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{ "login": "lucasjinreal", "id": 21303438, "node_id": "MDQ6VXNlcjIxMzAzNDM4", "avatar_url": "https://avatars.githubusercontent.com/u/21303438?v=4", "gravatar_id": "", "url": "https://api.github.com/users/lucasjinreal", "html_url": "https://github.com/lucasjinreal", "followers_url": "https://api.github.com/users/lucasjinreal/followers", "following_url": "https://api.github.com/users/lucasjinreal/following{/other_user}", "gists_url": "https://api.github.com/users/lucasjinreal/gists{/gist_id}", "starred_url": "https://api.github.com/users/lucasjinreal/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/lucasjinreal/subscriptions", "organizations_url": "https://api.github.com/users/lucasjinreal/orgs", "repos_url": "https://api.github.com/users/lucasjinreal/repos", "events_url": "https://api.github.com/users/lucasjinreal/events{/privacy}", "received_events_url": "https://api.github.com/users/lucasjinreal/received_events", "type": "User", "user_view_type": "public", "site_admin": false }

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[ "Hello,\r\n\r\nHave you tried loading the dataset in streaming mode? [Documentation](https://huggingface.co/docs/datasets/v2.20.0/stream)\r\n\r\nThis way you wouldn't have to load it all. Also, let's be nice to Parquet, it's a really nice technology and we don't need to be mean :)", "I have downloaded part of it, just want to know how to load part of it, stream mode is not work for me since my network (in china) not stable, I don't want do it all again and again.\r\n\r\nJust curious, doesn't there a way to load part of it?", "Could you convert the IterableDataset to a Dataset after taking the first 100 rows with `.take`? This way, you would have a local copy of the first 100 rows on your system and thus won't need to download. Would that work?\r\n\r\nHere is a [SO question](https://stackoverflow.com/questions/76227219/can-i-convert-an-iterabledataset-to-dataset) detailing how to do the conversion.", "I mean, the parquet is like:\r\n\r\n00000-0143554\r\n00001-0143554\r\n00002-0143554\r\n...\r\n00100-0143554\r\n...\r\n09100-0143554\r\n\r\nI just downloaded the first 9900 part of it. \r\n\r\nI can not load with load_dataset, it throw an error says my file is not same as parquet all amount.\r\n\r\nHow could I load the only I have? \r\n\r\n( I really don't want downlaod them all, cause, I don't need all, and pulus, its huge.... )\r\n\r\nAs I said, I have donwloaded about 9999... It's not about stream... I just wnat to konw how to load offline... part....", "Hi, @lucasjinreal.\r\n\r\nI am not sure of understanding your issue. What is the error message and stack trace you get? What version of `datasets` are you using? Could you provide a reproducible example?\r\n\r\nWithout knowing all those details, I would naively say that you can load whatever number of Parquet files by using the \"parquet\" loader: https://huggingface.co/docs/datasets/loading#parquet\r\n```python\r\nds = load_dataset(\"parquet\", data_files=\"data/train-001*-of-00314.parquet\", split=\"train\")\r\n```", "@albertvillanova Not sure you have tested with this or not, but I have tried,\r\n\r\nthe only error I got is it still laodding all parquet with a progress bar maxium to the whole number 014354, and it loads my 0 - 000999 part, then throws an error.\r\n\r\nSays Numinfo is not same.\r\n\r\nI am so confused,", "Yes, my code snippet works.\n\nCould you copy-paste your code and the output? Otherwise we are not able to know what the issue is.", "@albertvillanova Hi, thanks for the tracing of the issue.\r\n\r\nThis is the output:\r\n\r\n```\r\nython get_llava_recap_cc3m.py\r\nGenerating train split: 3%|███▋ | 101910/3199866 [00:16<08:30, 6065.67 examples/s]\r\nTraceback (most recent call last):\r\n File \"get_llava_recap_cc3m.py\", line 31, in <module>\r\n dataset = load_dataset(\"llava-recap-cc3m/\", data_files=\"data/train-0000*-of-00314.parquet\")\r\n File \"/usr/local/lib/python3.8/dist-packages/datasets/load.py\", line 2582, in load_dataset\r\n builder_instance.download_and_prepare(\r\n File \"/usr/local/lib/python3.8/dist-packages/datasets/builder.py\", line 1005, in download_and_prepare\r\n self._download_and_prepare(\r\n File \"/usr/local/lib/python3.8/dist-packages/datasets/builder.py\", line 1118, in _download_and_prepare\r\n verify_splits(self.info.splits, split_dict)\r\n File \"/usr/local/lib/python3.8/dist-packages/datasets/utils/info_utils.py\", line 101, in verify_splits\r\n raise NonMatchingSplitsSizesError(str(bad_splits))\r\ndatasets.utils.info_utils.NonMatchingSplitsSizesError: [{'expected': SplitInfo(name='train', num_bytes=156885281898.75, num_examples=3199866, shard_lengths=None, dataset_name=None), 'recorded': SplitInfo(name='train', num_bytes=4994080770, num_examples=101910, shard_lengths=[10191, 10291, 10291, 10291, 10291, 10191, 10191, 10291, 10291, 9591], dataset_name='llava-recap-cc3m')}]\r\n```\r\n\r\nthis is my code:\r\n\r\n```\r\ndataset = load_dataset(\"llava-recap-cc3m/\", data_files=\"data/train-0000*-of-00314.parquet\")\r\n```\r\n\r\nMy situation and requirements:\r\n\r\n00314 is all, but I downlaode about 150, half of it, as you can see, i used `0000*-of-00314.` which should be at most 99 file being loaded.\r\n\r\nBut it just fail.\r\n\r\nCan u understand my issue now?\r\n\r\nIf so, then **do not** suggest me with stream, Just want to know, is there a way to load part if it...... **and please don't say you can not replicate my issue when you have downloaded them all**, my english is not good, but I think all situations and all prerequists I have addressed already.\r\n\r\n", "I see you did not use the \"parquet\" loader as I suggested in my code snippet above: https://github.com/huggingface/datasets/issues/6979#issuecomment-2182031415\r\nPlease try passing \"parquet\" instead of \"llava-recap-cc3m/\" to `load_dataset`, and the complete path to data files in `data_files`:\r\n```python\r\nload_dataset(\"parquet\", data_files=\"llava-recap-cc3m/data/train-001*-of-00314.parquet\")\r\n```", "Let me explain that you get the error because of this content within the `dataset_info` YAML tag in the `llava-recap-cc3m/README.md`:\r\n```\r\n - name: train\r\n num_bytes: 156885281898.75\r\n num_examples: 3199866\r\n```\r\n\r\nBy default, if there is that content in the README file, `load_dataset` performs a basic check to verify it the generated number of examples matches the expected one and raises a `NonMatchingSplitsSizesError` if that is not the case. \r\n\r\nYou can avoid this basic check by passing `verification_mode=\"no_checks\"`:\r\n```python\r\nload_dataset(\"llava-recap-cc3m/\", data_files=\"data/train-0000*-of-00314.parquet\", verification_mode=\"no_checks\")\r\n```", "And please, next time you have an issue, please fill the Bug template issue with all the necessary information: https://github.com/huggingface/datasets/issues/new?assignees=&labels=&projects=&template=bug-report.yml\r\n\r\nOtherwise it is very difficult for us to understand the underlying problem and to propose a pertinent solution.", "thank u albert!\r\n\r\nIt solved my issue!" ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6978). 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) | 0.005144 / 0.011353 (-0.006209) | 0.003500 / 0.011008 (-0.007509) | 0.063670 / 0.038508 (0.025162) | 0.031793 / 0.023109 (0.008683) | 0.239611 / 0.275898 (-0.036287) | 0.276681 / 0.323480 (-0.046799) | 0.004148 / 0.007986 (-0.003838) | 0.002713 / 0.004328 (-0.001615) | 0.048832 / 0.004250 (0.044582) | 0.043066 / 0.037052 (0.006014) | 0.256835 / 0.258489 (-0.001655) | 0.292224 / 0.293841 (-0.001617) | 0.027530 / 0.128546 (-0.101017) | 0.010509 / 0.075646 (-0.065137) | 0.203370 / 0.419271 (-0.215901) | 0.035643 / 0.043533 (-0.007890) | 0.252161 / 0.255139 (-0.002978) | 0.271883 / 0.283200 (-0.011316) | 0.018658 / 0.141683 (-0.123024) | 1.081676 / 1.452155 (-0.370479) | 1.142146 / 1.492716 (-0.350571) |\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) | 0.093484 / 0.018006 (0.075477) | 0.298607 / 0.000490 (0.298117) | 0.000220 / 0.000200 (0.000020) | 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) | 0.019021 / 0.037411 (-0.018390) | 0.062471 / 0.014526 (0.047946) | 0.075393 / 0.176557 (-0.101163) | 0.121040 / 0.737135 (-0.616095) | 0.077613 / 0.296338 (-0.218726) |\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) | 0.294857 / 0.215209 (0.079648) | 2.931143 / 2.077655 (0.853489) | 1.510866 / 1.504120 (0.006746) | 1.379574 / 1.541195 (-0.161621) | 1.352358 / 1.468490 (-0.116133) | 0.561670 / 4.584777 (-4.023107) | 2.378434 / 3.745712 (-1.367278) | 2.713203 / 5.269862 (-2.556658) | 1.706416 / 4.565676 (-2.859260) | 0.062355 / 0.424275 (-0.361920) | 0.004971 / 0.007607 (-0.002636) | 0.336498 / 0.226044 (0.110453) | 3.316464 / 2.268929 (1.047535) | 1.833035 / 55.444624 (-53.611589) | 1.532808 / 6.876477 (-5.343668) | 1.537323 / 2.142072 (-0.604749) | 0.639430 / 4.805227 (-4.165798) | 0.115808 / 6.500664 (-6.384856) | 0.043545 / 0.075469 (-0.031924) |\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) | 0.974428 / 1.841788 (-0.867360) | 11.368914 / 8.074308 (3.294606) | 9.754488 / 10.191392 (-0.436904) | 0.146277 / 0.680424 (-0.534146) | 0.013917 / 0.534201 (-0.520284) | 0.286809 / 0.579283 (-0.292474) | 0.267144 / 0.434364 (-0.167219) | 0.326161 / 0.540337 (-0.214177) | 0.418059 / 1.386936 (-0.968877) |\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) | 0.005341 / 0.011353 (-0.006012) | 0.003460 / 0.011008 (-0.007548) | 0.050135 / 0.038508 (0.011627) | 0.032014 / 0.023109 (0.008905) | 0.259835 / 0.275898 (-0.016063) | 0.286275 / 0.323480 (-0.037205) | 0.004350 / 0.007986 (-0.003636) | 0.002800 / 0.004328 (-0.001529) | 0.049358 / 0.004250 (0.045107) | 0.040182 / 0.037052 (0.003130) | 0.278352 / 0.258489 (0.019863) | 0.307869 / 0.293841 (0.014028) | 0.029151 / 0.128546 (-0.099395) | 0.010091 / 0.075646 (-0.065555) | 0.058814 / 0.419271 (-0.360458) | 0.033150 / 0.043533 (-0.010383) | 0.263594 / 0.255139 (0.008455) | 0.284065 / 0.283200 (0.000866) | 0.017968 / 0.141683 (-0.123714) | 1.145605 / 1.452155 (-0.306550) | 1.196884 / 1.492716 (-0.295832) |\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) | 0.094045 / 0.018006 (0.076039) | 0.299031 / 0.000490 (0.298541) | 0.000210 / 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) | 0.022510 / 0.037411 (-0.014901) | 0.077478 / 0.014526 (0.062953) | 0.087746 / 0.176557 (-0.088811) | 0.129311 / 0.737135 (-0.607825) | 0.089921 / 0.296338 (-0.206418) |\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) | 0.290279 / 0.215209 (0.075070) | 2.880725 / 2.077655 (0.803070) | 1.541262 / 1.504120 (0.037142) | 1.424475 / 1.541195 (-0.116719) | 1.436397 / 1.468490 (-0.032093) | 0.578237 / 4.584777 (-4.006540) | 0.965249 / 3.745712 (-2.780463) | 2.682534 / 5.269862 (-2.587327) | 1.732859 / 4.565676 (-2.832817) | 0.065523 / 0.424275 (-0.358752) | 0.005466 / 0.007607 (-0.002141) | 0.343985 / 0.226044 (0.117940) | 3.397463 / 2.268929 (1.128534) | 1.929370 / 55.444624 (-53.515255) | 1.605135 / 6.876477 (-5.271342) | 1.753926 / 2.142072 (-0.388146) | 0.659929 / 4.805227 (-4.145298) | 0.118093 / 6.500664 (-6.382571) | 0.041252 / 0.075469 (-0.034217) |\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) | 1.009177 / 1.841788 (-0.832610) | 11.959624 / 8.074308 (3.885316) | 10.484672 / 10.191392 (0.293280) | 0.142085 / 0.680424 (-0.538339) | 0.015955 / 0.534201 (-0.518245) | 0.283649 / 0.579283 (-0.295634) | 0.125681 / 0.434364 (-0.308683) | 0.320490 / 0.540337 (-0.219847) | 0.440353 / 1.386936 (-0.946583) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#e47a746bcda4b97db2467542b76d3215b3569ff0 \"CML watermark\")\n", "Maybe a patch release will be needed with this fix." ]

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[ "Thanks for reporting, @xiaoyaolangzhi.\r\n\r\nIndeed, we are currently requiring `pandas` >= 2.0.0.\r\n\r\nYou will need to update pandas in your local environment:\r\n```\r\npip install -U pandas\r\n``` ", "Thank you very much." ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6976). 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) | 0.005361 / 0.011353 (-0.005992) | 0.003983 / 0.011008 (-0.007025) | 0.062865 / 0.038508 (0.024357) | 0.029880 / 0.023109 (0.006771) | 0.261465 / 0.275898 (-0.014433) | 0.269791 / 0.323480 (-0.053689) | 0.004198 / 0.007986 (-0.003788) | 0.002942 / 0.004328 (-0.001387) | 0.049002 / 0.004250 (0.044751) | 0.043232 / 0.037052 (0.006180) | 0.328774 / 0.258489 (0.070285) | 0.297308 / 0.293841 (0.003467) | 0.030552 / 0.128546 (-0.097994) | 0.012632 / 0.075646 (-0.063015) | 0.204156 / 0.419271 (-0.215116) | 0.036014 / 0.043533 (-0.007519) | 0.241224 / 0.255139 (-0.013915) | 0.268358 / 0.283200 (-0.014842) | 0.019227 / 0.141683 (-0.122456) | 1.114515 / 1.452155 (-0.337639) | 1.147029 / 1.492716 (-0.345688) |\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) | 0.094925 / 0.018006 (0.076919) | 0.301548 / 0.000490 (0.301059) | 0.000211 / 0.000200 (0.000011) | 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) | 0.018875 / 0.037411 (-0.018536) | 0.062824 / 0.014526 (0.048298) | 0.075657 / 0.176557 (-0.100900) | 0.121926 / 0.737135 (-0.615209) | 0.077102 / 0.296338 (-0.219236) |\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) | 0.286018 / 0.215209 (0.070808) | 2.832222 / 2.077655 (0.754567) | 1.462629 / 1.504120 (-0.041491) | 1.354746 / 1.541195 (-0.186449) | 1.339504 / 1.468490 (-0.128986) | 0.718381 / 4.584777 (-3.866396) | 2.401456 / 3.745712 (-1.344256) | 3.013518 / 5.269862 (-2.256343) | 1.944892 / 4.565676 (-2.620784) | 0.078793 / 0.424275 (-0.345482) | 0.005219 / 0.007607 (-0.002388) | 0.349551 / 0.226044 (0.123507) | 3.417844 / 2.268929 (1.148916) | 1.830669 / 55.444624 (-53.613956) | 1.502134 / 6.876477 (-5.374343) | 1.529242 / 2.142072 (-0.612830) | 0.793732 / 4.805227 (-4.011495) | 0.133571 / 6.500664 (-6.367093) | 0.042588 / 0.075469 (-0.032881) |\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) | 0.988167 / 1.841788 (-0.853620) | 11.926728 / 8.074308 (3.852420) | 9.806971 / 10.191392 (-0.384421) | 0.173951 / 0.680424 (-0.506473) | 0.015308 / 0.534201 (-0.518893) | 0.310768 / 0.579283 (-0.268515) | 0.268261 / 0.434364 (-0.166103) | 0.342962 / 0.540337 (-0.197375) | 0.431255 / 1.386936 (-0.955681) |\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) | 0.005680 / 0.011353 (-0.005673) | 0.004231 / 0.011008 (-0.006778) | 0.051009 / 0.038508 (0.012501) | 0.031431 / 0.023109 (0.008322) | 0.268582 / 0.275898 (-0.007316) | 0.287942 / 0.323480 (-0.035538) | 0.004442 / 0.007986 (-0.003543) | 0.002818 / 0.004328 (-0.001511) | 0.050241 / 0.004250 (0.045991) | 0.039933 / 0.037052 (0.002881) | 0.285814 / 0.258489 (0.027325) | 0.316082 / 0.293841 (0.022241) | 0.032416 / 0.128546 (-0.096130) | 0.012398 / 0.075646 (-0.063248) | 0.060779 / 0.419271 (-0.358493) | 0.033706 / 0.043533 (-0.009827) | 0.273915 / 0.255139 (0.018776) | 0.289752 / 0.283200 (0.006553) | 0.017859 / 0.141683 (-0.123824) | 1.150224 / 1.452155 (-0.301930) | 1.197467 / 1.492716 (-0.295250) |\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) | 0.093810 / 0.018006 (0.075803) | 0.302529 / 0.000490 (0.302039) | 0.000221 / 0.000200 (0.000021) | 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) | 0.022903 / 0.037411 (-0.014508) | 0.077445 / 0.014526 (0.062919) | 0.089335 / 0.176557 (-0.087222) | 0.130848 / 0.737135 (-0.606287) | 0.091106 / 0.296338 (-0.205232) |\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) | 0.294194 / 0.215209 (0.078985) | 2.886983 / 2.077655 (0.809328) | 1.557768 / 1.504120 (0.053648) | 1.424467 / 1.541195 (-0.116727) | 1.440625 / 1.468490 (-0.027865) | 0.724793 / 4.584777 (-3.859984) | 0.985216 / 3.745712 (-2.760496) | 2.856826 / 5.269862 (-2.413036) | 1.911638 / 4.565676 (-2.654039) | 0.080350 / 0.424275 (-0.343925) | 0.005616 / 0.007607 (-0.001991) | 0.348713 / 0.226044 (0.122668) | 3.414764 / 2.268929 (1.145835) | 1.925056 / 55.444624 (-53.519568) | 1.635752 / 6.876477 (-5.240725) | 1.761117 / 2.142072 (-0.380955) | 0.808309 / 4.805227 (-3.996918) | 0.136893 / 6.500664 (-6.363771) | 0.042116 / 0.075469 (-0.033354) |\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) | 1.004740 / 1.841788 (-0.837048) | 12.495859 / 8.074308 (4.421550) | 10.681233 / 10.191392 (0.489841) | 0.133320 / 0.680424 (-0.547104) | 0.015943 / 0.534201 (-0.518258) | 0.304869 / 0.579283 (-0.274414) | 0.128616 / 0.434364 (-0.305748) | 0.345930 / 0.540337 (-0.194407) | 0.457434 / 1.386936 (-0.929502) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#84d9dea52098c9403efb43d5b542dd6d45000bec \"CML watermark\")\n" ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6975). 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) | 0.005168 / 0.011353 (-0.006185) | 0.003720 / 0.011008 (-0.007288) | 0.063347 / 0.038508 (0.024839) | 0.031474 / 0.023109 (0.008364) | 0.243233 / 0.275898 (-0.032665) | 0.276695 / 0.323480 (-0.046785) | 0.004109 / 0.007986 (-0.003877) | 0.002689 / 0.004328 (-0.001639) | 0.049522 / 0.004250 (0.045271) | 0.043477 / 0.037052 (0.006425) | 0.258578 / 0.258489 (0.000088) | 0.288134 / 0.293841 (-0.005707) | 0.027836 / 0.128546 (-0.100710) | 0.010677 / 0.075646 (-0.064969) | 0.206412 / 0.419271 (-0.212860) | 0.036204 / 0.043533 (-0.007329) | 0.250588 / 0.255139 (-0.004551) | 0.272354 / 0.283200 (-0.010846) | 0.018359 / 0.141683 (-0.123324) | 1.118867 / 1.452155 (-0.333288) | 1.157318 / 1.492716 (-0.335399) |\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) | 0.092927 / 0.018006 (0.074921) | 0.298252 / 0.000490 (0.297762) | 0.000228 / 0.000200 (0.000028) | 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) | 0.018824 / 0.037411 (-0.018588) | 0.069304 / 0.014526 (0.054778) | 0.075094 / 0.176557 (-0.101462) | 0.122546 / 0.737135 (-0.614590) | 0.076453 / 0.296338 (-0.219885) |\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) | 0.287131 / 0.215209 (0.071922) | 2.838945 / 2.077655 (0.761291) | 1.473578 / 1.504120 (-0.030542) | 1.351214 / 1.541195 (-0.189981) | 1.354924 / 1.468490 (-0.113566) | 0.577092 / 4.584777 (-4.007685) | 2.348072 / 3.745712 (-1.397640) | 2.762130 / 5.269862 (-2.507732) | 1.725195 / 4.565676 (-2.840482) | 0.063596 / 0.424275 (-0.360679) | 0.004921 / 0.007607 (-0.002686) | 0.335422 / 0.226044 (0.109377) | 3.340398 / 2.268929 (1.071469) | 1.789390 / 55.444624 (-53.655234) | 1.516247 / 6.876477 (-5.360229) | 1.529653 / 2.142072 (-0.612420) | 0.643547 / 4.805227 (-4.161680) | 0.116491 / 6.500664 (-6.384173) | 0.042404 / 0.075469 (-0.033065) |\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) | 0.959839 / 1.841788 (-0.881948) | 11.269778 / 8.074308 (3.195470) | 9.574898 / 10.191392 (-0.616494) | 0.128979 / 0.680424 (-0.551444) | 0.013901 / 0.534201 (-0.520300) | 0.280778 / 0.579283 (-0.298505) | 0.256511 / 0.434364 (-0.177853) | 0.319361 / 0.540337 (-0.220977) | 0.411803 / 1.386936 (-0.975133) |\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) | 0.005453 / 0.011353 (-0.005899) | 0.003478 / 0.011008 (-0.007530) | 0.050055 / 0.038508 (0.011547) | 0.031415 / 0.023109 (0.008306) | 0.275057 / 0.275898 (-0.000841) | 0.296690 / 0.323480 (-0.026789) | 0.004253 / 0.007986 (-0.003732) | 0.002777 / 0.004328 (-0.001551) | 0.049553 / 0.004250 (0.045303) | 0.039843 / 0.037052 (0.002791) | 0.286938 / 0.258489 (0.028449) | 0.318579 / 0.293841 (0.024738) | 0.029773 / 0.128546 (-0.098774) | 0.010404 / 0.075646 (-0.065242) | 0.057915 / 0.419271 (-0.361356) | 0.033486 / 0.043533 (-0.010047) | 0.273293 / 0.255139 (0.018154) | 0.293155 / 0.283200 (0.009955) | 0.017843 / 0.141683 (-0.123839) | 1.131130 / 1.452155 (-0.321024) | 1.167412 / 1.492716 (-0.325304) |\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) | 0.092553 / 0.018006 (0.074547) | 0.298888 / 0.000490 (0.298399) | 0.000201 / 0.000200 (0.000001) | 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) | 0.022646 / 0.037411 (-0.014765) | 0.076921 / 0.014526 (0.062395) | 0.089238 / 0.176557 (-0.087318) | 0.128793 / 0.737135 (-0.608342) | 0.089190 / 0.296338 (-0.207148) |\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) | 0.292552 / 0.215209 (0.077343) | 2.884277 / 2.077655 (0.806622) | 1.568798 / 1.504120 (0.064678) | 1.441819 / 1.541195 (-0.099375) | 1.435766 / 1.468490 (-0.032724) | 0.572435 / 4.584777 (-4.012342) | 0.957387 / 3.745712 (-2.788326) | 2.650843 / 5.269862 (-2.619019) | 1.727424 / 4.565676 (-2.838252) | 0.063470 / 0.424275 (-0.360805) | 0.005314 / 0.007607 (-0.002293) | 0.345881 / 0.226044 (0.119836) | 3.395463 / 2.268929 (1.126535) | 1.921340 / 55.444624 (-53.523285) | 1.621563 / 6.876477 (-5.254914) | 1.742561 / 2.142072 (-0.399512) | 0.639948 / 4.805227 (-4.165279) | 0.116091 / 6.500664 (-6.384573) | 0.041218 / 0.075469 (-0.034251) |\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) | 0.991506 / 1.841788 (-0.850281) | 11.897462 / 8.074308 (3.823154) | 10.083008 / 10.191392 (-0.108384) | 0.140626 / 0.680424 (-0.539798) | 0.015454 / 0.534201 (-0.518747) | 0.283856 / 0.579283 (-0.295427) | 0.125935 / 0.434364 (-0.308429) | 0.323884 / 0.540337 (-0.216454) | 0.438348 / 1.386936 (-0.948588) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#e59582adc7fcb53a86a8ca8eda7e04a4e7b25bd2 \"CML watermark\")\n" ]

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[ "add remove_unused_columns=False to training_args\r\nhttps://github.com/huggingface/datasets/issues/6535#issuecomment-1874024704", "Closing this issue because it was a reported and fixed in transformers." ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6972). 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) | 0.005195 / 0.011353 (-0.006157) | 0.003734 / 0.011008 (-0.007275) | 0.063087 / 0.038508 (0.024579) | 0.031467 / 0.023109 (0.008358) | 0.245183 / 0.275898 (-0.030715) | 0.280071 / 0.323480 (-0.043409) | 0.003205 / 0.007986 (-0.004780) | 0.003311 / 0.004328 (-0.001018) | 0.049967 / 0.004250 (0.045717) | 0.044927 / 0.037052 (0.007875) | 0.262244 / 0.258489 (0.003755) | 0.284549 / 0.293841 (-0.009292) | 0.027595 / 0.128546 (-0.100952) | 0.010521 / 0.075646 (-0.065126) | 0.206928 / 0.419271 (-0.212343) | 0.036179 / 0.043533 (-0.007354) | 0.254256 / 0.255139 (-0.000883) | 0.272733 / 0.283200 (-0.010467) | 0.020456 / 0.141683 (-0.121226) | 1.118527 / 1.452155 (-0.333628) | 1.152741 / 1.492716 (-0.339975) |\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) | 0.096642 / 0.018006 (0.078636) | 0.306981 / 0.000490 (0.306491) | 0.000220 / 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) | 0.019031 / 0.037411 (-0.018380) | 0.063960 / 0.014526 (0.049435) | 0.074428 / 0.176557 (-0.102129) | 0.121226 / 0.737135 (-0.615909) | 0.077111 / 0.296338 (-0.219228) |\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) | 0.279830 / 0.215209 (0.064621) | 2.748243 / 2.077655 (0.670588) | 1.481554 / 1.504120 (-0.022566) | 1.355015 / 1.541195 (-0.186180) | 1.379655 / 1.468490 (-0.088835) | 0.560378 / 4.584777 (-4.024399) | 2.407241 / 3.745712 (-1.338471) | 2.837090 / 5.269862 (-2.432771) | 1.767084 / 4.565676 (-2.798593) | 0.063517 / 0.424275 (-0.360758) | 0.005024 / 0.007607 (-0.002584) | 0.334845 / 0.226044 (0.108800) | 3.290712 / 2.268929 (1.021783) | 1.836923 / 55.444624 (-53.607702) | 1.543671 / 6.876477 (-5.332806) | 1.582319 / 2.142072 (-0.559754) | 0.637689 / 4.805227 (-4.167538) | 0.119515 / 6.500664 (-6.381149) | 0.042191 / 0.075469 (-0.033278) |\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) | 0.980018 / 1.841788 (-0.861770) | 11.620211 / 8.074308 (3.545903) | 9.697799 / 10.191392 (-0.493593) | 0.131733 / 0.680424 (-0.548691) | 0.014007 / 0.534201 (-0.520193) | 0.286046 / 0.579283 (-0.293237) | 0.264776 / 0.434364 (-0.169588) | 0.325041 / 0.540337 (-0.215296) | 0.452740 / 1.386936 (-0.934196) |\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) | 0.005603 / 0.011353 (-0.005750) | 0.003810 / 0.011008 (-0.007199) | 0.050773 / 0.038508 (0.012265) | 0.032601 / 0.023109 (0.009492) | 0.268035 / 0.275898 (-0.007863) | 0.292614 / 0.323480 (-0.030866) | 0.005076 / 0.007986 (-0.002910) | 0.004487 / 0.004328 (0.000159) | 0.049988 / 0.004250 (0.045737) | 0.040258 / 0.037052 (0.003205) | 0.284145 / 0.258489 (0.025656) | 0.318291 / 0.293841 (0.024450) | 0.029672 / 0.128546 (-0.098875) | 0.010534 / 0.075646 (-0.065113) | 0.059020 / 0.419271 (-0.360252) | 0.033451 / 0.043533 (-0.010082) | 0.270220 / 0.255139 (0.015081) | 0.290500 / 0.283200 (0.007300) | 0.017123 / 0.141683 (-0.124560) | 1.130870 / 1.452155 (-0.321285) | 1.160038 / 1.492716 (-0.332678) |\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) | 0.097045 / 0.018006 (0.079039) | 0.314573 / 0.000490 (0.314083) | 0.000203 / 0.000200 (0.000003) | 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) | 0.022396 / 0.037411 (-0.015015) | 0.079393 / 0.014526 (0.064867) | 0.088460 / 0.176557 (-0.088097) | 0.128050 / 0.737135 (-0.609085) | 0.093070 / 0.296338 (-0.203268) |\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) | 0.293858 / 0.215209 (0.078649) | 2.819956 / 2.077655 (0.742301) | 1.540181 / 1.504120 (0.036061) | 1.419671 / 1.541195 (-0.121524) | 1.441594 / 1.468490 (-0.026897) | 0.565200 / 4.584777 (-4.019577) | 0.963967 / 3.745712 (-2.781745) | 2.752137 / 5.269862 (-2.517725) | 1.779239 / 4.565676 (-2.786438) | 0.063787 / 0.424275 (-0.360488) | 0.005344 / 0.007607 (-0.002263) | 0.344283 / 0.226044 (0.118239) | 3.353263 / 2.268929 (1.084334) | 1.898678 / 55.444624 (-53.545947) | 1.607868 / 6.876477 (-5.268609) | 1.781938 / 2.142072 (-0.360134) | 0.652119 / 4.805227 (-4.153108) | 0.117883 / 6.500664 (-6.382781) | 0.048811 / 0.075469 (-0.026658) |\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) | 1.013154 / 1.841788 (-0.828634) | 12.421963 / 8.074308 (4.347655) | 10.352056 / 10.191392 (0.160664) | 0.143784 / 0.680424 (-0.536640) | 0.016370 / 0.534201 (-0.517831) | 0.283668 / 0.579283 (-0.295615) | 0.127070 / 0.434364 (-0.307294) | 0.326199 / 0.540337 (-0.214138) | 0.432776 / 1.386936 (-0.954160) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#5e72fb13b4824dcb27aedb807e4e28c420dec244 \"CML watermark\")\n" ]

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[]

[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6971). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "@HuggingFaceDocBuilderDev There is no doc for this change. Call a human.", "Haha it was me who triggered the CI for your PR", "<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) | 0.005051 / 0.011353 (-0.006302) | 0.004831 / 0.011008 (-0.006178) | 0.063006 / 0.038508 (0.024498) | 0.031589 / 0.023109 (0.008480) | 0.296202 / 0.275898 (0.020304) | 0.274274 / 0.323480 (-0.049205) | 0.003199 / 0.007986 (-0.004786) | 0.002768 / 0.004328 (-0.001561) | 0.049422 / 0.004250 (0.045172) | 0.045174 / 0.037052 (0.008121) | 0.263814 / 0.258489 (0.005325) | 0.288125 / 0.293841 (-0.005716) | 0.027641 / 0.128546 (-0.100905) | 0.010439 / 0.075646 (-0.065207) | 0.203075 / 0.419271 (-0.216196) | 0.036259 / 0.043533 (-0.007274) | 0.245159 / 0.255139 (-0.009980) | 0.268897 / 0.283200 (-0.014303) | 0.019493 / 0.141683 (-0.122190) | 1.108330 / 1.452155 (-0.343824) | 1.155835 / 1.492716 (-0.336881) |\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) | 0.096860 / 0.018006 (0.078854) | 0.309428 / 0.000490 (0.308938) | 0.000197 / 0.000200 (-0.000003) | 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) | 0.019275 / 0.037411 (-0.018136) | 0.062623 / 0.014526 (0.048098) | 0.073871 / 0.176557 (-0.102686) | 0.120410 / 0.737135 (-0.616726) | 0.075766 / 0.296338 (-0.220572) |\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) | 0.279876 / 0.215209 (0.064667) | 2.742429 / 2.077655 (0.664774) | 1.414368 / 1.504120 (-0.089752) | 1.293194 / 1.541195 (-0.248001) | 1.318043 / 1.468490 (-0.150447) | 0.570904 / 4.584777 (-4.013873) | 2.384386 / 3.745712 (-1.361326) | 2.757953 / 5.269862 (-2.511908) | 1.728766 / 4.565676 (-2.836910) | 0.062699 / 0.424275 (-0.361576) | 0.004951 / 0.007607 (-0.002656) | 0.332222 / 0.226044 (0.106177) | 3.407429 / 2.268929 (1.138500) | 1.777136 / 55.444624 (-53.667488) | 1.521269 / 6.876477 (-5.355207) | 1.544814 / 2.142072 (-0.597258) | 0.646249 / 4.805227 (-4.158978) | 0.117032 / 6.500664 (-6.383632) | 0.042274 / 0.075469 (-0.033195) |\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) | 1.016249 / 1.841788 (-0.825539) | 11.794003 / 8.074308 (3.719695) | 9.871925 / 10.191392 (-0.319467) | 0.133694 / 0.680424 (-0.546730) | 0.014904 / 0.534201 (-0.519297) | 0.287453 / 0.579283 (-0.291831) | 0.271802 / 0.434364 (-0.162561) | 0.324711 / 0.540337 (-0.215626) | 0.411812 / 1.386936 (-0.975124) |\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) | 0.005376 / 0.011353 (-0.005977) | 0.003631 / 0.011008 (-0.007377) | 0.050154 / 0.038508 (0.011646) | 0.033665 / 0.023109 (0.010556) | 0.279062 / 0.275898 (0.003164) | 0.298899 / 0.323480 (-0.024581) | 0.004388 / 0.007986 (-0.003598) | 0.002810 / 0.004328 (-0.001518) | 0.049032 / 0.004250 (0.044781) | 0.040531 / 0.037052 (0.003478) | 0.287220 / 0.258489 (0.028731) | 0.319060 / 0.293841 (0.025219) | 0.029473 / 0.128546 (-0.099073) | 0.010317 / 0.075646 (-0.065329) | 0.058483 / 0.419271 (-0.360789) | 0.033359 / 0.043533 (-0.010174) | 0.276404 / 0.255139 (0.021265) | 0.295013 / 0.283200 (0.011813) | 0.019372 / 0.141683 (-0.122311) | 1.172624 / 1.452155 (-0.279531) | 1.176815 / 1.492716 (-0.315902) |\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) | 0.097347 / 0.018006 (0.079341) | 0.306959 / 0.000490 (0.306469) | 0.000200 / 0.000200 (-0.000000) | 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) | 0.022776 / 0.037411 (-0.014635) | 0.077865 / 0.014526 (0.063340) | 0.088806 / 0.176557 (-0.087751) | 0.130448 / 0.737135 (-0.606687) | 0.090973 / 0.296338 (-0.205365) |\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) | 0.301168 / 0.215209 (0.085959) | 2.957634 / 2.077655 (0.879979) | 1.556999 / 1.504120 (0.052879) | 1.413940 / 1.541195 (-0.127255) | 1.427970 / 1.468490 (-0.040520) | 0.587653 / 4.584777 (-3.997124) | 0.951295 / 3.745712 (-2.794417) | 2.691004 / 5.269862 (-2.578858) | 1.755826 / 4.565676 (-2.809851) | 0.064883 / 0.424275 (-0.359392) | 0.005379 / 0.007607 (-0.002228) | 0.353790 / 0.226044 (0.127745) | 3.457747 / 2.268929 (1.188818) | 1.891884 / 55.444624 (-53.552740) | 1.616619 / 6.876477 (-5.259858) | 1.736167 / 2.142072 (-0.405906) | 0.669257 / 4.805227 (-4.135970) | 0.119620 / 6.500664 (-6.381044) | 0.041390 / 0.075469 (-0.034080) |\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) | 1.008851 / 1.841788 (-0.832937) | 13.151216 / 8.074308 (5.076908) | 10.398371 / 10.191392 (0.206979) | 0.143420 / 0.680424 (-0.537004) | 0.015759 / 0.534201 (-0.518442) | 0.293068 / 0.579283 (-0.286215) | 0.131449 / 0.434364 (-0.302914) | 0.334715 / 0.540337 (-0.205623) | 0.445824 / 1.386936 (-0.941112) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#087671dcaf817c906a8649404c07b0440e2732ea \"CML watermark\")\n" ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6970). 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) | 0.005450 / 0.011353 (-0.005902) | 0.003911 / 0.011008 (-0.007098) | 0.063467 / 0.038508 (0.024959) | 0.031029 / 0.023109 (0.007920) | 0.247916 / 0.275898 (-0.027982) | 0.274737 / 0.323480 (-0.048743) | 0.003255 / 0.007986 (-0.004731) | 0.002842 / 0.004328 (-0.001487) | 0.049617 / 0.004250 (0.045366) | 0.046689 / 0.037052 (0.009637) | 0.255152 / 0.258489 (-0.003337) | 0.288630 / 0.293841 (-0.005211) | 0.028174 / 0.128546 (-0.100372) | 0.010773 / 0.075646 (-0.064873) | 0.202119 / 0.419271 (-0.217153) | 0.035914 / 0.043533 (-0.007619) | 0.248197 / 0.255139 (-0.006942) | 0.273508 / 0.283200 (-0.009691) | 0.020626 / 0.141683 (-0.121057) | 1.125668 / 1.452155 (-0.326487) | 1.156678 / 1.492716 (-0.336038) |\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) | 0.098294 / 0.018006 (0.080288) | 0.306661 / 0.000490 (0.306172) | 0.000227 / 0.000200 (0.000027) | 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) | 0.019118 / 0.037411 (-0.018293) | 0.063086 / 0.014526 (0.048560) | 0.077735 / 0.176557 (-0.098822) | 0.123159 / 0.737135 (-0.613976) | 0.077228 / 0.296338 (-0.219111) |\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) | 0.280031 / 0.215209 (0.064822) | 2.762524 / 2.077655 (0.684870) | 1.444571 / 1.504120 (-0.059549) | 1.330590 / 1.541195 (-0.210604) | 1.371937 / 1.468490 (-0.096553) | 0.563847 / 4.584777 (-4.020930) | 2.369908 / 3.745712 (-1.375804) | 2.827441 / 5.269862 (-2.442420) | 1.749864 / 4.565676 (-2.815812) | 0.063996 / 0.424275 (-0.360279) | 0.005060 / 0.007607 (-0.002547) | 0.326067 / 0.226044 (0.100023) | 3.270170 / 2.268929 (1.001242) | 1.785164 / 55.444624 (-53.659460) | 1.560432 / 6.876477 (-5.316045) | 1.587005 / 2.142072 (-0.555068) | 0.645714 / 4.805227 (-4.159513) | 0.119975 / 6.500664 (-6.380689) | 0.043962 / 0.075469 (-0.031507) |\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) | 0.979003 / 1.841788 (-0.862785) | 11.988701 / 8.074308 (3.914393) | 9.788564 / 10.191392 (-0.402828) | 0.142644 / 0.680424 (-0.537780) | 0.014924 / 0.534201 (-0.519277) | 0.285942 / 0.579283 (-0.293341) | 0.264086 / 0.434364 (-0.170278) | 0.343360 / 0.540337 (-0.196977) | 0.413467 / 1.386936 (-0.973469) |\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) | 0.005818 / 0.011353 (-0.005535) | 0.003726 / 0.011008 (-0.007283) | 0.050936 / 0.038508 (0.012428) | 0.032000 / 0.023109 (0.008890) | 0.273282 / 0.275898 (-0.002616) | 0.293889 / 0.323480 (-0.029591) | 0.004287 / 0.007986 (-0.003699) | 0.002797 / 0.004328 (-0.001531) | 0.049088 / 0.004250 (0.044838) | 0.040235 / 0.037052 (0.003183) | 0.280240 / 0.258489 (0.021751) | 0.315749 / 0.293841 (0.021908) | 0.029986 / 0.128546 (-0.098560) | 0.010440 / 0.075646 (-0.065206) | 0.058935 / 0.419271 (-0.360336) | 0.033198 / 0.043533 (-0.010335) | 0.274321 / 0.255139 (0.019182) | 0.288039 / 0.283200 (0.004840) | 0.018865 / 0.141683 (-0.122818) | 1.114915 / 1.452155 (-0.337240) | 1.180548 / 1.492716 (-0.312169) |\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) | 0.095028 / 0.018006 (0.077022) | 0.304797 / 0.000490 (0.304307) | 0.000221 / 0.000200 (0.000021) | 0.000056 / 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) | 0.022556 / 0.037411 (-0.014855) | 0.076839 / 0.014526 (0.062313) | 0.090255 / 0.176557 (-0.086302) | 0.128748 / 0.737135 (-0.608387) | 0.091718 / 0.296338 (-0.204621) |\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) | 0.296061 / 0.215209 (0.080852) | 2.851376 / 2.077655 (0.773722) | 1.548084 / 1.504120 (0.043964) | 1.428589 / 1.541195 (-0.112606) | 1.467244 / 1.468490 (-0.001246) | 0.583533 / 4.584777 (-4.001244) | 0.967436 / 3.745712 (-2.778277) | 2.774775 / 5.269862 (-2.495087) | 1.800435 / 4.565676 (-2.765242) | 0.063998 / 0.424275 (-0.360277) | 0.005420 / 0.007607 (-0.002187) | 0.346353 / 0.226044 (0.120308) | 3.383885 / 2.268929 (1.114956) | 1.902914 / 55.444624 (-53.541710) | 1.599545 / 6.876477 (-5.276932) | 1.772754 / 2.142072 (-0.369318) | 0.651804 / 4.805227 (-4.153423) | 0.120380 / 6.500664 (-6.380284) | 0.043311 / 0.075469 (-0.032159) |\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) | 1.004414 / 1.841788 (-0.837374) | 12.356077 / 8.074308 (4.281769) | 10.513420 / 10.191392 (0.322028) | 0.132419 / 0.680424 (-0.548005) | 0.015470 / 0.534201 (-0.518731) | 0.284883 / 0.579283 (-0.294400) | 0.130763 / 0.434364 (-0.303601) | 0.320068 / 0.540337 (-0.220270) | 0.430284 / 1.386936 (-0.956652) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#574791e0a0cf57ba761f679a054b9e89e4a3ee22 \"CML watermark\")\n" ]

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[]

[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6969). 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) | 0.005414 / 0.011353 (-0.005939) | 0.003936 / 0.011008 (-0.007073) | 0.064129 / 0.038508 (0.025621) | 0.032985 / 0.023109 (0.009875) | 0.244051 / 0.275898 (-0.031847) | 0.273500 / 0.323480 (-0.049980) | 0.003227 / 0.007986 (-0.004759) | 0.002858 / 0.004328 (-0.001470) | 0.049212 / 0.004250 (0.044962) | 0.046432 / 0.037052 (0.009380) | 0.249543 / 0.258489 (-0.008946) | 0.297339 / 0.293841 (0.003498) | 0.027880 / 0.128546 (-0.100666) | 0.010582 / 0.075646 (-0.065065) | 0.202345 / 0.419271 (-0.216927) | 0.036402 / 0.043533 (-0.007131) | 0.253157 / 0.255139 (-0.001982) | 0.283355 / 0.283200 (0.000155) | 0.021907 / 0.141683 (-0.119776) | 1.174431 / 1.452155 (-0.277723) | 1.172103 / 1.492716 (-0.320613) |\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) | 0.097942 / 0.018006 (0.079936) | 0.307114 / 0.000490 (0.306624) | 0.000230 / 0.000200 (0.000030) | 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) | 0.019149 / 0.037411 (-0.018262) | 0.064283 / 0.014526 (0.049758) | 0.075643 / 0.176557 (-0.100913) | 0.122531 / 0.737135 (-0.614604) | 0.077360 / 0.296338 (-0.218978) |\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) | 0.291790 / 0.215209 (0.076581) | 2.869234 / 2.077655 (0.791580) | 1.550266 / 1.504120 (0.046146) | 1.392392 / 1.541195 (-0.148802) | 1.375700 / 1.468490 (-0.092790) | 0.574963 / 4.584777 (-4.009814) | 2.444746 / 3.745712 (-1.300966) | 2.920602 / 5.269862 (-2.349259) | 1.812720 / 4.565676 (-2.752957) | 0.064811 / 0.424275 (-0.359464) | 0.005163 / 0.007607 (-0.002444) | 0.341306 / 0.226044 (0.115261) | 3.443177 / 2.268929 (1.174249) | 1.843510 / 55.444624 (-53.601115) | 1.534023 / 6.876477 (-5.342454) | 1.603575 / 2.142072 (-0.538498) | 0.656923 / 4.805227 (-4.148304) | 0.120338 / 6.500664 (-6.380326) | 0.042958 / 0.075469 (-0.032511) |\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) | 0.975993 / 1.841788 (-0.865795) | 11.942335 / 8.074308 (3.868027) | 9.964277 / 10.191392 (-0.227115) | 0.131247 / 0.680424 (-0.549176) | 0.014166 / 0.534201 (-0.520035) | 0.283994 / 0.579283 (-0.295290) | 0.267516 / 0.434364 (-0.166848) | 0.328363 / 0.540337 (-0.211974) | 0.412204 / 1.386936 (-0.974732) |\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) | 0.005867 / 0.011353 (-0.005486) | 0.003860 / 0.011008 (-0.007148) | 0.050247 / 0.038508 (0.011739) | 0.033819 / 0.023109 (0.010710) | 0.264840 / 0.275898 (-0.011058) | 0.291253 / 0.323480 (-0.032227) | 0.004481 / 0.007986 (-0.003504) | 0.002880 / 0.004328 (-0.001449) | 0.048528 / 0.004250 (0.044278) | 0.041720 / 0.037052 (0.004667) | 0.280467 / 0.258489 (0.021978) | 0.315244 / 0.293841 (0.021404) | 0.030569 / 0.128546 (-0.097977) | 0.010494 / 0.075646 (-0.065152) | 0.058652 / 0.419271 (-0.360620) | 0.034181 / 0.043533 (-0.009352) | 0.266466 / 0.255139 (0.011327) | 0.292038 / 0.283200 (0.008838) | 0.018501 / 0.141683 (-0.123182) | 1.115965 / 1.452155 (-0.336189) | 1.162753 / 1.492716 (-0.329963) |\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) | 0.101301 / 0.018006 (0.083295) | 0.296812 / 0.000490 (0.296322) | 0.000212 / 0.000200 (0.000012) | 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) | 0.023662 / 0.037411 (-0.013749) | 0.080678 / 0.014526 (0.066153) | 0.089867 / 0.176557 (-0.086689) | 0.130803 / 0.737135 (-0.606332) | 0.091479 / 0.296338 (-0.204860) |\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) | 0.286028 / 0.215209 (0.070819) | 2.780072 / 2.077655 (0.702418) | 1.520146 / 1.504120 (0.016026) | 1.372952 / 1.541195 (-0.168243) | 1.428734 / 1.468490 (-0.039756) | 0.571484 / 4.584777 (-4.013293) | 0.969643 / 3.745712 (-2.776069) | 2.788157 / 5.269862 (-2.481705) | 1.841166 / 4.565676 (-2.724511) | 0.063311 / 0.424275 (-0.360964) | 0.005320 / 0.007607 (-0.002287) | 0.333341 / 0.226044 (0.107296) | 3.295141 / 2.268929 (1.026213) | 1.865537 / 55.444624 (-53.579088) | 1.584655 / 6.876477 (-5.291821) | 1.747417 / 2.142072 (-0.394655) | 0.634549 / 4.805227 (-4.170678) | 0.116373 / 6.500664 (-6.384291) | 0.041567 / 0.075469 (-0.033902) |\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) | 1.023086 / 1.841788 (-0.818702) | 13.091905 / 8.074308 (5.017597) | 10.572164 / 10.191392 (0.380772) | 0.142208 / 0.680424 (-0.538216) | 0.015692 / 0.534201 (-0.518509) | 0.284309 / 0.579283 (-0.294974) | 0.126467 / 0.434364 (-0.307897) | 0.322719 / 0.540337 (-0.217618) | 0.439952 / 1.386936 (-0.946985) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#98fdc9e78e6d057ca66e58a37f49d6618aab8130 \"CML watermark\")\n" ]

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[]

[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6968). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "Oops, sorry for the style issue. Fixed in https://github.com/huggingface/datasets/pull/6968/commits/a4e2b28fa647b28190ae2615d7271e6ac63c8499.\r\n\r\nRegarding docs, I can't find mentions of `HF_DATASETS_OFFLINE` anywhere else in `datasets`/`hub-docs`. Once this is merged and released, I'm planning to update some `transformers` docs that briefly mention it.", "<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) | 0.005173 / 0.011353 (-0.006180) | 0.003485 / 0.011008 (-0.007524) | 0.063867 / 0.038508 (0.025359) | 0.031338 / 0.023109 (0.008229) | 0.242093 / 0.275898 (-0.033805) | 0.266606 / 0.323480 (-0.056874) | 0.003069 / 0.007986 (-0.004916) | 0.003307 / 0.004328 (-0.001022) | 0.051059 / 0.004250 (0.046808) | 0.044396 / 0.037052 (0.007344) | 0.254896 / 0.258489 (-0.003593) | 0.282835 / 0.293841 (-0.011006) | 0.027548 / 0.128546 (-0.100998) | 0.010520 / 0.075646 (-0.065126) | 0.201701 / 0.419271 (-0.217570) | 0.035613 / 0.043533 (-0.007920) | 0.240955 / 0.255139 (-0.014184) | 0.271902 / 0.283200 (-0.011298) | 0.019826 / 0.141683 (-0.121857) | 1.116994 / 1.452155 (-0.335161) | 1.162886 / 1.492716 (-0.329831) |\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) | 0.093683 / 0.018006 (0.075677) | 0.297970 / 0.000490 (0.297480) | 0.000211 / 0.000200 (0.000011) | 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) | 0.018952 / 0.037411 (-0.018459) | 0.062710 / 0.014526 (0.048184) | 0.073641 / 0.176557 (-0.102916) | 0.121200 / 0.737135 (-0.615935) | 0.075723 / 0.296338 (-0.220616) |\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) | 0.286056 / 0.215209 (0.070847) | 2.811424 / 2.077655 (0.733770) | 1.448045 / 1.504120 (-0.056075) | 1.338309 / 1.541195 (-0.202885) | 1.328371 / 1.468490 (-0.140119) | 0.557282 / 4.584777 (-4.027495) | 2.362235 / 3.745712 (-1.383477) | 2.732108 / 5.269862 (-2.537754) | 1.730911 / 4.565676 (-2.834765) | 0.061689 / 0.424275 (-0.362586) | 0.004947 / 0.007607 (-0.002660) | 0.346700 / 0.226044 (0.120656) | 3.355989 / 2.268929 (1.087060) | 1.828078 / 55.444624 (-53.616546) | 1.511531 / 6.876477 (-5.364946) | 1.535897 / 2.142072 (-0.606175) | 0.630276 / 4.805227 (-4.174951) | 0.115808 / 6.500664 (-6.384857) | 0.042199 / 0.075469 (-0.033270) |\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) | 0.969203 / 1.841788 (-0.872584) | 11.282997 / 8.074308 (3.208689) | 9.538914 / 10.191392 (-0.652478) | 0.140072 / 0.680424 (-0.540352) | 0.014021 / 0.534201 (-0.520180) | 0.283784 / 0.579283 (-0.295499) | 0.255973 / 0.434364 (-0.178391) | 0.320284 / 0.540337 (-0.220053) | 0.412689 / 1.386936 (-0.974247) |\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) | 0.005201 / 0.011353 (-0.006152) | 0.003312 / 0.011008 (-0.007697) | 0.050044 / 0.038508 (0.011536) | 0.033610 / 0.023109 (0.010501) | 0.266429 / 0.275898 (-0.009469) | 0.287782 / 0.323480 (-0.035698) | 0.004316 / 0.007986 (-0.003670) | 0.002696 / 0.004328 (-0.001633) | 0.049667 / 0.004250 (0.045417) | 0.040244 / 0.037052 (0.003192) | 0.278870 / 0.258489 (0.020381) | 0.311415 / 0.293841 (0.017574) | 0.029150 / 0.128546 (-0.099396) | 0.010046 / 0.075646 (-0.065600) | 0.058527 / 0.419271 (-0.360744) | 0.032871 / 0.043533 (-0.010662) | 0.266582 / 0.255139 (0.011443) | 0.286157 / 0.283200 (0.002957) | 0.017197 / 0.141683 (-0.124486) | 1.120944 / 1.452155 (-0.331211) | 1.161111 / 1.492716 (-0.331606) |\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) | 0.092679 / 0.018006 (0.074672) | 0.299195 / 0.000490 (0.298705) | 0.000204 / 0.000200 (0.000004) | 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) | 0.022212 / 0.037411 (-0.015199) | 0.076734 / 0.014526 (0.062208) | 0.088326 / 0.176557 (-0.088230) | 0.128209 / 0.737135 (-0.608926) | 0.088807 / 0.296338 (-0.207531) |\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) | 0.291782 / 0.215209 (0.076573) | 2.882990 / 2.077655 (0.805335) | 1.601638 / 1.504120 (0.097518) | 1.457560 / 1.541195 (-0.083635) | 1.470517 / 1.468490 (0.002027) | 0.565738 / 4.584777 (-4.019039) | 0.949235 / 3.745712 (-2.796478) | 2.661927 / 5.269862 (-2.607934) | 1.722178 / 4.565676 (-2.843498) | 0.063680 / 0.424275 (-0.360595) | 0.005339 / 0.007607 (-0.002268) | 0.344280 / 0.226044 (0.118235) | 3.432998 / 2.268929 (1.164070) | 1.985516 / 55.444624 (-53.459108) | 1.651826 / 6.876477 (-5.224651) | 1.764541 / 2.142072 (-0.377531) | 0.640219 / 4.805227 (-4.165008) | 0.116541 / 6.500664 (-6.384124) | 0.041237 / 0.075469 (-0.034232) |\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) | 1.013927 / 1.841788 (-0.827861) | 11.876661 / 8.074308 (3.802353) | 10.264144 / 10.191392 (0.072752) | 0.131151 / 0.680424 (-0.549273) | 0.015774 / 0.534201 (-0.518427) | 0.284948 / 0.579283 (-0.294335) | 0.125924 / 0.434364 (-0.308439) | 0.319845 / 0.540337 (-0.220493) | 0.431978 / 1.386936 (-0.954958) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#68f67741ffde68c98d0a2f59ac4d8e3a7bc03065 \"CML watermark\")\n" ]

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[ "<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) | 0.005326 / 0.011353 (-0.006027) | 0.003448 / 0.011008 (-0.007560) | 0.062516 / 0.038508 (0.024008) | 0.030222 / 0.023109 (0.007113) | 0.237006 / 0.275898 (-0.038892) | 0.258224 / 0.323480 (-0.065256) | 0.003191 / 0.007986 (-0.004795) | 0.002768 / 0.004328 (-0.001560) | 0.048754 / 0.004250 (0.044504) | 0.043694 / 0.037052 (0.006641) | 0.248832 / 0.258489 (-0.009657) | 0.272217 / 0.293841 (-0.021624) | 0.029684 / 0.128546 (-0.098862) | 0.011997 / 0.075646 (-0.063650) | 0.204047 / 0.419271 (-0.215225) | 0.035944 / 0.043533 (-0.007589) | 0.242094 / 0.255139 (-0.013045) | 0.258897 / 0.283200 (-0.024303) | 0.019228 / 0.141683 (-0.122455) | 1.110193 / 1.452155 (-0.341961) | 1.166780 / 1.492716 (-0.325937) |\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) | 0.097162 / 0.018006 (0.079156) | 0.303148 / 0.000490 (0.302659) | 0.000229 / 0.000200 (0.000029) | 0.000050 / 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) | 0.019981 / 0.037411 (-0.017431) | 0.062669 / 0.014526 (0.048144) | 0.074801 / 0.176557 (-0.101756) | 0.120509 / 0.737135 (-0.616626) | 0.075957 / 0.296338 (-0.220382) |\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) | 0.279527 / 0.215209 (0.064318) | 2.722749 / 2.077655 (0.645094) | 1.441770 / 1.504120 (-0.062350) | 1.312172 / 1.541195 (-0.229023) | 1.329418 / 1.468490 (-0.139072) | 0.723939 / 4.584777 (-3.860838) | 2.359146 / 3.745712 (-1.386566) | 2.963445 / 5.269862 (-2.306416) | 1.881974 / 4.565676 (-2.683702) | 0.078189 / 0.424275 (-0.346086) | 0.005249 / 0.007607 (-0.002358) | 0.334508 / 0.226044 (0.108463) | 3.271961 / 2.268929 (1.003032) | 1.817365 / 55.444624 (-53.627259) | 1.522755 / 6.876477 (-5.353721) | 1.514203 / 2.142072 (-0.627870) | 0.803486 / 4.805227 (-4.001741) | 0.134189 / 6.500664 (-6.366475) | 0.042761 / 0.075469 (-0.032708) |\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) | 0.971126 / 1.841788 (-0.870662) | 11.367159 / 8.074308 (3.292851) | 9.520174 / 10.191392 (-0.671218) | 0.142705 / 0.680424 (-0.537719) | 0.014586 / 0.534201 (-0.519615) | 0.300869 / 0.579283 (-0.278414) | 0.263161 / 0.434364 (-0.171203) | 0.336403 / 0.540337 (-0.203935) | 0.436088 / 1.386936 (-0.950848) |\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) | 0.005800 / 0.011353 (-0.005553) | 0.003906 / 0.011008 (-0.007103) | 0.050197 / 0.038508 (0.011689) | 0.031348 / 0.023109 (0.008238) | 0.265636 / 0.275898 (-0.010262) | 0.286550 / 0.323480 (-0.036930) | 0.004502 / 0.007986 (-0.003484) | 0.002828 / 0.004328 (-0.001501) | 0.049668 / 0.004250 (0.045417) | 0.039552 / 0.037052 (0.002499) | 0.279091 / 0.258489 (0.020602) | 0.309987 / 0.293841 (0.016146) | 0.032104 / 0.128546 (-0.096442) | 0.011989 / 0.075646 (-0.063657) | 0.059875 / 0.419271 (-0.359397) | 0.033446 / 0.043533 (-0.010087) | 0.265256 / 0.255139 (0.010117) | 0.285649 / 0.283200 (0.002449) | 0.018330 / 0.141683 (-0.123353) | 1.140073 / 1.452155 (-0.312081) | 1.194538 / 1.492716 (-0.298178) |\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) | 0.093692 / 0.018006 (0.075685) | 0.301422 / 0.000490 (0.300932) | 0.000216 / 0.000200 (0.000016) | 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) | 0.022844 / 0.037411 (-0.014568) | 0.077129 / 0.014526 (0.062603) | 0.087948 / 0.176557 (-0.088608) | 0.129905 / 0.737135 (-0.607230) | 0.089872 / 0.296338 (-0.206466) |\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) | 0.293135 / 0.215209 (0.077926) | 2.880280 / 2.077655 (0.802626) | 1.554250 / 1.504120 (0.050130) | 1.428005 / 1.541195 (-0.113190) | 1.520863 / 1.468490 (0.052373) | 0.759903 / 4.584777 (-3.824874) | 0.959674 / 3.745712 (-2.786038) | 2.848914 / 5.269862 (-2.420948) | 1.900355 / 4.565676 (-2.665322) | 0.079434 / 0.424275 (-0.344841) | 0.005487 / 0.007607 (-0.002121) | 0.344837 / 0.226044 (0.118793) | 3.401730 / 2.268929 (1.132802) | 1.887526 / 55.444624 (-53.557098) | 1.596821 / 6.876477 (-5.279655) | 1.732190 / 2.142072 (-0.409882) | 0.800929 / 4.805227 (-4.004299) | 0.132763 / 6.500664 (-6.367901) | 0.041185 / 0.075469 (-0.034284) |\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) | 0.994396 / 1.841788 (-0.847391) | 12.488692 / 8.074308 (4.414384) | 10.365952 / 10.191392 (0.174560) | 0.142951 / 0.680424 (-0.537472) | 0.015448 / 0.534201 (-0.518753) | 0.305577 / 0.579283 (-0.273706) | 0.126897 / 0.434364 (-0.307467) | 0.340784 / 0.540337 (-0.199554) | 0.461955 / 1.386936 (-0.924981) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#1d65718438ac4bc401468e57d5358e69012ed0c8 \"CML watermark\")\n" ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6965). 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) | 0.005879 / 0.011353 (-0.005474) | 0.004144 / 0.011008 (-0.006865) | 0.063327 / 0.038508 (0.024819) | 0.032577 / 0.023109 (0.009468) | 0.242936 / 0.275898 (-0.032962) | 0.269882 / 0.323480 (-0.053598) | 0.003339 / 0.007986 (-0.004647) | 0.002901 / 0.004328 (-0.001428) | 0.049163 / 0.004250 (0.044912) | 0.047072 / 0.037052 (0.010019) | 0.261120 / 0.258489 (0.002631) | 0.287857 / 0.293841 (-0.005984) | 0.029688 / 0.128546 (-0.098858) | 0.012702 / 0.075646 (-0.062944) | 0.204040 / 0.419271 (-0.215231) | 0.036012 / 0.043533 (-0.007521) | 0.244210 / 0.255139 (-0.010929) | 0.267600 / 0.283200 (-0.015599) | 0.019627 / 0.141683 (-0.122056) | 1.103770 / 1.452155 (-0.348385) | 1.197710 / 1.492716 (-0.295006) |\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) | 0.101683 / 0.018006 (0.083677) | 0.311825 / 0.000490 (0.311335) | 0.000236 / 0.000200 (0.000036) | 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) | 0.019642 / 0.037411 (-0.017769) | 0.061618 / 0.014526 (0.047092) | 0.075237 / 0.176557 (-0.101320) | 0.122250 / 0.737135 (-0.614886) | 0.076087 / 0.296338 (-0.220251) |\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) | 0.285120 / 0.215209 (0.069911) | 2.811527 / 2.077655 (0.733872) | 1.457961 / 1.504120 (-0.046159) | 1.333819 / 1.541195 (-0.207376) | 1.387863 / 1.468490 (-0.080627) | 0.730828 / 4.584777 (-3.853949) | 2.417224 / 3.745712 (-1.328488) | 2.994842 / 5.269862 (-2.275020) | 1.922079 / 4.565676 (-2.643598) | 0.087486 / 0.424275 (-0.336789) | 0.005211 / 0.007607 (-0.002396) | 0.335585 / 0.226044 (0.109541) | 3.297664 / 2.268929 (1.028735) | 1.809391 / 55.444624 (-53.635233) | 1.501646 / 6.876477 (-5.374831) | 1.567573 / 2.142072 (-0.574500) | 0.800816 / 4.805227 (-4.004411) | 0.134204 / 6.500664 (-6.366460) | 0.043156 / 0.075469 (-0.032313) |\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) | 0.982955 / 1.841788 (-0.858833) | 12.256850 / 8.074308 (4.182542) | 9.821500 / 10.191392 (-0.369892) | 0.143739 / 0.680424 (-0.536685) | 0.014425 / 0.534201 (-0.519776) | 0.302718 / 0.579283 (-0.276565) | 0.267746 / 0.434364 (-0.166618) | 0.340036 / 0.540337 (-0.200301) | 0.436211 / 1.386936 (-0.950725) |\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) | 0.006136 / 0.011353 (-0.005217) | 0.004125 / 0.011008 (-0.006883) | 0.050341 / 0.038508 (0.011833) | 0.034547 / 0.023109 (0.011438) | 0.270237 / 0.275898 (-0.005661) | 0.294503 / 0.323480 (-0.028977) | 0.004528 / 0.007986 (-0.003458) | 0.003103 / 0.004328 (-0.001225) | 0.048817 / 0.004250 (0.044566) | 0.041301 / 0.037052 (0.004249) | 0.279461 / 0.258489 (0.020972) | 0.319376 / 0.293841 (0.025535) | 0.032733 / 0.128546 (-0.095813) | 0.012426 / 0.075646 (-0.063221) | 0.060543 / 0.419271 (-0.358729) | 0.034015 / 0.043533 (-0.009518) | 0.267387 / 0.255139 (0.012248) | 0.288590 / 0.283200 (0.005390) | 0.019697 / 0.141683 (-0.121986) | 1.145994 / 1.452155 (-0.306161) | 1.198122 / 1.492716 (-0.294595) |\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) | 0.099091 / 0.018006 (0.081085) | 0.313767 / 0.000490 (0.313277) | 0.000220 / 0.000200 (0.000020) | 0.000054 / 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) | 0.023219 / 0.037411 (-0.014192) | 0.083609 / 0.014526 (0.069084) | 0.089529 / 0.176557 (-0.087028) | 0.131025 / 0.737135 (-0.606110) | 0.091947 / 0.296338 (-0.204391) |\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) | 0.283711 / 0.215209 (0.068502) | 2.811702 / 2.077655 (0.734047) | 1.577720 / 1.504120 (0.073600) | 1.415700 / 1.541195 (-0.125495) | 1.436097 / 1.468490 (-0.032393) | 0.732090 / 4.584777 (-3.852687) | 0.990552 / 3.745712 (-2.755160) | 2.887319 / 5.269862 (-2.382543) | 1.923707 / 4.565676 (-2.641969) | 0.079361 / 0.424275 (-0.344915) | 0.005520 / 0.007607 (-0.002087) | 0.336684 / 0.226044 (0.110639) | 3.325342 / 2.268929 (1.056413) | 1.911853 / 55.444624 (-53.532771) | 1.621450 / 6.876477 (-5.255027) | 1.807964 / 2.142072 (-0.334109) | 0.813958 / 4.805227 (-3.991269) | 0.137564 / 6.500664 (-6.363100) | 0.043151 / 0.075469 (-0.032318) |\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) | 1.002775 / 1.841788 (-0.839013) | 12.526367 / 8.074308 (4.452058) | 10.426992 / 10.191392 (0.235600) | 0.134902 / 0.680424 (-0.545522) | 0.016726 / 0.534201 (-0.517475) | 0.303549 / 0.579283 (-0.275734) | 0.129334 / 0.434364 (-0.305030) | 0.339254 / 0.540337 (-0.201084) | 0.456845 / 1.386936 (-0.930091) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#c5464b32ce03739431235c13f314732201abcfac \"CML watermark\")\n" ]

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[]

[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6964). 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) | 0.005735 / 0.011353 (-0.005618) | 0.003746 / 0.011008 (-0.007263) | 0.063115 / 0.038508 (0.024606) | 0.033557 / 0.023109 (0.010447) | 0.247599 / 0.275898 (-0.028299) | 0.275310 / 0.323480 (-0.048170) | 0.004203 / 0.007986 (-0.003783) | 0.002770 / 0.004328 (-0.001558) | 0.050951 / 0.004250 (0.046700) | 0.046609 / 0.037052 (0.009557) | 0.256237 / 0.258489 (-0.002252) | 0.292050 / 0.293841 (-0.001791) | 0.027991 / 0.128546 (-0.100556) | 0.010367 / 0.075646 (-0.065279) | 0.202295 / 0.419271 (-0.216977) | 0.037287 / 0.043533 (-0.006246) | 0.250330 / 0.255139 (-0.004809) | 0.281250 / 0.283200 (-0.001950) | 0.018832 / 0.141683 (-0.122851) | 1.117303 / 1.452155 (-0.334852) | 1.141593 / 1.492716 (-0.351123) |\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) | 0.097318 / 0.018006 (0.079312) | 0.304853 / 0.000490 (0.304364) | 0.000220 / 0.000200 (0.000020) | 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) | 0.020353 / 0.037411 (-0.017058) | 0.065497 / 0.014526 (0.050971) | 0.076205 / 0.176557 (-0.100351) | 0.122471 / 0.737135 (-0.614665) | 0.079522 / 0.296338 (-0.216816) |\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) | 0.282604 / 0.215209 (0.067395) | 2.743198 / 2.077655 (0.665543) | 1.480436 / 1.504120 (-0.023684) | 1.373935 / 1.541195 (-0.167260) | 1.388901 / 1.468490 (-0.079589) | 0.571961 / 4.584777 (-4.012816) | 2.431790 / 3.745712 (-1.313922) | 2.942126 / 5.269862 (-2.327736) | 1.857361 / 4.565676 (-2.708316) | 0.063535 / 0.424275 (-0.360740) | 0.005039 / 0.007607 (-0.002568) | 0.331726 / 0.226044 (0.105682) | 3.282504 / 2.268929 (1.013576) | 1.852303 / 55.444624 (-53.592321) | 1.506665 / 6.876477 (-5.369812) | 1.577524 / 2.142072 (-0.564548) | 0.646267 / 4.805227 (-4.158960) | 0.118706 / 6.500664 (-6.381958) | 0.043437 / 0.075469 (-0.032033) |\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) | 0.978073 / 1.841788 (-0.863714) | 12.028575 / 8.074308 (3.954267) | 10.066303 / 10.191392 (-0.125090) | 0.131763 / 0.680424 (-0.548661) | 0.016479 / 0.534201 (-0.517722) | 0.286012 / 0.579283 (-0.293271) | 0.266824 / 0.434364 (-0.167540) | 0.328452 / 0.540337 (-0.211885) | 0.414562 / 1.386936 (-0.972374) |\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) | 0.005943 / 0.011353 (-0.005409) | 0.003992 / 0.011008 (-0.007016) | 0.051159 / 0.038508 (0.012651) | 0.033805 / 0.023109 (0.010695) | 0.268425 / 0.275898 (-0.007474) | 0.295662 / 0.323480 (-0.027818) | 0.004473 / 0.007986 (-0.003512) | 0.002910 / 0.004328 (-0.001418) | 0.048595 / 0.004250 (0.044345) | 0.043724 / 0.037052 (0.006671) | 0.280552 / 0.258489 (0.022063) | 0.319052 / 0.293841 (0.025211) | 0.031269 / 0.128546 (-0.097278) | 0.010976 / 0.075646 (-0.064671) | 0.060128 / 0.419271 (-0.359144) | 0.034198 / 0.043533 (-0.009335) | 0.269664 / 0.255139 (0.014525) | 0.292249 / 0.283200 (0.009049) | 0.019950 / 0.141683 (-0.121733) | 1.143073 / 1.452155 (-0.309082) | 1.188553 / 1.492716 (-0.304164) |\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) | 0.095188 / 0.018006 (0.077182) | 0.300207 / 0.000490 (0.299717) | 0.000205 / 0.000200 (0.000005) | 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) | 0.023610 / 0.037411 (-0.013802) | 0.082868 / 0.014526 (0.068342) | 0.089059 / 0.176557 (-0.087498) | 0.131735 / 0.737135 (-0.605401) | 0.091467 / 0.296338 (-0.204872) |\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) | 0.302497 / 0.215209 (0.087287) | 2.985794 / 2.077655 (0.908140) | 1.590783 / 1.504120 (0.086663) | 1.468819 / 1.541195 (-0.072375) | 1.503115 / 1.468490 (0.034625) | 0.575109 / 4.584777 (-4.009668) | 0.972370 / 3.745712 (-2.773342) | 2.727976 / 5.269862 (-2.541886) | 1.793438 / 4.565676 (-2.772238) | 0.068840 / 0.424275 (-0.355435) | 0.005440 / 0.007607 (-0.002167) | 0.351843 / 0.226044 (0.125799) | 3.523108 / 2.268929 (1.254180) | 1.928576 / 55.444624 (-53.516049) | 1.627939 / 6.876477 (-5.248538) | 1.837618 / 2.142072 (-0.304454) | 0.669351 / 4.805227 (-4.135876) | 0.121822 / 6.500664 (-6.378842) | 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) | 1.020081 / 1.841788 (-0.821707) | 13.417448 / 8.074308 (5.343140) | 10.974516 / 10.191392 (0.783124) | 0.135240 / 0.680424 (-0.545184) | 0.017581 / 0.534201 (-0.516620) | 0.289080 / 0.579283 (-0.290203) | 0.127679 / 0.434364 (-0.306685) | 0.331818 / 0.540337 (-0.208520) | 0.453143 / 1.386936 (-0.933793) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#ef2fb358433678b322d275c0bdee3239fa6485b2 \"CML watermark\")\n" ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6963). 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 r-unrelated to this PR, merging", "<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) | 0.005532 / 0.011353 (-0.005821) | 0.004018 / 0.011008 (-0.006991) | 0.064685 / 0.038508 (0.026177) | 0.031303 / 0.023109 (0.008194) | 0.254670 / 0.275898 (-0.021228) | 0.271357 / 0.323480 (-0.052123) | 0.003372 / 0.007986 (-0.004614) | 0.004153 / 0.004328 (-0.000175) | 0.050381 / 0.004250 (0.046131) | 0.046837 / 0.037052 (0.009784) | 0.253166 / 0.258489 (-0.005323) | 0.294257 / 0.293841 (0.000416) | 0.029746 / 0.128546 (-0.098800) | 0.012519 / 0.075646 (-0.063127) | 0.208822 / 0.419271 (-0.210449) | 0.036925 / 0.043533 (-0.006608) | 0.247636 / 0.255139 (-0.007503) | 0.269102 / 0.283200 (-0.014097) | 0.019021 / 0.141683 (-0.122662) | 1.138825 / 1.452155 (-0.313330) | 1.203301 / 1.492716 (-0.289415) |\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) | 0.095950 / 0.018006 (0.077944) | 0.303347 / 0.000490 (0.302857) | 0.000221 / 0.000200 (0.000022) | 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) | 0.019014 / 0.037411 (-0.018397) | 0.062220 / 0.014526 (0.047694) | 0.074811 / 0.176557 (-0.101745) | 0.122917 / 0.737135 (-0.614218) | 0.075765 / 0.296338 (-0.220574) |\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) | 0.288359 / 0.215209 (0.073150) | 2.849491 / 2.077655 (0.771837) | 1.479448 / 1.504120 (-0.024672) | 1.350560 / 1.541195 (-0.190635) | 1.366079 / 1.468490 (-0.102411) | 0.733609 / 4.584777 (-3.851168) | 2.416014 / 3.745712 (-1.329698) | 2.954834 / 5.269862 (-2.315028) | 1.985703 / 4.565676 (-2.579974) | 0.080589 / 0.424275 (-0.343686) | 0.005581 / 0.007607 (-0.002026) | 0.343706 / 0.226044 (0.117661) | 3.416257 / 2.268929 (1.147329) | 1.865937 / 55.444624 (-53.578687) | 1.545911 / 6.876477 (-5.330566) | 1.711004 / 2.142072 (-0.431069) | 0.821231 / 4.805227 (-3.983996) | 0.138865 / 6.500664 (-6.361799) | 0.046466 / 0.075469 (-0.029003) |\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) | 0.965632 / 1.841788 (-0.876155) | 11.812101 / 8.074308 (3.737792) | 9.399156 / 10.191392 (-0.792236) | 0.143325 / 0.680424 (-0.537099) | 0.014824 / 0.534201 (-0.519377) | 0.306143 / 0.579283 (-0.273140) | 0.264063 / 0.434364 (-0.170301) | 0.347820 / 0.540337 (-0.192517) | 0.476818 / 1.386936 (-0.910118) |\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) | 0.005978 / 0.011353 (-0.005375) | 0.004482 / 0.011008 (-0.006526) | 0.053788 / 0.038508 (0.015280) | 0.033963 / 0.023109 (0.010853) | 0.267258 / 0.275898 (-0.008640) | 0.290916 / 0.323480 (-0.032563) | 0.004485 / 0.007986 (-0.003500) | 0.002876 / 0.004328 (-0.001453) | 0.048637 / 0.004250 (0.044386) | 0.042050 / 0.037052 (0.004997) | 0.278607 / 0.258489 (0.020118) | 0.315411 / 0.293841 (0.021570) | 0.032059 / 0.128546 (-0.096487) | 0.012851 / 0.075646 (-0.062795) | 0.061672 / 0.419271 (-0.357600) | 0.034545 / 0.043533 (-0.008988) | 0.262068 / 0.255139 (0.006929) | 0.291197 / 0.283200 (0.007997) | 0.019092 / 0.141683 (-0.122591) | 1.108690 / 1.452155 (-0.343464) | 1.161025 / 1.492716 (-0.331691) |\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) | 0.096775 / 0.018006 (0.078768) | 0.306825 / 0.000490 (0.306335) | 0.000210 / 0.000200 (0.000010) | 0.000054 / 0.000054 (-0.000000) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.023160 / 0.037411 (-0.014251) | 0.078794 / 0.014526 (0.064268) | 0.088954 / 0.176557 (-0.087602) | 0.129488 / 0.737135 (-0.607648) | 0.091239 / 0.296338 (-0.205099) |\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) | 0.292911 / 0.215209 (0.077702) | 2.910802 / 2.077655 (0.833148) | 1.569310 / 1.504120 (0.065191) | 1.433807 / 1.541195 (-0.107388) | 1.478619 / 1.468490 (0.010129) | 0.720982 / 4.584777 (-3.863795) | 0.972104 / 3.745712 (-2.773608) | 3.026941 / 5.269862 (-2.242921) | 1.919170 / 4.565676 (-2.646506) | 0.079292 / 0.424275 (-0.344983) | 0.005227 / 0.007607 (-0.002380) | 0.345363 / 0.226044 (0.119319) | 3.416149 / 2.268929 (1.147221) | 1.938377 / 55.444624 (-53.506248) | 1.626037 / 6.876477 (-5.250440) | 1.644405 / 2.142072 (-0.497668) | 0.802485 / 4.805227 (-4.002742) | 0.135114 / 6.500664 (-6.365550) | 0.042015 / 0.075469 (-0.033454) |\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) | 1.014812 / 1.841788 (-0.826976) | 12.583844 / 8.074308 (4.509536) | 10.522495 / 10.191392 (0.331103) | 0.143336 / 0.680424 (-0.537088) | 0.015843 / 0.534201 (-0.518357) | 0.306556 / 0.579283 (-0.272727) | 0.129654 / 0.434364 (-0.304710) | 0.340442 / 0.540337 (-0.199896) | 0.445220 / 1.386936 (-0.941716) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#5cab892dcd26fb51938634e13e300c6611ab66e0 \"CML watermark\")\n" ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6962). 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) | 0.005520 / 0.011353 (-0.005833) | 0.003989 / 0.011008 (-0.007019) | 0.064786 / 0.038508 (0.026278) | 0.031075 / 0.023109 (0.007966) | 0.241619 / 0.275898 (-0.034279) | 0.275341 / 0.323480 (-0.048139) | 0.003139 / 0.007986 (-0.004847) | 0.002820 / 0.004328 (-0.001508) | 0.049766 / 0.004250 (0.045515) | 0.045047 / 0.037052 (0.007995) | 0.251906 / 0.258489 (-0.006583) | 0.285889 / 0.293841 (-0.007952) | 0.028297 / 0.128546 (-0.100249) | 0.010683 / 0.075646 (-0.064963) | 0.206467 / 0.419271 (-0.212805) | 0.036267 / 0.043533 (-0.007266) | 0.250720 / 0.255139 (-0.004419) | 0.268565 / 0.283200 (-0.014635) | 0.020394 / 0.141683 (-0.121289) | 1.114283 / 1.452155 (-0.337872) | 1.163884 / 1.492716 (-0.328833) |\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) | 0.112698 / 0.018006 (0.094692) | 0.302740 / 0.000490 (0.302251) | 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) | 0.019337 / 0.037411 (-0.018075) | 0.062854 / 0.014526 (0.048328) | 0.077088 / 0.176557 (-0.099468) | 0.120926 / 0.737135 (-0.616209) | 0.075594 / 0.296338 (-0.220744) |\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) | 0.290787 / 0.215209 (0.075578) | 2.867894 / 2.077655 (0.790239) | 1.490043 / 1.504120 (-0.014076) | 1.356383 / 1.541195 (-0.184812) | 1.400229 / 1.468490 (-0.068261) | 0.582076 / 4.584777 (-4.002701) | 2.398270 / 3.745712 (-1.347442) | 2.856459 / 5.269862 (-2.413403) | 1.815545 / 4.565676 (-2.750131) | 0.063259 / 0.424275 (-0.361016) | 0.005056 / 0.007607 (-0.002551) | 0.347699 / 0.226044 (0.121655) | 3.466511 / 2.268929 (1.197582) | 1.862096 / 55.444624 (-53.582528) | 1.532324 / 6.876477 (-5.344152) | 1.599411 / 2.142072 (-0.542661) | 0.657350 / 4.805227 (-4.147878) | 0.118981 / 6.500664 (-6.381683) | 0.042224 / 0.075469 (-0.033245) |\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) | 0.965649 / 1.841788 (-0.876139) | 11.896501 / 8.074308 (3.822193) | 9.873923 / 10.191392 (-0.317469) | 0.141165 / 0.680424 (-0.539258) | 0.013885 / 0.534201 (-0.520316) | 0.291464 / 0.579283 (-0.287819) | 0.273153 / 0.434364 (-0.161211) | 0.324395 / 0.540337 (-0.215942) | 0.422040 / 1.386936 (-0.964897) |\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) | 0.005640 / 0.011353 (-0.005713) | 0.004035 / 0.011008 (-0.006973) | 0.050831 / 0.038508 (0.012323) | 0.032841 / 0.023109 (0.009732) | 0.272226 / 0.275898 (-0.003672) | 0.297880 / 0.323480 (-0.025599) | 0.004397 / 0.007986 (-0.003588) | 0.002762 / 0.004328 (-0.001566) | 0.049887 / 0.004250 (0.045637) | 0.040372 / 0.037052 (0.003320) | 0.286337 / 0.258489 (0.027848) | 0.320015 / 0.293841 (0.026174) | 0.029992 / 0.128546 (-0.098554) | 0.010781 / 0.075646 (-0.064865) | 0.059391 / 0.419271 (-0.359880) | 0.034410 / 0.043533 (-0.009123) | 0.273024 / 0.255139 (0.017885) | 0.288953 / 0.283200 (0.005754) | 0.018072 / 0.141683 (-0.123611) | 1.125742 / 1.452155 (-0.326413) | 1.175233 / 1.492716 (-0.317483) |\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) | 0.093470 / 0.018006 (0.075463) | 0.313248 / 0.000490 (0.312758) | 0.000324 / 0.000200 (0.000124) | 0.000081 / 0.000054 (0.000026) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.023529 / 0.037411 (-0.013882) | 0.077305 / 0.014526 (0.062779) | 0.088916 / 0.176557 (-0.087640) | 0.128792 / 0.737135 (-0.608344) | 0.090141 / 0.296338 (-0.206197) |\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) | 0.291110 / 0.215209 (0.075901) | 2.848118 / 2.077655 (0.770464) | 1.581664 / 1.504120 (0.077544) | 1.446390 / 1.541195 (-0.094804) | 1.452594 / 1.468490 (-0.015896) | 0.571213 / 4.584777 (-4.013564) | 0.976382 / 3.745712 (-2.769330) | 2.756192 / 5.269862 (-2.513670) | 1.770274 / 4.565676 (-2.795403) | 0.064513 / 0.424275 (-0.359763) | 0.005334 / 0.007607 (-0.002273) | 0.347380 / 0.226044 (0.121335) | 3.424800 / 2.268929 (1.155871) | 1.942374 / 55.444624 (-53.502250) | 1.636069 / 6.876477 (-5.240407) | 1.795327 / 2.142072 (-0.346745) | 0.658942 / 4.805227 (-4.146285) | 0.119542 / 6.500664 (-6.381123) | 0.041826 / 0.075469 (-0.033643) |\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) | 1.007230 / 1.841788 (-0.834558) | 12.293084 / 8.074308 (4.218776) | 10.618104 / 10.191392 (0.426712) | 0.133691 / 0.680424 (-0.546733) | 0.015725 / 0.534201 (-0.518476) | 0.288860 / 0.579283 (-0.290423) | 0.130546 / 0.434364 (-0.303818) | 0.327279 / 0.540337 (-0.213059) | 0.428768 / 1.386936 (-0.958168) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#af3acfdfcf76bb980dbac871540e30c2cade0cf9 \"CML watermark\")\n" ]

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[]

[ "We're unlikely to add more features/support for datasets with python loading scripts, which include datasets with manual download. Sorry for the inconvenience" ]

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[]

[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6960). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "Yes!", "<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) | 0.005007 / 0.011353 (-0.006346) | 0.003603 / 0.011008 (-0.007405) | 0.062719 / 0.038508 (0.024211) | 0.029327 / 0.023109 (0.006217) | 0.250360 / 0.275898 (-0.025538) | 0.265095 / 0.323480 (-0.058385) | 0.004205 / 0.007986 (-0.003781) | 0.002713 / 0.004328 (-0.001616) | 0.049209 / 0.004250 (0.044958) | 0.045162 / 0.037052 (0.008110) | 0.260439 / 0.258489 (0.001950) | 0.287778 / 0.293841 (-0.006063) | 0.027458 / 0.128546 (-0.101088) | 0.010169 / 0.075646 (-0.065477) | 0.199487 / 0.419271 (-0.219784) | 0.036584 / 0.043533 (-0.006949) | 0.254523 / 0.255139 (-0.000616) | 0.269902 / 0.283200 (-0.013298) | 0.017138 / 0.141683 (-0.124545) | 1.099285 / 1.452155 (-0.352869) | 1.150878 / 1.492716 (-0.341839) |\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) | 0.092868 / 0.018006 (0.074862) | 0.300421 / 0.000490 (0.299932) | 0.000213 / 0.000200 (0.000013) | 0.000053 / 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) | 0.018810 / 0.037411 (-0.018601) | 0.062341 / 0.014526 (0.047815) | 0.074779 / 0.176557 (-0.101777) | 0.120641 / 0.737135 (-0.616494) | 0.075020 / 0.296338 (-0.221318) |\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) | 0.277782 / 0.215209 (0.062573) | 2.716427 / 2.077655 (0.638772) | 1.434204 / 1.504120 (-0.069916) | 1.335990 / 1.541195 (-0.205205) | 1.336636 / 1.468490 (-0.131854) | 0.557562 / 4.584777 (-4.027215) | 2.323517 / 3.745712 (-1.422196) | 2.647937 / 5.269862 (-2.621925) | 1.728735 / 4.565676 (-2.836941) | 0.061888 / 0.424275 (-0.362387) | 0.004981 / 0.007607 (-0.002627) | 0.329429 / 0.226044 (0.103385) | 3.324708 / 2.268929 (1.055779) | 1.832641 / 55.444624 (-53.611983) | 1.514386 / 6.876477 (-5.362091) | 1.656912 / 2.142072 (-0.485160) | 0.630706 / 4.805227 (-4.174521) | 0.116250 / 6.500664 (-6.384414) | 0.042598 / 0.075469 (-0.032871) |\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) | 0.969217 / 1.841788 (-0.872570) | 11.232580 / 8.074308 (3.158272) | 9.541306 / 10.191392 (-0.650086) | 0.139544 / 0.680424 (-0.540880) | 0.014441 / 0.534201 (-0.519760) | 0.285834 / 0.579283 (-0.293449) | 0.261950 / 0.434364 (-0.172414) | 0.325449 / 0.540337 (-0.214889) | 0.415501 / 1.386936 (-0.971435) |\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) | 0.005422 / 0.011353 (-0.005931) | 0.003528 / 0.011008 (-0.007480) | 0.049582 / 0.038508 (0.011074) | 0.032683 / 0.023109 (0.009574) | 0.277309 / 0.275898 (0.001411) | 0.298598 / 0.323480 (-0.024882) | 0.004325 / 0.007986 (-0.003661) | 0.002741 / 0.004328 (-0.001588) | 0.047933 / 0.004250 (0.043683) | 0.040778 / 0.037052 (0.003726) | 0.287492 / 0.258489 (0.029003) | 0.311408 / 0.293841 (0.017567) | 0.029482 / 0.128546 (-0.099064) | 0.010630 / 0.075646 (-0.065016) | 0.057745 / 0.419271 (-0.361526) | 0.033501 / 0.043533 (-0.010031) | 0.279880 / 0.255139 (0.024741) | 0.297421 / 0.283200 (0.014221) | 0.017907 / 0.141683 (-0.123776) | 1.152221 / 1.452155 (-0.299934) | 1.189332 / 1.492716 (-0.303385) |\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) | 0.094464 / 0.018006 (0.076457) | 0.300769 / 0.000490 (0.300279) | 0.000196 / 0.000200 (-0.000004) | 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) | 0.022232 / 0.037411 (-0.015179) | 0.076626 / 0.014526 (0.062100) | 0.087807 / 0.176557 (-0.088750) | 0.128847 / 0.737135 (-0.608288) | 0.092135 / 0.296338 (-0.204203) |\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) | 0.299013 / 0.215209 (0.083804) | 2.929788 / 2.077655 (0.852133) | 1.614185 / 1.504120 (0.110065) | 1.486720 / 1.541195 (-0.054475) | 1.492473 / 1.468490 (0.023983) | 0.563699 / 4.584777 (-4.021078) | 0.928820 / 3.745712 (-2.816892) | 2.597271 / 5.269862 (-2.672590) | 1.716534 / 4.565676 (-2.849142) | 0.062568 / 0.424275 (-0.361707) | 0.005168 / 0.007607 (-0.002439) | 0.353781 / 0.226044 (0.127737) | 3.493732 / 2.268929 (1.224803) | 2.018343 / 55.444624 (-53.426282) | 1.694516 / 6.876477 (-5.181961) | 1.796950 / 2.142072 (-0.345123) | 0.634846 / 4.805227 (-4.170382) | 0.115230 / 6.500664 (-6.385434) | 0.040816 / 0.075469 (-0.034654) |\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) | 0.986212 / 1.841788 (-0.855575) | 11.954392 / 8.074308 (3.880084) | 10.299670 / 10.191392 (0.108278) | 0.128358 / 0.680424 (-0.552066) | 0.016313 / 0.534201 (-0.517888) | 0.289621 / 0.579283 (-0.289662) | 0.124708 / 0.434364 (-0.309656) | 0.325269 / 0.540337 (-0.215068) | 0.415133 / 1.386936 (-0.971803) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#97513be330114a8aa07e5199ec252ac662aeb76d \"CML watermark\")\n" ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6959). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "Test should be fixed by https://github.com/huggingface/datasets/pull/6959/commits/ef8f7cee79ffb070d9b5190f21128fc523b3d3ee (tested locally). Let's see what CI says :crossed_fingers: ", "<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) | 0.005678 / 0.011353 (-0.005675) | 0.004119 / 0.011008 (-0.006889) | 0.063901 / 0.038508 (0.025393) | 0.032071 / 0.023109 (0.008961) | 0.243182 / 0.275898 (-0.032716) | 0.280709 / 0.323480 (-0.042770) | 0.004195 / 0.007986 (-0.003791) | 0.002810 / 0.004328 (-0.001518) | 0.048722 / 0.004250 (0.044472) | 0.049381 / 0.037052 (0.012328) | 0.257816 / 0.258489 (-0.000673) | 0.288460 / 0.293841 (-0.005381) | 0.028518 / 0.128546 (-0.100029) | 0.010775 / 0.075646 (-0.064871) | 0.203149 / 0.419271 (-0.216122) | 0.038792 / 0.043533 (-0.004741) | 0.248502 / 0.255139 (-0.006637) | 0.268251 / 0.283200 (-0.014949) | 0.019536 / 0.141683 (-0.122147) | 1.133935 / 1.452155 (-0.318220) | 1.182855 / 1.492716 (-0.309862) |\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) | 0.097531 / 0.018006 (0.079525) | 0.303612 / 0.000490 (0.303122) | 0.000222 / 0.000200 (0.000022) | 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) | 0.019670 / 0.037411 (-0.017741) | 0.063439 / 0.014526 (0.048913) | 0.075119 / 0.176557 (-0.101438) | 0.122419 / 0.737135 (-0.614717) | 0.076965 / 0.296338 (-0.219374) |\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) | 0.286780 / 0.215209 (0.071571) | 2.811860 / 2.077655 (0.734206) | 1.485165 / 1.504120 (-0.018954) | 1.373296 / 1.541195 (-0.167898) | 1.412700 / 1.468490 (-0.055790) | 0.566442 / 4.584777 (-4.018335) | 2.382616 / 3.745712 (-1.363096) | 2.677214 / 5.269862 (-2.592647) | 1.760073 / 4.565676 (-2.805603) | 0.062673 / 0.424275 (-0.361602) | 0.005050 / 0.007607 (-0.002557) | 0.341701 / 0.226044 (0.115657) | 3.321182 / 2.268929 (1.052253) | 1.811715 / 55.444624 (-53.632909) | 1.554986 / 6.876477 (-5.321491) | 1.727448 / 2.142072 (-0.414624) | 0.642193 / 4.805227 (-4.163034) | 0.117878 / 6.500664 (-6.382786) | 0.042814 / 0.075469 (-0.032655) |\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) | 0.985894 / 1.841788 (-0.855894) | 12.195975 / 8.074308 (4.121667) | 9.890180 / 10.191392 (-0.301212) | 0.142638 / 0.680424 (-0.537786) | 0.015207 / 0.534201 (-0.518994) | 0.283140 / 0.579283 (-0.296143) | 0.266016 / 0.434364 (-0.168348) | 0.325518 / 0.540337 (-0.214820) | 0.418994 / 1.386936 (-0.967942) |\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) | 0.005978 / 0.011353 (-0.005374) | 0.003915 / 0.011008 (-0.007093) | 0.051592 / 0.038508 (0.013084) | 0.033338 / 0.023109 (0.010229) | 0.267925 / 0.275898 (-0.007973) | 0.296011 / 0.323480 (-0.027469) | 0.004503 / 0.007986 (-0.003483) | 0.002854 / 0.004328 (-0.001475) | 0.049958 / 0.004250 (0.045707) | 0.041708 / 0.037052 (0.004656) | 0.287185 / 0.258489 (0.028696) | 0.322715 / 0.293841 (0.028874) | 0.030088 / 0.128546 (-0.098458) | 0.010709 / 0.075646 (-0.064938) | 0.059736 / 0.419271 (-0.359536) | 0.034294 / 0.043533 (-0.009239) | 0.264316 / 0.255139 (0.009177) | 0.285471 / 0.283200 (0.002272) | 0.019197 / 0.141683 (-0.122486) | 1.135571 / 1.452155 (-0.316583) | 1.190019 / 1.492716 (-0.302698) |\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) | 0.099251 / 0.018006 (0.081245) | 0.305357 / 0.000490 (0.304867) | 0.000215 / 0.000200 (0.000015) | 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) | 0.023206 / 0.037411 (-0.014205) | 0.077835 / 0.014526 (0.063310) | 0.090242 / 0.176557 (-0.086315) | 0.131208 / 0.737135 (-0.605928) | 0.091726 / 0.296338 (-0.204612) |\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) | 0.292487 / 0.215209 (0.077278) | 2.837044 / 2.077655 (0.759389) | 1.553155 / 1.504120 (0.049035) | 1.433645 / 1.541195 (-0.107550) | 1.476702 / 1.468490 (0.008212) | 0.561926 / 4.584777 (-4.022851) | 0.954630 / 3.745712 (-2.791082) | 2.752286 / 5.269862 (-2.517575) | 1.782746 / 4.565676 (-2.782931) | 0.062984 / 0.424275 (-0.361291) | 0.005056 / 0.007607 (-0.002551) | 0.341700 / 0.226044 (0.115656) | 3.343726 / 2.268929 (1.074798) | 1.953390 / 55.444624 (-53.491234) | 1.616989 / 6.876477 (-5.259488) | 1.785104 / 2.142072 (-0.356969) | 0.643465 / 4.805227 (-4.161763) | 0.115905 / 6.500664 (-6.384759) | 0.041678 / 0.075469 (-0.033791) |\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) | 1.000237 / 1.841788 (-0.841550) | 12.633517 / 8.074308 (4.559208) | 10.553485 / 10.191392 (0.362092) | 0.143188 / 0.680424 (-0.537236) | 0.016020 / 0.534201 (-0.518181) | 0.286739 / 0.579283 (-0.292544) | 0.128488 / 0.434364 (-0.305876) | 0.321932 / 0.540337 (-0.218405) | 0.418635 / 1.386936 (-0.968301) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#9510252f03fded02b8cc87ca6dfa3195d17594ba \"CML watermark\")\n" ]

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[ "I can load public dataset, but for my private dataset it fails", "https://huggingface.co/docs/datasets/upload_dataset", "I have checked the API HTTP link. Repository Not Found for url: https://huggingface.co/api/datasets/xxx/xxx.\r\n\r\n\r\n\r\nIt just works fine.", "It seems that everything is in a mass huh....\r\n\r\n\r\n", "https://huggingface.co/datasets/rajpurkar/squad/blob/main/squad.py fails again", "https://github.com/huggingface/datasets/blob/main/templates/new_dataset_script.py#L81 can not use this, too complex. I just need a def to load my file to a dict", "I am facing the same issue. Did you find a fix?", "You should authenticate to be able to access private or gated repos: https://huggingface.co/docs/hub/datasets-gated#access-gated-datasets-as-a-user" ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6957). 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) | 0.005371 / 0.011353 (-0.005982) | 0.003834 / 0.011008 (-0.007174) | 0.063032 / 0.038508 (0.024524) | 0.031623 / 0.023109 (0.008514) | 0.250008 / 0.275898 (-0.025890) | 0.273998 / 0.323480 (-0.049482) | 0.004114 / 0.007986 (-0.003871) | 0.002821 / 0.004328 (-0.001508) | 0.049470 / 0.004250 (0.045220) | 0.046586 / 0.037052 (0.009534) | 0.276807 / 0.258489 (0.018318) | 0.288607 / 0.293841 (-0.005234) | 0.027427 / 0.128546 (-0.101119) | 0.010634 / 0.075646 (-0.065012) | 0.202451 / 0.419271 (-0.216821) | 0.036346 / 0.043533 (-0.007187) | 0.250426 / 0.255139 (-0.004713) | 0.274104 / 0.283200 (-0.009096) | 0.018461 / 0.141683 (-0.123222) | 1.120326 / 1.452155 (-0.331829) | 1.157635 / 1.492716 (-0.335081) |\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) | 0.102287 / 0.018006 (0.084281) | 0.313145 / 0.000490 (0.312655) | 0.000255 / 0.000200 (0.000055) | 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) | 0.019494 / 0.037411 (-0.017917) | 0.063252 / 0.014526 (0.048727) | 0.075318 / 0.176557 (-0.101239) | 0.122194 / 0.737135 (-0.614942) | 0.076837 / 0.296338 (-0.219501) |\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) | 0.284098 / 0.215209 (0.068889) | 2.822301 / 2.077655 (0.744647) | 1.490185 / 1.504120 (-0.013935) | 1.366723 / 1.541195 (-0.174472) | 1.398832 / 1.468490 (-0.069658) | 0.563661 / 4.584777 (-4.021116) | 2.385129 / 3.745712 (-1.360583) | 2.689823 / 5.269862 (-2.580039) | 1.731271 / 4.565676 (-2.834405) | 0.063351 / 0.424275 (-0.360924) | 0.004974 / 0.007607 (-0.002633) | 0.332163 / 0.226044 (0.106119) | 3.314906 / 2.268929 (1.045977) | 1.811331 / 55.444624 (-53.633294) | 1.513357 / 6.876477 (-5.363120) | 1.718454 / 2.142072 (-0.423618) | 0.639663 / 4.805227 (-4.165564) | 0.120377 / 6.500664 (-6.380287) | 0.043254 / 0.075469 (-0.032215) |\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) | 0.978534 / 1.841788 (-0.863253) | 11.622313 / 8.074308 (3.548005) | 9.608732 / 10.191392 (-0.582660) | 0.131339 / 0.680424 (-0.549085) | 0.015226 / 0.534201 (-0.518975) | 0.287317 / 0.579283 (-0.291966) | 0.266647 / 0.434364 (-0.167717) | 0.324243 / 0.540337 (-0.216094) | 0.442025 / 1.386936 (-0.944911) |\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) | 0.005673 / 0.011353 (-0.005680) | 0.003722 / 0.011008 (-0.007286) | 0.049483 / 0.038508 (0.010975) | 0.033308 / 0.023109 (0.010199) | 0.261912 / 0.275898 (-0.013986) | 0.291151 / 0.323480 (-0.032329) | 0.004389 / 0.007986 (-0.003596) | 0.002762 / 0.004328 (-0.001567) | 0.048970 / 0.004250 (0.044719) | 0.041509 / 0.037052 (0.004457) | 0.273288 / 0.258489 (0.014798) | 0.308351 / 0.293841 (0.014510) | 0.029958 / 0.128546 (-0.098589) | 0.010500 / 0.075646 (-0.065146) | 0.058253 / 0.419271 (-0.361019) | 0.033820 / 0.043533 (-0.009713) | 0.261089 / 0.255139 (0.005950) | 0.282179 / 0.283200 (-0.001021) | 0.018543 / 0.141683 (-0.123140) | 1.121303 / 1.452155 (-0.330852) | 1.166141 / 1.492716 (-0.326575) |\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) | 0.099209 / 0.018006 (0.081203) | 0.316920 / 0.000490 (0.316430) | 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) | 0.023339 / 0.037411 (-0.014072) | 0.077127 / 0.014526 (0.062602) | 0.088160 / 0.176557 (-0.088396) | 0.129449 / 0.737135 (-0.607686) | 0.093159 / 0.296338 (-0.203180) |\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) | 0.281262 / 0.215209 (0.066053) | 2.797504 / 2.077655 (0.719850) | 1.513354 / 1.504120 (0.009234) | 1.383034 / 1.541195 (-0.158161) | 1.395202 / 1.468490 (-0.073288) | 0.563180 / 4.584777 (-4.021597) | 0.979330 / 3.745712 (-2.766383) | 2.674008 / 5.269862 (-2.595853) | 1.762174 / 4.565676 (-2.803502) | 0.062333 / 0.424275 (-0.361942) | 0.004991 / 0.007607 (-0.002616) | 0.336043 / 0.226044 (0.109999) | 3.313500 / 2.268929 (1.044571) | 1.848083 / 55.444624 (-53.596541) | 1.554723 / 6.876477 (-5.321754) | 1.743485 / 2.142072 (-0.398587) | 0.657117 / 4.805227 (-4.148111) | 0.115736 / 6.500664 (-6.384928) | 0.040527 / 0.075469 (-0.034942) |\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) | 1.005876 / 1.841788 (-0.835911) | 12.525895 / 8.074308 (4.451587) | 10.492961 / 10.191392 (0.301569) | 0.143443 / 0.680424 (-0.536981) | 0.016652 / 0.534201 (-0.517548) | 0.288236 / 0.579283 (-0.291047) | 0.131401 / 0.434364 (-0.302963) | 0.322885 / 0.540337 (-0.217452) | 0.416048 / 1.386936 (-0.970888) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#6548e0e282aeeda7bfb18beafbc65ebecd780c63 \"CML watermark\")\n" ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6956). 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) | 0.005348 / 0.011353 (-0.006005) | 0.003785 / 0.011008 (-0.007223) | 0.061674 / 0.038508 (0.023166) | 0.032127 / 0.023109 (0.009017) | 0.247095 / 0.275898 (-0.028803) | 0.276466 / 0.323480 (-0.047014) | 0.004197 / 0.007986 (-0.003789) | 0.002734 / 0.004328 (-0.001594) | 0.049604 / 0.004250 (0.045354) | 0.048553 / 0.037052 (0.011500) | 0.253230 / 0.258489 (-0.005259) | 0.286954 / 0.293841 (-0.006887) | 0.028181 / 0.128546 (-0.100365) | 0.010602 / 0.075646 (-0.065044) | 0.200719 / 0.419271 (-0.218552) | 0.037278 / 0.043533 (-0.006254) | 0.251565 / 0.255139 (-0.003574) | 0.269026 / 0.283200 (-0.014174) | 0.017632 / 0.141683 (-0.124050) | 1.136216 / 1.452155 (-0.315939) | 1.181158 / 1.492716 (-0.311559) |\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) | 0.004892 / 0.018006 (-0.013114) | 0.312921 / 0.000490 (0.312431) | 0.000247 / 0.000200 (0.000047) | 0.000054 / 0.000054 (-0.000000) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.019303 / 0.037411 (-0.018108) | 0.062699 / 0.014526 (0.048174) | 0.075227 / 0.176557 (-0.101329) | 0.122919 / 0.737135 (-0.614217) | 0.076506 / 0.296338 (-0.219833) |\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) | 0.277299 / 0.215209 (0.062090) | 2.754771 / 2.077655 (0.677116) | 1.457164 / 1.504120 (-0.046956) | 1.318878 / 1.541195 (-0.222317) | 1.374245 / 1.468490 (-0.094245) | 0.566253 / 4.584777 (-4.018524) | 2.352589 / 3.745712 (-1.393123) | 2.764263 / 5.269862 (-2.505599) | 1.843141 / 4.565676 (-2.722535) | 0.063996 / 0.424275 (-0.360279) | 0.005045 / 0.007607 (-0.002562) | 0.336703 / 0.226044 (0.110658) | 3.342538 / 2.268929 (1.073609) | 1.836664 / 55.444624 (-53.607960) | 1.528901 / 6.876477 (-5.347576) | 1.769562 / 2.142072 (-0.372511) | 0.674192 / 4.805227 (-4.131035) | 0.122421 / 6.500664 (-6.378243) | 0.043714 / 0.075469 (-0.031756) |\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) | 0.989432 / 1.841788 (-0.852356) | 12.178341 / 8.074308 (4.104033) | 9.730838 / 10.191392 (-0.460554) | 0.146751 / 0.680424 (-0.533673) | 0.014720 / 0.534201 (-0.519481) | 0.285821 / 0.579283 (-0.293462) | 0.266474 / 0.434364 (-0.167889) | 0.327886 / 0.540337 (-0.212451) | 0.455672 / 1.386936 (-0.931264) |\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) | 0.005691 / 0.011353 (-0.005662) | 0.004089 / 0.011008 (-0.006919) | 0.049878 / 0.038508 (0.011370) | 0.033578 / 0.023109 (0.010469) | 0.268295 / 0.275898 (-0.007603) | 0.288918 / 0.323480 (-0.034561) | 0.005092 / 0.007986 (-0.002894) | 0.002916 / 0.004328 (-0.001412) | 0.049489 / 0.004250 (0.045239) | 0.042495 / 0.037052 (0.005442) | 0.276253 / 0.258489 (0.017764) | 0.313321 / 0.293841 (0.019480) | 0.029386 / 0.128546 (-0.099160) | 0.010926 / 0.075646 (-0.064720) | 0.071747 / 0.419271 (-0.347525) | 0.033642 / 0.043533 (-0.009891) | 0.264950 / 0.255139 (0.009811) | 0.282962 / 0.283200 (-0.000238) | 0.018878 / 0.141683 (-0.122805) | 1.170685 / 1.452155 (-0.281470) | 1.198321 / 1.492716 (-0.294396) |\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) | 0.100422 / 0.018006 (0.082415) | 0.311750 / 0.000490 (0.311260) | 0.000235 / 0.000200 (0.000035) | 0.000063 / 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) | 0.023093 / 0.037411 (-0.014318) | 0.076934 / 0.014526 (0.062408) | 0.088959 / 0.176557 (-0.087598) | 0.129511 / 0.737135 (-0.607624) | 0.090151 / 0.296338 (-0.206187) |\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) | 0.301646 / 0.215209 (0.086437) | 2.961780 / 2.077655 (0.884126) | 1.656051 / 1.504120 (0.151931) | 1.533154 / 1.541195 (-0.008041) | 1.585152 / 1.468490 (0.116662) | 0.582157 / 4.584777 (-4.002620) | 0.954881 / 3.745712 (-2.790831) | 2.813174 / 5.269862 (-2.456688) | 1.842840 / 4.565676 (-2.722837) | 0.065598 / 0.424275 (-0.358677) | 0.005306 / 0.007607 (-0.002301) | 0.359610 / 0.226044 (0.133565) | 3.575320 / 2.268929 (1.306391) | 2.015327 / 55.444624 (-53.429297) | 1.734086 / 6.876477 (-5.142391) | 1.919081 / 2.142072 (-0.222991) | 0.671178 / 4.805227 (-4.134049) | 0.120109 / 6.500664 (-6.380555) | 0.042353 / 0.075469 (-0.033116) |\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) | 1.011726 / 1.841788 (-0.830062) | 13.007806 / 8.074308 (4.933498) | 10.632486 / 10.191392 (0.441094) | 0.148535 / 0.680424 (-0.531889) | 0.015988 / 0.534201 (-0.518213) | 0.290023 / 0.579283 (-0.289260) | 0.130685 / 0.434364 (-0.303679) | 0.322912 / 0.540337 (-0.217425) | 0.420596 / 1.386936 (-0.966340) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#336512dcba4fdb4c349d5ecb632b6ced80e038d5 \"CML watermark\")\n" ]

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[ "<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) | 0.005507 / 0.011353 (-0.005845) | 0.003757 / 0.011008 (-0.007251) | 0.063274 / 0.038508 (0.024766) | 0.029720 / 0.023109 (0.006610) | 0.247974 / 0.275898 (-0.027924) | 0.272283 / 0.323480 (-0.051197) | 0.004186 / 0.007986 (-0.003799) | 0.002820 / 0.004328 (-0.001508) | 0.049070 / 0.004250 (0.044820) | 0.050026 / 0.037052 (0.012973) | 0.256501 / 0.258489 (-0.001988) | 0.297082 / 0.293841 (0.003241) | 0.028549 / 0.128546 (-0.099997) | 0.010361 / 0.075646 (-0.065285) | 0.213202 / 0.419271 (-0.206070) | 0.038117 / 0.043533 (-0.005416) | 0.258878 / 0.255139 (0.003739) | 0.282980 / 0.283200 (-0.000220) | 0.018911 / 0.141683 (-0.122772) | 1.118857 / 1.452155 (-0.333298) | 1.157763 / 1.492716 (-0.334953) |\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) | 0.004499 / 0.018006 (-0.013507) | 0.310445 / 0.000490 (0.309956) | 0.000218 / 0.000200 (0.000018) | 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) | 0.019275 / 0.037411 (-0.018137) | 0.063257 / 0.014526 (0.048731) | 0.075833 / 0.176557 (-0.100724) | 0.122323 / 0.737135 (-0.614812) | 0.079046 / 0.296338 (-0.217292) |\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) | 0.292811 / 0.215209 (0.077602) | 2.903501 / 2.077655 (0.825846) | 1.592434 / 1.504120 (0.088314) | 1.450833 / 1.541195 (-0.090362) | 1.481285 / 1.468490 (0.012795) | 0.570150 / 4.584777 (-4.014627) | 2.388618 / 3.745712 (-1.357094) | 2.699322 / 5.269862 (-2.570540) | 1.781405 / 4.565676 (-2.784272) | 0.063451 / 0.424275 (-0.360824) | 0.004979 / 0.007607 (-0.002628) | 0.353346 / 0.226044 (0.127302) | 3.541217 / 2.268929 (1.272289) | 1.972335 / 55.444624 (-53.472289) | 1.634780 / 6.876477 (-5.241697) | 1.815944 / 2.142072 (-0.326128) | 0.651559 / 4.805227 (-4.153669) | 0.118398 / 6.500664 (-6.382266) | 0.041962 / 0.075469 (-0.033507) |\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) | 0.971435 / 1.841788 (-0.870352) | 11.843740 / 8.074308 (3.769431) | 9.716333 / 10.191392 (-0.475059) | 0.145923 / 0.680424 (-0.534501) | 0.015073 / 0.534201 (-0.519128) | 0.293307 / 0.579283 (-0.285976) | 0.265505 / 0.434364 (-0.168859) | 0.327578 / 0.540337 (-0.212760) | 0.436409 / 1.386936 (-0.950527) |\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) | 0.005647 / 0.011353 (-0.005706) | 0.003669 / 0.011008 (-0.007339) | 0.050234 / 0.038508 (0.011726) | 0.033033 / 0.023109 (0.009924) | 0.269303 / 0.275898 (-0.006595) | 0.282472 / 0.323480 (-0.041008) | 0.004283 / 0.007986 (-0.003703) | 0.002821 / 0.004328 (-0.001507) | 0.050887 / 0.004250 (0.046637) | 0.041618 / 0.037052 (0.004565) | 0.277628 / 0.258489 (0.019139) | 0.310539 / 0.293841 (0.016698) | 0.030036 / 0.128546 (-0.098511) | 0.010401 / 0.075646 (-0.065245) | 0.058845 / 0.419271 (-0.360427) | 0.033676 / 0.043533 (-0.009857) | 0.261148 / 0.255139 (0.006009) | 0.295232 / 0.283200 (0.012032) | 0.018603 / 0.141683 (-0.123080) | 1.132182 / 1.452155 (-0.319972) | 1.173763 / 1.492716 (-0.318953) |\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) | 0.100594 / 0.018006 (0.082588) | 0.308101 / 0.000490 (0.307611) | 0.000217 / 0.000200 (0.000017) | 0.000055 / 0.000054 (0.000000) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.023040 / 0.037411 (-0.014371) | 0.080676 / 0.014526 (0.066150) | 0.094687 / 0.176557 (-0.081870) | 0.129780 / 0.737135 (-0.607356) | 0.092241 / 0.296338 (-0.204097) |\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) | 0.294799 / 0.215209 (0.079590) | 2.957570 / 2.077655 (0.879915) | 1.576795 / 1.504120 (0.072675) | 1.446869 / 1.541195 (-0.094326) | 1.463133 / 1.468490 (-0.005357) | 0.568511 / 4.584777 (-4.016266) | 1.011502 / 3.745712 (-2.734211) | 2.759571 / 5.269862 (-2.510291) | 1.771738 / 4.565676 (-2.793939) | 0.064104 / 0.424275 (-0.360171) | 0.005160 / 0.007607 (-0.002448) | 0.347554 / 0.226044 (0.121510) | 3.463905 / 2.268929 (1.194976) | 1.931843 / 55.444624 (-53.512781) | 1.622765 / 6.876477 (-5.253712) | 1.809146 / 2.142072 (-0.332926) | 0.653388 / 4.805227 (-4.151839) | 0.122703 / 6.500664 (-6.377961) | 0.041680 / 0.075469 (-0.033790) |\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) | 1.000428 / 1.841788 (-0.841359) | 12.503003 / 8.074308 (4.428695) | 10.434802 / 10.191392 (0.243410) | 0.144684 / 0.680424 (-0.535740) | 0.015988 / 0.534201 (-0.518213) | 0.287179 / 0.579283 (-0.292104) | 0.124811 / 0.434364 (-0.309553) | 0.327855 / 0.540337 (-0.212482) | 0.425144 / 1.386936 (-0.961792) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#f7170067f819222153fcd45682db61279bdfe673 \"CML watermark\")\n" ]

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[]

[]

[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6954). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "yay! 🎉 ", "<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) | 0.004881 / 0.011353 (-0.006472) | 0.003246 / 0.011008 (-0.007762) | 0.062496 / 0.038508 (0.023988) | 0.030760 / 0.023109 (0.007651) | 0.241500 / 0.275898 (-0.034398) | 0.272073 / 0.323480 (-0.051407) | 0.004123 / 0.007986 (-0.003863) | 0.002796 / 0.004328 (-0.001533) | 0.049015 / 0.004250 (0.044764) | 0.047095 / 0.037052 (0.010043) | 0.257002 / 0.258489 (-0.001487) | 0.287602 / 0.293841 (-0.006239) | 0.027281 / 0.128546 (-0.101265) | 0.010132 / 0.075646 (-0.065514) | 0.203699 / 0.419271 (-0.215572) | 0.036553 / 0.043533 (-0.006980) | 0.246221 / 0.255139 (-0.008918) | 0.268137 / 0.283200 (-0.015062) | 0.017260 / 0.141683 (-0.124423) | 1.100677 / 1.452155 (-0.351478) | 1.148367 / 1.492716 (-0.344349) |\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) | 0.102519 / 0.018006 (0.084513) | 0.301929 / 0.000490 (0.301439) | 0.000223 / 0.000200 (0.000023) | 0.000046 / 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) | 0.018590 / 0.037411 (-0.018821) | 0.061615 / 0.014526 (0.047089) | 0.074579 / 0.176557 (-0.101978) | 0.121415 / 0.737135 (-0.615720) | 0.075696 / 0.296338 (-0.220642) |\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) | 0.283842 / 0.215209 (0.068633) | 2.788321 / 2.077655 (0.710666) | 1.481376 / 1.504120 (-0.022743) | 1.356064 / 1.541195 (-0.185131) | 1.380592 / 1.468490 (-0.087898) | 0.575577 / 4.584777 (-4.009199) | 2.471858 / 3.745712 (-1.273854) | 2.760769 / 5.269862 (-2.509093) | 1.808638 / 4.565676 (-2.757038) | 0.064930 / 0.424275 (-0.359345) | 0.005056 / 0.007607 (-0.002551) | 0.337794 / 0.226044 (0.111750) | 3.359444 / 2.268929 (1.090515) | 1.829540 / 55.444624 (-53.615084) | 1.518660 / 6.876477 (-5.357817) | 1.671612 / 2.142072 (-0.470460) | 0.664286 / 4.805227 (-4.140941) | 0.119593 / 6.500664 (-6.381071) | 0.042519 / 0.075469 (-0.032950) |\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) | 0.993152 / 1.841788 (-0.848636) | 11.733054 / 8.074308 (3.658746) | 9.746734 / 10.191392 (-0.444658) | 0.143026 / 0.680424 (-0.537398) | 0.014900 / 0.534201 (-0.519301) | 0.292243 / 0.579283 (-0.287040) | 0.261301 / 0.434364 (-0.173063) | 0.330838 / 0.540337 (-0.209500) | 0.523719 / 1.386936 (-0.863217) |\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) | 0.005707 / 0.011353 (-0.005646) | 0.003523 / 0.011008 (-0.007485) | 0.052265 / 0.038508 (0.013757) | 0.034296 / 0.023109 (0.011187) | 0.266589 / 0.275898 (-0.009309) | 0.288441 / 0.323480 (-0.035039) | 0.004507 / 0.007986 (-0.003478) | 0.002745 / 0.004328 (-0.001583) | 0.049417 / 0.004250 (0.045167) | 0.042679 / 0.037052 (0.005627) | 0.278518 / 0.258489 (0.020029) | 0.328751 / 0.293841 (0.034911) | 0.029530 / 0.128546 (-0.099016) | 0.010373 / 0.075646 (-0.065274) | 0.058207 / 0.419271 (-0.361064) | 0.033434 / 0.043533 (-0.010099) | 0.267902 / 0.255139 (0.012763) | 0.288192 / 0.283200 (0.004993) | 0.018866 / 0.141683 (-0.122817) | 1.132734 / 1.452155 (-0.319421) | 1.172879 / 1.492716 (-0.319837) |\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) | 0.097787 / 0.018006 (0.079780) | 0.305509 / 0.000490 (0.305019) | 0.000268 / 0.000200 (0.000068) | 0.000060 / 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) | 0.023230 / 0.037411 (-0.014181) | 0.076637 / 0.014526 (0.062111) | 0.088386 / 0.176557 (-0.088171) | 0.131079 / 0.737135 (-0.606057) | 0.091142 / 0.296338 (-0.205197) |\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) | 0.295586 / 0.215209 (0.080377) | 2.872090 / 2.077655 (0.794435) | 1.538152 / 1.504120 (0.034032) | 1.405695 / 1.541195 (-0.135500) | 1.421058 / 1.468490 (-0.047432) | 0.561179 / 4.584777 (-4.023598) | 0.943954 / 3.745712 (-2.801758) | 2.684381 / 5.269862 (-2.585481) | 1.757457 / 4.565676 (-2.808220) | 0.062903 / 0.424275 (-0.361372) | 0.004998 / 0.007607 (-0.002610) | 0.370290 / 0.226044 (0.144245) | 3.374988 / 2.268929 (1.106059) | 1.899282 / 55.444624 (-53.545342) | 1.598787 / 6.876477 (-5.277690) | 1.735371 / 2.142072 (-0.406702) | 0.647367 / 4.805227 (-4.157860) | 0.116975 / 6.500664 (-6.383689) | 0.040811 / 0.075469 (-0.034658) |\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) | 0.996380 / 1.841788 (-0.845408) | 12.225657 / 8.074308 (4.151349) | 10.291221 / 10.191392 (0.099829) | 0.142791 / 0.680424 (-0.537633) | 0.016087 / 0.534201 (-0.518114) | 0.299978 / 0.579283 (-0.279305) | 0.149444 / 0.434364 (-0.284920) | 0.321354 / 0.540337 (-0.218984) | 0.414492 / 1.386936 (-0.972444) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#a2dc287cbef5311cf1a32ad4e3685f4052db227c \"CML watermark\")\n", "@lhoestq Thanks for the PR, Is there a way to detect if `trust_remote_code=True` will be required for loading the dataset, without loading it? It would be great if you could please point me to the relevant documentation.", "You can check the presence of a python loading script in the repository.\r\n\r\nIf there is a .py file named after the repository name, then it requires trust_remote_code.", "Thanks @lhoestq for the reference." ]

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[ "Canonical datasets are no longer mentioned in the docs." ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6952). 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) | 0.005232 / 0.011353 (-0.006121) | 0.003744 / 0.011008 (-0.007264) | 0.064089 / 0.038508 (0.025581) | 0.032409 / 0.023109 (0.009300) | 0.255886 / 0.275898 (-0.020013) | 0.276033 / 0.323480 (-0.047447) | 0.004165 / 0.007986 (-0.003821) | 0.002741 / 0.004328 (-0.001588) | 0.052145 / 0.004250 (0.047894) | 0.043863 / 0.037052 (0.006811) | 0.258844 / 0.258489 (0.000355) | 0.290108 / 0.293841 (-0.003733) | 0.027390 / 0.128546 (-0.101156) | 0.010543 / 0.075646 (-0.065103) | 0.206936 / 0.419271 (-0.212335) | 0.036778 / 0.043533 (-0.006755) | 0.254331 / 0.255139 (-0.000808) | 0.279037 / 0.283200 (-0.004163) | 0.018564 / 0.141683 (-0.123119) | 1.112765 / 1.452155 (-0.339390) | 1.160099 / 1.492716 (-0.332617) |\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) | 0.092148 / 0.018006 (0.074142) | 0.297156 / 0.000490 (0.296667) | 0.000211 / 0.000200 (0.000011) | 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) | 0.018797 / 0.037411 (-0.018615) | 0.062992 / 0.014526 (0.048466) | 0.076361 / 0.176557 (-0.100195) | 0.121168 / 0.737135 (-0.615968) | 0.075845 / 0.296338 (-0.220494) |\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) | 0.293842 / 0.215209 (0.078633) | 2.880720 / 2.077655 (0.803065) | 1.477779 / 1.504120 (-0.026341) | 1.345136 / 1.541195 (-0.196059) | 1.352153 / 1.468490 (-0.116337) | 0.574722 / 4.584777 (-4.010055) | 2.373925 / 3.745712 (-1.371787) | 2.750704 / 5.269862 (-2.519157) | 1.725979 / 4.565676 (-2.839697) | 0.063006 / 0.424275 (-0.361269) | 0.005019 / 0.007607 (-0.002588) | 0.341228 / 0.226044 (0.115184) | 3.352576 / 2.268929 (1.083647) | 1.821363 / 55.444624 (-53.623261) | 1.529441 / 6.876477 (-5.347036) | 1.543401 / 2.142072 (-0.598671) | 0.634282 / 4.805227 (-4.170945) | 0.115565 / 6.500664 (-6.385099) | 0.042514 / 0.075469 (-0.032956) |\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) | 0.987532 / 1.841788 (-0.854255) | 11.483853 / 8.074308 (3.409545) | 9.565657 / 10.191392 (-0.625735) | 0.141247 / 0.680424 (-0.539176) | 0.015026 / 0.534201 (-0.519175) | 0.299905 / 0.579283 (-0.279378) | 0.267667 / 0.434364 (-0.166697) | 0.320661 / 0.540337 (-0.219676) | 0.427368 / 1.386936 (-0.959568) |\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) | 0.005448 / 0.011353 (-0.005905) | 0.003726 / 0.011008 (-0.007283) | 0.049776 / 0.038508 (0.011268) | 0.032733 / 0.023109 (0.009624) | 0.261387 / 0.275898 (-0.014511) | 0.280087 / 0.323480 (-0.043393) | 0.004351 / 0.007986 (-0.003634) | 0.002842 / 0.004328 (-0.001487) | 0.049440 / 0.004250 (0.045190) | 0.039585 / 0.037052 (0.002533) | 0.266331 / 0.258489 (0.007842) | 0.299643 / 0.293841 (0.005802) | 0.029649 / 0.128546 (-0.098897) | 0.010381 / 0.075646 (-0.065265) | 0.058596 / 0.419271 (-0.360676) | 0.033271 / 0.043533 (-0.010262) | 0.251070 / 0.255139 (-0.004069) | 0.272850 / 0.283200 (-0.010349) | 0.016728 / 0.141683 (-0.124955) | 1.146952 / 1.452155 (-0.305202) | 1.182602 / 1.492716 (-0.310114) |\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) | 0.091673 / 0.018006 (0.073667) | 0.297228 / 0.000490 (0.296738) | 0.000197 / 0.000200 (-0.000003) | 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) | 0.023174 / 0.037411 (-0.014237) | 0.078866 / 0.014526 (0.064341) | 0.088436 / 0.176557 (-0.088121) | 0.129650 / 0.737135 (-0.607485) | 0.091100 / 0.296338 (-0.205238) |\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) | 0.293882 / 0.215209 (0.078673) | 2.882667 / 2.077655 (0.805012) | 1.562949 / 1.504120 (0.058829) | 1.435104 / 1.541195 (-0.106090) | 1.450815 / 1.468490 (-0.017675) | 0.584090 / 4.584777 (-4.000687) | 0.984176 / 3.745712 (-2.761536) | 2.668740 / 5.269862 (-2.601121) | 1.766993 / 4.565676 (-2.798683) | 0.064710 / 0.424275 (-0.359565) | 0.005329 / 0.007607 (-0.002278) | 0.346008 / 0.226044 (0.119964) | 3.414576 / 2.268929 (1.145647) | 1.911388 / 55.444624 (-53.533236) | 1.660357 / 6.876477 (-5.216120) | 1.818628 / 2.142072 (-0.323444) | 0.659585 / 4.805227 (-4.145643) | 0.116980 / 6.500664 (-6.383684) | 0.041364 / 0.075469 (-0.034105) |\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) | 1.005659 / 1.841788 (-0.836129) | 12.023761 / 8.074308 (3.949453) | 10.351086 / 10.191392 (0.159694) | 0.143261 / 0.680424 (-0.537162) | 0.016143 / 0.534201 (-0.518058) | 0.287793 / 0.579283 (-0.291490) | 0.123698 / 0.434364 (-0.310666) | 0.325241 / 0.540337 (-0.215097) | 0.418772 / 1.386936 (-0.968164) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#37a603679f451826cfafd8aae00738b01dcb9d58 \"CML watermark\")\n" ]

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[ "@xianbaoqian ", "Feel free to open a PR in `m-a-p/COIG-CQIA` to define a default subset. Currently there is no default.\r\n\r\nYou can find some documentation at https://huggingface.co/docs/hub/datasets-manual-configuration#multiple-configurations", "@lhoestq \r\n\r\nWhilst having a default subset readily available (e.g. `all`) by the dataset author is an ideal solution, it is not always the reality.\r\n\r\nWithout the ability to fork the dataset, this can be problematic.\r\n\r\nAs far as I know, it is not possible at all to specify multiple subsets in a generalized programmatic way without hard coding subset names for a specific dataset.\r\n\r\nEven the ability to fetch subset names and loop over them would be sufficient.", "Please note that each subset can have different feature columns, thus making it impossible to load them all into a unique Dataset instance.\r\n\r\nThat is why subsets were created: to support different but related datasets to coexist in a single dataset repository.\r\n\r\nIf you would like to programmatically get the list of subset names, you can use `datasets.get_dataset_config_names`: https://huggingface.co/docs/datasets/v2.20.0/en/load_hub#configurations" ]

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[ "Hi ! It seems the documentation was outdated in this paragraph\r\n\r\nI fixed it here: https://github.com/huggingface/datasets/pull/6956", "Fixed." ]

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[ "Hi, @lion-ops.\r\n\r\nIn our Continuous Integration we have many tests on loading JSON files and all of them work properly.\r\n\r\nCould you please share your \"train.json\" file, so that we can try to reproduce the issue you have? ", "> Hi, @lion-ops.\r\n> \r\n> In our Continuous Integration we have many tests on loading JSON files and all of them work properly.\r\n> \r\n> Could you please share your \"train.json\" file, so that we can try to reproduce the issue you have?\r\n\r\nThank you for your reply. I can load it normally in another server. Is it possible that the disk of my server is a network disk in the LAN, so it will be downloaded from the LAN and get stuck?" ]

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[ "same problem here", "Hello,\r\n\r\nAre you sure you are really using datasets version 2.19.2? We just made the patch release yesterday specifically to fix this issue:\r\n- #6925\r\n\r\nI can't reproduce the error:\r\n```python\r\nIn [1]: from datasets import load_dataset\r\n\r\nIn [2]: ds = load_dataset('allenai/c4', data_files={'validation': 'en/c4-validation.00003-of-00008.json.gz'}, split='validation')\r\nDownloading readme: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 41.1k/41.1k [00:00<00:00, 596kB/s]\r\nDownloading data: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 40.7M/40.7M [00:04<00:00, 8.50MB/s]\r\nGenerating validation split: 45576 examples [00:01, 44956.75 examples/s]\r\n\r\nIn [3]: ds\r\nOut[3]: \r\nDataset({\r\n features: ['text', 'timestamp', 'url'],\r\n num_rows: 45576\r\n})\r\n```", "> Hello,\r\n> \r\n> Are you sure you are really using datasets version 2.19.2? We just made the patch release yesterday specifically to fix this issue:\r\n> \r\n> * [Fix NonMatchingSplitsSizesError/ExpectedMoreSplits when passing data_dir/data_files in no-code Hub datasets #6925](https://github.com/huggingface/datasets/pull/6925)\r\n> \r\n> I can't reproduce the error:\r\n> \r\n> ```python\r\n> In [1]: from datasets import load_dataset\r\n> \r\n> In [2]: ds = load_dataset('allenai/c4', data_files={'validation': 'en/c4-validation.00003-of-00008.json.gz'}, split='validation')\r\n> Downloading readme: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 41.1k/41.1k [00:00<00:00, 596kB/s]\r\n> Downloading data: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 40.7M/40.7M [00:04<00:00, 8.50MB/s]\r\n> Generating validation split: 45576 examples [00:01, 44956.75 examples/s]\r\n> \r\n> In [3]: ds\r\n> Out[3]: \r\n> Dataset({\r\n> features: ['text', 'timestamp', 'url'],\r\n> num_rows: 45576\r\n> })\r\n> ```\r\nThank you for your reply,ExpectedMoreSplits was encountered in datasets version 2.12.2. After I updated the version, that is, datasets version 2.19.2, I encountered the FileNotFoundError problem mentioned above.", "That might be due to a corrupted cache.\r\n\r\nPlease, retry loading the dataset passing: `download_mode=\"force_redownload\"`\r\n```python\r\nds = load_dataset('allenai/c4', data_files={'validation': 'en/c4-validation.00003-of-00008.json.gz'}, split='validation', download_mode=\"force_redownload\")\r\n```\r\n\r\nIt the above command does not fix the issue, then you will need to fix the cache manually, by removing the corresponding directory inside `~/.cache/huggingface/`.\r\n", "> That might be due to a corrupted cache.\r\n> \r\n> Please, retry loading the dataset passing: `download_mode=\"force_redownload\"`\r\n> \r\n> ```python\r\n> ds = load_dataset('allenai/c4', data_files={'validation': 'en/c4-validation.00003-of-00008.json.gz'}, split='validation', download_mode=\"force_redownload\")\r\n> ```\r\n> \r\n> It the above command does not fix the issue, then you will need to fix the cache manually, by removing the corresponding directory inside `~/.cache/huggingface/`.\r\n\r\nThe two methods you mentioned above can not solve this problem, but the command line interface shows Downloading readme: 41.1kB [00:00, 281kB/s], and then FileNotFoundError appears. It is worth noting that I have no problem loading other datasets with the initial method, such as wikitext datasets", "> The two methods you mentioned above can not solve this problem, but the command line interface shows Downloading readme: 41.1kB [00:00, 281kB/s], and then FileNotFoundError appears.\r\n\r\nSame issue encountered.\r\n", "I really think the issue is caused by a corrupted cache, between versions 2.12.0 (there does not exist 2.12.2 version) and 2.19.2.\r\n\r\nAre you sure you removed all the corresponding corrupted directories within the cache?\r\n\r\nYou can easily check if the issue is caused by a corrupted cache by removing the entire cache:\r\n```shell\r\nmv ~/.cache/huggingface ~/.cache/huggingface.bak\r\n```\r\nand then reloading the dataset:\r\n```python\r\nds = load_dataset('allenai/c4', data_files={'validation': 'en/c4-validation.00003-of-00008.json.gz'}, split='validation', download_mode=\"force_redownload\")\r\n```", "@albertvillanova Thanks for the reply. I tried removing the entire cache and reloading the dataset as you suggest. However, the same issue still exists. \r\n\r\nAs a test, I switch to a new platform, which (is a Windows system and) hasn't downloaded huggingface dataset before, and the dataset is loaded successfully. So I think \"a corrupted cache\" explanation makes sense. I wonder, besides `~/.cache/huggingface`, is there any other directory that may save the cache thing?\r\n\r\nAs a side note, I am using `datasets==2.20.0` and proxy `export HF_ENDPOINT=https://hf-mirror.com`.", "Ho @ZhangGe6,\r\n\r\nAs far as I know, that directory is the only one where the cache is saved, unless you configured another one. You can check it:\r\n```python\r\nimport datasets.config\r\n\r\nprint(datasets.config.HF_CACHE_HOME)\r\n# ~/.cache/huggingface\r\n\r\nprint(datasets.config.HF_DATASETS_CACHE)\r\n# ~/.cache/huggingface/datasets\r\n\r\nprint(datasets.config.HF_MODULES_CACHE)\r\n# ~/.cache/huggingface/modules\r\n\r\nprint(datasets.config.DOWNLOADED_DATASETS_PATH)\r\n# ~/.cache/huggingface/datasets/downloads\r\n\r\nprint(datasets.config.EXTRACTED_DATASETS_PATH)\r\n# ~/.cache/huggingface/datasets/downloads/extracted\r\n```\r\n\r\nAdditionally, `datasets` uses `huggingface_hub`, but its cache directory should also be inside `~/.cache/huggingface`, unless you configured another one. You can check it:\r\n```python\r\nimport huggingface_hub.constants\r\n\r\nprint(huggingface_hub.constants.HF_HOME)\r\n# ~/.cache/huggingface\r\n\r\nprint(huggingface_hub.constants.HF_HUB_CACHE)\r\n# ~/.cache/huggingface/hub\r\n```", "@albertvillanova I checked the directories you listed, and find that they are the same as the ones you provided. I am going to find more clues and will update what I find here.", "I've had a similar problem, and for some reason decreasing the number of workers in the dataloader solved it", "Same issue.\r\n", "Hi folks. Finally, I find it is a network issue that causes huggingface hub unreachable (in China).\r\n\r\nTo run the following script \r\n```python\r\nfrom datasets import load_dataset\r\n\r\nds = load_dataset('allenai/c4', data_files={'validation': 'en/c4-validation.00003-of-00008.json.gz'}, split='validation', download_mode=\"force_redownload\")\r\n```\r\nWithout setting `export HF_ENDPOINT=https://hf-mirror.com`, I get the following error log\r\n```bash\r\nTraceback (most recent call last):\r\n File \".\\demo.py\", line 8, in <module>\r\n ds = load_dataset('allenai/c4', data_files={'validation': 'en/c4-validation.00003-of-00008.json.gz'}, split='validation', download_mode=\"force_redownload\")\r\n File \"D:\\SoftwareInstall\\Python\\lib\\site-packages\\datasets\\load.py\", line 2594, in load_dataset\r\n builder_instance = load_dataset_builder(\r\n File \"D:\\SoftwareInstall\\Python\\lib\\site-packages\\datasets\\load.py\", line 2266, in load_dataset_builder\r\n dataset_module = dataset_module_factory(\r\n File \"D:\\SoftwareInstall\\Python\\lib\\site-packages\\datasets\\load.py\", line 1914, in dataset_module_factory\r\n raise e1 from None\r\n File \"D:\\SoftwareInstall\\Python\\lib\\site-packages\\datasets\\load.py\", line 1845, in dataset_module_factory\r\n raise ConnectionError(f\"Couldn't reach '{path}' on the Hub ({e.__class__.__name__})\") from e\r\nConnectionError: Couldn't reach 'allenai/c4' on the Hub (ConnectionError)\r\n```\r\nAfter setting `export HF_ENDPOINT=https://hf-mirror.com`, I get the following error, which is exactly the same as what we are debugging in this issue\r\n```bash\r\nDownloading readme: 41.1kB [00:00, 41.1MB/s]\r\nTraceback (most recent call last):\r\n File \".\\demo.py\", line 8, in <module>\r\n ds = load_dataset('allenai/c4', data_files={'validation': 'en/c4-validation.00003-of-00008.json.gz'}, split='validation', download_mode=\"force_redownload\")\r\n File \"D:\\SoftwareInstall\\Python\\lib\\site-packages\\datasets\\load.py\", line 2594, in loa builder_instance = load_dataset_builder(\r\n File \"D:\\SoftwareInstall\\Python\\lib\\site-packages\\datasets\\load.py\", line 2266, in load_dataset_builder\r\n dataset_module = dataset_module_factory(\r\n raise FileNotFoundError(\r\nFileNotFoundError: Couldn't find a dataset script at C:\\Users\\ZhangGe\\Desktop\\allenai\\c4\\c4.py or any data file in the same directory. Couldn't find 'allenai/c4' on the Hugging Face Hub either: FileNotFoundError: Unable to find 'hf://datasets/allenai/c4@1588ec454eed 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', \r\n'.h5', '.hdf', '.png', '.apng', '.jp2', '.j2k', '.jpc', '.jpf', '.jpx', '.j2c', '.icns',pm', '.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', \r\n'.SVX', '.MAT4', '.MAT5', '.MPC2K', '.OGG', '.PAF', '.PVF', '.RAW', '.RF64', '.SD2', '.SDS', '.IRCAM', '.VOC', '.W64', '.WAV', '.NIST', '.WAVEX', '.WVE', '.XI', '.MP3', '.OPUS', '.zip']\r\n```\r\n\r\n**Using a proxy software that avoids the internet access restrictions imposed by China, I can download the dataset using the same script**\r\n```bash\r\nDownloading readme: 100%|███████████████████████████████████████████| 41.1k/41.1k [00:00<00:00, 312kB/s] \r\nDownloading data: 100%|████████████████████████████████████████████| 40.7M/40.7M [00:19<00:00, 2.07MB/s] \r\nGenerating validation split: 45576 examples [00:00, 54883.48 examples/s]\r\n```\r\nSo `allenai/c4` is still unreachable even after setting `export HF_ENDPOINT=https://hf-mirror.com`.", "I have created an issue to inform the maintainers of `hf-mirror`：https://github.com/padeoe/hf-mirror-site/issues/30", "Thanks for the investigation: so finally it is an issue with the specific endpoint you are using.\r\n\r\nYou properly opened an issue in their repo, so they can fix it.\r\n\r\nI am closing this issue here." ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6946). 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) | 0.004847 / 0.011353 (-0.006506) | 0.003199 / 0.011008 (-0.007810) | 0.060677 / 0.038508 (0.022169) | 0.030544 / 0.023109 (0.007435) | 0.240870 / 0.275898 (-0.035028) | 0.261320 / 0.323480 (-0.062160) | 0.002816 / 0.007986 (-0.005170) | 0.002483 / 0.004328 (-0.001845) | 0.048527 / 0.004250 (0.044277) | 0.045496 / 0.037052 (0.008444) | 0.251296 / 0.258489 (-0.007193) | 0.285746 / 0.293841 (-0.008095) | 0.025076 / 0.128546 (-0.103470) | 0.009417 / 0.075646 (-0.066229) | 0.191361 / 0.419271 (-0.227911) | 0.033778 / 0.043533 (-0.009755) | 0.235581 / 0.255139 (-0.019558) | 0.261069 / 0.283200 (-0.022131) | 0.018255 / 0.141683 (-0.123428) | 1.098437 / 1.452155 (-0.353718) | 1.127124 / 1.492716 (-0.365592) |\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) | 0.004479 / 0.018006 (-0.013527) | 0.283706 / 0.000490 (0.283216) | 0.000214 / 0.000200 (0.000014) | 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) | 0.018364 / 0.037411 (-0.019048) | 0.058398 / 0.014526 (0.043872) | 0.073056 / 0.176557 (-0.103501) | 0.117147 / 0.737135 (-0.619989) | 0.073683 / 0.296338 (-0.222656) |\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) | 0.265121 / 0.215209 (0.049912) | 2.636981 / 2.077655 (0.559327) | 1.380192 / 1.504120 (-0.123928) | 1.270779 / 1.541195 (-0.270416) | 1.295729 / 1.468490 (-0.172762) | 0.523768 / 4.584777 (-4.061009) | 2.295720 / 3.745712 (-1.449992) | 2.519211 / 5.269862 (-2.750650) | 1.618712 / 4.565676 (-2.946965) | 0.058321 / 0.424275 (-0.365954) | 0.004492 / 0.007607 (-0.003115) | 0.316101 / 0.226044 (0.090057) | 3.169913 / 2.268929 (0.900984) | 1.793412 / 55.444624 (-53.651213) | 1.473784 / 6.876477 (-5.402693) | 1.565325 / 2.142072 (-0.576748) | 0.592734 / 4.805227 (-4.212493) | 0.109333 / 6.500664 (-6.391331) | 0.039063 / 0.075469 (-0.036406) |\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) | 0.935504 / 1.841788 (-0.906284) | 10.865520 / 8.074308 (2.791212) | 9.219337 / 10.191392 (-0.972055) | 0.135284 / 0.680424 (-0.545140) | 0.013664 / 0.534201 (-0.520537) | 0.271601 / 0.579283 (-0.307682) | 0.260456 / 0.434364 (-0.173908) | 0.302931 / 0.540337 (-0.237406) | 0.414643 / 1.386936 (-0.972293) |\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) | 0.004801 / 0.011353 (-0.006552) | 0.003092 / 0.011008 (-0.007917) | 0.046471 / 0.038508 (0.007963) | 0.031337 / 0.023109 (0.008228) | 0.258920 / 0.275898 (-0.016978) | 0.269842 / 0.323480 (-0.053638) | 0.003976 / 0.007986 (-0.004009) | 0.002661 / 0.004328 (-0.001668) | 0.045676 / 0.004250 (0.041426) | 0.038199 / 0.037052 (0.001146) | 0.277382 / 0.258489 (0.018893) | 0.289351 / 0.293841 (-0.004490) | 0.028452 / 0.128546 (-0.100094) | 0.009737 / 0.075646 (-0.065910) | 0.055201 / 0.419271 (-0.364071) | 0.032686 / 0.043533 (-0.010847) | 0.259617 / 0.255139 (0.004478) | 0.277163 / 0.283200 (-0.006037) | 0.017825 / 0.141683 (-0.123858) | 1.102797 / 1.452155 (-0.349357) | 1.105018 / 1.492716 (-0.387699) |\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) | 0.094844 / 0.018006 (0.076838) | 0.290519 / 0.000490 (0.290029) | 0.000211 / 0.000200 (0.000012) | 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) | 0.021917 / 0.037411 (-0.015494) | 0.075278 / 0.014526 (0.060753) | 0.085971 / 0.176557 (-0.090586) | 0.127072 / 0.737135 (-0.610063) | 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) | 0.276704 / 0.215209 (0.061495) | 2.736960 / 2.077655 (0.659305) | 1.519634 / 1.504120 (0.015514) | 1.403026 / 1.541195 (-0.138168) | 1.418465 / 1.468490 (-0.050025) | 0.552425 / 4.584777 (-4.032352) | 0.955244 / 3.745712 (-2.790468) | 2.556563 / 5.269862 (-2.713298) | 1.705095 / 4.565676 (-2.860582) | 0.061212 / 0.424275 (-0.363063) | 0.004707 / 0.007607 (-0.002900) | 0.326284 / 0.226044 (0.100239) | 3.253911 / 2.268929 (0.984983) | 1.868649 / 55.444624 (-53.575976) | 1.598697 / 6.876477 (-5.277780) | 1.682617 / 2.142072 (-0.459455) | 0.606379 / 4.805227 (-4.198848) | 0.114126 / 6.500664 (-6.386538) | 0.038869 / 0.075469 (-0.036601) |\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) | 0.966354 / 1.841788 (-0.875433) | 11.575918 / 8.074308 (3.501609) | 9.816597 / 10.191392 (-0.374795) | 0.141492 / 0.680424 (-0.538932) | 0.015375 / 0.534201 (-0.518826) | 0.276027 / 0.579283 (-0.303256) | 0.118979 / 0.434364 (-0.315385) | 0.313467 / 0.540337 (-0.226870) | 0.403539 / 1.386936 (-0.983397) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#1b59c75856d765e60b66a5216062102d001c6612 \"CML watermark\")\n" ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6945). 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) | 0.005725 / 0.011353 (-0.005627) | 0.003788 / 0.011008 (-0.007220) | 0.063059 / 0.038508 (0.024551) | 0.031364 / 0.023109 (0.008255) | 0.259209 / 0.275898 (-0.016689) | 0.278805 / 0.323480 (-0.044675) | 0.003032 / 0.007986 (-0.004953) | 0.002633 / 0.004328 (-0.001696) | 0.049804 / 0.004250 (0.045554) | 0.046717 / 0.037052 (0.009665) | 0.267246 / 0.258489 (0.008757) | 0.299271 / 0.293841 (0.005430) | 0.027687 / 0.128546 (-0.100860) | 0.010524 / 0.075646 (-0.065123) | 0.201736 / 0.419271 (-0.217536) | 0.036192 / 0.043533 (-0.007341) | 0.264492 / 0.255139 (0.009353) | 0.280809 / 0.283200 (-0.002391) | 0.018187 / 0.141683 (-0.123496) | 1.170751 / 1.452155 (-0.281404) | 1.223450 / 1.492716 (-0.269266) |\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) | 0.096610 / 0.018006 (0.078604) | 0.297122 / 0.000490 (0.296632) | 0.000211 / 0.000200 (0.000011) | 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) | 0.018380 / 0.037411 (-0.019031) | 0.062214 / 0.014526 (0.047688) | 0.075833 / 0.176557 (-0.100723) | 0.121825 / 0.737135 (-0.615310) | 0.075475 / 0.296338 (-0.220864) |\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) | 0.275601 / 0.215209 (0.060392) | 2.698014 / 2.077655 (0.620359) | 1.434043 / 1.504120 (-0.070077) | 1.313217 / 1.541195 (-0.227978) | 1.339014 / 1.468490 (-0.129476) | 0.566703 / 4.584777 (-4.018074) | 2.367794 / 3.745712 (-1.377918) | 2.660787 / 5.269862 (-2.609074) | 1.738503 / 4.565676 (-2.827174) | 0.061693 / 0.424275 (-0.362582) | 0.004978 / 0.007607 (-0.002629) | 0.334719 / 0.226044 (0.108675) | 3.300889 / 2.268929 (1.031960) | 1.764493 / 55.444624 (-53.680131) | 1.475956 / 6.876477 (-5.400521) | 1.635988 / 2.142072 (-0.506084) | 0.643906 / 4.805227 (-4.161321) | 0.118002 / 6.500664 (-6.382662) | 0.042593 / 0.075469 (-0.032876) |\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) | 0.953511 / 1.841788 (-0.888276) | 11.489727 / 8.074308 (3.415419) | 9.775017 / 10.191392 (-0.416375) | 0.139864 / 0.680424 (-0.540560) | 0.014219 / 0.534201 (-0.519982) | 0.284389 / 0.579283 (-0.294894) | 0.264250 / 0.434364 (-0.170113) | 0.323471 / 0.540337 (-0.216866) | 0.415189 / 1.386936 (-0.971747) |\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) | 0.005437 / 0.011353 (-0.005916) | 0.003710 / 0.011008 (-0.007298) | 0.049940 / 0.038508 (0.011432) | 0.032565 / 0.023109 (0.009456) | 0.266374 / 0.275898 (-0.009524) | 0.288069 / 0.323480 (-0.035411) | 0.004140 / 0.007986 (-0.003845) | 0.002669 / 0.004328 (-0.001660) | 0.049646 / 0.004250 (0.045395) | 0.040926 / 0.037052 (0.003874) | 0.278805 / 0.258489 (0.020316) | 0.311396 / 0.293841 (0.017555) | 0.029363 / 0.128546 (-0.099183) | 0.010260 / 0.075646 (-0.065386) | 0.058222 / 0.419271 (-0.361049) | 0.033063 / 0.043533 (-0.010470) | 0.266798 / 0.255139 (0.011659) | 0.283091 / 0.283200 (-0.000109) | 0.017904 / 0.141683 (-0.123779) | 1.139531 / 1.452155 (-0.312624) | 1.163909 / 1.492716 (-0.328808) |\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) | 0.089063 / 0.018006 (0.071057) | 0.296757 / 0.000490 (0.296268) | 0.000202 / 0.000200 (0.000002) | 0.000054 / 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) | 0.022843 / 0.037411 (-0.014568) | 0.076032 / 0.014526 (0.061507) | 0.087545 / 0.176557 (-0.089012) | 0.128870 / 0.737135 (-0.608266) | 0.089359 / 0.296338 (-0.206980) |\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) | 0.285213 / 0.215209 (0.070004) | 2.854950 / 2.077655 (0.777295) | 1.539311 / 1.504120 (0.035191) | 1.413753 / 1.541195 (-0.127442) | 1.440819 / 1.468490 (-0.027671) | 0.564734 / 4.584777 (-4.020043) | 0.944924 / 3.745712 (-2.800788) | 2.703612 / 5.269862 (-2.566249) | 1.749429 / 4.565676 (-2.816247) | 0.063239 / 0.424275 (-0.361036) | 0.005024 / 0.007607 (-0.002583) | 0.340866 / 0.226044 (0.114821) | 3.359511 / 2.268929 (1.090582) | 1.895794 / 55.444624 (-53.548831) | 1.606613 / 6.876477 (-5.269864) | 1.756539 / 2.142072 (-0.385533) | 0.646553 / 4.805227 (-4.158675) | 0.121278 / 6.500664 (-6.379386) | 0.041066 / 0.075469 (-0.034403) |\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) | 1.005548 / 1.841788 (-0.836240) | 12.080103 / 8.074308 (4.005794) | 10.444822 / 10.191392 (0.253430) | 0.145024 / 0.680424 (-0.535400) | 0.015287 / 0.534201 (-0.518914) | 0.288567 / 0.579283 (-0.290716) | 0.118034 / 0.434364 (-0.316330) | 0.333474 / 0.540337 (-0.206864) | 0.421716 / 1.386936 (-0.965220) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#3d95159dbd918009e1ff710dba0cd15d96d4264e \"CML watermark\")\n", "@albertvillanova could I ask why we should use latest `requests` here? we are using `docker` and `datasets` in the same time. However, docker requires requests<2.32.0.", "Hi @pingsutw,\r\n\r\nWe updated the minimum required `requests` version for security reasons: https://www.cve.org/CVERecord?id=CVE-2024-35195\r\n- affected versions < 2.32.0 \r\n\r\nLatest version of `docker` should normally support `requests` >= 2.32.0: https://github.com/docker/docker-py/releases/tag/7.1.0\r\n> Fixed an issue due to an update in the [requests](https://github.com/psf/requests) package breaking docker-py by applying the https://github.com/psf/requests/pull/6710\r\n- https://github.com/docker/docker-py/pull/3257\r\n\r\nI guess you need to update your `docker` library as well:\r\n```\r\npip install -U docker\r\n```", "> I guess you need to update your docker library as well:\r\n\r\nThank you! it works for me 👍 " ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6944). 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) | 0.005150 / 0.011353 (-0.006203) | 0.003663 / 0.011008 (-0.007346) | 0.062832 / 0.038508 (0.024324) | 0.031928 / 0.023109 (0.008819) | 0.246455 / 0.275898 (-0.029443) | 0.272121 / 0.323480 (-0.051359) | 0.004220 / 0.007986 (-0.003765) | 0.002756 / 0.004328 (-0.001573) | 0.050071 / 0.004250 (0.045821) | 0.046074 / 0.037052 (0.009022) | 0.259676 / 0.258489 (0.001187) | 0.290674 / 0.293841 (-0.003167) | 0.027822 / 0.128546 (-0.100724) | 0.010791 / 0.075646 (-0.064855) | 0.202827 / 0.419271 (-0.216445) | 0.037057 / 0.043533 (-0.006476) | 0.256128 / 0.255139 (0.000989) | 0.269422 / 0.283200 (-0.013777) | 0.017395 / 0.141683 (-0.124288) | 1.125919 / 1.452155 (-0.326236) | 1.177708 / 1.492716 (-0.315008) |\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) | 0.098466 / 0.018006 (0.080460) | 0.305508 / 0.000490 (0.305018) | 0.000232 / 0.000200 (0.000032) | 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) | 0.018866 / 0.037411 (-0.018545) | 0.062079 / 0.014526 (0.047553) | 0.074670 / 0.176557 (-0.101886) | 0.121025 / 0.737135 (-0.616111) | 0.075883 / 0.296338 (-0.220455) |\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) | 0.291880 / 0.215209 (0.076671) | 2.874064 / 2.077655 (0.796409) | 1.477040 / 1.504120 (-0.027080) | 1.356198 / 1.541195 (-0.184997) | 1.354676 / 1.468490 (-0.113814) | 0.559731 / 4.584777 (-4.025046) | 2.362746 / 3.745712 (-1.382966) | 2.678838 / 5.269862 (-2.591024) | 1.752633 / 4.565676 (-2.813044) | 0.064023 / 0.424275 (-0.360252) | 0.005035 / 0.007607 (-0.002572) | 0.354807 / 0.226044 (0.128762) | 3.424463 / 2.268929 (1.155534) | 1.810476 / 55.444624 (-53.634149) | 1.519031 / 6.876477 (-5.357446) | 1.693957 / 2.142072 (-0.448116) | 0.647987 / 4.805227 (-4.157240) | 0.118993 / 6.500664 (-6.381671) | 0.042186 / 0.075469 (-0.033283) |\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) | 0.982565 / 1.841788 (-0.859223) | 11.645075 / 8.074308 (3.570767) | 9.588360 / 10.191392 (-0.603032) | 0.142369 / 0.680424 (-0.538055) | 0.014025 / 0.534201 (-0.520176) | 0.285668 / 0.579283 (-0.293616) | 0.265825 / 0.434364 (-0.168539) | 0.323371 / 0.540337 (-0.216966) | 0.421227 / 1.386936 (-0.965709) |\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) | 0.005587 / 0.011353 (-0.005766) | 0.003664 / 0.011008 (-0.007345) | 0.050411 / 0.038508 (0.011903) | 0.033268 / 0.023109 (0.010159) | 0.266631 / 0.275898 (-0.009267) | 0.291135 / 0.323480 (-0.032345) | 0.004275 / 0.007986 (-0.003710) | 0.002822 / 0.004328 (-0.001506) | 0.049349 / 0.004250 (0.045099) | 0.040653 / 0.037052 (0.003601) | 0.282641 / 0.258489 (0.024152) | 0.315460 / 0.293841 (0.021619) | 0.029343 / 0.128546 (-0.099203) | 0.010606 / 0.075646 (-0.065040) | 0.058783 / 0.419271 (-0.360489) | 0.033205 / 0.043533 (-0.010327) | 0.266805 / 0.255139 (0.011666) | 0.288907 / 0.283200 (0.005707) | 0.017817 / 0.141683 (-0.123866) | 1.128132 / 1.452155 (-0.324023) | 1.175120 / 1.492716 (-0.317597) |\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) | 0.095653 / 0.018006 (0.077647) | 0.304825 / 0.000490 (0.304335) | 0.000212 / 0.000200 (0.000012) | 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) | 0.022766 / 0.037411 (-0.014645) | 0.076598 / 0.014526 (0.062072) | 0.088314 / 0.176557 (-0.088242) | 0.127888 / 0.737135 (-0.609247) | 0.090391 / 0.296338 (-0.205947) |\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) | 0.293384 / 0.215209 (0.078175) | 2.883742 / 2.077655 (0.806087) | 1.533868 / 1.504120 (0.029748) | 1.391964 / 1.541195 (-0.149231) | 1.423732 / 1.468490 (-0.044759) | 0.575457 / 4.584777 (-4.009320) | 0.970860 / 3.745712 (-2.774852) | 2.711405 / 5.269862 (-2.558457) | 1.774468 / 4.565676 (-2.791208) | 0.064611 / 0.424275 (-0.359664) | 0.005120 / 0.007607 (-0.002487) | 0.343892 / 0.226044 (0.117847) | 3.362579 / 2.268929 (1.093650) | 1.880200 / 55.444624 (-53.564424) | 1.587435 / 6.876477 (-5.289042) | 1.756464 / 2.142072 (-0.385609) | 0.661469 / 4.805227 (-4.143759) | 0.119030 / 6.500664 (-6.381634) | 0.041704 / 0.075469 (-0.033765) |\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) | 1.025008 / 1.841788 (-0.816780) | 12.146244 / 8.074308 (4.071936) | 10.397267 / 10.191392 (0.205875) | 0.145917 / 0.680424 (-0.534507) | 0.015779 / 0.534201 (-0.518422) | 0.287122 / 0.579283 (-0.292161) | 0.125464 / 0.434364 (-0.308900) | 0.323315 / 0.540337 (-0.217023) | 0.416761 / 1.386936 (-0.970175) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#e2d15a6b1871f3998986853298e4338d72891491 \"CML watermark\")\n" ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6943). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update." ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6938). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "fix is included in https://github.com/huggingface/datasets/pull/6925" ]

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[ "I got the same issue. Any updates so far for this issue?" ]

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[ "+1 I just noticed this when I tried to update `datasets` today." ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6934). 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) | 0.005218 / 0.011353 (-0.006135) | 0.003313 / 0.011008 (-0.007695) | 0.062992 / 0.038508 (0.024484) | 0.029621 / 0.023109 (0.006512) | 0.244421 / 0.275898 (-0.031477) | 0.267178 / 0.323480 (-0.056302) | 0.002986 / 0.007986 (-0.005000) | 0.002607 / 0.004328 (-0.001721) | 0.049149 / 0.004250 (0.044898) | 0.045362 / 0.037052 (0.008310) | 0.252862 / 0.258489 (-0.005627) | 0.286326 / 0.293841 (-0.007515) | 0.027888 / 0.128546 (-0.100658) | 0.010295 / 0.075646 (-0.065352) | 0.205525 / 0.419271 (-0.213746) | 0.036696 / 0.043533 (-0.006837) | 0.248716 / 0.255139 (-0.006423) | 0.263803 / 0.283200 (-0.019397) | 0.016926 / 0.141683 (-0.124757) | 1.123093 / 1.452155 (-0.329062) | 1.155434 / 1.492716 (-0.337282) |\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) | 0.092349 / 0.018006 (0.074343) | 0.298154 / 0.000490 (0.297664) | 0.000213 / 0.000200 (0.000013) | 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) | 0.018496 / 0.037411 (-0.018915) | 0.061983 / 0.014526 (0.047457) | 0.075043 / 0.176557 (-0.101514) | 0.120678 / 0.737135 (-0.616457) | 0.074917 / 0.296338 (-0.221422) |\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) | 0.290558 / 0.215209 (0.075349) | 2.842635 / 2.077655 (0.764981) | 1.485761 / 1.504120 (-0.018359) | 1.346948 / 1.541195 (-0.194247) | 1.352424 / 1.468490 (-0.116066) | 0.564567 / 4.584777 (-4.020210) | 2.393583 / 3.745712 (-1.352129) | 2.654061 / 5.269862 (-2.615800) | 1.729154 / 4.565676 (-2.836523) | 0.064652 / 0.424275 (-0.359623) | 0.004973 / 0.007607 (-0.002634) | 0.334924 / 0.226044 (0.108879) | 3.330518 / 2.268929 (1.061590) | 1.773848 / 55.444624 (-53.670776) | 1.513796 / 6.876477 (-5.362681) | 1.676492 / 2.142072 (-0.465580) | 0.650551 / 4.805227 (-4.154677) | 0.118423 / 6.500664 (-6.382241) | 0.042700 / 0.075469 (-0.032769) |\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) | 0.943394 / 1.841788 (-0.898394) | 11.235766 / 8.074308 (3.161458) | 9.896586 / 10.191392 (-0.294806) | 0.130174 / 0.680424 (-0.550249) | 0.014148 / 0.534201 (-0.520053) | 0.284002 / 0.579283 (-0.295281) | 0.261354 / 0.434364 (-0.173010) | 0.320839 / 0.540337 (-0.219499) | 0.422399 / 1.386936 (-0.964537) |\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) | 0.005496 / 0.011353 (-0.005857) | 0.003603 / 0.011008 (-0.007406) | 0.050104 / 0.038508 (0.011596) | 0.032939 / 0.023109 (0.009830) | 0.265643 / 0.275898 (-0.010255) | 0.291819 / 0.323480 (-0.031661) | 0.004273 / 0.007986 (-0.003713) | 0.002715 / 0.004328 (-0.001613) | 0.049191 / 0.004250 (0.044941) | 0.040782 / 0.037052 (0.003730) | 0.276562 / 0.258489 (0.018072) | 0.314307 / 0.293841 (0.020466) | 0.029878 / 0.128546 (-0.098669) | 0.010134 / 0.075646 (-0.065513) | 0.058686 / 0.419271 (-0.360585) | 0.033562 / 0.043533 (-0.009971) | 0.265961 / 0.255139 (0.010822) | 0.282009 / 0.283200 (-0.001191) | 0.018956 / 0.141683 (-0.122727) | 1.149668 / 1.452155 (-0.302487) | 1.192242 / 1.492716 (-0.300474) |\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) | 0.089449 / 0.018006 (0.071443) | 0.300346 / 0.000490 (0.299856) | 0.000198 / 0.000200 (-0.000001) | 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) | 0.022094 / 0.037411 (-0.015317) | 0.075987 / 0.014526 (0.061461) | 0.088191 / 0.176557 (-0.088365) | 0.127698 / 0.737135 (-0.609437) | 0.089642 / 0.296338 (-0.206696) |\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) | 0.299127 / 0.215209 (0.083918) | 2.961219 / 2.077655 (0.883565) | 1.589108 / 1.504120 (0.084988) | 1.464060 / 1.541195 (-0.077135) | 1.475249 / 1.468490 (0.006759) | 0.569041 / 4.584777 (-4.015736) | 0.966965 / 3.745712 (-2.778747) | 2.653049 / 5.269862 (-2.616813) | 1.733650 / 4.565676 (-2.832026) | 0.062537 / 0.424275 (-0.361738) | 0.005003 / 0.007607 (-0.002605) | 0.353345 / 0.226044 (0.127301) | 3.432888 / 2.268929 (1.163960) | 1.953217 / 55.444624 (-53.491407) | 1.651995 / 6.876477 (-5.224482) | 1.764549 / 2.142072 (-0.377523) | 0.647255 / 4.805227 (-4.157973) | 0.116827 / 6.500664 (-6.383837) | 0.040765 / 0.075469 (-0.034704) |\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) | 0.985490 / 1.841788 (-0.856298) | 11.965147 / 8.074308 (3.890839) | 10.488286 / 10.191392 (0.296894) | 0.142134 / 0.680424 (-0.538290) | 0.015415 / 0.534201 (-0.518786) | 0.289864 / 0.579283 (-0.289419) | 0.122778 / 0.434364 (-0.311586) | 0.328691 / 0.540337 (-0.211647) | 0.422677 / 1.386936 (-0.964259) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#456f790d2c2e9181bc305ab3d54fe2ca58742b9b \"CML watermark\")\n", "There was an incident in hub-ci that invalidated our token. It's been fixed so I reverted this change" ]

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[]

[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6933). 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) | 0.004937 / 0.011353 (-0.006416) | 0.003706 / 0.011008 (-0.007302) | 0.062627 / 0.038508 (0.024119) | 0.031372 / 0.023109 (0.008263) | 0.246616 / 0.275898 (-0.029282) | 0.272196 / 0.323480 (-0.051284) | 0.004129 / 0.007986 (-0.003856) | 0.002766 / 0.004328 (-0.001562) | 0.049975 / 0.004250 (0.045725) | 0.045098 / 0.037052 (0.008046) | 0.261802 / 0.258489 (0.003313) | 0.290088 / 0.293841 (-0.003753) | 0.027082 / 0.128546 (-0.101465) | 0.010442 / 0.075646 (-0.065205) | 0.201795 / 0.419271 (-0.217477) | 0.037081 / 0.043533 (-0.006452) | 0.249500 / 0.255139 (-0.005639) | 0.268800 / 0.283200 (-0.014399) | 0.017556 / 0.141683 (-0.124127) | 1.137201 / 1.452155 (-0.314953) | 1.186993 / 1.492716 (-0.305723) |\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) | 0.097426 / 0.018006 (0.079419) | 0.303653 / 0.000490 (0.303163) | 0.000235 / 0.000200 (0.000035) | 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) | 0.020206 / 0.037411 (-0.017206) | 0.063673 / 0.014526 (0.049147) | 0.076173 / 0.176557 (-0.100383) | 0.122459 / 0.737135 (-0.614676) | 0.076958 / 0.296338 (-0.219380) |\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) | 0.282146 / 0.215209 (0.066937) | 2.785682 / 2.077655 (0.708027) | 1.468847 / 1.504120 (-0.035273) | 1.346731 / 1.541195 (-0.194464) | 1.378459 / 1.468490 (-0.090031) | 0.564961 / 4.584777 (-4.019816) | 2.400095 / 3.745712 (-1.345617) | 2.658285 / 5.269862 (-2.611577) | 1.747873 / 4.565676 (-2.817803) | 0.063763 / 0.424275 (-0.360512) | 0.004969 / 0.007607 (-0.002638) | 0.337764 / 0.226044 (0.111720) | 3.309568 / 2.268929 (1.040639) | 1.812516 / 55.444624 (-53.632109) | 1.521519 / 6.876477 (-5.354957) | 1.690091 / 2.142072 (-0.451982) | 0.640922 / 4.805227 (-4.164305) | 0.119291 / 6.500664 (-6.381373) | 0.042195 / 0.075469 (-0.033274) |\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) | 0.965327 / 1.841788 (-0.876461) | 11.538832 / 8.074308 (3.464523) | 9.594644 / 10.191392 (-0.596748) | 0.144687 / 0.680424 (-0.535737) | 0.014049 / 0.534201 (-0.520152) | 0.296873 / 0.579283 (-0.282410) | 0.269281 / 0.434364 (-0.165083) | 0.325091 / 0.540337 (-0.215246) | 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) | 0.005239 / 0.011353 (-0.006114) | 0.003168 / 0.011008 (-0.007840) | 0.049301 / 0.038508 (0.010793) | 0.032248 / 0.023109 (0.009139) | 0.266463 / 0.275898 (-0.009435) | 0.293311 / 0.323480 (-0.030168) | 0.004185 / 0.007986 (-0.003800) | 0.002681 / 0.004328 (-0.001647) | 0.048644 / 0.004250 (0.044393) | 0.040366 / 0.037052 (0.003314) | 0.280345 / 0.258489 (0.021856) | 0.312745 / 0.293841 (0.018904) | 0.029616 / 0.128546 (-0.098930) | 0.010001 / 0.075646 (-0.065646) | 0.057365 / 0.419271 (-0.361906) | 0.033189 / 0.043533 (-0.010344) | 0.267601 / 0.255139 (0.012462) | 0.285647 / 0.283200 (0.002448) | 0.017119 / 0.141683 (-0.124564) | 1.139776 / 1.452155 (-0.312378) | 1.172451 / 1.492716 (-0.320266) |\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) | 0.095462 / 0.018006 (0.077455) | 0.303009 / 0.000490 (0.302519) | 0.000227 / 0.000200 (0.000027) | 0.000055 / 0.000054 (0.000000) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.023026 / 0.037411 (-0.014385) | 0.077905 / 0.014526 (0.063380) | 0.087275 / 0.176557 (-0.089282) | 0.127355 / 0.737135 (-0.609780) | 0.088940 / 0.296338 (-0.207399) |\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) | 0.298267 / 0.215209 (0.083058) | 2.894679 / 2.077655 (0.817024) | 1.568663 / 1.504120 (0.064543) | 1.438342 / 1.541195 (-0.102853) | 1.456110 / 1.468490 (-0.012380) | 0.556337 / 4.584777 (-4.028440) | 0.969795 / 3.745712 (-2.775917) | 2.667348 / 5.269862 (-2.602513) | 1.767169 / 4.565676 (-2.798507) | 0.060969 / 0.424275 (-0.363306) | 0.005009 / 0.007607 (-0.002598) | 0.343299 / 0.226044 (0.117255) | 3.396529 / 2.268929 (1.127601) | 1.889816 / 55.444624 (-53.554808) | 1.635077 / 6.876477 (-5.241400) | 1.795238 / 2.142072 (-0.346835) | 0.631876 / 4.805227 (-4.173352) | 0.115483 / 6.500664 (-6.385181) | 0.041772 / 0.075469 (-0.033697) |\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) | 1.008423 / 1.841788 (-0.833364) | 12.432488 / 8.074308 (4.358180) | 10.418002 / 10.191392 (0.226610) | 0.142395 / 0.680424 (-0.538029) | 0.015718 / 0.534201 (-0.518483) | 0.281917 / 0.579283 (-0.297366) | 0.132619 / 0.434364 (-0.301745) | 0.318500 / 0.540337 (-0.221838) | 0.410798 / 1.386936 (-0.976138) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#3d6cd158d2e3bb9030fea7c5a9580b9d34d721ac \"CML watermark\")\n" ]

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[ "thanks !", "<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) | 0.003786 / 0.011008 (-0.007222) | 0.062406 / 0.038508 (0.023898) | 0.029459 / 0.023109 (0.006349) | 0.262388 / 0.275898 (-0.013510) | 0.274119 / 0.323480 (-0.049361) | 0.004085 / 0.007986 (-0.003901) | 0.002754 / 0.004328 (-0.001574) | 0.048779 / 0.004250 (0.044529) | 0.046187 / 0.037052 (0.009135) | 0.263513 / 0.258489 (0.005024) | 0.294260 / 0.293841 (0.000419) | 0.027391 / 0.128546 (-0.101155) | 0.010567 / 0.075646 (-0.065080) | 0.200225 / 0.419271 (-0.219046) | 0.036165 / 0.043533 (-0.007367) | 0.251757 / 0.255139 (-0.003382) | 0.268271 / 0.283200 (-0.014928) | 0.018446 / 0.141683 (-0.123237) | 1.125787 / 1.452155 (-0.326368) | 1.163172 / 1.492716 (-0.329544) |\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) | 0.004428 / 0.018006 (-0.013578) | 0.301730 / 0.000490 (0.301241) | 0.000215 / 0.000200 (0.000015) | 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) | 0.019424 / 0.037411 (-0.017987) | 0.062269 / 0.014526 (0.047743) | 0.074289 / 0.176557 (-0.102268) | 0.121069 / 0.737135 (-0.616067) | 0.076485 / 0.296338 (-0.219853) |\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) | 0.277315 / 0.215209 (0.062106) | 2.742027 / 2.077655 (0.664372) | 1.472970 / 1.504120 (-0.031150) | 1.350065 / 1.541195 (-0.191130) | 1.378806 / 1.468490 (-0.089684) | 0.567742 / 4.584777 (-4.017035) | 2.376752 / 3.745712 (-1.368960) | 2.662459 / 5.269862 (-2.607402) | 1.750396 / 4.565676 (-2.815280) | 0.063589 / 0.424275 (-0.360686) | 0.004987 / 0.007607 (-0.002620) | 0.326441 / 0.226044 (0.100397) | 3.224125 / 2.268929 (0.955197) | 1.801623 / 55.444624 (-53.643001) | 1.534712 / 6.876477 (-5.341765) | 1.652365 / 2.142072 (-0.489708) | 0.647624 / 4.805227 (-4.157603) | 0.117161 / 6.500664 (-6.383504) | 0.041908 / 0.075469 (-0.033561) |\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) | 0.954879 / 1.841788 (-0.886909) | 11.571875 / 8.074308 (3.497567) | 9.489146 / 10.191392 (-0.702246) | 0.141630 / 0.680424 (-0.538794) | 0.014764 / 0.534201 (-0.519437) | 0.285003 / 0.579283 (-0.294280) | 0.266138 / 0.434364 (-0.168226) | 0.323527 / 0.540337 (-0.216810) | 0.419658 / 1.386936 (-0.967278) |\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) | 0.005359 / 0.011353 (-0.005994) | 0.003615 / 0.011008 (-0.007393) | 0.050692 / 0.038508 (0.012184) | 0.033632 / 0.023109 (0.010522) | 0.273614 / 0.275898 (-0.002284) | 0.303780 / 0.323480 (-0.019700) | 0.004171 / 0.007986 (-0.003814) | 0.002687 / 0.004328 (-0.001642) | 0.050002 / 0.004250 (0.045751) | 0.040824 / 0.037052 (0.003772) | 0.287759 / 0.258489 (0.029270) | 0.324144 / 0.293841 (0.030303) | 0.029101 / 0.128546 (-0.099445) | 0.010244 / 0.075646 (-0.065402) | 0.059599 / 0.419271 (-0.359672) | 0.033146 / 0.043533 (-0.010387) | 0.276592 / 0.255139 (0.021453) | 0.293670 / 0.283200 (0.010470) | 0.018270 / 0.141683 (-0.123413) | 1.126216 / 1.452155 (-0.325939) | 1.155658 / 1.492716 (-0.337058) |\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) | 0.093537 / 0.018006 (0.075530) | 0.302706 / 0.000490 (0.302216) | 0.000216 / 0.000200 (0.000016) | 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) | 0.023118 / 0.037411 (-0.014293) | 0.076995 / 0.014526 (0.062469) | 0.089476 / 0.176557 (-0.087080) | 0.130705 / 0.737135 (-0.606430) | 0.090258 / 0.296338 (-0.206081) |\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) | 0.285920 / 0.215209 (0.070710) | 2.830581 / 2.077655 (0.752927) | 1.561695 / 1.504120 (0.057575) | 1.522791 / 1.541195 (-0.018403) | 1.429875 / 1.468490 (-0.038615) | 0.566683 / 4.584777 (-4.018094) | 0.957157 / 3.745712 (-2.788555) | 2.663718 / 5.269862 (-2.606143) | 1.748885 / 4.565676 (-2.816791) | 0.063697 / 0.424275 (-0.360578) | 0.004996 / 0.007607 (-0.002611) | 0.340042 / 0.226044 (0.113998) | 3.352792 / 2.268929 (1.083863) | 1.907189 / 55.444624 (-53.537435) | 1.608177 / 6.876477 (-5.268300) | 1.775438 / 2.142072 (-0.366634) | 0.645264 / 4.805227 (-4.159963) | 0.116441 / 6.500664 (-6.384223) | 0.040671 / 0.075469 (-0.034798) |\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) | 1.005050 / 1.841788 (-0.836738) | 12.040057 / 8.074308 (3.965749) | 10.213560 / 10.191392 (0.022168) | 0.138383 / 0.680424 (-0.542041) | 0.015409 / 0.534201 (-0.518792) | 0.283509 / 0.579283 (-0.295774) | 0.125501 / 0.434364 (-0.308863) | 0.318816 / 0.540337 (-0.221521) | 0.415454 / 1.386936 (-0.971482) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#cbb29cea0e21dc0eb8f7de01d0c6ed5718d6ce4e \"CML watermark\")\n" ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6931). 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) | 0.005362 / 0.011353 (-0.005991) | 0.003969 / 0.011008 (-0.007039) | 0.063390 / 0.038508 (0.024882) | 0.030814 / 0.023109 (0.007705) | 0.246891 / 0.275898 (-0.029007) | 0.271047 / 0.323480 (-0.052432) | 0.004036 / 0.007986 (-0.003950) | 0.002732 / 0.004328 (-0.001597) | 0.049466 / 0.004250 (0.045216) | 0.047227 / 0.037052 (0.010175) | 0.255978 / 0.258489 (-0.002511) | 0.297956 / 0.293841 (0.004115) | 0.028641 / 0.128546 (-0.099905) | 0.010510 / 0.075646 (-0.065136) | 0.204268 / 0.419271 (-0.215004) | 0.037093 / 0.043533 (-0.006440) | 0.247287 / 0.255139 (-0.007852) | 0.263830 / 0.283200 (-0.019370) | 0.018335 / 0.141683 (-0.123348) | 1.116074 / 1.452155 (-0.336081) | 1.182589 / 1.492716 (-0.310128) |\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) | 0.094435 / 0.018006 (0.076429) | 0.310422 / 0.000490 (0.309932) | 0.000215 / 0.000200 (0.000015) | 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) | 0.019220 / 0.037411 (-0.018192) | 0.062090 / 0.014526 (0.047564) | 0.074511 / 0.176557 (-0.102046) | 0.121825 / 0.737135 (-0.615310) | 0.075406 / 0.296338 (-0.220933) |\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) | 0.281185 / 0.215209 (0.065976) | 2.770157 / 2.077655 (0.692502) | 1.472095 / 1.504120 (-0.032025) | 1.339342 / 1.541195 (-0.201853) | 1.374621 / 1.468490 (-0.093869) | 0.566607 / 4.584777 (-4.018170) | 2.357642 / 3.745712 (-1.388070) | 2.735034 / 5.269862 (-2.534827) | 1.782779 / 4.565676 (-2.782897) | 0.063046 / 0.424275 (-0.361229) | 0.005015 / 0.007607 (-0.002592) | 0.336690 / 0.226044 (0.110646) | 3.360955 / 2.268929 (1.092027) | 1.804424 / 55.444624 (-53.640200) | 1.517334 / 6.876477 (-5.359143) | 1.665254 / 2.142072 (-0.476818) | 0.627185 / 4.805227 (-4.178042) | 0.114388 / 6.500664 (-6.386276) | 0.041788 / 0.075469 (-0.033681) |\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) | 0.975270 / 1.841788 (-0.866517) | 11.647633 / 8.074308 (3.573325) | 9.872873 / 10.191392 (-0.318519) | 0.141744 / 0.680424 (-0.538680) | 0.014524 / 0.534201 (-0.519677) | 0.286697 / 0.579283 (-0.292586) | 0.266837 / 0.434364 (-0.167527) | 0.328513 / 0.540337 (-0.211825) | 0.424676 / 1.386936 (-0.962260) |\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) | 0.005654 / 0.011353 (-0.005699) | 0.004058 / 0.011008 (-0.006950) | 0.051030 / 0.038508 (0.012522) | 0.033085 / 0.023109 (0.009976) | 0.307532 / 0.275898 (0.031634) | 0.335672 / 0.323480 (0.012192) | 0.004244 / 0.007986 (-0.003742) | 0.002842 / 0.004328 (-0.001487) | 0.050131 / 0.004250 (0.045880) | 0.040709 / 0.037052 (0.003656) | 0.319514 / 0.258489 (0.061025) | 0.357153 / 0.293841 (0.063312) | 0.029014 / 0.128546 (-0.099532) | 0.010999 / 0.075646 (-0.064648) | 0.058789 / 0.419271 (-0.360482) | 0.033284 / 0.043533 (-0.010249) | 0.310783 / 0.255139 (0.055644) | 0.331466 / 0.283200 (0.048266) | 0.018998 / 0.141683 (-0.122685) | 1.138822 / 1.452155 (-0.313332) | 1.180731 / 1.492716 (-0.311985) |\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) | 0.095725 / 0.018006 (0.077719) | 0.302788 / 0.000490 (0.302298) | 0.000206 / 0.000200 (0.000006) | 0.000056 / 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) | 0.023247 / 0.037411 (-0.014164) | 0.077619 / 0.014526 (0.063093) | 0.090489 / 0.176557 (-0.086067) | 0.132033 / 0.737135 (-0.605102) | 0.090964 / 0.296338 (-0.205374) |\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) | 0.297912 / 0.215209 (0.082703) | 2.954107 / 2.077655 (0.876452) | 1.591155 / 1.504120 (0.087035) | 1.469217 / 1.541195 (-0.071978) | 1.513315 / 1.468490 (0.044825) | 0.562728 / 4.584777 (-4.022049) | 0.960093 / 3.745712 (-2.785620) | 2.852106 / 5.269862 (-2.417756) | 1.861668 / 4.565676 (-2.704009) | 0.063530 / 0.424275 (-0.360745) | 0.005194 / 0.007607 (-0.002413) | 0.351116 / 0.226044 (0.125072) | 3.498787 / 2.268929 (1.229859) | 1.952223 / 55.444624 (-53.492401) | 1.696208 / 6.876477 (-5.180269) | 1.861650 / 2.142072 (-0.280422) | 0.653494 / 4.805227 (-4.151733) | 0.123797 / 6.500664 (-6.376868) | 0.042696 / 0.075469 (-0.032773) |\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) | 1.006657 / 1.841788 (-0.835131) | 12.659771 / 8.074308 (4.585463) | 10.672140 / 10.191392 (0.480748) | 0.143726 / 0.680424 (-0.536698) | 0.015895 / 0.534201 (-0.518306) | 0.285952 / 0.579283 (-0.293331) | 0.126078 / 0.434364 (-0.308286) | 0.325943 / 0.540337 (-0.214395) | 0.410774 / 1.386936 (-0.976162) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#88d53d1ae762bec6736fffb000e6540e52bf1998 \"CML watermark\")\n" ]

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[ "How do you solve it ?\r\n", "> How do you solve it ?\r\n\r\nPlease check your Python environment and dataset version. I have just resolved the issue, which was caused by a Python environment switching error\r\n" ]

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[]

[ "you're right, we're tackling this here: https://github.com/huggingface/dataset-viewer/issues/2757", "@severo : great !" ]

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[ "<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) | 0.005062 / 0.011353 (-0.006291) | 0.003410 / 0.011008 (-0.007598) | 0.062241 / 0.038508 (0.023733) | 0.030294 / 0.023109 (0.007185) | 0.249249 / 0.275898 (-0.026649) | 0.267718 / 0.323480 (-0.055761) | 0.003047 / 0.007986 (-0.004938) | 0.002661 / 0.004328 (-0.001668) | 0.049142 / 0.004250 (0.044892) | 0.047929 / 0.037052 (0.010877) | 0.255262 / 0.258489 (-0.003227) | 0.286241 / 0.293841 (-0.007600) | 0.027064 / 0.128546 (-0.101482) | 0.010374 / 0.075646 (-0.065273) | 0.201454 / 0.419271 (-0.217818) | 0.036586 / 0.043533 (-0.006947) | 0.255200 / 0.255139 (0.000061) | 0.267660 / 0.283200 (-0.015539) | 0.018621 / 0.141683 (-0.123062) | 1.159821 / 1.452155 (-0.292334) | 1.171597 / 1.492716 (-0.321120) |\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) | 0.004752 / 0.018006 (-0.013254) | 0.295427 / 0.000490 (0.294937) | 0.000225 / 0.000200 (0.000025) | 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) | 0.018914 / 0.037411 (-0.018497) | 0.061180 / 0.014526 (0.046654) | 0.073649 / 0.176557 (-0.102907) | 0.120142 / 0.737135 (-0.616993) | 0.074754 / 0.296338 (-0.221585) |\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) | 0.286637 / 0.215209 (0.071428) | 2.807941 / 2.077655 (0.730287) | 1.473577 / 1.504120 (-0.030542) | 1.353112 / 1.541195 (-0.188083) | 1.363020 / 1.468490 (-0.105470) | 0.567745 / 4.584777 (-4.017032) | 2.384887 / 3.745712 (-1.360826) | 2.685132 / 5.269862 (-2.584730) | 1.755922 / 4.565676 (-2.809755) | 0.062296 / 0.424275 (-0.361979) | 0.004941 / 0.007607 (-0.002666) | 0.346752 / 0.226044 (0.120707) | 3.378623 / 2.268929 (1.109694) | 1.809070 / 55.444624 (-53.635555) | 1.531490 / 6.876477 (-5.344986) | 1.687954 / 2.142072 (-0.454119) | 0.639917 / 4.805227 (-4.165310) | 0.118455 / 6.500664 (-6.382209) | 0.043072 / 0.075469 (-0.032397) |\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) | 0.977154 / 1.841788 (-0.864634) | 11.380127 / 8.074308 (3.305819) | 9.621632 / 10.191392 (-0.569760) | 0.141768 / 0.680424 (-0.538655) | 0.014120 / 0.534201 (-0.520081) | 0.285073 / 0.579283 (-0.294210) | 0.264801 / 0.434364 (-0.169563) | 0.322357 / 0.540337 (-0.217981) | 0.431192 / 1.386936 (-0.955744) |\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) | 0.005162 / 0.011353 (-0.006191) | 0.003499 / 0.011008 (-0.007509) | 0.049667 / 0.038508 (0.011159) | 0.032473 / 0.023109 (0.009363) | 0.259988 / 0.275898 (-0.015910) | 0.285723 / 0.323480 (-0.037757) | 0.004197 / 0.007986 (-0.003789) | 0.002710 / 0.004328 (-0.001618) | 0.049235 / 0.004250 (0.044984) | 0.040440 / 0.037052 (0.003387) | 0.276791 / 0.258489 (0.018302) | 0.311990 / 0.293841 (0.018149) | 0.029217 / 0.128546 (-0.099329) | 0.010217 / 0.075646 (-0.065429) | 0.057844 / 0.419271 (-0.361427) | 0.032799 / 0.043533 (-0.010734) | 0.260705 / 0.255139 (0.005566) | 0.280439 / 0.283200 (-0.002761) | 0.018682 / 0.141683 (-0.123001) | 1.135946 / 1.452155 (-0.316208) | 1.163144 / 1.492716 (-0.329572) |\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) | 0.097968 / 0.018006 (0.079961) | 0.309276 / 0.000490 (0.308786) | 0.000214 / 0.000200 (0.000014) | 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) | 0.022623 / 0.037411 (-0.014788) | 0.075471 / 0.014526 (0.060945) | 0.087928 / 0.176557 (-0.088629) | 0.129537 / 0.737135 (-0.607599) | 0.089376 / 0.296338 (-0.206963) |\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) | 0.298223 / 0.215209 (0.083014) | 2.940462 / 2.077655 (0.862807) | 1.586024 / 1.504120 (0.081904) | 1.451161 / 1.541195 (-0.090034) | 1.457707 / 1.468490 (-0.010783) | 0.571172 / 4.584777 (-4.013604) | 0.961591 / 3.745712 (-2.784121) | 2.661258 / 5.269862 (-2.608604) | 1.755172 / 4.565676 (-2.810504) | 0.063430 / 0.424275 (-0.360845) | 0.005034 / 0.007607 (-0.002573) | 0.352356 / 0.226044 (0.126312) | 3.454986 / 2.268929 (1.186057) | 1.967375 / 55.444624 (-53.477249) | 1.638465 / 6.876477 (-5.238012) | 1.774098 / 2.142072 (-0.367975) | 0.650094 / 4.805227 (-4.155134) | 0.117377 / 6.500664 (-6.383287) | 0.041229 / 0.075469 (-0.034240) |\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) | 1.014356 / 1.841788 (-0.827432) | 12.175823 / 8.074308 (4.101515) | 10.657486 / 10.191392 (0.466094) | 0.145080 / 0.680424 (-0.535344) | 0.015563 / 0.534201 (-0.518638) | 0.287093 / 0.579283 (-0.292190) | 0.127164 / 0.434364 (-0.307200) | 0.318518 / 0.540337 (-0.221820) | 0.415333 / 1.386936 (-0.971603) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#372078f617d9210c7f073c22f5f6f4fbee52c67f \"CML watermark\")\n" ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6925). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "Do you think this is worth making a patch release for?\r\nCC: @huggingface/datasets", "I will add some regression tests before merging.\r\n\r\nAnd I will make a patch release afterwards.", "<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) | 0.004959 / 0.011353 (-0.006394) | 0.003654 / 0.011008 (-0.007354) | 0.064087 / 0.038508 (0.025579) | 0.031942 / 0.023109 (0.008833) | 0.236830 / 0.275898 (-0.039068) | 0.265359 / 0.323480 (-0.058121) | 0.003108 / 0.007986 (-0.004878) | 0.002824 / 0.004328 (-0.001504) | 0.049102 / 0.004250 (0.044852) | 0.046070 / 0.037052 (0.009017) | 0.248830 / 0.258489 (-0.009659) | 0.283900 / 0.293841 (-0.009941) | 0.027799 / 0.128546 (-0.100747) | 0.010572 / 0.075646 (-0.065074) | 0.223595 / 0.419271 (-0.195677) | 0.036951 / 0.043533 (-0.006582) | 0.238813 / 0.255139 (-0.016326) | 0.253841 / 0.283200 (-0.029359) | 0.018471 / 0.141683 (-0.123212) | 1.131969 / 1.452155 (-0.320186) | 1.173763 / 1.492716 (-0.318954) |\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) | 0.095504 / 0.018006 (0.077498) | 0.301469 / 0.000490 (0.300979) | 0.000212 / 0.000200 (0.000012) | 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) | 0.019194 / 0.037411 (-0.018217) | 0.062313 / 0.014526 (0.047787) | 0.075852 / 0.176557 (-0.100704) | 0.121996 / 0.737135 (-0.615140) | 0.076416 / 0.296338 (-0.219923) |\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) | 0.292465 / 0.215209 (0.077256) | 2.910234 / 2.077655 (0.832579) | 1.479672 / 1.504120 (-0.024448) | 1.332281 / 1.541195 (-0.208913) | 1.354095 / 1.468490 (-0.114395) | 0.573438 / 4.584777 (-4.011339) | 2.382406 / 3.745712 (-1.363307) | 2.708289 / 5.269862 (-2.561572) | 1.739665 / 4.565676 (-2.826011) | 0.063514 / 0.424275 (-0.360761) | 0.005008 / 0.007607 (-0.002599) | 0.350070 / 0.226044 (0.124025) | 3.475837 / 2.268929 (1.206909) | 1.804639 / 55.444624 (-53.639985) | 1.520472 / 6.876477 (-5.356005) | 1.658061 / 2.142072 (-0.484011) | 0.648495 / 4.805227 (-4.156732) | 0.118394 / 6.500664 (-6.382270) | 0.042557 / 0.075469 (-0.032912) |\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) | 0.960772 / 1.841788 (-0.881016) | 11.451629 / 8.074308 (3.377321) | 9.613331 / 10.191392 (-0.578061) | 0.130259 / 0.680424 (-0.550164) | 0.015828 / 0.534201 (-0.518373) | 0.287581 / 0.579283 (-0.291702) | 0.266517 / 0.434364 (-0.167847) | 0.327334 / 0.540337 (-0.213003) | 0.427881 / 1.386936 (-0.959055) |\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) | 0.005364 / 0.011353 (-0.005989) | 0.003723 / 0.011008 (-0.007285) | 0.049990 / 0.038508 (0.011482) | 0.032023 / 0.023109 (0.008913) | 0.258609 / 0.275898 (-0.017289) | 0.281250 / 0.323480 (-0.042230) | 0.004222 / 0.007986 (-0.003764) | 0.002799 / 0.004328 (-0.001529) | 0.049546 / 0.004250 (0.045296) | 0.040298 / 0.037052 (0.003246) | 0.273552 / 0.258489 (0.015063) | 0.304042 / 0.293841 (0.010201) | 0.030116 / 0.128546 (-0.098430) | 0.010792 / 0.075646 (-0.064855) | 0.058427 / 0.419271 (-0.360845) | 0.033415 / 0.043533 (-0.010118) | 0.258794 / 0.255139 (0.003655) | 0.275304 / 0.283200 (-0.007896) | 0.017944 / 0.141683 (-0.123739) | 1.109291 / 1.452155 (-0.342864) | 1.156627 / 1.492716 (-0.336090) |\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) | 0.096700 / 0.018006 (0.078693) | 0.301108 / 0.000490 (0.300618) | 0.000208 / 0.000200 (0.000008) | 0.000054 / 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) | 0.022632 / 0.037411 (-0.014779) | 0.075813 / 0.014526 (0.061287) | 0.090302 / 0.176557 (-0.086254) | 0.130375 / 0.737135 (-0.606760) | 0.089710 / 0.296338 (-0.206629) |\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) | 0.297091 / 0.215209 (0.081882) | 2.910379 / 2.077655 (0.832725) | 1.570460 / 1.504120 (0.066340) | 1.441619 / 1.541195 (-0.099576) | 1.442417 / 1.468490 (-0.026073) | 0.570034 / 4.584777 (-4.014743) | 0.952613 / 3.745712 (-2.793099) | 2.659274 / 5.269862 (-2.610588) | 1.751013 / 4.565676 (-2.814663) | 0.064639 / 0.424275 (-0.359636) | 0.005145 / 0.007607 (-0.002462) | 0.347478 / 0.226044 (0.121434) | 3.443862 / 2.268929 (1.174933) | 1.897246 / 55.444624 (-53.547379) | 1.609267 / 6.876477 (-5.267210) | 1.755116 / 2.142072 (-0.386956) | 0.658982 / 4.805227 (-4.146245) | 0.117000 / 6.500664 (-6.383664) | 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) | 1.005843 / 1.841788 (-0.835944) | 12.101306 / 8.074308 (4.026998) | 10.370706 / 10.191392 (0.179314) | 0.139374 / 0.680424 (-0.541050) | 0.015605 / 0.534201 (-0.518596) | 0.286978 / 0.579283 (-0.292305) | 0.122951 / 0.434364 (-0.311413) | 0.331729 / 0.540337 (-0.208609) | 0.422088 / 1.386936 (-0.964848) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#157585f964b1c7f675860af0d21712555b34aabc \"CML watermark\")\n", "I'm hitting this error now, using Spaces. Here's what an attempt to just get the 'validation' split is doing:\r\n\r\ncode:\r\n\r\n```\r\n\r\n  | import os\r\n  | from huggingface_hub import HfApi\r\n  | from datasets import Dataset, load_dataset, DownloadConfig\r\n  |  \r\n  |  \r\n  | GATED_IMAGENET = os.environ.get(\"GATED_IMAGENET\")\r\n  | api = HfApi(token=GATED_IMAGENET)\r\n |\r\n  | ds = load_dataset('datacomp/imagenet-1k-random0.0', token=GATED_IMAGENET, data_files={'validation': 'data/val*'}, split='validation', trust_remote_code=True)\r\n\r\n\r\n```\r\n\r\nlog:\r\n\r\n```\r\nGenerating validation split: 0%| | 0/50000 [00:00<?, ? examples/s]\r\nGenerating validation split: 12%|█▏ | 6172/50000 [00:01<00:07, 5804.90 examples/s]\r\nGenerating validation split: 25%|██▌ | 12716/50000 [00:02<00:06, 6167.77 examples/s]\r\nGenerating validation split: 38%|███▊ | 19060/50000 [00:03<00:04, 6218.99 examples/s]\r\nGenerating validation split: 51%|█████ | 25603/50000 [00:04<00:03, 6126.35 examples/s]\r\nGenerating validation split: 64%|██████▍ | 32145/50000 [00:05<00:02, 6166.95 examples/s]\r\nGenerating validation split: 77%|███████▋ | 38716/50000 [00:06<00:01, 6272.66 examples/s]\r\nGenerating validation split: 90%|█████████ | 45158/50000 [00:07<00:00, 6307.44 examples/s]\r\nGenerating validation split: 100%|██████████| 50000/50000 [00:08<00:00, 6212.19 examples/s]\r\nTraceback (most recent call last):\r\n File \"/home/user/app/app.py\", line 12, in <module>\r\n ds = load_dataset('datacomp/imagenet-1k-random0.0', token=GATED_IMAGENET, data_files={'validation': 'data/val*'}, split='validation', trust_remote_code=True)\r\n File \"/usr/local/lib/python3.10/site-packages/datasets/load.py\", line 2154, in load_dataset\r\n builder_instance.download_and_prepare(\r\n File \"/usr/local/lib/python3.10/site-packages/datasets/builder.py\", line 924, in download_and_prepare\r\n self._download_and_prepare(\r\n File \"/usr/local/lib/python3.10/site-packages/datasets/builder.py\", line 1018, in _download_and_prepare\r\n verify_splits(self.info.splits, split_dict)\r\n File \"/usr/local/lib/python3.10/site-packages/datasets/utils/info_utils.py\", line 68, in verify_splits\r\n raise ExpectedMoreSplitsError(str(set(expected_splits) - set(recorded_splits)))\r\ndatasets.exceptions.ExpectedMoreSplitsError: {'train', 'test'}\r\n```", "Hi Meg ! Thanks for reporting, I'll see how I can fix this. In the meantime feel free to pass `verification_mode=\"no_checks\"` to `load_dataset`" ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6922). 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) | 0.005525 / 0.011353 (-0.005828) | 0.004013 / 0.011008 (-0.006996) | 0.063931 / 0.038508 (0.025423) | 0.033857 / 0.023109 (0.010748) | 0.250910 / 0.275898 (-0.024988) | 0.278289 / 0.323480 (-0.045191) | 0.004289 / 0.007986 (-0.003697) | 0.002800 / 0.004328 (-0.001529) | 0.050127 / 0.004250 (0.045877) | 0.048901 / 0.037052 (0.011848) | 0.260628 / 0.258489 (0.002139) | 0.293904 / 0.293841 (0.000063) | 0.028339 / 0.128546 (-0.100207) | 0.010879 / 0.075646 (-0.064767) | 0.203618 / 0.419271 (-0.215654) | 0.036241 / 0.043533 (-0.007292) | 0.250481 / 0.255139 (-0.004657) | 0.274274 / 0.283200 (-0.008926) | 0.018912 / 0.141683 (-0.122771) | 1.146785 / 1.452155 (-0.305370) | 1.199795 / 1.492716 (-0.292921) |\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) | 0.095571 / 0.018006 (0.077564) | 0.302961 / 0.000490 (0.302471) | 0.000217 / 0.000200 (0.000017) | 0.000109 / 0.000054 (0.000055) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.020121 / 0.037411 (-0.017290) | 0.063231 / 0.014526 (0.048705) | 0.075434 / 0.176557 (-0.101122) | 0.123994 / 0.737135 (-0.613141) | 0.076479 / 0.296338 (-0.219860) |\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) | 0.277816 / 0.215209 (0.062607) | 2.775481 / 2.077655 (0.697826) | 1.454881 / 1.504120 (-0.049239) | 1.339055 / 1.541195 (-0.202140) | 1.347810 / 1.468490 (-0.120681) | 0.572802 / 4.584777 (-4.011975) | 2.357490 / 3.745712 (-1.388222) | 2.822548 / 5.269862 (-2.447313) | 1.746538 / 4.565676 (-2.819138) | 0.066159 / 0.424275 (-0.358116) | 0.005037 / 0.007607 (-0.002570) | 0.329256 / 0.226044 (0.103212) | 3.277511 / 2.268929 (1.008582) | 1.807855 / 55.444624 (-53.636769) | 1.505507 / 6.876477 (-5.370970) | 1.634237 / 2.142072 (-0.507835) | 0.643999 / 4.805227 (-4.161229) | 0.117494 / 6.500664 (-6.383170) | 0.042634 / 0.075469 (-0.032835) |\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) | 0.977689 / 1.841788 (-0.864098) | 12.261836 / 8.074308 (4.187528) | 9.871541 / 10.191392 (-0.319851) | 0.147293 / 0.680424 (-0.533130) | 0.015134 / 0.534201 (-0.519067) | 0.287677 / 0.579283 (-0.291606) | 0.264622 / 0.434364 (-0.169742) | 0.330511 / 0.540337 (-0.209826) | 0.467618 / 1.386936 (-0.919318) |\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) | 0.005690 / 0.011353 (-0.005663) | 0.003801 / 0.011008 (-0.007207) | 0.051817 / 0.038508 (0.013309) | 0.033355 / 0.023109 (0.010246) | 0.264416 / 0.275898 (-0.011482) | 0.288494 / 0.323480 (-0.034986) | 0.004246 / 0.007986 (-0.003740) | 0.002814 / 0.004328 (-0.001515) | 0.050547 / 0.004250 (0.046297) | 0.042977 / 0.037052 (0.005925) | 0.276884 / 0.258489 (0.018395) | 0.303758 / 0.293841 (0.009917) | 0.029412 / 0.128546 (-0.099134) | 0.010697 / 0.075646 (-0.064949) | 0.059497 / 0.419271 (-0.359775) | 0.033670 / 0.043533 (-0.009862) | 0.261311 / 0.255139 (0.006172) | 0.286478 / 0.283200 (0.003278) | 0.019386 / 0.141683 (-0.122297) | 1.155943 / 1.452155 (-0.296211) | 1.198512 / 1.492716 (-0.294205) |\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) | 0.092954 / 0.018006 (0.074948) | 0.294144 / 0.000490 (0.293655) | 0.000213 / 0.000200 (0.000013) | 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) | 0.023013 / 0.037411 (-0.014398) | 0.077161 / 0.014526 (0.062635) | 0.089957 / 0.176557 (-0.086600) | 0.129305 / 0.737135 (-0.607831) | 0.091006 / 0.296338 (-0.205333) |\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) | 0.294091 / 0.215209 (0.078882) | 2.885395 / 2.077655 (0.807741) | 1.555658 / 1.504120 (0.051538) | 1.423276 / 1.541195 (-0.117919) | 1.476485 / 1.468490 (0.007995) | 0.569507 / 4.584777 (-4.015270) | 0.979221 / 3.745712 (-2.766491) | 2.818503 / 5.269862 (-2.451358) | 1.871938 / 4.565676 (-2.693739) | 0.064342 / 0.424275 (-0.359933) | 0.005495 / 0.007607 (-0.002112) | 0.351451 / 0.226044 (0.125407) | 3.516078 / 2.268929 (1.247149) | 1.928351 / 55.444624 (-53.516273) | 1.625362 / 6.876477 (-5.251115) | 1.813756 / 2.142072 (-0.328317) | 0.657642 / 4.805227 (-4.147585) | 0.117893 / 6.500664 (-6.382771) | 0.042009 / 0.075469 (-0.033460) |\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) | 1.032893 / 1.841788 (-0.808894) | 12.983400 / 8.074308 (4.909092) | 10.747204 / 10.191392 (0.555812) | 0.133163 / 0.680424 (-0.547261) | 0.015875 / 0.534201 (-0.518326) | 0.312592 / 0.579283 (-0.266691) | 0.124780 / 0.434364 (-0.309584) | 0.350735 / 0.540337 (-0.189603) | 0.447130 / 1.386936 (-0.939806) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#048c789607af0370c1f2337248897956f7a91617 \"CML watermark\")\n" ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6921). 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) | 0.005252 / 0.011353 (-0.006100) | 0.003752 / 0.011008 (-0.007257) | 0.064034 / 0.038508 (0.025526) | 0.031205 / 0.023109 (0.008096) | 0.248903 / 0.275898 (-0.026995) | 0.275808 / 0.323480 (-0.047671) | 0.003135 / 0.007986 (-0.004851) | 0.002635 / 0.004328 (-0.001693) | 0.049869 / 0.004250 (0.045619) | 0.047602 / 0.037052 (0.010549) | 0.259738 / 0.258489 (0.001249) | 0.296131 / 0.293841 (0.002290) | 0.027467 / 0.128546 (-0.101080) | 0.010449 / 0.075646 (-0.065197) | 0.201369 / 0.419271 (-0.217903) | 0.036317 / 0.043533 (-0.007216) | 0.244347 / 0.255139 (-0.010792) | 0.267597 / 0.283200 (-0.015602) | 0.019930 / 0.141683 (-0.121753) | 1.149012 / 1.452155 (-0.303143) | 1.188083 / 1.492716 (-0.304633) |\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) | 0.095190 / 0.018006 (0.077184) | 0.300705 / 0.000490 (0.300215) | 0.000222 / 0.000200 (0.000022) | 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) | 0.019297 / 0.037411 (-0.018115) | 0.063183 / 0.014526 (0.048657) | 0.075094 / 0.176557 (-0.101463) | 0.123556 / 0.737135 (-0.613579) | 0.076721 / 0.296338 (-0.219618) |\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) | 0.284136 / 0.215209 (0.068927) | 2.814041 / 2.077655 (0.736387) | 1.471038 / 1.504120 (-0.033082) | 1.344002 / 1.541195 (-0.197193) | 1.353875 / 1.468490 (-0.114615) | 0.599495 / 4.584777 (-3.985282) | 2.394491 / 3.745712 (-1.351221) | 2.781734 / 5.269862 (-2.488128) | 1.729829 / 4.565676 (-2.835848) | 0.064194 / 0.424275 (-0.360081) | 0.005022 / 0.007607 (-0.002585) | 0.343384 / 0.226044 (0.117340) | 3.357067 / 2.268929 (1.088139) | 1.816323 / 55.444624 (-53.628301) | 1.549405 / 6.876477 (-5.327072) | 1.594394 / 2.142072 (-0.547679) | 0.660650 / 4.805227 (-4.144578) | 0.120271 / 6.500664 (-6.380393) | 0.042422 / 0.075469 (-0.033047) |\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) | 0.975776 / 1.841788 (-0.866011) | 11.828093 / 8.074308 (3.753784) | 9.384164 / 10.191392 (-0.807228) | 0.140761 / 0.680424 (-0.539663) | 0.014038 / 0.534201 (-0.520163) | 0.284904 / 0.579283 (-0.294379) | 0.263430 / 0.434364 (-0.170934) | 0.320856 / 0.540337 (-0.219482) | 0.419199 / 1.386936 (-0.967737) |\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) | 0.005672 / 0.011353 (-0.005681) | 0.003667 / 0.011008 (-0.007341) | 0.049989 / 0.038508 (0.011481) | 0.033115 / 0.023109 (0.010006) | 0.269808 / 0.275898 (-0.006090) | 0.293286 / 0.323480 (-0.030193) | 0.004238 / 0.007986 (-0.003748) | 0.002722 / 0.004328 (-0.001606) | 0.049516 / 0.004250 (0.045265) | 0.042076 / 0.037052 (0.005024) | 0.282182 / 0.258489 (0.023693) | 0.310817 / 0.293841 (0.016976) | 0.029824 / 0.128546 (-0.098722) | 0.010516 / 0.075646 (-0.065130) | 0.058223 / 0.419271 (-0.361049) | 0.033263 / 0.043533 (-0.010270) | 0.268769 / 0.255139 (0.013630) | 0.288308 / 0.283200 (0.005108) | 0.018531 / 0.141683 (-0.123151) | 1.136806 / 1.452155 (-0.315349) | 1.192636 / 1.492716 (-0.300080) |\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) | 0.096583 / 0.018006 (0.078577) | 0.303678 / 0.000490 (0.303188) | 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) | 0.022741 / 0.037411 (-0.014670) | 0.075799 / 0.014526 (0.061273) | 0.089930 / 0.176557 (-0.086626) | 0.129093 / 0.737135 (-0.608042) | 0.089672 / 0.296338 (-0.206666) |\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) | 0.292789 / 0.215209 (0.077580) | 2.860137 / 2.077655 (0.782483) | 1.566678 / 1.504120 (0.062558) | 1.437756 / 1.541195 (-0.103439) | 1.472347 / 1.468490 (0.003857) | 0.566814 / 4.584777 (-4.017963) | 0.963918 / 3.745712 (-2.781794) | 2.717199 / 5.269862 (-2.552663) | 1.763612 / 4.565676 (-2.802064) | 0.063601 / 0.424275 (-0.360674) | 0.005308 / 0.007607 (-0.002299) | 0.363111 / 0.226044 (0.137066) | 3.458222 / 2.268929 (1.189293) | 1.939185 / 55.444624 (-53.505440) | 1.659552 / 6.876477 (-5.216925) | 1.801006 / 2.142072 (-0.341067) | 0.648884 / 4.805227 (-4.156343) | 0.116259 / 6.500664 (-6.384405) | 0.041384 / 0.075469 (-0.034085) |\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) | 1.001594 / 1.841788 (-0.840194) | 12.371125 / 8.074308 (4.296817) | 10.489763 / 10.191392 (0.298371) | 0.132500 / 0.680424 (-0.547924) | 0.014742 / 0.534201 (-0.519459) | 0.282258 / 0.579283 (-0.297026) | 0.122755 / 0.434364 (-0.311608) | 0.346068 / 0.540337 (-0.194269) | 0.424943 / 1.386936 (-0.961994) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#df445c20346a34c08e7e039e4ec1a302eef3a69c \"CML watermark\")\n" ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6920). 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) | 0.005643 / 0.011353 (-0.005710) | 0.003810 / 0.011008 (-0.007198) | 0.065896 / 0.038508 (0.027388) | 0.031692 / 0.023109 (0.008583) | 0.258297 / 0.275898 (-0.017601) | 0.294555 / 0.323480 (-0.028925) | 0.004403 / 0.007986 (-0.003583) | 0.002857 / 0.004328 (-0.001472) | 0.049848 / 0.004250 (0.045597) | 0.049719 / 0.037052 (0.012666) | 0.266393 / 0.258489 (0.007904) | 0.306214 / 0.293841 (0.012373) | 0.028283 / 0.128546 (-0.100264) | 0.010450 / 0.075646 (-0.065196) | 0.203064 / 0.419271 (-0.216208) | 0.036535 / 0.043533 (-0.006998) | 0.247839 / 0.255139 (-0.007300) | 0.270538 / 0.283200 (-0.012661) | 0.018748 / 0.141683 (-0.122935) | 1.117478 / 1.452155 (-0.334677) | 1.162575 / 1.492716 (-0.330141) |\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) | 0.101074 / 0.018006 (0.083068) | 0.304321 / 0.000490 (0.303831) | 0.000270 / 0.000200 (0.000070) | 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) | 0.019036 / 0.037411 (-0.018376) | 0.064496 / 0.014526 (0.049970) | 0.076848 / 0.176557 (-0.099709) | 0.122979 / 0.737135 (-0.614156) | 0.078008 / 0.296338 (-0.218330) |\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) | 0.287009 / 0.215209 (0.071800) | 2.839084 / 2.077655 (0.761429) | 1.495977 / 1.504120 (-0.008143) | 1.379147 / 1.541195 (-0.162047) | 1.413170 / 1.468490 (-0.055320) | 0.616408 / 4.584777 (-3.968369) | 2.419183 / 3.745712 (-1.326529) | 2.905720 / 5.269862 (-2.364142) | 1.801634 / 4.565676 (-2.764043) | 0.064034 / 0.424275 (-0.360241) | 0.005098 / 0.007607 (-0.002509) | 0.341732 / 0.226044 (0.115688) | 3.365262 / 2.268929 (1.096334) | 1.844335 / 55.444624 (-53.600289) | 1.561450 / 6.876477 (-5.315027) | 1.646254 / 2.142072 (-0.495819) | 0.654993 / 4.805227 (-4.150234) | 0.119837 / 6.500664 (-6.380827) | 0.043375 / 0.075469 (-0.032094) |\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) | 1.000352 / 1.841788 (-0.841435) | 12.765122 / 8.074308 (4.690813) | 9.818879 / 10.191392 (-0.372513) | 0.133986 / 0.680424 (-0.546438) | 0.014065 / 0.534201 (-0.520136) | 0.295859 / 0.579283 (-0.283424) | 0.268497 / 0.434364 (-0.165867) | 0.330909 / 0.540337 (-0.209429) | 0.449218 / 1.386936 (-0.937718) |\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) | 0.005646 / 0.011353 (-0.005707) | 0.003926 / 0.011008 (-0.007082) | 0.050437 / 0.038508 (0.011929) | 0.031828 / 0.023109 (0.008719) | 0.268218 / 0.275898 (-0.007680) | 0.292987 / 0.323480 (-0.030493) | 0.004353 / 0.007986 (-0.003633) | 0.002933 / 0.004328 (-0.001395) | 0.050357 / 0.004250 (0.046107) | 0.042988 / 0.037052 (0.005935) | 0.281627 / 0.258489 (0.023138) | 0.305664 / 0.293841 (0.011824) | 0.030162 / 0.128546 (-0.098385) | 0.010856 / 0.075646 (-0.064790) | 0.059528 / 0.419271 (-0.359744) | 0.033800 / 0.043533 (-0.009733) | 0.268200 / 0.255139 (0.013061) | 0.284982 / 0.283200 (0.001782) | 0.019105 / 0.141683 (-0.122578) | 1.171714 / 1.452155 (-0.280441) | 1.205690 / 1.492716 (-0.287026) |\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) | 0.100979 / 0.018006 (0.082973) | 0.314691 / 0.000490 (0.314201) | 0.000217 / 0.000200 (0.000017) | 0.000050 / 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) | 0.023816 / 0.037411 (-0.013596) | 0.081749 / 0.014526 (0.067223) | 0.090118 / 0.176557 (-0.086438) | 0.131615 / 0.737135 (-0.605520) | 0.091821 / 0.296338 (-0.204517) |\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) | 0.301222 / 0.215209 (0.086013) | 2.835310 / 2.077655 (0.757655) | 1.562396 / 1.504120 (0.058276) | 1.432365 / 1.541195 (-0.108830) | 1.468358 / 1.468490 (-0.000132) | 0.561300 / 4.584777 (-4.023477) | 0.962294 / 3.745712 (-2.783419) | 2.799705 / 5.269862 (-2.470157) | 1.803035 / 4.565676 (-2.762642) | 0.064104 / 0.424275 (-0.360171) | 0.005480 / 0.007607 (-0.002127) | 0.342519 / 0.226044 (0.116475) | 3.406286 / 2.268929 (1.137357) | 1.966962 / 55.444624 (-53.477663) | 1.654664 / 6.876477 (-5.221813) | 1.829303 / 2.142072 (-0.312769) | 0.650932 / 4.805227 (-4.154295) | 0.119211 / 6.500664 (-6.381453) | 0.043739 / 0.075469 (-0.031730) |\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) | 1.006657 / 1.841788 (-0.835130) | 12.915348 / 8.074308 (4.841040) | 10.808156 / 10.191392 (0.616764) | 0.132664 / 0.680424 (-0.547760) | 0.015574 / 0.534201 (-0.518627) | 0.284525 / 0.579283 (-0.294758) | 0.122322 / 0.434364 (-0.312042) | 0.326826 / 0.540337 (-0.213511) | 0.416593 / 1.386936 (-0.970343) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#15ffefe5be194790a50af88ae1236a51b0ac95e6 \"CML watermark\")\n" ]

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[ "Thanks for reporting, @srehaag.\r\n\r\nWe are investigating this issue.", "I confirm there is a bug for data-based Hub datasets when the user passes `data_dir`, which was introduced by PR:\r\n- #6714" ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6915). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "I pushed a change that fixes 2.15 cache reloading (I fixed the packaged module hash), feel free to merge if this change is fine for you", "Something weird happened in GitHub: I just merged this PR to main, See: https://github.com/huggingface/datasets/commit/5bbbf1b19766e31a6905f3e82bf3aa3f9f84a982\r\n\r\nHowever this PR still appears as Open...\r\n\r\nIf I retry to merge this PR, an error appears: \"Merge attempt failed: Merge already in progress\"\r\n\r\n", "<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) | 0.005543 / 0.011353 (-0.005810) | 0.004059 / 0.011008 (-0.006949) | 0.064678 / 0.038508 (0.026170) | 0.032615 / 0.023109 (0.009506) | 0.245883 / 0.275898 (-0.030015) | 0.273545 / 0.323480 (-0.049935) | 0.004268 / 0.007986 (-0.003718) | 0.003160 / 0.004328 (-0.001168) | 0.051982 / 0.004250 (0.047731) | 0.051186 / 0.037052 (0.014134) | 0.254009 / 0.258489 (-0.004480) | 0.289594 / 0.293841 (-0.004247) | 0.028459 / 0.128546 (-0.100087) | 0.011061 / 0.075646 (-0.064585) | 0.203571 / 0.419271 (-0.215700) | 0.038049 / 0.043533 (-0.005484) | 0.243700 / 0.255139 (-0.011439) | 0.264816 / 0.283200 (-0.018383) | 0.019556 / 0.141683 (-0.122127) | 1.114395 / 1.452155 (-0.337759) | 1.168915 / 1.492716 (-0.323802) |\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) | 0.098814 / 0.018006 (0.080808) | 0.308218 / 0.000490 (0.307728) | 0.000221 / 0.000200 (0.000022) | 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) | 0.019660 / 0.037411 (-0.017752) | 0.070542 / 0.014526 (0.056017) | 0.078906 / 0.176557 (-0.097650) | 0.126658 / 0.737135 (-0.610477) | 0.080427 / 0.296338 (-0.215911) |\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) | 0.280686 / 0.215209 (0.065477) | 2.767480 / 2.077655 (0.689825) | 1.455325 / 1.504120 (-0.048795) | 1.336677 / 1.541195 (-0.204518) | 1.380359 / 1.468490 (-0.088131) | 0.576310 / 4.584777 (-4.008467) | 2.431829 / 3.745712 (-1.313883) | 2.815266 / 5.269862 (-2.454595) | 1.908962 / 4.565676 (-2.656714) | 0.065306 / 0.424275 (-0.358969) | 0.005229 / 0.007607 (-0.002378) | 0.336018 / 0.226044 (0.109973) | 3.349283 / 2.268929 (1.080355) | 1.814696 / 55.444624 (-53.629929) | 1.520969 / 6.876477 (-5.355508) | 1.735322 / 2.142072 (-0.406751) | 0.661513 / 4.805227 (-4.143714) | 0.121465 / 6.500664 (-6.379199) | 0.044505 / 0.075469 (-0.030964) |\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) | 0.989204 / 1.841788 (-0.852584) | 12.608414 / 8.074308 (4.534106) | 10.133358 / 10.191392 (-0.058034) | 0.133986 / 0.680424 (-0.546438) | 0.014332 / 0.534201 (-0.519869) | 0.293207 / 0.579283 (-0.286076) | 0.265657 / 0.434364 (-0.168707) | 0.325972 / 0.540337 (-0.214365) | 0.478103 / 1.386936 (-0.908833) |\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) | 0.006070 / 0.011353 (-0.005283) | 0.004122 / 0.011008 (-0.006886) | 0.050572 / 0.038508 (0.012064) | 0.033732 / 0.023109 (0.010623) | 0.271282 / 0.275898 (-0.004616) | 0.296247 / 0.323480 (-0.027233) | 0.004400 / 0.007986 (-0.003585) | 0.002914 / 0.004328 (-0.001415) | 0.049332 / 0.004250 (0.045082) | 0.042213 / 0.037052 (0.005161) | 0.281230 / 0.258489 (0.022741) | 0.315514 / 0.293841 (0.021673) | 0.030864 / 0.128546 (-0.097682) | 0.011185 / 0.075646 (-0.064461) | 0.059227 / 0.419271 (-0.360044) | 0.034006 / 0.043533 (-0.009527) | 0.270059 / 0.255139 (0.014920) | 0.284014 / 0.283200 (0.000814) | 0.019502 / 0.141683 (-0.122181) | 1.143650 / 1.452155 (-0.308505) | 1.190968 / 1.492716 (-0.301749) |\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) | 0.100502 / 0.018006 (0.082496) | 0.307863 / 0.000490 (0.307373) | 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) | 0.023442 / 0.037411 (-0.013969) | 0.080185 / 0.014526 (0.065659) | 0.089372 / 0.176557 (-0.087185) | 0.131030 / 0.737135 (-0.606105) | 0.091174 / 0.296338 (-0.205165) |\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) | 0.304187 / 0.215209 (0.088978) | 3.043055 / 2.077655 (0.965400) | 1.629578 / 1.504120 (0.125459) | 1.533762 / 1.541195 (-0.007432) | 1.546134 / 1.468490 (0.077643) | 0.577739 / 4.584777 (-4.007038) | 0.986310 / 3.745712 (-2.759402) | 2.791650 / 5.269862 (-2.478212) | 1.841190 / 4.565676 (-2.724487) | 0.064943 / 0.424275 (-0.359333) | 0.005251 / 0.007607 (-0.002356) | 0.355009 / 0.226044 (0.128965) | 3.560935 / 2.268929 (1.292007) | 1.991995 / 55.444624 (-53.452629) | 1.708796 / 6.876477 (-5.167681) | 1.917721 / 2.142072 (-0.224351) | 0.667667 / 4.805227 (-4.137561) | 0.119956 / 6.500664 (-6.380708) | 0.042069 / 0.075469 (-0.033400) |\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) | 1.006242 / 1.841788 (-0.835546) | 13.321644 / 8.074308 (5.247336) | 10.712409 / 10.191392 (0.521017) | 0.134036 / 0.680424 (-0.546388) | 0.017645 / 0.534201 (-0.516555) | 0.289077 / 0.579283 (-0.290206) | 0.131356 / 0.434364 (-0.303007) | 0.333062 / 0.540337 (-0.207275) | 0.425327 / 1.386936 (-0.961609) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#09ebf5190afbd017f3ca24ef444be2d933411eed \"CML watermark\")\n", "Indeed, the merge commit is: https://github.com/huggingface/datasets/commit/5bbbf1b19766e31a6905f3e82bf3aa3f9f84a982\r\n\r\nThe following commit is just empty: https://github.com/huggingface/datasets/commit/09ebf5190afbd017f3ca24ef444be2d933411eed" ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6914). 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) | 0.005492 / 0.011353 (-0.005861) | 0.004087 / 0.011008 (-0.006921) | 0.065334 / 0.038508 (0.026826) | 0.032282 / 0.023109 (0.009173) | 0.246441 / 0.275898 (-0.029457) | 0.278807 / 0.323480 (-0.044673) | 0.003245 / 0.007986 (-0.004741) | 0.003795 / 0.004328 (-0.000534) | 0.050082 / 0.004250 (0.045832) | 0.050613 / 0.037052 (0.013561) | 0.258885 / 0.258489 (0.000396) | 0.297257 / 0.293841 (0.003416) | 0.028847 / 0.128546 (-0.099699) | 0.011377 / 0.075646 (-0.064270) | 0.206089 / 0.419271 (-0.213182) | 0.037354 / 0.043533 (-0.006178) | 0.257319 / 0.255139 (0.002180) | 0.275134 / 0.283200 (-0.008066) | 0.018064 / 0.141683 (-0.123619) | 1.112371 / 1.452155 (-0.339783) | 1.160909 / 1.492716 (-0.331807) |\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) | 0.101893 / 0.018006 (0.083887) | 0.311084 / 0.000490 (0.310594) | 0.000208 / 0.000200 (0.000008) | 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) | 0.019548 / 0.037411 (-0.017863) | 0.064396 / 0.014526 (0.049870) | 0.074900 / 0.176557 (-0.101656) | 0.122750 / 0.737135 (-0.614385) | 0.076693 / 0.296338 (-0.219646) |\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) | 0.288609 / 0.215209 (0.073400) | 2.831354 / 2.077655 (0.753699) | 1.453961 / 1.504120 (-0.050159) | 1.327702 / 1.541195 (-0.213493) | 1.382140 / 1.468490 (-0.086351) | 0.568465 / 4.584777 (-4.016312) | 2.427199 / 3.745712 (-1.318513) | 2.810586 / 5.269862 (-2.459275) | 1.839227 / 4.565676 (-2.726449) | 0.063219 / 0.424275 (-0.361056) | 0.005111 / 0.007607 (-0.002496) | 0.341447 / 0.226044 (0.115403) | 3.357429 / 2.268929 (1.088501) | 1.806501 / 55.444624 (-53.638123) | 1.541696 / 6.876477 (-5.334781) | 1.755400 / 2.142072 (-0.386673) | 0.661442 / 4.805227 (-4.143785) | 0.120203 / 6.500664 (-6.380461) | 0.044429 / 0.075469 (-0.031040) |\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) | 0.987810 / 1.841788 (-0.853978) | 12.765467 / 8.074308 (4.691159) | 10.497788 / 10.191392 (0.306396) | 0.132723 / 0.680424 (-0.547701) | 0.014484 / 0.534201 (-0.519717) | 0.285763 / 0.579283 (-0.293520) | 0.264377 / 0.434364 (-0.169987) | 0.326971 / 0.540337 (-0.213367) | 0.429432 / 1.386936 (-0.957504) |\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) | 0.005996 / 0.011353 (-0.005357) | 0.004092 / 0.011008 (-0.006916) | 0.051660 / 0.038508 (0.013152) | 0.036661 / 0.023109 (0.013552) | 0.271133 / 0.275898 (-0.004765) | 0.295728 / 0.323480 (-0.027752) | 0.004452 / 0.007986 (-0.003534) | 0.002915 / 0.004328 (-0.001413) | 0.050669 / 0.004250 (0.046418) | 0.044431 / 0.037052 (0.007378) | 0.284683 / 0.258489 (0.026194) | 0.318799 / 0.293841 (0.024958) | 0.031094 / 0.128546 (-0.097452) | 0.010810 / 0.075646 (-0.064836) | 0.059740 / 0.419271 (-0.359531) | 0.034912 / 0.043533 (-0.008621) | 0.268779 / 0.255139 (0.013640) | 0.291294 / 0.283200 (0.008095) | 0.019769 / 0.141683 (-0.121914) | 1.124833 / 1.452155 (-0.327322) | 1.168301 / 1.492716 (-0.324416) |\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) | 0.097080 / 0.018006 (0.079074) | 0.304636 / 0.000490 (0.304146) | 0.000232 / 0.000200 (0.000032) | 0.000060 / 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) | 0.023186 / 0.037411 (-0.014225) | 0.082232 / 0.014526 (0.067706) | 0.089427 / 0.176557 (-0.087130) | 0.132715 / 0.737135 (-0.604421) | 0.092820 / 0.296338 (-0.203518) |\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) | 0.300672 / 0.215209 (0.085463) | 2.969603 / 2.077655 (0.891948) | 1.577827 / 1.504120 (0.073707) | 1.440768 / 1.541195 (-0.100427) | 1.494526 / 1.468490 (0.026035) | 0.574599 / 4.584777 (-4.010178) | 0.963300 / 3.745712 (-2.782412) | 2.847854 / 5.269862 (-2.422008) | 1.841248 / 4.565676 (-2.724428) | 0.062321 / 0.424275 (-0.361954) | 0.005389 / 0.007607 (-0.002218) | 0.350853 / 0.226044 (0.124808) | 3.463514 / 2.268929 (1.194586) | 1.937661 / 55.444624 (-53.506964) | 1.665320 / 6.876477 (-5.211157) | 1.849028 / 2.142072 (-0.293044) | 0.655333 / 4.805227 (-4.149894) | 0.119062 / 6.500664 (-6.381602) | 0.043387 / 0.075469 (-0.032082) |\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) | 1.004118 / 1.841788 (-0.837670) | 13.350894 / 8.074308 (5.276585) | 11.179363 / 10.191392 (0.987971) | 0.135169 / 0.680424 (-0.545255) | 0.016298 / 0.534201 (-0.517903) | 0.288467 / 0.579283 (-0.290816) | 0.132712 / 0.434364 (-0.301651) | 0.325436 / 0.540337 (-0.214901) | 0.413406 / 1.386936 (-0.973530) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#670e1cf31606f397ae0f858b568b1b4ed50c1843 \"CML watermark\")\n" ]

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[ "@mariosasko, @lhoestq, @albertvillanova\r\nHello! Can anyone help? or can you guys suggest who can help with this?", "Hi ! Feel free to download the dataset and create a `Dataset` object with it.\r\n\r\nThen your'll be able to use `push_to_hub()` to upload the dataset to HF in Parquet format and make it streamable :)", "> Hi ! Feel free to download the dataset and create a `Dataset` object with it.\r\n> \r\n> Then your'll be able to use `push_to_hub()` to upload the dataset to HF in Parquet format and make it streamable :)\r\n\r\nThe dataset is several TB in total, which I do not have the resources to handle.", "Hi @lhoestq and @albertvillanova , just following up about this.", "for big datasets you can push_to_hub one part at a time (e.g. as different splits) and merge the parts (just a simple modification in the YAML part of the README)", "Sure, that makes sense. However, isn't there a size limit to what typical users can push?", "Yes there is a limit, simply let us know by email at datasets [at] huggingface.co - this way we can give you a storage grant also help making sure the dataset is all good for people to use it easily", "> Yes there is a limit, simply let us know by email at datasets [at] huggingface.co - this way we can give you a storage grant also help making sure the dataset is all good for people to use it easily\r\n\r\nGot it, that would be great." ]

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