 (-6.383696) \| 0.040380 / 0.075469 (-0.035089) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 1.017337 / 1.841788 (-0.824451) \| 11.858212 / 8.074308 (3.783904) \| 10.270287 / 10.191392 (0.078895) \| 0.154266 / 0.680424 (-0.526158) \| 0.014886 / 0.534201 (-0.519315) \| 0.292354 / 0.579283 (-0.286929) \| 0.270888 / 0.434364 (-0.163476) \| 0.333289 / 0.540337 (-0.207049) \| 0.423001 / 1.386936 (-0.963935) \|\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#d9cc95f6d0513bbc692bb73c669346e3d1825cb0 \"CML watermark\")\n" ]	2024-04-10T17:46:08	2024-04-11T15:41:06	2024-04-11T15:34:58	CONTRIBUTOR	null	false	{ "url": "https://api.github.com/repos/huggingface/datasets/pulls/6799", "html_url": "https://github.com/huggingface/datasets/pull/6799", "diff_url": "https://github.com/huggingface/datasets/pull/6799.diff", "patch_url": "https://github.com/huggingface/datasets/pull/6799.patch", "merged_at": "2024-04-11T15:34:58" }	solve #6798: add missing `StreamingDownloadManager` type annotation to the `dl_manager` argument of the `DatasetBuilder._split_generators` function	{ "login": "mariosasko", "id": 47462742, "node_id": "MDQ6VXNlcjQ3NDYyNzQy", "avatar_url": "https://avatars.githubusercontent.com/u/47462742?v=4", "gravatar_id": "", "url": "https://api.github.com/users/mariosasko", "html_url": "https://github.com/mariosasko", "followers_url": "https://api.github.com/users/mariosasko/followers", "following_url": "https://api.github.com/users/mariosasko/following{/other_user}", "gists_url": "https://api.github.com/users/mariosasko/gists{/gist_id}", "starred_url": "https://api.github.com/users/mariosasko/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/mariosasko/subscriptions", "organizations_url": "https://api.github.com/users/mariosasko/orgs", "repos_url": "https://api.github.com/users/mariosasko/repos", "events_url": "https://api.github.com/users/mariosasko/events{/privacy}", "received_events_url": "https://api.github.com/users/mariosasko/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6799/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6799/timeline	null	null	true
https://api.github.com/repos/huggingface/datasets/issues/6798	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6798/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6798/comments	https://api.github.com/repos/huggingface/datasets/issues/6798/events	https://github.com/huggingface/datasets/issues/6798	2,235,768,891	I_kwDODunzps6FQyA7	6,798	`DatasetBuilder._split_generators` incomplete type annotation	{ "login": "JonasLoos", "id": 33965649, "node_id": "MDQ6VXNlcjMzOTY1NjQ5", "avatar_url": "https://avatars.githubusercontent.com/u/33965649?v=4", "gravatar_id": "", "url": "https://api.github.com/users/JonasLoos", "html_url": "https://github.com/JonasLoos", "followers_url": "https://api.github.com/users/JonasLoos/followers", "following_url": "https://api.github.com/users/JonasLoos/following{/other_user}", "gists_url": "https://api.github.com/users/JonasLoos/gists{/gist_id}", "starred_url": "https://api.github.com/users/JonasLoos/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/JonasLoos/subscriptions", "organizations_url": "https://api.github.com/users/JonasLoos/orgs", "repos_url": "https://api.github.com/users/JonasLoos/repos", "events_url": "https://api.github.com/users/JonasLoos/events{/privacy}", "received_events_url": "https://api.github.com/users/JonasLoos/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	null	[]	null	[ "Good catch! Feel free to open a PR with the suggested fix :).", "There is also the [`MockDownloadManager`](https://github.com/JonasLoos/datasets/blob/main/src/datasets/download/mock_download_manager.py#L33), which seems like it might get passed here too. However, to me, it doesn't really seem relevant to the users of the datasets library, so I would just ignore it. What do you think, @mariosasko?", "The API (`dummy_data` CLI command ) that uses the `MockDownloadManager` has been deprecated, so ignoring it sounds good!" ]	2024-04-10T14:38:50	2024-04-11T15:34:59	2024-04-11T15:34:59	CONTRIBUTOR	null	null	null	### Describe the bug The [`DatasetBuilder._split_generators`](https://github.com/huggingface/datasets/blob/0f27d7b77c73412cfc50b24354bfd7a3e838202f/src/datasets/builder.py#L1449) function has currently the following signature: ```python class DatasetBuilder: def _split_generators(self, dl_manager: DownloadManager): ... ``` However, the `dl_manager` argument can also be of type [`StreamingDownloadManager`](https://github.com/huggingface/datasets/blob/0f27d7b77c73412cfc50b24354bfd7a3e838202f/src/datasets/download/streaming_download_manager.py#L962), which has different functionality. For example, the `download` function doesn't download, but rather just returns the given url(s). I suggest changing the function signature to: ```python class DatasetBuilder: def _split_generators(self, dl_manager: Union[DownloadManager, StreamingDownloadManager]): ... ``` and also adjust the docstring accordingly. I would like to create a Pull Request to fix this, and have the following questions: * Are there also other options than `DownloadManager`, and `StreamingDownloadManager`? * Should this also be changed in other functions? ### Steps to reproduce the bug Minimal example to print the different class names: ```python import tempfile from datasets import load_dataset example = b''' from datasets import GeneratorBasedBuilder, DatasetInfo, Features, Value, SplitGenerator class Test(GeneratorBasedBuilder): def _info(self): return DatasetInfo(features=Features({"x": Value("int64")})) def _split_generators(self, dl_manager): print(type(dl_manager)) return [SplitGenerator('test')] def _generate_examples(self): yield 0, {'x': 42} ''' with tempfile.NamedTemporaryFile(suffix='.py') as f: f.write(example) f.flush() load_dataset(f.name, streaming=False) load_dataset(f.name, streaming=True) ``` ### Expected behavior complete type annotations ### Environment info /	{ "login": "mariosasko", "id": 47462742, "node_id": "MDQ6VXNlcjQ3NDYyNzQy", "avatar_url": "https://avatars.githubusercontent.com/u/47462742?v=4", "gravatar_id": "", "url": "https://api.github.com/users/mariosasko", "html_url": "https://github.com/mariosasko", "followers_url": "https://api.github.com/users/mariosasko/followers", "following_url": "https://api.github.com/users/mariosasko/following{/other_user}", "gists_url": "https://api.github.com/users/mariosasko/gists{/gist_id}", "starred_url": "https://api.github.com/users/mariosasko/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/mariosasko/subscriptions", "organizations_url": "https://api.github.com/users/mariosasko/orgs", "repos_url": "https://api.github.com/users/mariosasko/repos", "events_url": "https://api.github.com/users/mariosasko/events{/privacy}", "received_events_url": "https://api.github.com/users/mariosasko/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6798/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6798/timeline	null	completed	false
https://api.github.com/repos/huggingface/datasets/issues/6797	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6797/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6797/comments	https://api.github.com/repos/huggingface/datasets/issues/6797/events	https://github.com/huggingface/datasets/pull/6797	2,234,890,097	PR_kwDODunzps5sNYKZ	6,797	Fix CI test_load_dataset_distributed_with_script	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	null	[]	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6797). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "Finally:\r\n- the initial issue seems it was temporary\r\n- there is a different issue now \r\n\r\n```\r\nFAILED tests/test_load.py::ModuleFactoryTest::test_HubDatasetModuleFactoryWithParquetExport - datasets.utils._dataset_viewer.DatasetViewerError: No exported Parquet files available.\r\nFAILED tests/test_load.py::ModuleFactoryTest::test_HubDatasetModuleFactoryWithParquetExport_errors_on_wrong_sha - datasets.utils._dataset_viewer.DatasetViewerError: No exported Parquet files available.\r\nFAILED tests/test_load.py::test_load_dataset_builder_for_community_dataset_with_script - AssertionError: assert 'dataset_with_script' == 'parquet'\r\n \r\n - parquet\r\n + dataset_with_script\r\n```" ]	2024-04-10T06:57:48	2024-04-10T08:25:00	2024-04-10T08:18:01	MEMBER	null	false	{ "url": "https://api.github.com/repos/huggingface/datasets/pulls/6797", "html_url": "https://github.com/huggingface/datasets/pull/6797", "diff_url": "https://github.com/huggingface/datasets/pull/6797.diff", "patch_url": "https://github.com/huggingface/datasets/pull/6797.patch", "merged_at": null }	Fix #6796.	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6797/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6797/timeline	null	null	true
https://api.github.com/repos/huggingface/datasets/issues/6796	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6796/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6796/comments	https://api.github.com/repos/huggingface/datasets/issues/6796/events	https://github.com/huggingface/datasets/issues/6796	2,234,887,618	I_kwDODunzps6FNa3C	6,796	CI is broken due to hf-internal-testing/dataset_with_script	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[ { "id": 1935892857, "node_id": "MDU6TGFiZWwxOTM1ODkyODU3", "url": "https://api.github.com/repos/huggingface/datasets/labels/bug", "name": "bug", "color": "d73a4a", "default": true, "description": "Something isn't working" } ]	closed	false	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[ { "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false } ]	null	[ "Finally:\r\n- the initial issue seems it was temporary\r\n- there is a different issue now: https://github.com/huggingface/datasets/actions/runs/8627153993/job/23646584590?pr=6797\r\n```\r\nFAILED tests/test_load.py::ModuleFactoryTest::test_HubDatasetModuleFactoryWithParquetExport - datasets.utils._dataset_viewer.DatasetViewerError: No exported Parquet files available.\r\nFAILED tests/test_load.py::ModuleFactoryTest::test_HubDatasetModuleFactoryWithParquetExport_errors_on_wrong_sha - datasets.utils._dataset_viewer.DatasetViewerError: No exported Parquet files available.\r\nFAILED tests/test_load.py::test_load_dataset_builder_for_community_dataset_with_script - AssertionError: assert 'dataset_with_script' == 'parquet'\r\n \r\n - parquet\r\n + dataset_with_script\r\n```\r\n\r\nMaybe related to `hf-internal-testing/dataset_with_script` dataset: https://huggingface.co/datasets/hf-internal-testing/dataset_with_script", "This URL: https://datasets-server.huggingface.co/parquet?dataset=hf-internal-testing/dataset_with_script\r\nraises:\r\n> {\"error\":\"The dataset viewer doesn't support this dataset because it runs arbitrary python code. Please open a discussion in the discussion tab if you think this is an error and tag @lhoestq and @severo.\"}\r\n\r\nWas there a recent change on the Hub enforcing this behavior?", "OK, I just saw this PR:\r\n- https://github.com/huggingface/dataset-viewer/pull/2689\r\n\r\nOnce merged and deployed, it should fix the issue.", "Once the script-dataset has been allowed in the dataset-viewer, we should fix our test to make the CI pass.\r\n\r\nI am addressing this." ]	2024-04-10T06:56:02	2024-04-12T09:02:13	2024-04-12T09:02:13	MEMBER	null	null	null	CI is broken for test_load_dataset_distributed_with_script. See: https://github.com/huggingface/datasets/actions/runs/8614926216/job/23609378127 ``` FAILED tests/test_load.py::test_load_dataset_distributed_with_script[None] - assert False + where False = all(<generator object test_load_dataset_distributed_with_script.<locals>.<genexpr> at 0x7f0c741de3b0>) FAILED tests/test_load.py::test_load_dataset_distributed_with_script[force_redownload] - assert False + where False = all(<generator object test_load_dataset_distributed_with_script.<locals>.<genexpr> at 0x7f0be45f6ea0>) ```	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6796/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6796/timeline	null	completed	false
https://api.github.com/repos/huggingface/datasets/issues/6795	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6795/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6795/comments	https://api.github.com/repos/huggingface/datasets/issues/6795/events	https://github.com/huggingface/datasets/pull/6795	2,233,618,719	PR_kwDODunzps5sJAC8	6,795	Add CLI function to convert script-dataset to Parquet	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	null	[]	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6795). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "@huggingface/datasets once this PR is merged, I would suggest making a release. Do you agree?", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005367 / 0.011353 (-0.005986) \| 0.003161 / 0.011008 (-0.007847) \| 0.063259 / 0.038508 (0.024751) \| 0.030550 / 0.023109 (0.007441) \| 0.243789 / 0.275898 (-0.032109) \| 0.262474 / 0.323480 (-0.061006) \| 0.003157 / 0.007986 (-0.004829) \| 0.002586 / 0.004328 (-0.001742) \| 0.049336 / 0.004250 (0.045085) \| 0.046434 / 0.037052 (0.009382) \| 0.249142 / 0.258489 (-0.009347) \| 0.282953 / 0.293841 (-0.010888) \| 0.027881 / 0.128546 (-0.100666) \| 0.010069 / 0.075646 (-0.065578) \| 0.207937 / 0.419271 (-0.211334) \| 0.036005 / 0.043533 (-0.007528) \| 0.251850 / 0.255139 (-0.003288) \| 0.265156 / 0.283200 (-0.018044) \| 0.019780 / 0.141683 (-0.121903) \| 1.124301 / 1.452155 (-0.327853) \| 1.177392 / 1.492716 (-0.315324) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.091045 / 0.018006 (0.073039) \| 0.301258 / 0.000490 (0.300769) \| 0.000214 / 0.000200 (0.000014) \| 0.000048 / 0.000054 (-0.000006) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.018726 / 0.037411 (-0.018686) \| 0.061623 / 0.014526 (0.047097) \| 0.073905 / 0.176557 (-0.102651) \| 0.119444 / 0.737135 (-0.617692) \| 0.074614 / 0.296338 (-0.221725) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.287313 / 0.215209 (0.072104) \| 2.772864 / 2.077655 (0.695209) \| 1.465267 / 1.504120 (-0.038853) \| 1.343666 / 1.541195 (-0.197528) \| 1.329390 / 1.468490 (-0.139100) \| 0.570222 / 4.584777 (-4.014555) \| 2.421835 / 3.745712 (-1.323877) \| 2.747282 / 5.269862 (-2.522579) \| 1.728733 / 4.565676 (-2.836943) \| 0.063671 / 0.424275 (-0.360604) \| 0.005343 / 0.007607 (-0.002264) \| 0.335078 / 0.226044 (0.109033) \| 3.334305 / 2.268929 (1.065376) \| 1.779496 / 55.444624 (-53.665129) \| 1.496475 / 6.876477 (-5.380002) \| 1.507848 / 2.142072 (-0.634224) \| 0.653653 / 4.805227 (-4.151575) \| 0.118373 / 6.500664 (-6.382291) \| 0.041727 / 0.075469 (-0.033742) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.981985 / 1.841788 (-0.859803) \| 11.290978 / 8.074308 (3.216670) \| 9.499217 / 10.191392 (-0.692175) \| 0.131353 / 0.680424 (-0.549071) \| 0.014416 / 0.534201 (-0.519785) \| 0.288381 / 0.579283 (-0.290902) \| 0.265483 / 0.434364 (-0.168880) \| 0.323438 / 0.540337 (-0.216900) \| 0.417946 / 1.386936 (-0.968990) \|\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005272 / 0.011353 (-0.006081) \| 0.003551 / 0.011008 (-0.007457) \| 0.050173 / 0.038508 (0.011665) \| 0.031291 / 0.023109 (0.008182) \| 0.278658 / 0.275898 (0.002760) \| 0.301812 / 0.323480 (-0.021668) \| 0.004237 / 0.007986 (-0.003748) \| 0.002713 / 0.004328 (-0.001615) \| 0.049483 / 0.004250 (0.045233) \| 0.039995 / 0.037052 (0.002943) \| 0.293101 / 0.258489 (0.034612) \| 0.319956 / 0.293841 (0.026116) \| 0.029127 / 0.128546 (-0.099419) \| 0.010247 / 0.075646 (-0.065400) \| 0.057929 / 0.419271 (-0.361342) \| 0.032942 / 0.043533 (-0.010591) \| 0.281677 / 0.255139 (0.026538) \| 0.297937 / 0.283200 (0.014737) \| 0.018285 / 0.141683 (-0.123398) \| 1.272858 / 1.452155 (-0.179297) \| 1.213375 / 1.492716 (-0.279342) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.091110 / 0.018006 (0.073104) \| 0.302589 / 0.000490 (0.302099) \| 0.000214 / 0.000200 (0.000014) \| 0.000070 / 0.000054 (0.000015) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.021520 / 0.037411 (-0.015891) \| 0.075013 / 0.014526 (0.060487) \| 0.088695 / 0.176557 (-0.087862) \| 0.128281 / 0.737135 (-0.608854) \| 0.090611 / 0.296338 (-0.205727) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.297457 / 0.215209 (0.082248) \| 2.928612 / 2.077655 (0.850957) \| 1.613245 / 1.504120 (0.109125) \| 1.485263 / 1.541195 (-0.055931) \| 1.496885 / 1.468490 (0.028395) \| 0.570120 / 4.584777 (-4.014657) \| 2.487532 / 3.745712 (-1.258180) \| 2.761552 / 5.269862 (-2.508309) \| 1.731864 / 4.565676 (-2.833812) \| 0.062989 / 0.424275 (-0.361286) \| 0.005428 / 0.007607 (-0.002179) \| 0.354932 / 0.226044 (0.128888) \| 3.524475 / 2.268929 (1.255547) \| 1.977684 / 55.444624 (-53.466941) \| 1.692568 / 6.876477 (-5.183909) \| 1.673003 / 2.142072 (-0.469069) \| 0.643976 / 4.805227 (-4.161251) \| 0.116499 / 6.500664 (-6.384165) \| 0.040772 / 0.075469 (-0.034697) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 1.020354 / 1.841788 (-0.821434) \| 12.143991 / 8.074308 (4.069683) \| 10.354058 / 10.191392 (0.162666) \| 0.145460 / 0.680424 (-0.534964) \| 0.015356 / 0.534201 (-0.518845) \| 0.307190 / 0.579283 (-0.272093) \| 0.276664 / 0.434364 (-0.157699) \| 0.350068 / 0.540337 (-0.190269) \| 0.440824 / 1.386936 (-0.946112) \|\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#a3bc89d8bfd47c2a175c3ce16d92b7307cdeafd6 \"CML watermark\")\n" ]	2024-04-09T14:45:12	2024-04-17T08:41:23	2024-04-12T15:27:04	MEMBER	null	false	{ "url": "https://api.github.com/repos/huggingface/datasets/pulls/6795", "html_url": "https://github.com/huggingface/datasets/pull/6795", "diff_url": "https://github.com/huggingface/datasets/pull/6795.diff", "patch_url": "https://github.com/huggingface/datasets/pull/6795.patch", "merged_at": "2024-04-12T15:27:04" }	Close #6690.	{ "login": "albertvillanova", "id": 8515462, "node_id": "MDQ6VXNlcjg1MTU0NjI=", "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "gravatar_id": "", "url": "https://api.github.com/users/albertvillanova", "html_url": "https://github.com/albertvillanova", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "repos_url": "https://api.github.com/users/albertvillanova/repos", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6795/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6795/timeline	null	null	true
https://api.github.com/repos/huggingface/datasets/issues/6794	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6794/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6794/comments	https://api.github.com/repos/huggingface/datasets/issues/6794/events	https://github.com/huggingface/datasets/pull/6794	2,233,202,088	PR_kwDODunzps5sHkJF	6,794	Multithreaded downloads	{ "login": "lhoestq", "id": 42851186, "node_id": "MDQ6VXNlcjQyODUxMTg2", "avatar_url": "https://avatars.githubusercontent.com/u/42851186?v=4", "gravatar_id": "", "url": "https://api.github.com/users/lhoestq", "html_url": "https://github.com/lhoestq", "followers_url": "https://api.github.com/users/lhoestq/followers", "following_url": "https://api.github.com/users/lhoestq/following{/other_user}", "gists_url": "https://api.github.com/users/lhoestq/gists{/gist_id}", "starred_url": "https://api.github.com/users/lhoestq/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/lhoestq/subscriptions", "organizations_url": "https://api.github.com/users/lhoestq/orgs", "repos_url": "https://api.github.com/users/lhoestq/repos", "events_url": "https://api.github.com/users/lhoestq/events{/privacy}", "received_events_url": "https://api.github.com/users/lhoestq/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	null	[]	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6794). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "CI is failing because of the missing parquet export of one test dataset, PR to fix this at https://github.com/huggingface/dataset-viewer/pull/2689", "I took your comments into account :) lmk what you think @mariosasko ", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.004956 / 0.011353 (-0.006397) \| 0.003282 / 0.011008 (-0.007726) \| 0.064028 / 0.038508 (0.025520) \| 0.030420 / 0.023109 (0.007311) \| 0.240097 / 0.275898 (-0.035801) \| 0.266356 / 0.323480 (-0.057124) \| 0.003116 / 0.007986 (-0.004869) \| 0.002597 / 0.004328 (-0.001731) \| 0.050230 / 0.004250 (0.045980) \| 0.043864 / 0.037052 (0.006812) \| 0.258711 / 0.258489 (0.000222) \| 0.290816 / 0.293841 (-0.003025) \| 0.027898 / 0.128546 (-0.100648) \| 0.009941 / 0.075646 (-0.065705) \| 0.208917 / 0.419271 (-0.210355) \| 0.035891 / 0.043533 (-0.007642) \| 0.253332 / 0.255139 (-0.001807) \| 0.274300 / 0.283200 (-0.008900) \| 0.019466 / 0.141683 (-0.122217) \| 1.133896 / 1.452155 (-0.318259) \| 1.178130 / 1.492716 (-0.314586) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.091093 / 0.018006 (0.073087) \| 0.293632 / 0.000490 (0.293142) \| 0.000216 / 0.000200 (0.000016) \| 0.000042 / 0.000054 (-0.000013) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.017722 / 0.037411 (-0.019689) \| 0.060241 / 0.014526 (0.045715) \| 0.072024 / 0.176557 (-0.104533) \| 0.118521 / 0.737135 (-0.618615) \| 0.071107 / 0.296338 (-0.225232) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.280950 / 0.215209 (0.065741) \| 2.781361 / 2.077655 (0.703706) \| 1.477949 / 1.504120 (-0.026171) \| 1.356388 / 1.541195 (-0.184807) \| 1.361808 / 1.468490 (-0.106682) \| 0.565499 / 4.584777 (-4.019278) \| 2.389206 / 3.745712 (-1.356506) \| 2.712782 / 5.269862 (-2.557079) \| 1.701402 / 4.565676 (-2.864274) \| 0.063619 / 0.424275 (-0.360656) \| 0.005321 / 0.007607 (-0.002286) \| 0.336783 / 0.226044 (0.110739) \| 3.299628 / 2.268929 (1.030699) \| 1.794686 / 55.444624 (-53.649939) \| 1.504207 / 6.876477 (-5.372270) \| 1.524637 / 2.142072 (-0.617436) \| 0.642833 / 4.805227 (-4.162395) \| 0.117808 / 6.500664 (-6.382856) \| 0.041539 / 0.075469 (-0.033930) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.960193 / 1.841788 (-0.881595) \| 11.229147 / 8.074308 (3.154839) \| 9.380653 / 10.191392 (-0.810739) \| 0.137184 / 0.680424 (-0.543240) \| 0.013399 / 0.534201 (-0.520802) \| 0.314904 / 0.579283 (-0.264379) \| 0.262539 / 0.434364 (-0.171825) \| 0.354007 / 0.540337 (-0.186331) \| 0.451698 / 1.386936 (-0.935238) \|\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005207 / 0.011353 (-0.006146) \| 0.003660 / 0.011008 (-0.007348) \| 0.049931 / 0.038508 (0.011423) \| 0.030918 / 0.023109 (0.007809) \| 0.271243 / 0.275898 (-0.004655) \| 0.295706 / 0.323480 (-0.027774) \| 0.004106 / 0.007986 (-0.003879) \| 0.002750 / 0.004328 (-0.001578) \| 0.048337 / 0.004250 (0.044086) \| 0.039944 / 0.037052 (0.002892) \| 0.284013 / 0.258489 (0.025524) \| 0.306827 / 0.293841 (0.012987) \| 0.029183 / 0.128546 (-0.099363) \| 0.010033 / 0.075646 (-0.065613) \| 0.058126 / 0.419271 (-0.361146) \| 0.032427 / 0.043533 (-0.011106) \| 0.276471 / 0.255139 (0.021332) \| 0.288428 / 0.283200 (0.005229) \| 0.017549 / 0.141683 (-0.124134) \| 1.142361 / 1.452155 (-0.309793) \| 1.184514 / 1.492716 (-0.308202) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.090350 / 0.018006 (0.072344) \| 0.292511 / 0.000490 (0.292021) \| 0.000215 / 0.000200 (0.000015) \| 0.000041 / 0.000054 (-0.000013) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.021572 / 0.037411 (-0.015840) \| 0.074310 / 0.014526 (0.059784) \| 0.086102 / 0.176557 (-0.090455) \| 0.123507 / 0.737135 (-0.613629) \| 0.087397 / 0.296338 (-0.208941) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.294038 / 0.215209 (0.078829) \| 2.889662 / 2.077655 (0.812007) \| 1.591775 / 1.504120 (0.087655) \| 1.468815 / 1.541195 (-0.072379) \| 1.470226 / 1.468490 (0.001736) \| 0.574557 / 4.584777 (-4.010220) \| 2.481377 / 3.745712 (-1.264335) \| 2.763368 / 5.269862 (-2.506493) \| 1.713707 / 4.565676 (-2.851969) \| 0.064158 / 0.424275 (-0.360117) \| 0.005553 / 0.007607 (-0.002054) \| 0.353480 / 0.226044 (0.127436) \| 3.447689 / 2.268929 (1.178760) \| 1.975802 / 55.444624 (-53.468822) \| 1.673561 / 6.876477 (-5.202915) \| 1.637212 / 2.142072 (-0.504860) \| 0.640667 / 4.805227 (-4.164560) \| 0.114618 / 6.500664 (-6.386046) \| 0.038912 / 0.075469 (-0.036557) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 1.007581 / 1.841788 (-0.834207) \| 11.874250 / 8.074308 (3.799942) \| 10.312692 / 10.191392 (0.121300) \| 0.142705 / 0.680424 (-0.537719) \| 0.015438 / 0.534201 (-0.518763) \| 0.285919 / 0.579283 (-0.293364) \| 0.278223 / 0.434364 (-0.156141) \| 0.323806 / 0.540337 (-0.216531) \| 0.415007 / 1.386936 (-0.971929) \|\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#0f1f27c69f6cc8d085b66a8a2ba0440a39bc5bce \"CML watermark\")\n" ]	2024-04-09T11:13:19	2024-04-15T21:24:13	2024-04-15T21:18:08	MEMBER	null	false	{ "url": "https://api.github.com/repos/huggingface/datasets/pulls/6794", "html_url": "https://github.com/huggingface/datasets/pull/6794", "diff_url": "https://github.com/huggingface/datasets/pull/6794.diff", "patch_url": "https://github.com/huggingface/datasets/pull/6794.patch", "merged_at": "2024-04-15T21:18:08" }	...for faster dataset download when there are many many small files (e.g. imagefolder, audiofolder) ### Behcnmark for example on [lhoestq/tmp-images-writer_batch_size](https://hf.co/datasets/lhoestq/tmp-images-writer_batch_size) (128 images) \| \| duration of the download step in `load_dataset()` \| \|--\| ----------------------------------------------------------------------\| \| Before \| 58s \| \| Now \| 3s \| This should fix issues with the Dataset Viewer taking too much time to show up for imagefolder/audiofolder datasets. ### Implementation details The main change is in the `DownloadManager`: ```diff - download_func = partial(self._download, download_config=download_config) + download_func = partial(self._download_batched, download_config=download_config) downloaded_path_or_paths = map_nested( download_func, url_or_urls, map_tuple=True, num_proc=download_config.num_proc, desc="Downloading data files", + batched=True, + batch_size=-1, ) ``` and `_download_batched` is a multithreaded function. I only enable multithreading if there are more than 16 files and files are small though, otherwise the progress bar that counts the number of downloaded files is not fluid (updating when a big batch of big files are done downloading). To do so I simply check if the first file is smaller than 20MB. I also had to tweak `map_nested` to support batching. In particular it slices the data correctly if the user also enables multiprocessing.	{ "login": "lhoestq", "id": 42851186, "node_id": "MDQ6VXNlcjQyODUxMTg2", "avatar_url": "https://avatars.githubusercontent.com/u/42851186?v=4", "gravatar_id": "", "url": "https://api.github.com/users/lhoestq", "html_url": "https://github.com/lhoestq", "followers_url": "https://api.github.com/users/lhoestq/followers", "following_url": "https://api.github.com/users/lhoestq/following{/other_user}", "gists_url": "https://api.github.com/users/lhoestq/gists{/gist_id}", "starred_url": "https://api.github.com/users/lhoestq/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/lhoestq/subscriptions", "organizations_url": "https://api.github.com/users/lhoestq/orgs", "repos_url": "https://api.github.com/users/lhoestq/repos", "events_url": "https://api.github.com/users/lhoestq/events{/privacy}", "received_events_url": "https://api.github.com/users/lhoestq/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6794/reactions", "total_count": 1, "+1": 0, "-1": 0, "laugh": 0, "hooray": 1, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6794/timeline	null	null	true
https://api.github.com/repos/huggingface/datasets/issues/6793	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6793/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6793/comments	https://api.github.com/repos/huggingface/datasets/issues/6793/events	https://github.com/huggingface/datasets/issues/6793	2,231,400,200	I_kwDODunzps6FAHcI	6,793	Loading just one particular split is not possible for imagenet-1k	{ "login": "PaulPSta", "id": 165930106, "node_id": "U_kgDOCePkeg", "avatar_url": "https://avatars.githubusercontent.com/u/165930106?v=4", "gravatar_id": "", "url": "https://api.github.com/users/PaulPSta", "html_url": "https://github.com/PaulPSta", "followers_url": "https://api.github.com/users/PaulPSta/followers", "following_url": "https://api.github.com/users/PaulPSta/following{/other_user}", "gists_url": "https://api.github.com/users/PaulPSta/gists{/gist_id}", "starred_url": "https://api.github.com/users/PaulPSta/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/PaulPSta/subscriptions", "organizations_url": "https://api.github.com/users/PaulPSta/orgs", "repos_url": "https://api.github.com/users/PaulPSta/repos", "events_url": "https://api.github.com/users/PaulPSta/events{/privacy}", "received_events_url": "https://api.github.com/users/PaulPSta/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	open	false	null	[]	null	[ "+1" ]	2024-04-08T14:39:14	2024-09-12T16:24:48	null	NONE	null	null	null	### Describe the bug I'd expect the following code to download just the validation split but instead I get all data on my disk (train, test and validation splits) ` from datasets import load_dataset dataset = load_dataset("imagenet-1k", split="validation", trust_remote_code=True) ` Is it expected to work like that? ### Steps to reproduce the bug 1. Install the required libraries (python, datasets, huggingface_hub) 2. Login using huggingface cli 2. Run the code in the description ### Expected behavior Just a single (validation) split should be downloaded. ### Environment info python: 3.12.2 datasets: 2.18.0 huggingface_hub: 0.22.2	null	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6793/reactions", "total_count": 3, "+1": 3, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6793/timeline	null	null	false
https://api.github.com/repos/huggingface/datasets/issues/6792	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6792/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6792/comments	https://api.github.com/repos/huggingface/datasets/issues/6792/events	https://github.com/huggingface/datasets/pull/6792	2,231,318,682	PR_kwDODunzps5sBEyn	6,792	Fix cache conflict in `_check_legacy_cache2`	{ "login": "lhoestq", "id": 42851186, "node_id": "MDQ6VXNlcjQyODUxMTg2", "avatar_url": "https://avatars.githubusercontent.com/u/42851186?v=4", "gravatar_id": "", "url": "https://api.github.com/users/lhoestq", "html_url": "https://github.com/lhoestq", "followers_url": "https://api.github.com/users/lhoestq/followers", "following_url": "https://api.github.com/users/lhoestq/following{/other_user}", "gists_url": "https://api.github.com/users/lhoestq/gists{/gist_id}", "starred_url": "https://api.github.com/users/lhoestq/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/lhoestq/subscriptions", "organizations_url": "https://api.github.com/users/lhoestq/orgs", "repos_url": "https://api.github.com/users/lhoestq/repos", "events_url": "https://api.github.com/users/lhoestq/events{/privacy}", "received_events_url": "https://api.github.com/users/lhoestq/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	null	[]	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6792). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005212 / 0.011353 (-0.006141) \| 0.003536 / 0.011008 (-0.007472) \| 0.063042 / 0.038508 (0.024534) \| 0.032654 / 0.023109 (0.009545) \| 0.242040 / 0.275898 (-0.033858) \| 0.267735 / 0.323480 (-0.055745) \| 0.003188 / 0.007986 (-0.004797) \| 0.002697 / 0.004328 (-0.001631) \| 0.050127 / 0.004250 (0.045877) \| 0.045960 / 0.037052 (0.008908) \| 0.260926 / 0.258489 (0.002437) \| 0.293953 / 0.293841 (0.000112) \| 0.028352 / 0.128546 (-0.100194) \| 0.010558 / 0.075646 (-0.065088) \| 0.208104 / 0.419271 (-0.211167) \| 0.035889 / 0.043533 (-0.007644) \| 0.246265 / 0.255139 (-0.008874) \| 0.271819 / 0.283200 (-0.011381) \| 0.018491 / 0.141683 (-0.123192) \| 1.299274 / 1.452155 (-0.152881) \| 1.205932 / 1.492716 (-0.286784) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.095574 / 0.018006 (0.077568) \| 0.306493 / 0.000490 (0.306003) \| 0.000216 / 0.000200 (0.000016) \| 0.000042 / 0.000054 (-0.000012) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.018304 / 0.037411 (-0.019107) \| 0.061312 / 0.014526 (0.046786) \| 0.074483 / 0.176557 (-0.102073) \| 0.122231 / 0.737135 (-0.614905) \| 0.075315 / 0.296338 (-0.221024) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.275632 / 0.215209 (0.060423) \| 2.696402 / 2.077655 (0.618747) \| 1.418657 / 1.504120 (-0.085463) \| 1.300014 / 1.541195 (-0.241181) \| 1.299148 / 1.468490 (-0.169342) \| 0.561893 / 4.584777 (-4.022884) \| 2.410710 / 3.745712 (-1.335002) \| 2.749058 / 5.269862 (-2.520803) \| 1.712835 / 4.565676 (-2.852841) \| 0.062278 / 0.424275 (-0.361997) \| 0.005040 / 0.007607 (-0.002567) \| 0.330352 / 0.226044 (0.104308) \| 3.291274 / 2.268929 (1.022345) \| 1.780987 / 55.444624 (-53.663638) \| 1.514764 / 6.876477 (-5.361713) \| 1.533892 / 2.142072 (-0.608181) \| 0.632307 / 4.805227 (-4.172921) \| 0.116011 / 6.500664 (-6.384653) \| 0.041964 / 0.075469 (-0.033505) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.982713 / 1.841788 (-0.859075) \| 11.521597 / 8.074308 (3.447289) \| 9.713063 / 10.191392 (-0.478329) \| 0.132115 / 0.680424 (-0.548309) \| 0.014564 / 0.534201 (-0.519637) \| 0.294087 / 0.579283 (-0.285196) \| 0.267399 / 0.434364 (-0.166965) \| 0.327967 / 0.540337 (-0.212370) \| 0.419279 / 1.386936 (-0.967657) \|\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005098 / 0.011353 (-0.006255) \| 0.003513 / 0.011008 (-0.007495) \| 0.050121 / 0.038508 (0.011613) \| 0.030842 / 0.023109 (0.007732) \| 0.271323 / 0.275898 (-0.004575) \| 0.293592 / 0.323480 (-0.029887) \| 0.004225 / 0.007986 (-0.003761) \| 0.002802 / 0.004328 (-0.001527) \| 0.049035 / 0.004250 (0.044785) \| 0.040748 / 0.037052 (0.003696) \| 0.282542 / 0.258489 (0.024053) \| 0.303779 / 0.293841 (0.009938) \| 0.029213 / 0.128546 (-0.099333) \| 0.010578 / 0.075646 (-0.065068) \| 0.058053 / 0.419271 (-0.361219) \| 0.032830 / 0.043533 (-0.010703) \| 0.272226 / 0.255139 (0.017087) \| 0.290485 / 0.283200 (0.007285) \| 0.017968 / 0.141683 (-0.123714) \| 1.166998 / 1.452155 (-0.285156) \| 1.256354 / 1.492716 (-0.236362) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.096126 / 0.018006 (0.078120) \| 0.306303 / 0.000490 (0.305813) \| 0.000246 / 0.000200 (0.000047) \| 0.000049 / 0.000054 (-0.000006) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.022413 / 0.037411 (-0.014998) \| 0.075008 / 0.014526 (0.060482) \| 0.087703 / 0.176557 (-0.088854) \| 0.127358 / 0.737135 (-0.609777) \| 0.088817 / 0.296338 (-0.207521) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.301103 / 0.215209 (0.085894) \| 2.965441 / 2.077655 (0.887787) \| 1.608075 / 1.504120 (0.103955) \| 1.479214 / 1.541195 (-0.061981) \| 1.492039 / 1.468490 (0.023549) \| 0.574455 / 4.584777 (-4.010322) \| 2.483234 / 3.745712 (-1.262478) \| 2.795901 / 5.269862 (-2.473961) \| 1.742034 / 4.565676 (-2.823642) \| 0.064170 / 0.424275 (-0.360105) \| 0.005572 / 0.007607 (-0.002035) \| 0.349500 / 0.226044 (0.123456) \| 3.482161 / 2.268929 (1.213232) \| 1.950065 / 55.444624 (-53.494559) \| 1.675270 / 6.876477 (-5.201207) \| 1.674534 / 2.142072 (-0.467538) \| 0.657478 / 4.805227 (-4.147749) \| 0.117534 / 6.500664 (-6.383130) \| 0.040880 / 0.075469 (-0.034589) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 1.035276 / 1.841788 (-0.806511) \| 12.035581 / 8.074308 (3.961273) \| 10.127778 / 10.191392 (-0.063614) \| 0.142289 / 0.680424 (-0.538134) \| 0.014702 / 0.534201 (-0.519499) \| 0.288206 / 0.579283 (-0.291077) \| 0.282251 / 0.434364 (-0.152113) \| 0.323479 / 0.540337 (-0.216858) \| 0.419019 / 1.386936 (-0.967917) \|\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#0f27d7b77c73412cfc50b24354bfd7a3e838202f \"CML watermark\")\n" ]	2024-04-08T14:05:42	2024-04-09T11:34:08	2024-04-09T11:27:58	MEMBER	null	false	{ "url": "https://api.github.com/repos/huggingface/datasets/pulls/6792", "html_url": "https://github.com/huggingface/datasets/pull/6792", "diff_url": "https://github.com/huggingface/datasets/pull/6792.diff", "patch_url": "https://github.com/huggingface/datasets/pull/6792.patch", "merged_at": "2024-04-09T11:27:57" }	It was reloading from the wrong cache dir because of a bug in `_check_legacy_cache2`. This function should not trigger if there are config_kwars like `sample_by=` fix https://github.com/huggingface/datasets/issues/6758	{ "login": "lhoestq", "id": 42851186, "node_id": "MDQ6VXNlcjQyODUxMTg2", "avatar_url": "https://avatars.githubusercontent.com/u/42851186?v=4", "gravatar_id": "", "url": "https://api.github.com/users/lhoestq", "html_url": "https://github.com/lhoestq", "followers_url": "https://api.github.com/users/lhoestq/followers", "following_url": "https://api.github.com/users/lhoestq/following{/other_user}", "gists_url": "https://api.github.com/users/lhoestq/gists{/gist_id}", "starred_url": "https://api.github.com/users/lhoestq/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/lhoestq/subscriptions", "organizations_url": "https://api.github.com/users/lhoestq/orgs", "repos_url": "https://api.github.com/users/lhoestq/repos", "events_url": "https://api.github.com/users/lhoestq/events{/privacy}", "received_events_url": "https://api.github.com/users/lhoestq/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6792/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6792/timeline	null	null	true
https://api.github.com/repos/huggingface/datasets/issues/6791	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6791/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6791/comments	https://api.github.com/repos/huggingface/datasets/issues/6791/events	https://github.com/huggingface/datasets/issues/6791	2,230,102,332	I_kwDODunzps6E7Kk8	6,791	`add_faiss_index` raises ValueError: not enough values to unpack (expected 2, got 1)	{ "login": "NeuralFlux", "id": 40491005, "node_id": "MDQ6VXNlcjQwNDkxMDA1", "avatar_url": "https://avatars.githubusercontent.com/u/40491005?v=4", "gravatar_id": "", "url": "https://api.github.com/users/NeuralFlux", "html_url": "https://github.com/NeuralFlux", "followers_url": "https://api.github.com/users/NeuralFlux/followers", "following_url": "https://api.github.com/users/NeuralFlux/following{/other_user}", "gists_url": "https://api.github.com/users/NeuralFlux/gists{/gist_id}", "starred_url": "https://api.github.com/users/NeuralFlux/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/NeuralFlux/subscriptions", "organizations_url": "https://api.github.com/users/NeuralFlux/orgs", "repos_url": "https://api.github.com/users/NeuralFlux/repos", "events_url": "https://api.github.com/users/NeuralFlux/events{/privacy}", "received_events_url": "https://api.github.com/users/NeuralFlux/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	null	[]	null	[ "I realized I was passing a string column to this instead of float. Is it possible to add a warning or error to prevent users from falsely believing there's a bug?", "Hello!\r\n\r\nI agree that we could add some safeguards around the type of `ds[column]`. At least for FAISS, we need the column to be made of embeddings as FAISS doesn't perform the embeddings itself.\r\n\r\nI can propose a PR sometime this week.", "@Dref360 thanks for the initiative!" ]	2024-04-08T01:57:03	2024-04-11T15:38:05	2024-04-11T15:38:05	NONE	null	null	null	### Describe the bug Calling `add_faiss_index` on a `Dataset` with a column argument raises a ValueError. The following is the trace ```python 214 def replacement_add(self, x): 215 """Adds vectors to the index. 216 The index must be trained before vectors can be added to it. 217 The vectors are implicitly numbered in sequence. When `n` vectors are (...) 224 `dtype` must be float32. 225 """ --> 227 n, d = x.shape 228 assert d == self.d 229 x = np.ascontiguousarray(x, dtype='float32') ValueError: not enough values to unpack (expected 2, got 1) ``` ### Steps to reproduce the bug 1. Load any dataset like `ds = datasets.load_dataset("wikimedia/wikipedia", "20231101.en")["train"]` 2. Add an FAISS index on any column `ds.add_faiss_index('title')` ### Expected behavior The index should be created ### Environment info - `datasets` version: 2.18.0 - Platform: Linux-6.5.0-26-generic-x86_64-with-glibc2.35 - Python version: 3.9.19 - `huggingface_hub` version: 0.22.2 - PyArrow version: 15.0.2 - Pandas version: 2.2.1 - `fsspec` version: 2024.2.0 - `faiss-cpu` version: 1.8.0	{ "login": "mariosasko", "id": 47462742, "node_id": "MDQ6VXNlcjQ3NDYyNzQy", "avatar_url": "https://avatars.githubusercontent.com/u/47462742?v=4", "gravatar_id": "", "url": "https://api.github.com/users/mariosasko", "html_url": "https://github.com/mariosasko", "followers_url": "https://api.github.com/users/mariosasko/followers", "following_url": "https://api.github.com/users/mariosasko/following{/other_user}", "gists_url": "https://api.github.com/users/mariosasko/gists{/gist_id}", "starred_url": "https://api.github.com/users/mariosasko/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/mariosasko/subscriptions", "organizations_url": "https://api.github.com/users/mariosasko/orgs", "repos_url": "https://api.github.com/users/mariosasko/repos", "events_url": "https://api.github.com/users/mariosasko/events{/privacy}", "received_events_url": "https://api.github.com/users/mariosasko/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6791/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6791/timeline	null	completed	false
https://api.github.com/repos/huggingface/datasets/issues/6790	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6790/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6790/comments	https://api.github.com/repos/huggingface/datasets/issues/6790/events	https://github.com/huggingface/datasets/issues/6790	2,229,915,236	I_kwDODunzps6E6c5k	6,790	PyArrow 'Memory mapping file failed: Cannot allocate memory' bug	{ "login": "lasuomela", "id": 25725697, "node_id": "MDQ6VXNlcjI1NzI1Njk3", "avatar_url": "https://avatars.githubusercontent.com/u/25725697?v=4", "gravatar_id": "", "url": "https://api.github.com/users/lasuomela", "html_url": "https://github.com/lasuomela", "followers_url": "https://api.github.com/users/lasuomela/followers", "following_url": "https://api.github.com/users/lasuomela/following{/other_user}", "gists_url": "https://api.github.com/users/lasuomela/gists{/gist_id}", "starred_url": "https://api.github.com/users/lasuomela/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/lasuomela/subscriptions", "organizations_url": "https://api.github.com/users/lasuomela/orgs", "repos_url": "https://api.github.com/users/lasuomela/repos", "events_url": "https://api.github.com/users/lasuomela/events{/privacy}", "received_events_url": "https://api.github.com/users/lasuomela/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	open	false	null	[]	null	[ "Thanks for a very clean explanation. This happened to me too, and I don't have sudo access to update the value. I wonder if there might be another workaround.", "One option is to just have more data in each file - /proc/sys/vm/max_map_count limits the maximum number of concurrently open files, but I don't know if the size of a single file is restricted in any way. E.g. 5000 files with 1GB each is 5TB of data. https://huggingface.co/docs/datasets/v2.18.0/en/package_reference/main_classes#datasets.concatenate_datasets can come in handy." ]	2024-04-07T19:25:39	2024-09-06T19:09:37	null	NONE	null	null	null	### Describe the bug Hello, I've been struggling with a problem using Huggingface datasets caused by PyArrow memory allocation. I finally managed to solve it, and thought to document it since similar issues have been raised here before (https://github.com/huggingface/datasets/issues/5710, https://github.com/huggingface/datasets/issues/6176). In my case, I was trying to load ~70k dataset files from disk using `datasets.load_from_disk(data_path)` (meaning 70k repeated calls to load_from_disk). This triggered an (uninformative) exception around 64k loaded files: ``` File "pyarrow/io.pxi", line 1053, in pyarrow.lib.memory_map File "pyarrow/io.pxi", line 1000, in pyarrow.lib.MemoryMappedFile._open File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status OSError: Memory mapping file failed: Cannot allocate memory ``` Despite system RAM usage being very low. After a lot of digging around, I discovered that my Ubuntu machine had a limit on the maximum number of memory mapped files in `/proc/sys/vm/max_map_count` set to 65530, which was causing my data loader to crash. Increasing the limit in the file (`echo <new_mmap_size> \| sudo tee /proc/sys/vm/max_map_count`) made the issue go away. While this isn't a bug as such in either Datasets or PyArrow, this behavior can be very confusing to users. Maybe this should be mentioned in documentation? I suspect the other issues raised here about memory mapping OOM errors could actually be consequence of system configuration. Br, Lauri ### Steps to reproduce the bug ``` import numpy as np import pyarrow as pa import tqdm # Write some data to disk arr = pa.array(np.arange(100)) schema = pa.schema([ pa.field('nums', arr.type) ]) with pa.OSFile('arraydata.arrow', 'wb') as sink: with pa.ipc.new_file(sink, schema=schema) as writer: batch = pa.record_batch([arr], schema=schema) writer.write(batch) # Number of times to open the memory map nums = 70000 # Read the data back arrays = [pa.memory_map('arraydata.arrow', 'r') for _ in tqdm.tqdm(range(nums))] ``` ### Expected behavior No errors. ### Environment info datasets: 2.18.0 pyarrow: 15.0.0	null	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6790/reactions", "total_count": 2, "+1": 2, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6790/timeline	null	null	false
https://api.github.com/repos/huggingface/datasets/issues/6789	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6789/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6789/comments	https://api.github.com/repos/huggingface/datasets/issues/6789/events	https://github.com/huggingface/datasets/issues/6789	2,229,527,001	I_kwDODunzps6E4-HZ	6,789	Issue with map	{ "login": "Nsohko", "id": 102672238, "node_id": "U_kgDOBh6nbg", "avatar_url": "https://avatars.githubusercontent.com/u/102672238?v=4", "gravatar_id": "", "url": "https://api.github.com/users/Nsohko", "html_url": "https://github.com/Nsohko", "followers_url": "https://api.github.com/users/Nsohko/followers", "following_url": "https://api.github.com/users/Nsohko/following{/other_user}", "gists_url": "https://api.github.com/users/Nsohko/gists{/gist_id}", "starred_url": "https://api.github.com/users/Nsohko/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/Nsohko/subscriptions", "organizations_url": "https://api.github.com/users/Nsohko/orgs", "repos_url": "https://api.github.com/users/Nsohko/repos", "events_url": "https://api.github.com/users/Nsohko/events{/privacy}", "received_events_url": "https://api.github.com/users/Nsohko/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	open	false	null	[]	null	[ "Default `writer_batch_size `is set to 1000 (see [map](https://huggingface.co/docs/datasets/v2.16.1/en/package_reference/main_classes#datasets.Dataset.map)).\r\nThe \"tmp1335llua\" is probably the temp file it creates while writing to disk.\r\nMaybe try lowering the `writer_batch_size`.\r\n\r\nFor multi-processing you should probably pass the `processor `as an argument (with e.g. partial) to the function or create it inside so that the sub-processes have access to it and maybe add `if __name__ == \"__main__\"` (not sure that's necessary?).\r\n", "Hi @Modexus,\r\n\r\nThank you very much for the help! Yep after playing around with map, I managed to get the parallel processing to work by implementing it like you suggested.\r\n\r\nRegarding the temp files, it seems like the temp files just keep growing in size as the map continues. Eventually, once map finishes, the temp files are deleted, but they are instead saved as cache .arrow files. These cache files are absolutely gigantic (~ 30-50x the size of the initial dataset!).\r\n\r\nAfter playing around with the `prepare_dataset()` function above, it seems this issue is caused by the following line in the function, where the log-Mel spectrogram of the audio is calculated:\r\n\r\n`# compute log-Mel input features from input audio array\r\n batch[\"input_features\"] = processor.feature_extractor(audio[\"array\"], \r\n sampling_rate=audio[\"sampling_rate\"]).input_features[0]\r\n`\r\n\r\nWhen I remove this line, the final cache files are approximately the same size as the initial dataset.\r\n\r\nCan I check whether this is expected behavior with the whisper feature extractor? I cant imagine the spectrograms are that large!\r\n\r\nThank you so much for the help!", "I'm having a similar issue with the spectrographs taking up an incredibly large amount of space. (i.e. 100GB for 3GB of audio). Is this really normal behavior?", "Upon taking a look at the hex contents of the mapped dataset files I found that the overwhelming majority of the data contained within them was duplicated junk similar to this. I'm not very familiar with the inner workings of AI but I have to assume this is an inefficient way of storing data at best and a bug at worst.\r\n![image](https://github.com/huggingface/datasets/assets/157770431/70bcbf59-d9ac-4fbf-9b8c-c9e3acc1b539)\r\n", "Same problem, dataset.map takes long time to process 12GB raw audio data and create 200GB cache file. Is there any method can run process(map) during train, instead current run \r\nonce and save cache file ? ", "Same issue here. Just trying to normalise image data for a 300MB dataset, ends up with an 11GB cache. The initial .map() call takes 80s over the 15000 images, but then simply iterating over the dataset takes almost 2 minutes. It should be doing no processing here! Something seems wrong.\r\nkeep_in_memory=True also offers no speedup.\r\nEDIT: Running the normalisation with set_transform (i.e. on the fly) iterates through the dataset in 18s. With no normalisation it takes around 14s. No reason for .map() to take 5 mins!", "@eufrizz How you handle this using set_transform?\r\nI have a really big dataset of size 1.2TB and i am going to use it for fine-tunning whisper model. if i use map for dataset_preparing function it will take over 20 days!!!", "> @eufrizz How you handle this using set_transform?\n> I have a really big dataset of size 1.2TB and i am going to use it for fine-tunning whisper model. if i use map for dataset_preparing function it will take over 20 days!!!\n\nJust give the preprocessing function you were using for map to set_transform. Just look at the set_transform documentation. If you're going to do lots of epochs you might be better off just saving the preprocessed data into a new dataset. " ]	2024-04-07T02:52:06	2024-07-23T12:41:38	null	NONE	null	null	null	### Describe the bug Map has been taking extremely long to preprocess my data. It seems to process 1000 examples (which it does really fast in about 10 seconds), then it hangs for a good 1-2 minutes, before it moves on to the next batch of 1000 examples. It also keeps eating up my hard drive space for some reason by creating a file named tmp1335llua that is over 300GB. Trying to set num_proc to be >1 also gives me the following error: NameError: name 'processor' is not defined Please advise on how I could optimise this? ### Steps to reproduce the bug In general, I have been using map as per normal. Here is a snippet of my code: ```` ########################### DATASET LOADING AND PREP ######################### def load_custom_dataset(split): ds = [] if split == 'train': for dset in args.train_datasets: ds.append(load_from_disk(dset)) if split == 'test': for dset in args.test_datasets: ds.append(load_from_disk(dset)) ds_to_return = concatenate_datasets(ds) ds_to_return = ds_to_return.shuffle(seed=22) return ds_to_return def prepare_dataset(batch): # load and (possibly) resample audio data to 16kHz audio = batch["audio"] # compute log-Mel input features from input audio array batch["input_features"] = processor.feature_extractor(audio["array"], sampling_rate=audio["sampling_rate"]).input_features[0] # compute input length of audio sample in seconds batch["input_length"] = len(audio["array"]) / audio["sampling_rate"] # optional pre-processing steps transcription = batch["sentence"] if do_lower_case: transcription = transcription.lower() if do_remove_punctuation: transcription = normalizer(transcription).strip() # encode target text to label ids batch["labels"] = processor.tokenizer(transcription).input_ids return batch print('DATASET PREPARATION IN PROGRESS...') # case 3: combine_and_shuffle is true, only train provided # load train datasets train_set = load_custom_dataset('train') # split dataset raw_dataset = DatasetDict() raw_dataset = train_set.train_test_split(test_size = args.test_size, shuffle=True, seed=42) raw_dataset = raw_dataset.cast_column("audio", Audio(sampling_rate=args.sampling_rate)) print("Before Map:") print(raw_dataset) raw_dataset = raw_dataset.map(prepare_dataset, num_proc=1) print("After Map:") print(raw_dataset) ```` ### Expected behavior Based on the speed at which map is processing examples, I would expect a 5-6 hours completion for all mapping However, because it hangs every 1000 examples, I instead roughly estimate it would take about 40 hours! Moreover, i cant even finish the map because it keeps exponentially eating up my hard drive space ### Environment info - `datasets` version: 2.18.0 - Platform: Windows-10-10.0.22631-SP0 - Python version: 3.10.14 - `huggingface_hub` version: 0.22.2 - PyArrow version: 15.0.2 - Pandas version: 2.2.1 - `fsspec` version: 2024.2.0	null	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6789/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6789/timeline	null	null	false
https://api.github.com/repos/huggingface/datasets/issues/6788	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6788/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6788/comments	https://api.github.com/repos/huggingface/datasets/issues/6788/events	https://github.com/huggingface/datasets/issues/6788	2,229,207,521	I_kwDODunzps6E3wHh	6,788	A Question About the Map Function	{ "login": "Klein-Lan", "id": 87431052, "node_id": "MDQ6VXNlcjg3NDMxMDUy", "avatar_url": "https://avatars.githubusercontent.com/u/87431052?v=4", "gravatar_id": "", "url": "https://api.github.com/users/Klein-Lan", "html_url": "https://github.com/Klein-Lan", "followers_url": "https://api.github.com/users/Klein-Lan/followers", "following_url": "https://api.github.com/users/Klein-Lan/following{/other_user}", "gists_url": "https://api.github.com/users/Klein-Lan/gists{/gist_id}", "starred_url": "https://api.github.com/users/Klein-Lan/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/Klein-Lan/subscriptions", "organizations_url": "https://api.github.com/users/Klein-Lan/orgs", "repos_url": "https://api.github.com/users/Klein-Lan/repos", "events_url": "https://api.github.com/users/Klein-Lan/events{/privacy}", "received_events_url": "https://api.github.com/users/Klein-Lan/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	null	[]	null	[ "All data is saved in the arrow format on disk.\r\nIf you return a tensor it gets converted to arrow before saving to disk when using map.\r\n\r\nTo get a tensor when you access data elements you can use `dataset.set_format(\"pt\")`.\r\nNote that this just changes how the data is loaded, not how it is stored.", "> All data is saved in the arrow format on disk. If you return a tensor it gets converted to arrow before saving to disk when using map.\r\n> \r\n> To get a tensor when you access data elements you can use `dataset.set_format(\"pt\")`. Note that this just changes how the data is loaded, not how it is stored.\r\n\r\nThank you very much for your explanation, I understand what you mean now. So you're saying that when streaming=True, there's no need to convert it to the arrow format and save it to disk. But if we directly load all formats and then convert them into the arrow format after passing through the map function, it will convert torch.Tensor into a List. I see." ]	2024-04-06T11:45:23	2024-04-11T05:29:35	2024-04-11T05:29:35	NONE	null	null	null	### Describe the bug Hello, I have a question regarding the map function in the Hugging Face datasets. The situation is as follows: when I load a jsonl file using load_dataset(..., streaming=False), and then utilize the map function to process it, I specify that the returned example should be of type Torch.tensor. However, I noticed that after applying the map function, the datatype automatically changes to List, which leads to errors in my program. I attempted to use load_dataset(..., streaming=True), and this issue no longer occurs. I'm not entirely clear on why this happens. Could you please provide some insights into this? ### Steps to reproduce the bug 1.dataset = load_dataset(xxx, streaming = False) 2. dataset.map(function), function will return torch.Tensor. 3. you will find the format of data in dataset is List. ### Expected behavior I expected to receieve the format of data is torch.Tensor. ### Environment info 2.18.0	{ "login": "Klein-Lan", "id": 87431052, "node_id": "MDQ6VXNlcjg3NDMxMDUy", "avatar_url": "https://avatars.githubusercontent.com/u/87431052?v=4", "gravatar_id": "", "url": "https://api.github.com/users/Klein-Lan", "html_url": "https://github.com/Klein-Lan", "followers_url": "https://api.github.com/users/Klein-Lan/followers", "following_url": "https://api.github.com/users/Klein-Lan/following{/other_user}", "gists_url": "https://api.github.com/users/Klein-Lan/gists{/gist_id}", "starred_url": "https://api.github.com/users/Klein-Lan/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/Klein-Lan/subscriptions", "organizations_url": "https://api.github.com/users/Klein-Lan/orgs", "repos_url": "https://api.github.com/users/Klein-Lan/repos", "events_url": "https://api.github.com/users/Klein-Lan/events{/privacy}", "received_events_url": "https://api.github.com/users/Klein-Lan/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6788/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6788/timeline	null	completed	false
https://api.github.com/repos/huggingface/datasets/issues/6787	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6787/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6787/comments	https://api.github.com/repos/huggingface/datasets/issues/6787/events	https://github.com/huggingface/datasets/issues/6787	2,229,103,264	I_kwDODunzps6E3Wqg	6,787	TimeoutError in map	{ "login": "Jiaxin-Wen", "id": 48146603, "node_id": "MDQ6VXNlcjQ4MTQ2NjAz", "avatar_url": "https://avatars.githubusercontent.com/u/48146603?v=4", "gravatar_id": "", "url": "https://api.github.com/users/Jiaxin-Wen", "html_url": "https://github.com/Jiaxin-Wen", "followers_url": "https://api.github.com/users/Jiaxin-Wen/followers", "following_url": "https://api.github.com/users/Jiaxin-Wen/following{/other_user}", "gists_url": "https://api.github.com/users/Jiaxin-Wen/gists{/gist_id}", "starred_url": "https://api.github.com/users/Jiaxin-Wen/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/Jiaxin-Wen/subscriptions", "organizations_url": "https://api.github.com/users/Jiaxin-Wen/orgs", "repos_url": "https://api.github.com/users/Jiaxin-Wen/repos", "events_url": "https://api.github.com/users/Jiaxin-Wen/events{/privacy}", "received_events_url": "https://api.github.com/users/Jiaxin-Wen/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	open	false	null	[]	null	[ "From my current understanding, this timeout is only used when we need to get the results.\r\n\r\nOne of:\r\n1. All tasks are done\r\n2. One worker died\r\n\r\nYour function should work fine and it's definitely a bug if it doesn't.", "When one of the `map`'s worker processes crashes, the linked code re-raises an error from the crash and returns it to the caller.\r\n\r\nIf your question is how to limit the time of long-running tasks/worker processes, such functionality doesn't exist in `datasets` (yet), which means you need to implement it yourself.\r\n\r\nE.g., you can implement it using the built-in `signal` module like this:\r\n```python\r\nimport time\r\nimport signal\r\nfrom contextlib import contextmanager\r\n\r\nfrom datasets import Dataset\r\n\r\n\r\n@contextmanager\r\ndef max_exec_time(t):\r\n def raise_timeout_handler(signum, frame):\r\n raise TimeoutError\r\n \r\n orig_handler = signal.getsignal(signal.SIGALRM)\r\n signal.signal(signal.SIGALRM, raise_timeout_handler)\r\n try:\r\n signal.alarm(t)\r\n yield\r\n finally:\r\n signal.alarm(0)\r\n signal.signal(signal.SIGALRM, orig_handler)\r\n\r\n\r\ndef worker(example, rank):\r\n try:\r\n with max_exec_time(20): # 20 sec execution limit\r\n if rank % 2 == 0:\r\n time.sleep(50) # simulate a long-running task\r\n example[\"a\"] = 100\r\n except TimeoutError:\r\n example[\"a\"] = None # Or return empty batches here in the \"batched\" mode\r\n return example\r\n\r\ndata = Dataset.from_list([{\"a\": 1}, {\"a\": 2}])\r\ndata = data.map(worker, num_proc=2, with_rank=True)\r\nprint(data[0])\r\n```", "> From my current understanding, this timeout is only used when we need to get the results.\r\n> \r\n> One of:\r\n> \r\n> 1. All tasks are done\r\n> 2. One worker died\r\n> \r\n> Your function should work fine and it's definitely a bug if it doesn't.\r\n\r\nthanks for responding! can you reproduce the stuck with the above example code?", "> When one of the `map`'s worker processes crashes, the linked code re-raises an error from the crash and returns it to the caller.\r\n> \r\n> If your question is how to limit the time of long-running tasks/worker processes, such functionality doesn't exist in `datasets` (yet), which means you need to implement it yourself.\r\n> \r\n> E.g., you can implement it using the built-in `signal` module like this:\r\n> \r\n> ```python\r\n> import time\r\n> import signal\r\n> from contextlib import contextmanager\r\n> \r\n> from datasets import Dataset\r\n> \r\n> \r\n> @contextmanager\r\n> def max_exec_time(t):\r\n> def raise_timeout_handler(signum, frame):\r\n> raise TimeoutError\r\n> \r\n> orig_handler = signal.getsignal(signal.SIGALRM)\r\n> signal.signal(signal.SIGALRM, raise_timeout_handler)\r\n> try:\r\n> signal.alarm(t)\r\n> yield\r\n> finally:\r\n> signal.alarm(0)\r\n> signal.signal(signal.SIGALRM, orig_handler)\r\n> \r\n> \r\n> def worker(example, rank):\r\n> try:\r\n> with max_exec_time(20): # 20 sec execution limit\r\n> if rank % 2 == 0:\r\n> time.sleep(50) # simulate a long-running task\r\n> example[\"a\"] = 100\r\n> except TimeoutError:\r\n> example[\"a\"] = None # Or return empty batches here in the \"batched\" mode\r\n> return example\r\n> \r\n> data = Dataset.from_list([{\"a\": 1}, {\"a\": 2}])\r\n> data = data.map(worker, num_proc=2, with_rank=True)\r\n> print(data[0])\r\n> ```\r\n\r\nthanks for responding! However, I don't think we should use `signal` in the context of multiprocessing since sometimes it will crash one process and raise the following error\r\nhttps://github.com/huggingface/datasets/blob/c3ddb1ef00334a6f973679a51e783905fbc9ef0b/src/datasets/utils/py_utils.py#L664", "> thanks for responding! However, I don't think we should use signal in the context of multiprocessing since sometimes it will crash one process and raise the following error\r\n\r\nThe above code has `try/except` to catch the error from the handler. Or do you get an error other than `TimeoutError`?", "> > thanks for responding! However, I don't think we should use signal in the context of multiprocessing since sometimes it will crash one process and raise the following error\r\n> \r\n> The above code has `try/except` to catch the error from the handler. Or do you get an error other than `TimeoutError`?\r\n\r\nyup, it will raise the RuntimeError: https://github.com/huggingface/datasets/blob/c3ddb1ef00334a6f973679a51e783905fbc9ef0b/src/datasets/utils/py_utils.py#L667C19-L670C22\r\n\r\n```\r\n raise RuntimeError(\r\n \"One of the subprocesses has abruptly died during map operation.\"\r\n \"To debug the error, disable multiprocessing.\"\r\n )\r\n```", "What @mariosasko proposed it's very useful for debugging. Thank you!" ]	2024-04-06T06:25:39	2024-08-14T02:09:57	null	CONTRIBUTOR	null	null	null	### Describe the bug ```python from datasets import Dataset def worker(example): while True: continue example['a'] = 100 return example data = Dataset.from_list([{"a": 1}, {"a": 2}]) data = data.map(worker) print(data[0]) ``` I'm implementing a worker function whose runtime will depend on specific examples (e.g., while most examples take 0.01s in worker, several examples may take 50s). Therefore, I would like to know how the current implementation will handle those subprocesses that require a long (e.g., >= 5min) or even infinite time. I notice that the current implementation set a timeout of 0.05 second https://github.com/huggingface/datasets/blob/c3ddb1ef00334a6f973679a51e783905fbc9ef0b/src/datasets/utils/py_utils.py#L674 However, this example code still gets stuck. ### Steps to reproduce the bug run the example above ### Expected behavior I want to set a default worker to handle these timeout cases, instead of getting stuck ### Environment info main branch version	null	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6787/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6787/timeline	null	null	false
https://api.github.com/repos/huggingface/datasets/issues/6786	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6786/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6786/comments	https://api.github.com/repos/huggingface/datasets/issues/6786/events	https://github.com/huggingface/datasets/pull/6786	2,228,463,776	PR_kwDODunzps5r3kWg	6,786	Make Image cast storage faster	{ "login": "Modexus", "id": 37351874, "node_id": "MDQ6VXNlcjM3MzUxODc0", "avatar_url": "https://avatars.githubusercontent.com/u/37351874?v=4", "gravatar_id": "", "url": "https://api.github.com/users/Modexus", "html_url": "https://github.com/Modexus", "followers_url": "https://api.github.com/users/Modexus/followers", "following_url": "https://api.github.com/users/Modexus/following{/other_user}", "gists_url": "https://api.github.com/users/Modexus/gists{/gist_id}", "starred_url": "https://api.github.com/users/Modexus/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/Modexus/subscriptions", "organizations_url": "https://api.github.com/users/Modexus/orgs", "repos_url": "https://api.github.com/users/Modexus/repos", "events_url": "https://api.github.com/users/Modexus/events{/privacy}", "received_events_url": "https://api.github.com/users/Modexus/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	open	false	null	[]	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6786). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "Hi ! Thanks for diving into this, this conversion to python lists is indeed quite slow.\r\n\r\nArray2DExtensionType and Array3DExtensionType currently rely on pyarrow lists, but we will soon modify them to use FixedShapeTensorArray instead which is more efficient (e.g. doesn't need to store an offset for each value). So ideally it would be cool to speed this code up without using those extension types or it will be blocking to improve Array2DExtensionType and Array3DExtensionType.\r\n\r\nIf I understand correctly you just need the logic from ArrayExtensionArray.to_numpy ? If so feel free to make a separate function and ArrayExtensionArray.to_numpy can call it", "Hey! I didn't have time to look into this but I just stumbled upon another problem. \r\nWhile my fix kind of made it usable I now pre-embedded the images and even as Array3D they are really slow to load. \r\nDon't think this can be resolved with using ArrayExtensionArray.to_numpy.\r\n\r\nI think actually making the Array3DExtensionType faster would probably resolve both issues as you mentioned.\r\nIs there an update on using FixedShapeTensorArray?\r\nI'd gladly help implementing/testing it if there is some outline how to do it.", "No one is working on this atm afaik (and actually we don't have any ETA unfortunately).\r\n\r\nTo do this change I think we need to:\r\n- update the `_ArrayXD` parent class of all the `Array2D`, `Array3D` types to use `pa.fixed_shape_tensor` type\r\n ```diff\r\n - pa_type = globals()[self.__class__.__name__ + \"ExtensionType\"](self.shape, self.dtype)\r\n + pa_type = pa.fixed_shape_tensor(self.shape, string_to_arrow(self.dtype))\r\n ```\r\n- remove the old extension type `_ArrayXDExtensionType` and extension array `ArrayExtensionArray`\r\n- probably update some functions in `features.py` that were using those types and use the new ones instead", "Thanks, I have looked into this and have a working solution at least for my specific case.\r\nBut I had quite a few issues along the way that are not solved nicely.\r\nIt follows your suggestion though internally it is then just a fixed_shape_tensor as there is no ExtensionType anymore.\r\n\r\nHopefully, I can create a separate PR with these changes soon.", "Nice, thanks @Modexus ! ", "I have run into some issues, notably I don't think `FixedShapeTensorArray` is completely supported by `pandas `and `polars`.\r\nWell it seems to work for `pandas `but one loses the actual shape of the extension.\r\n`Polars `just throws an error and this cannot be changed with `schema_overrides` as they are applied after.\r\n\r\nI have tried to somehow cast the `FixedShapeTensorArray` to something else like a nested FixedSizeLists, however I have not found a clean solution to do that.\r\nIf somebody has a clean solution to cast it to something such that the shape survives the roundtrip to `pandas`/`polars `and back, it may be possible.\r\n", "Can we start using FixedShapeTensor or FixedSizeList even if pandas/polars don't support them fully yet ?\r\n\r\nWe would still get the benefit of optimized conversion to numpy" ]	2024-04-05T17:00:46	2024-10-01T09:09:14	null	CONTRIBUTOR	null	false	{ "url": "https://api.github.com/repos/huggingface/datasets/pulls/6786", "html_url": "https://github.com/huggingface/datasets/pull/6786", "diff_url": "https://github.com/huggingface/datasets/pull/6786.diff", "patch_url": "https://github.com/huggingface/datasets/pull/6786.patch", "merged_at": null }	PR for issue #6782. Makes `cast_storage` of the `Image` class faster by removing the slow call to `.pylist`. Instead directly convert each `ListArray` item to either `Array2DExtensionType` or `Array3DExtensionType`. This also preserves the `dtype` removing the warning if the array is already `uint8`.	null	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6786/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6786/timeline	null	null	true
https://api.github.com/repos/huggingface/datasets/issues/6785	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6785/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6785/comments	https://api.github.com/repos/huggingface/datasets/issues/6785/events	https://github.com/huggingface/datasets/pull/6785	2,228,429,852	PR_kwDODunzps5r3dCw	6,785	rename datasets-server to dataset-viewer	{ "login": "severo", "id": 1676121, "node_id": "MDQ6VXNlcjE2NzYxMjE=", "avatar_url": "https://avatars.githubusercontent.com/u/1676121?v=4", "gravatar_id": "", "url": "https://api.github.com/users/severo", "html_url": "https://github.com/severo", "followers_url": "https://api.github.com/users/severo/followers", "following_url": "https://api.github.com/users/severo/following{/other_user}", "gists_url": "https://api.github.com/users/severo/gists{/gist_id}", "starred_url": "https://api.github.com/users/severo/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/severo/subscriptions", "organizations_url": "https://api.github.com/users/severo/orgs", "repos_url": "https://api.github.com/users/severo/repos", "events_url": "https://api.github.com/users/severo/events{/privacy}", "received_events_url": "https://api.github.com/users/severo/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	null	[]	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6785). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005224 / 0.011353 (-0.006129) \| 0.003938 / 0.011008 (-0.007070) \| 0.063829 / 0.038508 (0.025321) \| 0.030975 / 0.023109 (0.007865) \| 0.265090 / 0.275898 (-0.010808) \| 0.290994 / 0.323480 (-0.032486) \| 0.003083 / 0.007986 (-0.004902) \| 0.002810 / 0.004328 (-0.001518) \| 0.048860 / 0.004250 (0.044609) \| 0.044663 / 0.037052 (0.007611) \| 0.272161 / 0.258489 (0.013672) \| 0.306966 / 0.293841 (0.013125) \| 0.028028 / 0.128546 (-0.100518) \| 0.010616 / 0.075646 (-0.065031) \| 0.211649 / 0.419271 (-0.207623) \| 0.035906 / 0.043533 (-0.007626) \| 0.251779 / 0.255139 (-0.003360) \| 0.275543 / 0.283200 (-0.007657) \| 0.017710 / 0.141683 (-0.123973) \| 1.127015 / 1.452155 (-0.325139) \| 1.173319 / 1.492716 (-0.319397) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.090625 / 0.018006 (0.072619) \| 0.301973 / 0.000490 (0.301483) \| 0.000217 / 0.000200 (0.000017) \| 0.000053 / 0.000054 (-0.000002) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.018868 / 0.037411 (-0.018543) \| 0.062402 / 0.014526 (0.047876) \| 0.074053 / 0.176557 (-0.102504) \| 0.121484 / 0.737135 (-0.615652) \| 0.078674 / 0.296338 (-0.217664) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.277821 / 0.215209 (0.062612) \| 2.761642 / 2.077655 (0.683987) \| 1.452735 / 1.504120 (-0.051385) \| 1.336303 / 1.541195 (-0.204891) \| 1.343045 / 1.468490 (-0.125445) \| 0.560917 / 4.584777 (-4.023860) \| 2.353427 / 3.745712 (-1.392286) \| 2.699067 / 5.269862 (-2.570795) \| 1.704752 / 4.565676 (-2.860925) \| 0.062668 / 0.424275 (-0.361607) \| 0.005120 / 0.007607 (-0.002487) \| 0.330455 / 0.226044 (0.104410) \| 3.264604 / 2.268929 (0.995675) \| 1.791940 / 55.444624 (-53.652685) \| 1.526083 / 6.876477 (-5.350394) \| 1.541429 / 2.142072 (-0.600643) \| 0.630343 / 4.805227 (-4.174884) \| 0.115189 / 6.500664 (-6.385475) \| 0.041716 / 0.075469 (-0.033753) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.975008 / 1.841788 (-0.866779) \| 11.326924 / 8.074308 (3.252616) \| 9.810300 / 10.191392 (-0.381092) \| 0.141068 / 0.680424 (-0.539356) \| 0.013950 / 0.534201 (-0.520251) \| 0.285691 / 0.579283 (-0.293592) \| 0.257968 / 0.434364 (-0.176396) \| 0.322976 / 0.540337 (-0.217361) \| 0.411114 / 1.386936 (-0.975822) \|\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005176 / 0.011353 (-0.006177) \| 0.003631 / 0.011008 (-0.007377) \| 0.050006 / 0.038508 (0.011498) \| 0.030622 / 0.023109 (0.007513) \| 0.277364 / 0.275898 (0.001466) \| 0.299752 / 0.323480 (-0.023728) \| 0.004110 / 0.007986 (-0.003876) \| 0.002694 / 0.004328 (-0.001634) \| 0.048966 / 0.004250 (0.044715) \| 0.039634 / 0.037052 (0.002582) \| 0.289959 / 0.258489 (0.031470) \| 0.320689 / 0.293841 (0.026848) \| 0.029285 / 0.128546 (-0.099261) \| 0.010435 / 0.075646 (-0.065211) \| 0.057432 / 0.419271 (-0.361840) \| 0.032554 / 0.043533 (-0.010979) \| 0.277354 / 0.255139 (0.022215) \| 0.296872 / 0.283200 (0.013673) \| 0.017338 / 0.141683 (-0.124344) \| 1.134174 / 1.452155 (-0.317981) \| 1.184695 / 1.492716 (-0.308021) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.089953 / 0.018006 (0.071947) \| 0.299372 / 0.000490 (0.298882) \| 0.000212 / 0.000200 (0.000012) \| 0.000043 / 0.000054 (-0.000012) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.021349 / 0.037411 (-0.016062) \| 0.075167 / 0.014526 (0.060641) \| 0.085910 / 0.176557 (-0.090647) \| 0.124729 / 0.737135 (-0.612406) \| 0.088313 / 0.296338 (-0.208025) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.291939 / 0.215209 (0.076730) \| 2.851077 / 2.077655 (0.773423) \| 1.609382 / 1.504120 (0.105262) \| 1.469656 / 1.541195 (-0.071539) \| 1.490469 / 1.468490 (0.021979) \| 0.570421 / 4.584777 (-4.014356) \| 2.441438 / 3.745712 (-1.304274) \| 2.756514 / 5.269862 (-2.513347) \| 1.714202 / 4.565676 (-2.851474) \| 0.063656 / 0.424275 (-0.360619) \| 0.005640 / 0.007607 (-0.001967) \| 0.336240 / 0.226044 (0.110196) \| 3.355434 / 2.268929 (1.086505) \| 1.947553 / 55.444624 (-53.497072) \| 1.672776 / 6.876477 (-5.203700) \| 1.685316 / 2.142072 (-0.456757) \| 0.638849 / 4.805227 (-4.166378) \| 0.116304 / 6.500664 (-6.384360) \| 0.041588 / 0.075469 (-0.033881) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 1.026700 / 1.841788 (-0.815088) \| 12.044628 / 8.074308 (3.970319) \| 10.464007 / 10.191392 (0.272615) \| 0.156169 / 0.680424 (-0.524255) \| 0.015624 / 0.534201 (-0.518577) \| 0.287233 / 0.579283 (-0.292050) \| 0.270374 / 0.434364 (-0.163990) \| 0.325255 / 0.540337 (-0.215083) \| 0.412021 / 1.386936 (-0.974915) \|\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#6f7f1718e3db54d7923ebe4383301fdd380c18b9 \"CML watermark\")\n" ]	2024-04-05T16:37:05	2024-04-08T12:41:13	2024-04-08T12:35:02	COLLABORATOR	null	false	{ "url": "https://api.github.com/repos/huggingface/datasets/pulls/6785", "html_url": "https://github.com/huggingface/datasets/pull/6785", "diff_url": "https://github.com/huggingface/datasets/pull/6785.diff", "patch_url": "https://github.com/huggingface/datasets/pull/6785.patch", "merged_at": "2024-04-08T12:35:02" }	See https://github.com/huggingface/dataset-viewer/issues/2650 Tell me if it's OK, or if it's a breaking change that must be handled differently. Also note that the docs page is still https://huggingface.co/docs/datasets-server/, so I didn't change it. And the API URL is still https://datasets-server.huggingface.co/ (and [might always be](https://github.com/huggingface/dataset-viewer/issues/2666)), so I let it too.	{ "login": "severo", "id": 1676121, "node_id": "MDQ6VXNlcjE2NzYxMjE=", "avatar_url": "https://avatars.githubusercontent.com/u/1676121?v=4", "gravatar_id": "", "url": "https://api.github.com/users/severo", "html_url": "https://github.com/severo", "followers_url": "https://api.github.com/users/severo/followers", "following_url": "https://api.github.com/users/severo/following{/other_user}", "gists_url": "https://api.github.com/users/severo/gists{/gist_id}", "starred_url": "https://api.github.com/users/severo/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/severo/subscriptions", "organizations_url": "https://api.github.com/users/severo/orgs", "repos_url": "https://api.github.com/users/severo/repos", "events_url": "https://api.github.com/users/severo/events{/privacy}", "received_events_url": "https://api.github.com/users/severo/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6785/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6785/timeline	null	null	true
https://api.github.com/repos/huggingface/datasets/issues/6784	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6784/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6784/comments	https://api.github.com/repos/huggingface/datasets/issues/6784/events	https://github.com/huggingface/datasets/pull/6784	2,228,390,504	PR_kwDODunzps5r3UTj	6,784	Extract data on the fly in packaged builders	{ "login": "mariosasko", "id": 47462742, "node_id": "MDQ6VXNlcjQ3NDYyNzQy", "avatar_url": "https://avatars.githubusercontent.com/u/47462742?v=4", "gravatar_id": "", "url": "https://api.github.com/users/mariosasko", "html_url": "https://github.com/mariosasko", "followers_url": "https://api.github.com/users/mariosasko/followers", "following_url": "https://api.github.com/users/mariosasko/following{/other_user}", "gists_url": "https://api.github.com/users/mariosasko/gists{/gist_id}", "starred_url": "https://api.github.com/users/mariosasko/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/mariosasko/subscriptions", "organizations_url": "https://api.github.com/users/mariosasko/orgs", "repos_url": "https://api.github.com/users/mariosasko/repos", "events_url": "https://api.github.com/users/mariosasko/events{/privacy}", "received_events_url": "https://api.github.com/users/mariosasko/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	null	[]	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6784). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "CI failures are unrelated, so this is ready for the review", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005130 / 0.011353 (-0.006223) \| 0.003784 / 0.011008 (-0.007224) \| 0.064899 / 0.038508 (0.026391) \| 0.029456 / 0.023109 (0.006347) \| 0.253384 / 0.275898 (-0.022514) \| 0.273509 / 0.323480 (-0.049971) \| 0.004116 / 0.007986 (-0.003870) \| 0.002713 / 0.004328 (-0.001615) \| 0.053984 / 0.004250 (0.049733) \| 0.043538 / 0.037052 (0.006485) \| 0.264696 / 0.258489 (0.006207) \| 0.298321 / 0.293841 (0.004480) \| 0.027916 / 0.128546 (-0.100630) \| 0.010734 / 0.075646 (-0.064912) \| 0.208284 / 0.419271 (-0.210988) \| 0.035873 / 0.043533 (-0.007659) \| 0.251028 / 0.255139 (-0.004111) \| 0.270835 / 0.283200 (-0.012364) \| 0.017475 / 0.141683 (-0.124208) \| 1.130728 / 1.452155 (-0.321426) \| 1.188672 / 1.492716 (-0.304044) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.094191 / 0.018006 (0.076185) \| 0.304064 / 0.000490 (0.303575) \| 0.000251 / 0.000200 (0.000051) \| 0.000058 / 0.000054 (0.000004) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.018414 / 0.037411 (-0.018998) \| 0.061550 / 0.014526 (0.047024) \| 0.074200 / 0.176557 (-0.102357) \| 0.120250 / 0.737135 (-0.616885) \| 0.076018 / 0.296338 (-0.220321) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.302517 / 0.215209 (0.087308) \| 2.943936 / 2.077655 (0.866282) \| 1.584847 / 1.504120 (0.080727) \| 1.464501 / 1.541195 (-0.076694) \| 1.472402 / 1.468490 (0.003912) \| 0.570971 / 4.584777 (-4.013806) \| 2.383207 / 3.745712 (-1.362505) \| 2.811520 / 5.269862 (-2.458342) \| 1.746997 / 4.565676 (-2.818680) \| 0.063391 / 0.424275 (-0.360884) \| 0.005296 / 0.007607 (-0.002311) \| 0.358948 / 0.226044 (0.132903) \| 3.604704 / 2.268929 (1.335776) \| 1.935813 / 55.444624 (-53.508812) \| 1.659944 / 6.876477 (-5.216533) \| 1.687151 / 2.142072 (-0.454922) \| 0.658044 / 4.805227 (-4.147183) \| 0.120425 / 6.500664 (-6.380240) \| 0.042694 / 0.075469 (-0.032775) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.986308 / 1.841788 (-0.855479) \| 11.727945 / 8.074308 (3.653637) \| 9.532785 / 10.191392 (-0.658607) \| 0.140071 / 0.680424 (-0.540352) \| 0.013472 / 0.534201 (-0.520729) \| 0.285828 / 0.579283 (-0.293455) \| 0.261571 / 0.434364 (-0.172793) \| 0.323114 / 0.540337 (-0.217223) \| 0.418132 / 1.386936 (-0.968804) \|\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005428 / 0.011353 (-0.005925) \| 0.003954 / 0.011008 (-0.007054) \| 0.050336 / 0.038508 (0.011828) \| 0.029941 / 0.023109 (0.006831) \| 0.281483 / 0.275898 (0.005585) \| 0.304822 / 0.323480 (-0.018658) \| 0.004151 / 0.007986 (-0.003835) \| 0.002862 / 0.004328 (-0.001466) \| 0.049196 / 0.004250 (0.044945) \| 0.040266 / 0.037052 (0.003213) \| 0.293515 / 0.258489 (0.035026) \| 0.319165 / 0.293841 (0.025324) \| 0.029186 / 0.128546 (-0.099360) \| 0.010838 / 0.075646 (-0.064809) \| 0.058789 / 0.419271 (-0.360483) \| 0.032847 / 0.043533 (-0.010686) \| 0.280164 / 0.255139 (0.025025) \| 0.299609 / 0.283200 (0.016410) \| 0.018291 / 0.141683 (-0.123392) \| 1.153858 / 1.452155 (-0.298297) \| 1.219108 / 1.492716 (-0.273608) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.093783 / 0.018006 (0.075777) \| 0.301526 / 0.000490 (0.301037) \| 0.000211 / 0.000200 (0.000011) \| 0.000055 / 0.000054 (0.000001) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.022105 / 0.037411 (-0.015306) \| 0.074844 / 0.014526 (0.060318) \| 0.087147 / 0.176557 (-0.089409) \| 0.127678 / 0.737135 (-0.609457) \| 0.088630 / 0.296338 (-0.207709) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.286805 / 0.215209 (0.071596) \| 2.828664 / 2.077655 (0.751009) \| 1.579771 / 1.504120 (0.075651) \| 1.463137 / 1.541195 (-0.078058) \| 1.509238 / 1.468490 (0.040748) \| 0.583425 / 4.584777 (-4.001352) \| 2.424905 / 3.745712 (-1.320807) \| 2.819354 / 5.269862 (-2.450508) \| 1.784695 / 4.565676 (-2.780981) \| 0.063374 / 0.424275 (-0.360901) \| 0.005337 / 0.007607 (-0.002270) \| 0.342291 / 0.226044 (0.116247) \| 3.404319 / 2.268929 (1.135390) \| 1.956909 / 55.444624 (-53.487716) \| 1.694317 / 6.876477 (-5.182160) \| 1.696256 / 2.142072 (-0.445817) \| 0.655748 / 4.805227 (-4.149480) \| 0.116785 / 6.500664 (-6.383879) \| 0.040930 / 0.075469 (-0.034539) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 1.034463 / 1.841788 (-0.807325) \| 12.252041 / 8.074308 (4.177733) \| 10.593960 / 10.191392 (0.402568) \| 0.139311 / 0.680424 (-0.541112) \| 0.016177 / 0.534201 (-0.518023) \| 0.288910 / 0.579283 (-0.290373) \| 0.281588 / 0.434364 (-0.152776) \| 0.323066 / 0.540337 (-0.217272) \| 0.427604 / 1.386936 (-0.959332) \|\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#a188022dc43a76a119d90c03832d51d6e4a94d91 \"CML watermark\")\n" ]	2024-04-05T16:12:25	2024-04-16T16:37:47	2024-04-16T16:31:29	COLLABORATOR	null	false	{ "url": "https://api.github.com/repos/huggingface/datasets/pulls/6784", "html_url": "https://github.com/huggingface/datasets/pull/6784", "diff_url": "https://github.com/huggingface/datasets/pull/6784.diff", "patch_url": "https://github.com/huggingface/datasets/pull/6784.patch", "merged_at": "2024-04-16T16:31:29" }	Instead of waiting for data files to be extracted in the packaged builders, we can prepend the compression prefix and extract them as they are being read (using `fsspec`). This saves disk space (deleting extracted archives is not set by default) and slightly speeds up dataset generation (less disk reads)	{ "login": "mariosasko", "id": 47462742, "node_id": "MDQ6VXNlcjQ3NDYyNzQy", "avatar_url": "https://avatars.githubusercontent.com/u/47462742?v=4", "gravatar_id": "", "url": "https://api.github.com/users/mariosasko", "html_url": "https://github.com/mariosasko", "followers_url": "https://api.github.com/users/mariosasko/followers", "following_url": "https://api.github.com/users/mariosasko/following{/other_user}", "gists_url": "https://api.github.com/users/mariosasko/gists{/gist_id}", "starred_url": "https://api.github.com/users/mariosasko/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/mariosasko/subscriptions", "organizations_url": "https://api.github.com/users/mariosasko/orgs", "repos_url": "https://api.github.com/users/mariosasko/repos", "events_url": "https://api.github.com/users/mariosasko/events{/privacy}", "received_events_url": "https://api.github.com/users/mariosasko/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6784/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6784/timeline	null	null	true
https://api.github.com/repos/huggingface/datasets/issues/6783	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6783/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6783/comments	https://api.github.com/repos/huggingface/datasets/issues/6783/events	https://github.com/huggingface/datasets/issues/6783	2,228,179,466	I_kwDODunzps6Ez1IK	6,783	AttributeError: module 'numpy' has no attribute 'object'. in Kaggle Notebook	{ "login": "petrov826", "id": 26062262, "node_id": "MDQ6VXNlcjI2MDYyMjYy", "avatar_url": "https://avatars.githubusercontent.com/u/26062262?v=4", "gravatar_id": "", "url": "https://api.github.com/users/petrov826", "html_url": "https://github.com/petrov826", "followers_url": "https://api.github.com/users/petrov826/followers", "following_url": "https://api.github.com/users/petrov826/following{/other_user}", "gists_url": "https://api.github.com/users/petrov826/gists{/gist_id}", "starred_url": "https://api.github.com/users/petrov826/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/petrov826/subscriptions", "organizations_url": "https://api.github.com/users/petrov826/orgs", "repos_url": "https://api.github.com/users/petrov826/repos", "events_url": "https://api.github.com/users/petrov826/events{/privacy}", "received_events_url": "https://api.github.com/users/petrov826/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	null	[]	null	[ "Hi! You can fix this by updating the `datasets` package with `pip install -U datasets` and restarting the notebook.\r\n", "Kaggle removed the problematic `datasets==2.1.0` pin last week, so I'm closing this issue (now it pre-installs the latest version)." ]	2024-04-05T14:31:48	2024-04-11T17:18:53	2024-04-11T17:18:53	NONE	null	null	null	### Describe the bug # problem I can't resample audio dataset in Kaggle Notebook. It looks like some code in `datasets` library use aliases that were deprecated in NumPy 1.20. ## code for resampling ``` from datasets import load_dataset, Audio from transformers import AutoFeatureExtractor from transformers import AutoModelForAudioClassification, TrainingArguments, Trainer minds = load_dataset("PolyAI/minds14", name="en-US", split="train") feature_extractor = AutoFeatureExtractor.from_pretrained("facebook/wav2vec2-base") def preprocess_function(examples): audio_arrays = [x["array"] for x in examples["audio"]] inputs = feature_extractor( audio_arrays, sampling_rate=feature_extractor.sampling_rate, max_length=16000, truncation=True ) return inputs dataset = dataset.map(preprocess_function, remove_columns="audio", batched=True, batch_size=100) ``` ## the error I got <details> <summary>Click to expand</summary> ``` --------------------------------------------------------------------------- AttributeError Traceback (most recent call last) Cell In[20], line 1 ----> 1 dataset = dataset.map(preprocess_function, remove_columns="audio", batched=True, batch_size=100) 2 dataset File /opt/conda/lib/python3.10/site-packages/datasets/arrow_dataset.py:1955, in Dataset.map(self, function, with_indices, with_rank, input_columns, batched, batch_size, drop_last_batch, remove_columns, keep_in_memory, load_from_cache_file, cache_file_name, writer_batch_size, features, disable_nullable, fn_kwargs, num_proc, suffix_template, new_fingerprint, desc) 1952 disable_tqdm = not logging.is_progress_bar_enabled() 1954 if num_proc is None or num_proc == 1: -> 1955 return self._map_single( 1956 function=function, 1957 with_indices=with_indices, 1958 with_rank=with_rank, 1959 input_columns=input_columns, 1960 batched=batched, 1961 batch_size=batch_size, 1962 drop_last_batch=drop_last_batch, 1963 remove_columns=remove_columns, 1964 keep_in_memory=keep_in_memory, 1965 load_from_cache_file=load_from_cache_file, 1966 cache_file_name=cache_file_name, 1967 writer_batch_size=writer_batch_size, 1968 features=features, 1969 disable_nullable=disable_nullable, 1970 fn_kwargs=fn_kwargs, 1971 new_fingerprint=new_fingerprint, 1972 disable_tqdm=disable_tqdm, 1973 desc=desc, 1974 ) 1975 else: 1977 def format_cache_file_name(cache_file_name, rank): File /opt/conda/lib/python3.10/site-packages/datasets/arrow_dataset.py:520, in transmit_tasks.<locals>.wrapper(args, kwargs) 518 self: "Dataset" = kwargs.pop("self") 519 # apply actual function --> 520 out: Union["Dataset", "DatasetDict"] = func(self, args, *kwargs) 521 datasets: List["Dataset"] = list(out.values()) if isinstance(out, dict) else [out] 522 for dataset in datasets: 523 # Remove task templates if a column mapping of the template is no longer valid File /opt/conda/lib/python3.10/site-packages/datasets/arrow_dataset.py:487, in transmit_format.<locals>.wrapper(args, *kwargs) 480 self_format = { 481 "type": self._format_type, 482 "format_kwargs": self._format_kwargs, 483 "columns": self._format_columns, 484 "output_all_columns": self._output_all_columns, 485 } 486 # apply actual function --> 487 out: Union["Dataset", "DatasetDict"] = func(self, args, *kwargs) 488 datasets: List["Dataset"] = list(out.values()) if isinstance(out, dict) else [out] 489 # re-apply format to the output File /opt/conda/lib/python3.10/site-packages/datasets/fingerprint.py:458, in fingerprint_transform.<locals>._fingerprint.<locals>.wrapper(args, *kwargs) 452 kwargs[fingerprint_name] = update_fingerprint( 453 self._fingerprint, transform, kwargs_for_fingerprint 454 ) 456 # Call actual function --> 458 out = func(self, args, **kwargs) 460 # Update fingerprint of in-place transforms + update in-place history of transforms 462 if inplace: # update after calling func so that the fingerprint doesn't change if the function fails File /opt/conda/lib/python3.10/site-packages/datasets/arrow_dataset.py:2356, in Dataset._map_single(self, function, with_indices, with_rank, input_columns, batched, batch_size, drop_last_batch, remove_columns, keep_in_memory, load_from_cache_file, cache_file_name, writer_batch_size, features, disable_nullable, fn_kwargs, new_fingerprint, rank, offset, disable_tqdm, desc, cache_only) 2354 writer.write_table(batch) 2355 else: -> 2356 writer.write_batch(batch) 2357 if update_data and writer is not None: 2358 writer.finalize() # close_stream=bool(buf_writer is None)) # We only close if we are writing in a file File /opt/conda/lib/python3.10/site-packages/datasets/arrow_writer.py:507, in ArrowWriter.write_batch(self, batch_examples, writer_batch_size) 505 col_try_type = try_features[col] if try_features is not None and col in try_features else None 506 typed_sequence = OptimizedTypedSequence(batch_examples[col], type=col_type, try_type=col_try_type, col=col) --> 507 arrays.append(pa.array(typed_sequence)) 508 inferred_features[col] = typed_sequence.get_inferred_type() 509 schema = inferred_features.arrow_schema if self.pa_writer is None else self.schema File /opt/conda/lib/python3.10/site-packages/pyarrow/array.pxi:236, in pyarrow.lib.array() File /opt/conda/lib/python3.10/site-packages/pyarrow/array.pxi:110, in pyarrow.lib._handle_arrow_array_protocol() File /opt/conda/lib/python3.10/site-packages/datasets/arrow_writer.py:184, in TypedSequence.__arrow_array__(self, type) 182 out = numpy_to_pyarrow_listarray(data) 183 elif isinstance(data, list) and data and isinstance(first_non_null_value(data)[1], np.ndarray): --> 184 out = list_of_np_array_to_pyarrow_listarray(data) 185 else: 186 trying_cast_to_python_objects = True File /opt/conda/lib/python3.10/site-packages/datasets/features/features.py:1174, in list_of_np_array_to_pyarrow_listarray(l_arr, type) 1172 """Build a PyArrow ListArray from a possibly nested list of NumPy arrays""" 1173 if len(l_arr) > 0: -> 1174 return list_of_pa_arrays_to_pyarrow_listarray( 1175 [numpy_to_pyarrow_listarray(arr, type=type) if arr is not None else None for arr in l_arr] 1176 ) 1177 else: 1178 return pa.array([], type=type) File /opt/conda/lib/python3.10/site-packages/datasets/features/features.py:1163, in list_of_pa_arrays_to_pyarrow_listarray(l_arr) 1160 null_indices = [i for i, arr in enumerate(l_arr) if arr is None] 1161 l_arr = [arr for arr in l_arr if arr is not None] 1162 offsets = np.cumsum( -> 1163 [0] + [len(arr) for arr in l_arr], dtype=np.object 1164 ) # convert to dtype object to allow None insertion 1165 offsets = np.insert(offsets, null_indices, None) 1166 offsets = pa.array(offsets, type=pa.int32()) File /opt/conda/lib/python3.10/site-packages/numpy/__init__.py:324, in __getattr__(attr) 319 warnings.warn( 320 f"In the future `np.{attr}` will be defined as the " 321 "corresponding NumPy scalar.", FutureWarning, stacklevel=2) 323 if attr in __former_attrs__: --> 324 raise AttributeError(__former_attrs__[attr]) 326 if attr == 'testing': 327 import numpy.testing as testing AttributeError: module 'numpy' has no attribute 'object'. `np.object` was a deprecated alias for the builtin `object`. To avoid this error in existing code, use `object` by itself. Doing this will not modify any behavior and is safe. The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations ``` </details> ### Steps to reproduce the bug Run above code in Kaggle Notebook. ### Expected behavior I can resample audio data without fail. ### Environment info - `datasets` version: 2.1.0 - Platform: Linux-5.15.133+-x86_64-with-glibc2.31 - Python version: 3.10.13 - PyArrow version: 11.0.0 - Pandas version: 2.2.1	{ "login": "mariosasko", "id": 47462742, "node_id": "MDQ6VXNlcjQ3NDYyNzQy", "avatar_url": "https://avatars.githubusercontent.com/u/47462742?v=4", "gravatar_id": "", "url": "https://api.github.com/users/mariosasko", "html_url": "https://github.com/mariosasko", "followers_url": "https://api.github.com/users/mariosasko/followers", "following_url": "https://api.github.com/users/mariosasko/following{/other_user}", "gists_url": "https://api.github.com/users/mariosasko/gists{/gist_id}", "starred_url": "https://api.github.com/users/mariosasko/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/mariosasko/subscriptions", "organizations_url": "https://api.github.com/users/mariosasko/orgs", "repos_url": "https://api.github.com/users/mariosasko/repos", "events_url": "https://api.github.com/users/mariosasko/events{/privacy}", "received_events_url": "https://api.github.com/users/mariosasko/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6783/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6783/timeline	null	completed	false
https://api.github.com/repos/huggingface/datasets/issues/6782	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6782/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6782/comments	https://api.github.com/repos/huggingface/datasets/issues/6782/events	https://github.com/huggingface/datasets/issues/6782	2,228,081,955	I_kwDODunzps6EzdUj	6,782	Image cast_storage very slow for arrays (e.g. numpy, tensors)	{ "login": "Modexus", "id": 37351874, "node_id": "MDQ6VXNlcjM3MzUxODc0", "avatar_url": "https://avatars.githubusercontent.com/u/37351874?v=4", "gravatar_id": "", "url": "https://api.github.com/users/Modexus", "html_url": "https://github.com/Modexus", "followers_url": "https://api.github.com/users/Modexus/followers", "following_url": "https://api.github.com/users/Modexus/following{/other_user}", "gists_url": "https://api.github.com/users/Modexus/gists{/gist_id}", "starred_url": "https://api.github.com/users/Modexus/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/Modexus/subscriptions", "organizations_url": "https://api.github.com/users/Modexus/orgs", "repos_url": "https://api.github.com/users/Modexus/repos", "events_url": "https://api.github.com/users/Modexus/events{/privacy}", "received_events_url": "https://api.github.com/users/Modexus/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	open	false	null	[]	null	[ "This may be a solution that only changes `cast_storage` of `Image`.\r\nHowever, I'm not totally sure that the assumptions hold that are made about the `ListArray`.\r\n\r\n```python\r\nelif pa.types.is_list(storage.type):\r\n from .features import Array3DExtensionType\r\n\r\n def get_shapes(arr):\r\n shape = ()\r\n while isinstance(arr, pa.ListArray):\r\n len_curr = len(arr)\r\n arr = arr.flatten()\r\n len_new = len(arr)\r\n shape = shape + (len_new // len_curr,)\r\n return shape\r\n\r\n def get_dtypes(arr):\r\n dtype = storage.type\r\n while hasattr(dtype, \"value_type\"):\r\n dtype = dtype.value_type\r\n return dtype\r\n\r\n arrays = []\r\n for i, is_null in enumerate(storage.is_null()):\r\n if not is_null.as_py():\r\n storage_part = storage.take([i])\r\n shape = get_shapes(storage_part)\r\n dtype = get_dtypes(storage_part)\r\n\r\n extension_type = Array3DExtensionType(shape=shape, dtype=str(dtype))\r\n array = pa.ExtensionArray.from_storage(extension_type, storage_part)\r\n arrays.append(array.to_numpy().squeeze(0))\r\n else:\r\n arrays.append(None)\r\n\r\n bytes_array = pa.array(\r\n [encode_np_array(arr)[\"bytes\"] if arr is not None else None for arr in arrays],\r\n type=pa.binary(),\r\n )\r\n path_array = pa.array([None] * len(storage), type=pa.string())\r\n storage = pa.StructArray.from_arrays(\r\n [bytes_array, path_array], [\"bytes\", \"path\"], mask=bytes_array.is_null()\r\n )\r\n```\r\n(Edited): to handle nulls\r\n\r\nNotably this doesn't change anything about the passing through of data or other things, just in the `Image` class.\r\nSeems quite fast:\r\n```bash\r\nFri Apr 5 17:55:51 2024 restats\r\n\r\n 63818 function calls (61995 primitive calls) in 0.812 seconds\r\n\r\n Ordered by: cumulative time\r\n List reduced from 1051 to 20 due to restriction <20>\r\n\r\n ncalls tottime percall cumtime percall filename:lineno(function)\r\n 47/1 0.000 0.000 0.810 0.810 {built-in method builtins.exec}\r\n 2/1 0.000 0.000 0.810 0.810 <string>:1(<module>)\r\n 2/1 0.000 0.000 0.809 0.809 arrow_dataset.py:594(wrapper)\r\n 2/1 0.000 0.000 0.809 0.809 arrow_dataset.py:551(wrapper)\r\n 2/1 0.000 0.000 0.809 0.809 arrow_dataset.py:2916(map)\r\n 3 0.000 0.000 0.807 0.269 arrow_dataset.py:3277(_map_single)\r\n 1 0.000 0.000 0.760 0.760 arrow_writer.py:589(finalize)\r\n 1 0.000 0.000 0.760 0.760 arrow_writer.py:423(write_examples_on_file)\r\n 1 0.000 0.000 0.759 0.759 arrow_writer.py:527(write_batch)\r\n 1 0.001 0.001 0.754 0.754 arrow_writer.py:161(__arrow_array__)\r\n 2/1 0.000 0.000 0.719 0.719 table.py:1800(wrapper)\r\n 1 0.000 0.000 0.719 0.719 table.py:1950(cast_array_to_feature)\r\n 1 0.006 0.006 0.718 0.718 image.py:209(cast_storage)\r\n 1 0.000 0.000 0.451 0.451 image.py:361(encode_np_array)\r\n 1 0.000 0.000 0.444 0.444 image.py:343(image_to_bytes)\r\n 1 0.000 0.000 0.413 0.413 Image.py:2376(save)\r\n 1 0.000 0.000 0.413 0.413 PngImagePlugin.py:1233(_save)\r\n 1 0.000 0.000 0.413 0.413 ImageFile.py:517(_save)\r\n 1 0.000 0.000 0.413 0.413 ImageFile.py:545(_encode_tile)\r\n 397 0.409 0.001 0.409 0.001 {method 'encode' of 'ImagingEncoder' objects}\r\n```", "Also encounter this problem. Has been strugging with it for a long time...", "This actually applies to all arrays (numpy or tensors like in torch), not only from external files.\r\n```python\r\nimport numpy as np\r\nimport datasets\r\n\r\nds = datasets.Dataset.from_dict(\r\n {\"image\": [np.random.randint(0, 255, (2048, 2048, 3), dtype=np.uint8)]},\r\n features=datasets.Features({\"image\": datasets.Image(decode=True)}),\r\n)\r\nds.set_format(\"numpy\")\r\n\r\nds = ds.map(load_from_cache_file=False)\r\n```" ]	2024-04-05T13:46:54	2024-04-10T14:36:13	null	CONTRIBUTOR	null	null	null	Update: see comments below ### Describe the bug Operations that save an image from a path are very slow. I believe the reason for this is that the image data (`numpy`) is converted into `pyarrow` format but then back to python using `.pylist()` before being converted to a numpy array again. `pylist` is already slow but used on a multi-dimensional numpy array such as an image it takes a very long time. From the trace below we can see that `__arrow_array__` takes a long time. It is currently also called in `get_inferred_type`, this should be removable #6781 but doesn't change the underyling issue. The conversion to `pyarrow` and back also leads to the `numpy` array having type `int64` which causes a warning message because the image type excepts `uint8`. However, originally the `numpy` image array was in `uint8`. ### Steps to reproduce the bug ```python from PIL import Image import numpy as np import datasets import cProfile image = Image.fromarray(np.random.randint(0, 255, (2048, 2048, 3), dtype=np.uint8)) image.save("test_image.jpg") ds = datasets.Dataset.from_dict( {"image": ["test_image.jpg"]}, features=datasets.Features({"image": datasets.Image(decode=True)}), ) # load as numpy array, e.g. for further processing with map # same result as map returning numpy arrays ds.set_format("numpy") cProfile.run("ds.map(writer_batch_size=1, load_from_cache_file=False)", "restats") ``` ```bash Fri Apr 5 14:56:17 2024 restats 66817 function calls (64992 primitive calls) in 33.382 seconds Ordered by: cumulative time List reduced from 1073 to 20 due to restriction <20> ncalls tottime percall cumtime percall filename:lineno(function) 46/1 0.000 0.000 33.382 33.382 {built-in method builtins.exec} 1 0.000 0.000 33.382 33.382 <string>:1(<module>) 1 0.000 0.000 33.382 33.382 arrow_dataset.py:594(wrapper) 1 0.000 0.000 33.382 33.382 arrow_dataset.py:551(wrapper) 1 0.000 0.000 33.379 33.379 arrow_dataset.py:2916(map) 4 0.000 0.000 33.327 8.332 arrow_dataset.py:3277(_map_single) 1 0.000 0.000 33.311 33.311 arrow_writer.py:465(write) 2 0.000 0.000 33.311 16.656 arrow_writer.py:423(write_examples_on_file) 1 0.000 0.000 33.311 33.311 arrow_writer.py:527(write_batch) 2 14.484 7.242 33.260 16.630 arrow_writer.py:161(__arrow_array__) 1 0.001 0.001 16.438 16.438 arrow_writer.py:121(get_inferred_type) 1 0.000 0.000 14.398 14.398 threading.py:637(wait) 1 0.000 0.000 14.398 14.398 threading.py:323(wait) 8 14.398 1.800 14.398 1.800 {method 'acquire' of '_thread.lock' objects} 4/2 0.000 0.000 4.337 2.169 table.py:1800(wrapper) 2 0.000 0.000 4.337 2.169 table.py:1950(cast_array_to_feature) 2 0.475 0.238 4.337 2.169 image.py:209(cast_storage) 9 2.583 0.287 2.583 0.287 {built-in method numpy.array} 2 0.000 0.000 1.284 0.642 image.py:319(encode_np_array) 2 0.000 0.000 1.246 0.623 image.py:301(image_to_bytes) ``` ### Expected behavior The `numpy` image data should be passed through as it will be directly consumed by `pillow` to convert it to bytes. As an example one can replace `list_of_np_array_to_pyarrow_listarray(data)` in `__arrow_array__` with just `out = data` as a test. We have to change `cast_storage` of the `Image` feature so it handles the passed through data (& if to handle type before) ```python bytes_array = pa.array( [encode_np_array(arr)["bytes"] if arr is not None else None for arr in storage], type=pa.binary(), ) ``` Leading to the following: ```bash Fri Apr 5 15:44:27 2024 restats 66419 function calls (64595 primitive calls) in 0.937 seconds Ordered by: cumulative time List reduced from 1023 to 20 due to restriction <20> ncalls tottime percall cumtime percall filename:lineno(function) 47/1 0.000 0.000 0.935 0.935 {built-in method builtins.exec} 2/1 0.000 0.000 0.935 0.935 <string>:1(<module>) 2/1 0.000 0.000 0.934 0.934 arrow_dataset.py:594(wrapper) 2/1 0.000 0.000 0.934 0.934 arrow_dataset.py:551(wrapper) 2/1 0.000 0.000 0.934 0.934 arrow_dataset.py:2916(map) 4 0.000 0.000 0.933 0.233 arrow_dataset.py:3277(_map_single) 1 0.000 0.000 0.883 0.883 arrow_writer.py:466(write) 2 0.000 0.000 0.883 0.441 arrow_writer.py:424(write_examples_on_file) 1 0.000 0.000 0.882 0.882 arrow_writer.py:528(write_batch) 2 0.000 0.000 0.877 0.439 arrow_writer.py:161(__arrow_array__) 4/2 0.000 0.000 0.877 0.439 table.py:1800(wrapper) 2 0.000 0.000 0.877 0.439 table.py:1950(cast_array_to_feature) 2 0.009 0.005 0.877 0.439 image.py:209(cast_storage) 2 0.000 0.000 0.868 0.434 image.py:335(encode_np_array) 2 0.000 0.000 0.856 0.428 image.py:317(image_to_bytes) 2 0.000 0.000 0.822 0.411 Image.py:2376(save) 2 0.000 0.000 0.822 0.411 PngImagePlugin.py:1233(_save) 2 0.000 0.000 0.822 0.411 ImageFile.py:517(_save) 2 0.000 0.000 0.821 0.411 ImageFile.py:545(_encode_tile) 589 0.803 0.001 0.803 0.001 {method 'encode' of 'ImagingEncoder' objects} ``` This is of course only a test as it passes through all `numpy` arrays irrespective of if they should be an image. Also I guess `cast_storage` is meant for casting `pyarrow` storage exclusively. Converting to `pyarrow` array seems like a good solution as it also handles `pytorch` tensors etc., maybe there is a more efficient way to create a PIL image from a `pyarrow` array? Not sure how this should be handled but I would be happy to help if there is a good solution. ### Environment info - `datasets` version: 2.18.1.dev0 - Platform: Linux-6.7.11-200.fc39.x86_64-x86_64-with-glibc2.38 - Python version: 3.12.2 - `huggingface_hub` version: 0.22.2 - PyArrow version: 15.0.2 - Pandas version: 2.2.1 - `fsspec` version: 2024.3.1	null	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6782/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6782/timeline	null	null	false
https://api.github.com/repos/huggingface/datasets/issues/6781	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6781/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6781/comments	https://api.github.com/repos/huggingface/datasets/issues/6781/events	https://github.com/huggingface/datasets/pull/6781	2,228,026,497	PR_kwDODunzps5r2DMe	6,781	Remove get_inferred_type from ArrowWriter write_batch	{ "login": "Modexus", "id": 37351874, "node_id": "MDQ6VXNlcjM3MzUxODc0", "avatar_url": "https://avatars.githubusercontent.com/u/37351874?v=4", "gravatar_id": "", "url": "https://api.github.com/users/Modexus", "html_url": "https://github.com/Modexus", "followers_url": "https://api.github.com/users/Modexus/followers", "following_url": "https://api.github.com/users/Modexus/following{/other_user}", "gists_url": "https://api.github.com/users/Modexus/gists{/gist_id}", "starred_url": "https://api.github.com/users/Modexus/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/Modexus/subscriptions", "organizations_url": "https://api.github.com/users/Modexus/orgs", "repos_url": "https://api.github.com/users/Modexus/repos", "events_url": "https://api.github.com/users/Modexus/events{/privacy}", "received_events_url": "https://api.github.com/users/Modexus/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	null	[]	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6781). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "Close in favor of #6786." ]	2024-04-05T13:21:05	2024-04-09T07:49:11	2024-04-09T07:49:11	CONTRIBUTOR	null	false	{ "url": "https://api.github.com/repos/huggingface/datasets/pulls/6781", "html_url": "https://github.com/huggingface/datasets/pull/6781", "diff_url": "https://github.com/huggingface/datasets/pull/6781.diff", "patch_url": "https://github.com/huggingface/datasets/pull/6781.patch", "merged_at": null }	Inferring the type seems to be unnecessary given that the pyarrow array has already been created. Because pyarrow array creation is sometimes extremely slow this doubles the time write_batch takes.	{ "login": "Modexus", "id": 37351874, "node_id": "MDQ6VXNlcjM3MzUxODc0", "avatar_url": "https://avatars.githubusercontent.com/u/37351874?v=4", "gravatar_id": "", "url": "https://api.github.com/users/Modexus", "html_url": "https://github.com/Modexus", "followers_url": "https://api.github.com/users/Modexus/followers", "following_url": "https://api.github.com/users/Modexus/following{/other_user}", "gists_url": "https://api.github.com/users/Modexus/gists{/gist_id}", "starred_url": "https://api.github.com/users/Modexus/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/Modexus/subscriptions", "organizations_url": "https://api.github.com/users/Modexus/orgs", "repos_url": "https://api.github.com/users/Modexus/repos", "events_url": "https://api.github.com/users/Modexus/events{/privacy}", "received_events_url": "https://api.github.com/users/Modexus/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6781/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6781/timeline	null	null	true
https://api.github.com/repos/huggingface/datasets/issues/6780	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6780/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6780/comments	https://api.github.com/repos/huggingface/datasets/issues/6780/events	https://github.com/huggingface/datasets/pull/6780	2,226,160,096	PR_kwDODunzps5rvkyj	6,780	Fix CI	{ "login": "mariosasko", "id": 47462742, "node_id": "MDQ6VXNlcjQ3NDYyNzQy", "avatar_url": "https://avatars.githubusercontent.com/u/47462742?v=4", "gravatar_id": "", "url": "https://api.github.com/users/mariosasko", "html_url": "https://github.com/mariosasko", "followers_url": "https://api.github.com/users/mariosasko/followers", "following_url": "https://api.github.com/users/mariosasko/following{/other_user}", "gists_url": "https://api.github.com/users/mariosasko/gists{/gist_id}", "starred_url": "https://api.github.com/users/mariosasko/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/mariosasko/subscriptions", "organizations_url": "https://api.github.com/users/mariosasko/orgs", "repos_url": "https://api.github.com/users/mariosasko/repos", "events_url": "https://api.github.com/users/mariosasko/events{/privacy}", "received_events_url": "https://api.github.com/users/mariosasko/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	null	[]	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6780). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005074 / 0.011353 (-0.006279) \| 0.003395 / 0.011008 (-0.007614) \| 0.062358 / 0.038508 (0.023849) \| 0.031041 / 0.023109 (0.007932) \| 0.244039 / 0.275898 (-0.031859) \| 0.266361 / 0.323480 (-0.057119) \| 0.003201 / 0.007986 (-0.004785) \| 0.002609 / 0.004328 (-0.001719) \| 0.049269 / 0.004250 (0.045018) \| 0.045713 / 0.037052 (0.008661) \| 0.264075 / 0.258489 (0.005586) \| 0.295428 / 0.293841 (0.001587) \| 0.027882 / 0.128546 (-0.100664) \| 0.010424 / 0.075646 (-0.065222) \| 0.208417 / 0.419271 (-0.210854) \| 0.035728 / 0.043533 (-0.007805) \| 0.246803 / 0.255139 (-0.008336) \| 0.267169 / 0.283200 (-0.016031) \| 0.019797 / 0.141683 (-0.121885) \| 1.163299 / 1.452155 (-0.288856) \| 1.196118 / 1.492716 (-0.296599) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.106091 / 0.018006 (0.088085) \| 0.303970 / 0.000490 (0.303480) \| 0.000219 / 0.000200 (0.000019) \| 0.000042 / 0.000054 (-0.000012) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.017955 / 0.037411 (-0.019456) \| 0.060539 / 0.014526 (0.046013) \| 0.072884 / 0.176557 (-0.103673) \| 0.119205 / 0.737135 (-0.617931) \| 0.074072 / 0.296338 (-0.222266) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.272676 / 0.215209 (0.057467) \| 2.715169 / 2.077655 (0.637514) \| 1.419090 / 1.504120 (-0.085030) \| 1.303903 / 1.541195 (-0.237292) \| 1.311903 / 1.468490 (-0.156587) \| 0.562005 / 4.584777 (-4.022772) \| 2.432817 / 3.745712 (-1.312896) \| 2.770599 / 5.269862 (-2.499263) \| 1.723043 / 4.565676 (-2.842633) \| 0.064341 / 0.424275 (-0.359934) \| 0.004923 / 0.007607 (-0.002684) \| 0.330507 / 0.226044 (0.104463) \| 3.240829 / 2.268929 (0.971901) \| 1.787638 / 55.444624 (-53.656986) \| 1.522971 / 6.876477 (-5.353506) \| 1.529496 / 2.142072 (-0.612576) \| 0.645768 / 4.805227 (-4.159459) \| 0.116405 / 6.500664 (-6.384259) \| 0.041524 / 0.075469 (-0.033945) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.968515 / 1.841788 (-0.873272) \| 11.628911 / 8.074308 (3.554603) \| 9.495023 / 10.191392 (-0.696369) \| 0.142219 / 0.680424 (-0.538204) \| 0.013859 / 0.534201 (-0.520342) \| 0.285727 / 0.579283 (-0.293556) \| 0.276842 / 0.434364 (-0.157522) \| 0.321247 / 0.540337 (-0.219090) \| 0.409958 / 1.386936 (-0.976978) \|\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005102 / 0.011353 (-0.006251) \| 0.003213 / 0.011008 (-0.007796) \| 0.049250 / 0.038508 (0.010742) \| 0.030649 / 0.023109 (0.007540) \| 0.276629 / 0.275898 (0.000731) \| 0.297315 / 0.323480 (-0.026165) \| 0.004198 / 0.007986 (-0.003787) \| 0.002744 / 0.004328 (-0.001585) \| 0.047899 / 0.004250 (0.043649) \| 0.040596 / 0.037052 (0.003544) \| 0.287248 / 0.258489 (0.028759) \| 0.313573 / 0.293841 (0.019732) \| 0.029067 / 0.128546 (-0.099480) \| 0.010122 / 0.075646 (-0.065524) \| 0.058869 / 0.419271 (-0.360402) \| 0.033012 / 0.043533 (-0.010521) \| 0.272995 / 0.255139 (0.017856) \| 0.297102 / 0.283200 (0.013903) \| 0.018209 / 0.141683 (-0.123474) \| 1.157785 / 1.452155 (-0.294369) \| 1.184999 / 1.492716 (-0.307717) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.094228 / 0.018006 (0.076221) \| 0.302055 / 0.000490 (0.301565) \| 0.000221 / 0.000200 (0.000021) \| 0.000044 / 0.000054 (-0.000010) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.022020 / 0.037411 (-0.015391) \| 0.074970 / 0.014526 (0.060444) \| 0.087682 / 0.176557 (-0.088875) \| 0.126506 / 0.737135 (-0.610629) \| 0.092046 / 0.296338 (-0.204293) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.295634 / 0.215209 (0.080425) \| 2.891554 / 2.077655 (0.813899) \| 1.579963 / 1.504120 (0.075843) \| 1.462924 / 1.541195 (-0.078271) \| 1.463806 / 1.468490 (-0.004684) \| 0.558371 / 4.584777 (-4.026406) \| 2.513500 / 3.745712 (-1.232212) \| 2.754146 / 5.269862 (-2.515716) \| 1.762317 / 4.565676 (-2.803360) \| 0.063965 / 0.424275 (-0.360310) \| 0.005538 / 0.007607 (-0.002069) \| 0.348114 / 0.226044 (0.122070) \| 3.484558 / 2.268929 (1.215630) \| 1.940002 / 55.444624 (-53.504623) \| 1.658469 / 6.876477 (-5.218008) \| 1.645777 / 2.142072 (-0.496295) \| 0.639367 / 4.805227 (-4.165861) \| 0.115605 / 6.500664 (-6.385059) \| 0.040647 / 0.075469 (-0.034822) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 1.036002 / 1.841788 (-0.805786) \| 12.286895 / 8.074308 (4.212587) \| 10.146719 / 10.191392 (-0.044673) \| 0.140867 / 0.680424 (-0.539557) \| 0.015517 / 0.534201 (-0.518684) \| 0.290126 / 0.579283 (-0.289157) \| 0.298702 / 0.434364 (-0.135662) \| 0.325518 / 0.540337 (-0.214819) \| 0.412597 / 1.386936 (-0.974339) \|\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#c3ddb1ef00334a6f973679a51e783905fbc9ef0b \"CML watermark\")\n" ]	2024-04-04T17:45:04	2024-04-04T18:46:04	2024-04-04T18:23:34	COLLABORATOR	null	false	{ "url": "https://api.github.com/repos/huggingface/datasets/pulls/6780", "html_url": "https://github.com/huggingface/datasets/pull/6780", "diff_url": "https://github.com/huggingface/datasets/pull/6780.diff", "patch_url": "https://github.com/huggingface/datasets/pull/6780.patch", "merged_at": "2024-04-04T18:23:34" }	Updates the `wmt_t2t` test to pin the `revision` to the version with a loading script (cc @albertvillanova). Additionally, it replaces the occurrences of the `lhoestq/test` repo id with `hf-internal-testing/dataset_with_script` and re-enables logging checks in the `Dataset.from_sql` tests.	{ "login": "mariosasko", "id": 47462742, "node_id": "MDQ6VXNlcjQ3NDYyNzQy", "avatar_url": "https://avatars.githubusercontent.com/u/47462742?v=4", "gravatar_id": "", "url": "https://api.github.com/users/mariosasko", "html_url": "https://github.com/mariosasko", "followers_url": "https://api.github.com/users/mariosasko/followers", "following_url": "https://api.github.com/users/mariosasko/following{/other_user}", "gists_url": "https://api.github.com/users/mariosasko/gists{/gist_id}", "starred_url": "https://api.github.com/users/mariosasko/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/mariosasko/subscriptions", "organizations_url": "https://api.github.com/users/mariosasko/orgs", "repos_url": "https://api.github.com/users/mariosasko/repos", "events_url": "https://api.github.com/users/mariosasko/events{/privacy}", "received_events_url": "https://api.github.com/users/mariosasko/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6780/reactions", "total_count": 1, "+1": 1, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6780/timeline	null	null	true
https://api.github.com/repos/huggingface/datasets/issues/6779	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6779/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6779/comments	https://api.github.com/repos/huggingface/datasets/issues/6779/events	https://github.com/huggingface/datasets/pull/6779	2,226,075,551	PR_kwDODunzps5rvSA8	6,779	Install dependencies with `uv` in CI	{ "login": "mariosasko", "id": 47462742, "node_id": "MDQ6VXNlcjQ3NDYyNzQy", "avatar_url": "https://avatars.githubusercontent.com/u/47462742?v=4", "gravatar_id": "", "url": "https://api.github.com/users/mariosasko", "html_url": "https://github.com/mariosasko", "followers_url": "https://api.github.com/users/mariosasko/followers", "following_url": "https://api.github.com/users/mariosasko/following{/other_user}", "gists_url": "https://api.github.com/users/mariosasko/gists{/gist_id}", "starred_url": "https://api.github.com/users/mariosasko/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/mariosasko/subscriptions", "organizations_url": "https://api.github.com/users/mariosasko/orgs", "repos_url": "https://api.github.com/users/mariosasko/repos", "events_url": "https://api.github.com/users/mariosasko/events{/privacy}", "received_events_url": "https://api.github.com/users/mariosasko/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	closed	false	null	[]	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6779). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005336 / 0.011353 (-0.006017) \| 0.004052 / 0.011008 (-0.006956) \| 0.063475 / 0.038508 (0.024967) \| 0.032963 / 0.023109 (0.009854) \| 0.243906 / 0.275898 (-0.031992) \| 0.269048 / 0.323480 (-0.054432) \| 0.003363 / 0.007986 (-0.004622) \| 0.002802 / 0.004328 (-0.001527) \| 0.049487 / 0.004250 (0.045236) \| 0.046990 / 0.037052 (0.009938) \| 0.260169 / 0.258489 (0.001680) \| 0.289145 / 0.293841 (-0.004696) \| 0.028030 / 0.128546 (-0.100517) \| 0.010706 / 0.075646 (-0.064940) \| 0.213640 / 0.419271 (-0.205632) \| 0.035866 / 0.043533 (-0.007667) \| 0.245106 / 0.255139 (-0.010033) \| 0.269588 / 0.283200 (-0.013612) \| 0.019791 / 0.141683 (-0.121892) \| 1.117684 / 1.452155 (-0.334470) \| 1.183389 / 1.492716 (-0.309327) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.095736 / 0.018006 (0.077730) \| 0.302586 / 0.000490 (0.302097) \| 0.000220 / 0.000200 (0.000020) \| 0.000051 / 0.000054 (-0.000003) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.018985 / 0.037411 (-0.018426) \| 0.062097 / 0.014526 (0.047571) \| 0.075617 / 0.176557 (-0.100939) \| 0.120570 / 0.737135 (-0.616566) \| 0.075949 / 0.296338 (-0.220390) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.279597 / 0.215209 (0.064388) \| 2.754319 / 2.077655 (0.676665) \| 1.444147 / 1.504120 (-0.059973) \| 1.328414 / 1.541195 (-0.212781) \| 1.371073 / 1.468490 (-0.097417) \| 0.553851 / 4.584777 (-4.030926) \| 2.351694 / 3.745712 (-1.394018) \| 2.860771 / 5.269862 (-2.409091) \| 1.749664 / 4.565676 (-2.816013) \| 0.061736 / 0.424275 (-0.362539) \| 0.005073 / 0.007607 (-0.002534) \| 0.329974 / 0.226044 (0.103930) \| 3.300487 / 2.268929 (1.031558) \| 1.812809 / 55.444624 (-53.631815) \| 1.559018 / 6.876477 (-5.317458) \| 1.628664 / 2.142072 (-0.513408) \| 0.635757 / 4.805227 (-4.169471) \| 0.116468 / 6.500664 (-6.384196) \| 0.042641 / 0.075469 (-0.032828) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.972048 / 1.841788 (-0.869740) \| 11.952721 / 8.074308 (3.878412) \| 9.754274 / 10.191392 (-0.437118) \| 0.132026 / 0.680424 (-0.548398) \| 0.015352 / 0.534201 (-0.518849) \| 0.290574 / 0.579283 (-0.288709) \| 0.275384 / 0.434364 (-0.158980) \| 0.330688 / 0.540337 (-0.209650) \| 0.414868 / 1.386936 (-0.972068) \|\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005412 / 0.011353 (-0.005941) \| 0.003814 / 0.011008 (-0.007194) \| 0.049988 / 0.038508 (0.011480) \| 0.031617 / 0.023109 (0.008507) \| 0.278975 / 0.275898 (0.003077) \| 0.303540 / 0.323480 (-0.019940) \| 0.004265 / 0.007986 (-0.003721) \| 0.002804 / 0.004328 (-0.001525) \| 0.049518 / 0.004250 (0.045268) \| 0.041176 / 0.037052 (0.004123) \| 0.291248 / 0.258489 (0.032759) \| 0.317401 / 0.293841 (0.023560) \| 0.029501 / 0.128546 (-0.099045) \| 0.010392 / 0.075646 (-0.065255) \| 0.057906 / 0.419271 (-0.361365) \| 0.033056 / 0.043533 (-0.010477) \| 0.280202 / 0.255139 (0.025063) \| 0.298684 / 0.283200 (0.015484) \| 0.018071 / 0.141683 (-0.123612) \| 1.167691 / 1.452155 (-0.284464) \| 1.211322 / 1.492716 (-0.281394) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.092325 / 0.018006 (0.074318) \| 0.301209 / 0.000490 (0.300719) \| 0.000221 / 0.000200 (0.000021) \| 0.000043 / 0.000054 (-0.000011) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.021432 / 0.037411 (-0.015980) \| 0.074556 / 0.014526 (0.060031) \| 0.086049 / 0.176557 (-0.090508) \| 0.125151 / 0.737135 (-0.611984) \| 0.088279 / 0.296338 (-0.208059) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.296755 / 0.215209 (0.081546) \| 2.922650 / 2.077655 (0.844995) \| 1.606031 / 1.504120 (0.101911) \| 1.489692 / 1.541195 (-0.051502) \| 1.530206 / 1.468490 (0.061716) \| 0.577827 / 4.584777 (-4.006950) \| 2.459716 / 3.745712 (-1.285997) \| 2.825192 / 5.269862 (-2.444669) \| 1.788110 / 4.565676 (-2.777566) \| 0.064011 / 0.424275 (-0.360264) \| 0.005616 / 0.007607 (-0.001991) \| 0.341612 / 0.226044 (0.115568) \| 3.455123 / 2.268929 (1.186194) \| 1.961635 / 55.444624 (-53.482990) \| 1.688107 / 6.876477 (-5.188370) \| 1.725490 / 2.142072 (-0.416583) \| 0.656011 / 4.805227 (-4.149216) \| 0.117633 / 6.500664 (-6.383031) \| 0.041386 / 0.075469 (-0.034083) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 1.025786 / 1.841788 (-0.816002) \| 12.294598 / 8.074308 (4.220290) \| 10.241136 / 10.191392 (0.049744) \| 0.130577 / 0.680424 (-0.549847) \| 0.016094 / 0.534201 (-0.518107) \| 0.291193 / 0.579283 (-0.288090) \| 0.273016 / 0.434364 (-0.161348) \| 0.327553 / 0.540337 (-0.212784) \| 0.418556 / 1.386936 (-0.968380) \|\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#3575036af2fd5cccff7fa60de30e2e444cf8a54e \"CML watermark\")\n" ]	2024-04-04T17:02:51	2024-04-08T13:34:01	2024-04-08T13:27:44	COLLABORATOR	null	false	{ "url": "https://api.github.com/repos/huggingface/datasets/pulls/6779", "html_url": "https://github.com/huggingface/datasets/pull/6779", "diff_url": "https://github.com/huggingface/datasets/pull/6779.diff", "patch_url": "https://github.com/huggingface/datasets/pull/6779.patch", "merged_at": "2024-04-08T13:27:43" }	`diffusers` (https://github.com/huggingface/diffusers/pull/7116) and `huggingface_hub` (https://github.com/huggingface/huggingface_hub/pull/2072) also use `uv` to install their dependencies, so we can do the same here. It seems to make the "Install dependencies" step in the `ubuntu` jobs 5-8x faster and 1.5-2x in the `windows` one. Besides introducing `uv` in CI, this PR bumps the `tensorflow` minimal version requirement to align with Transformers and simplifies the SpaCy hashing tests (use blank language models instead of the pre-trained ones)	{ "login": "mariosasko", "id": 47462742, "node_id": "MDQ6VXNlcjQ3NDYyNzQy", "avatar_url": "https://avatars.githubusercontent.com/u/47462742?v=4", "gravatar_id": "", "url": "https://api.github.com/users/mariosasko", "html_url": "https://github.com/mariosasko", "followers_url": "https://api.github.com/users/mariosasko/followers", "following_url": "https://api.github.com/users/mariosasko/following{/other_user}", "gists_url": "https://api.github.com/users/mariosasko/gists{/gist_id}", "starred_url": "https://api.github.com/users/mariosasko/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/mariosasko/subscriptions", "organizations_url": "https://api.github.com/users/mariosasko/orgs", "repos_url": "https://api.github.com/users/mariosasko/repos", "events_url": "https://api.github.com/users/mariosasko/events{/privacy}", "received_events_url": "https://api.github.com/users/mariosasko/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6779/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6779/timeline	null	null	true
https://api.github.com/repos/huggingface/datasets/issues/6778	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6778/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6778/comments	https://api.github.com/repos/huggingface/datasets/issues/6778/events	https://github.com/huggingface/datasets/issues/6778	2,226,040,636	I_kwDODunzps6Erq88	6,778	Dataset.to_csv() missing commas in columns with lists	{ "login": "mpickard-dataprof", "id": 100041276, "node_id": "U_kgDOBfaCPA", "avatar_url": "https://avatars.githubusercontent.com/u/100041276?v=4", "gravatar_id": "", "url": "https://api.github.com/users/mpickard-dataprof", "html_url": "https://github.com/mpickard-dataprof", "followers_url": "https://api.github.com/users/mpickard-dataprof/followers", "following_url": "https://api.github.com/users/mpickard-dataprof/following{/other_user}", "gists_url": "https://api.github.com/users/mpickard-dataprof/gists{/gist_id}", "starred_url": "https://api.github.com/users/mpickard-dataprof/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/mpickard-dataprof/subscriptions", "organizations_url": "https://api.github.com/users/mpickard-dataprof/orgs", "repos_url": "https://api.github.com/users/mpickard-dataprof/repos", "events_url": "https://api.github.com/users/mpickard-dataprof/events{/privacy}", "received_events_url": "https://api.github.com/users/mpickard-dataprof/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	open	false	null	[]	null	[ "Hello!\r\n\r\nThis is due to how pandas write numpy arrays to csv. [Source](https://stackoverflow.com/questions/54753179/to-csv-saves-np-array-as-string-instead-of-as-a-list)\r\nTo fix this, you can convert them to list yourselves.\r\n\r\n```python\r\ndf = ds.to_pandas()\r\ndf['int'] = df['int'].apply(lambda arr: list(arr))\r\ndf.to_csv(index=False, '../output/temp.csv')\r\n```\r\n\r\nI think it would be good if `datasets` would do the conversion itself, but it's a breaking change and I would wait for the greenlight from someone from HF." ]	2024-04-04T16:46:13	2024-04-08T15:24:41	null	NONE	null	null	null	### Describe the bug The `to_csv()` method does not output commas in lists. So when the Dataset is loaded back in the data structure of the column with a list is not correct. Here's an example: Obviously, it's not as trivial as inserting commas in the list, since its a comma-separated file. But hopefully there's a way to export the list in a way that it'll be imported by `load_dataset()` correctly. ### Steps to reproduce the bug Here's some code to reproduce the bug: ```python from datasets import Dataset ds = Dataset.from_dict( { "pokemon": ["bulbasaur", "squirtle"], "type": ["grass", "water"] } ) def ascii_to_hex(text): return [ord(c) for c in text] ds = ds.map(lambda x: {"int": ascii_to_hex(x['pokemon'])}) ds.to_csv('../output/temp.csv') ``` temp.csv then contains: ``` ### Expected behavior ACTUAL OUTPUT: ``` pokemon,type,int bulbasaur,grass,[ 98 117 108 98 97 115 97 117 114] squirtle,water,[115 113 117 105 114 116 108 101] ``` EXPECTED OUTPUT: ``` pokemon,type,int bulbasaur,grass,[98, 117, 108, 98, 97, 115, 97, 117, 114] squirtle,water,[115, 113, 117, 105, 114, 116, 108, 101] ``` or probably something more like this since it's a CSV file: ``` pokemon,type,int bulbasaur,grass,"[98, 117, 108, 98, 97, 115, 97, 117, 114]" squirtle,water,"[115, 113, 117, 105, 114, 116, 108, 101]" ``` ### Environment info ### Package Version Name: datasets Version: 2.16.1 ### Python version: 3.10.12 ### OS Info PRETTY_NAME="Ubuntu 22.04.4 LTS" NAME="Ubuntu" VERSION_ID="22.04" VERSION="22.04.4 LTS (Jammy Jellyfish)" VERSION_CODENAME=jammy ID=ubuntu ID_LIKE=debian ... UBUNTU_CODENAME=jammy	null	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6778/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6778/timeline	null	null	false
https://api.github.com/repos/huggingface/datasets/issues/6777	https://api.github.com/repos/huggingface/datasets	https://api.github.com/repos/huggingface/datasets/issues/6777/labels{/name}	https://api.github.com/repos/huggingface/datasets/issues/6777/comments	https://api.github.com/repos/huggingface/datasets/issues/6777/events	https://github.com/huggingface/datasets/issues/6777	2,224,611,247	I_kwDODunzps6EmN-v	6,777	.Jsonl metadata not detected	{ "login": "nighting0le01", "id": 81643693, "node_id": "MDQ6VXNlcjgxNjQzNjkz", "avatar_url": "https://avatars.githubusercontent.com/u/81643693?v=4", "gravatar_id": "", "url": "https://api.github.com/users/nighting0le01", "html_url": "https://github.com/nighting0le01", "followers_url": "https://api.github.com/users/nighting0le01/followers", "following_url": "https://api.github.com/users/nighting0le01/following{/other_user}", "gists_url": "https://api.github.com/users/nighting0le01/gists{/gist_id}", "starred_url": "https://api.github.com/users/nighting0le01/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/nighting0le01/subscriptions", "organizations_url": "https://api.github.com/users/nighting0le01/orgs", "repos_url": "https://api.github.com/users/nighting0le01/repos", "events_url": "https://api.github.com/users/nighting0le01/events{/privacy}", "received_events_url": "https://api.github.com/users/nighting0le01/received_events", "type": "User", "user_view_type": "public", "site_admin": false }	[]	open	false	null	[]	null	[ "Hi! `metadata.jsonl` (or `metadata.csv`) is the only allowed name for the `imagefolder`'s metadata files.", "@mariosasko hey i tried with metadata.jsonl also and it still doesn't get the right columns", "@mariosasko it says metadata.csv not found\r\n<img width=\"1150\" alt=\"image\" src=\"https://github.com/huggingface/datasets/assets/81643693/3754980c-6185-4413-88fa-b499bcdd4195\">\r\n\r\ndataset = load_dataset('/dataset',metadata.csv) \r\n\r\n\| workspace\r\n\|\| source code\r\n\| dataset\r\n\| \|-- images\r\n\| \|-- metadata.csv\r\n\| \|-- metadata.jsonl\r\n\| \|-- padded_images\r\n\r\nExample of metadata.jsonl file\r\n{\"caption\": \"a drawing depicts a full shot of a black t-shirt with a triangular pattern on the front there is a white label on the left side of the triangle\", \"image\": \"images/212734.png\", \"gaussian_padded_image\": \"padded_images/p_212734.png\"}\r\n{\"caption\": \"an eye-level full shot of a large elephant and a baby elephant standing in a watering hole on the left side is a small elephant with its head turned to the right of dry land, trees, and bushes\", \"image\": \"images/212735.png\", \"gaussian_padded_image\": \"padded_images/p_212735.png\"}\r\n", "Loading more than one image per row with `imagefolder` is not supported currently. You can subscribe to https://github.com/huggingface/datasets/issues/5760 to see when it will be.\r\n\r\nInstead, you can load the dataset with `Dataset.from_generator`:\r\n```python\r\nimport json\r\nfrom datasets import Dataset, Value, Image, Features\r\n\r\ndef gen():\r\n with open(\"./dataset/metadata.jsonl\") as f:\r\n for line in f:\r\n line = json.loads(line)\r\n yield {\"caption\": line[\"caption\"], \"image\": os.path.join(\"./dataset\", line[\"image\"], \"gaussian_padded_image\": os.path.join(\"./dataset\", line[\"gaussian_padded_image\"]))}\r\n\r\nfeatures = Features({\"caption\": Value(\"string\"), \"image\": Image(), \"gaussian_padded_image\": Image()})\r\ndataset = Dataset.from_generator(gen, features=features)\r\n```\r\n(E.g., if you want to share this dataset on the Hub, you can call `dataset.push_to_hub(...)` afterward)", "hi Thanks for sharing this, Actually I was trying with a webdataset format of the data as well and it did'nt work. Could you share how i can create Dataset object from webdataset format of this data?" ]	2024-04-04T06:31:53	2024-04-05T21:14:48	null	NONE	null	null	null	### Describe the bug Hi I have the following directory structure: \|--dataset \| \|-- images \| \|-- metadata1000.csv \| \|-- metadata1000.jsonl \| \|-- padded_images Example of metadata1000.jsonl file {"caption": "a drawing depicts a full shot of a black t-shirt with a triangular pattern on the front there is a white label on the left side of the triangle", "image": "images/212734.png", "gaussian_padded_image": "padded_images/p_212734.png"} {"caption": "an eye-level full shot of a large elephant and a baby elephant standing in a watering hole on the left side is a small elephant with its head turned to the right of dry land, trees, and bushes", "image": "images/212735.png", "gaussian_padded_image": "padded_images/p_212735.png"} . . . I'm trying to use dataset = load_dataset("imagefolder", data_dir='/dataset/', split='train') to load the the dataset, however it is not able to load according to the fields in the metadata1000.jsonl . please assist to load the data properly also getting ``` File "/workspace/train_trans_vae.py", line 1089, in <module> print(get_metadata_patterns('/dataset/')) File "/opt/conda/lib/python3.10/site-packages/datasets/data_files.py", line 499, in get_metadata_patterns raise FileNotFoundError(f"The directory at {base_path} doesn't contain any metadata file") from None FileNotFoundError: The directory at /dataset/ doesn't contain any metadata file ``` when trying ``` from datasets.data_files import get_metadata_patterns print(get_metadata_patterns('/dataset/')) ``` ### Steps to reproduce the bug dataset Version: 2.18.0 make a similar jsonl and similar directory format ### Expected behavior creates a dataset object with the column names, caption,image,gaussian_padded_image ### Environment info dataset Version: 2.18.0	null	{ "url": "https://api.github.com/repos/huggingface/datasets/issues/6777/reactions", "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 }	https://api.github.com/repos/huggingface/datasets/issues/6777/timeline	null	null	false