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2,437,354,975
PR_kwDODunzps522dTJ
7,082
Support HTTP authentication in non-streaming mode
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-30T09:25:49
2024-07-30T09:59:11
null
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Support HTTP authentication in non-streaming mode, by support passing HTTP storage_options in non-streaming mode. - Note that currently, HTTP authentication is supported only in streaming mode. For example, this is necessary if a remote HTTP host requires authentication to download the data.
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7,081
Set load_from_disk path type as PathLike
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-30T07:00:38
2024-07-30T08:30:37
2024-07-30T08:21:50
MEMBER
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Set `load_from_disk` path type as `PathLike`. This way it is aligned with `save_to_disk`.
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2,434,275,664
I_kwDODunzps6RGBlQ
7,080
Generating train split takes a long time
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-29T01:42:43
2024-07-29T01:42:43
null
NONE
null
null
### Describe the bug Loading a simple webdataset takes ~45 minutes. ### Steps to reproduce the bug ``` from datasets import load_dataset dataset = load_dataset("PixArt-alpha/SAM-LLaVA-Captions10M") ``` ### Expected behavior The dataset should load immediately as it does when loaded through a normal indexed WebDataset loader. Generating splits should be optional and there should be a message showing how to disable it. ### Environment info - `datasets` version: 2.20.0 - Platform: Linux-4.18.0-372.32.1.el8_6.x86_64-x86_64-with-glibc2.28 - Python version: 3.10.14 - `huggingface_hub` version: 0.24.1 - PyArrow version: 16.1.0 - Pandas version: 2.2.2 - `fsspec` version: 2024.5.0
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2,433,363,298
I_kwDODunzps6RCi1i
7,079
HfHubHTTPError: 500 Server Error: Internal Server Error for url:
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-27T08:21:03
2024-07-27T20:06:44
2024-07-27T19:52:30
NONE
null
null
### Describe the bug newly uploaded datasets, since yesterday, yields an error. old datasets, works fine. Seems like the datasets api server returns a 500 I'm getting the same error, when I invoke `load_dataset` with my dataset. Long discussion about it here, but I'm not sure anyone from huggingface have seen it. https://discuss.huggingface.co/t/hfhubhttperror-500-server-error-internal-server-error-for-url/99580/1 ### Steps to reproduce the bug this api url: https://huggingface.co/api/datasets/neoneye/simon-arc-shape-v4-rev3 respond with: ``` {"error":"Internal Error - We're working hard to fix this as soon as possible!"} ``` ### Expected behavior return no error with newer datasets. With older datasets I can load the datasets fine. ### Environment info # Browser When I access the api in the browser: https://huggingface.co/api/datasets/neoneye/simon-arc-shape-v4-rev3 ``` {"error":"Internal Error - We're working hard to fix this as soon as possible!"} ``` ### Request headers ``` Accept text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,*/*;q=0.8 Accept-Encoding gzip, deflate, br, zstd Accept-Language en-US,en;q=0.5 Connection keep-alive Host huggingface.co Priority u=1 Sec-Fetch-Dest document Sec-Fetch-Mode navigate Sec-Fetch-Site cross-site Upgrade-Insecure-Requests 1 User-Agent Mozilla/5.0 (Macintosh; Intel Mac OS X 10.15; rv:127.0) Gecko/20100101 Firefox/127.0 ``` ### Response headers ``` X-Firefox-Spdy h2 access-control-allow-origin https://huggingface.co access-control-expose-headers X-Repo-Commit,X-Request-Id,X-Error-Code,X-Error-Message,X-Total-Count,ETag,Link,Accept-Ranges,Content-Range content-length 80 content-type application/json; charset=utf-8 cross-origin-opener-policy same-origin date Fri, 26 Jul 2024 19:09:45 GMT etag W/"50-9qrwU+BNI4SD0Fe32p/nofkmv0c" referrer-policy strict-origin-when-cross-origin vary Origin via 1.1 1624c79cd07e6098196697a6a7907e4a.cloudfront.net (CloudFront) x-amz-cf-id SP8E7n5qRaP6i9c9G83dNAiOzJBU4GXSrDRAcVNTomY895K35H0nJQ== x-amz-cf-pop CPH50-C1 x-cache Error from cloudfront x-error-message Internal Error - We're working hard to fix this as soon as possible! x-powered-by huggingface-moon x-request-id Root=1-66a3f479-026417465ef42f49349fdca1 ```
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7,078
Fix CI test_convert_to_parquet
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-27T05:32:40
2024-07-27T05:50:57
2024-07-27T05:44:32
MEMBER
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Fix `test_convert_to_parquet` by patching `HfApi.preupload_lfs_files` and revert temporary fix: - #7074
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I_kwDODunzps6Q-qWR
7,077
column_names ignored by load_dataset() when loading CSV file
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-26T14:18:04
2024-07-30T07:52:26
null
NONE
null
null
### Describe the bug load_dataset() ignores the column_names kwarg when loading a CSV file. Instead, it uses whatever values are on the first line of the file. ### Steps to reproduce the bug Call `load_dataset` to load data from a CSV file and specify `column_names` kwarg. ### Expected behavior The resulting dataset should have the specified column names **and** the first line of the file should be considered as data values. ### Environment info - `datasets` version: 2.20.0 - Platform: Linux-5.10.0-30-cloud-amd64-x86_64-with-glibc2.31 - Python version: 3.9.2 - `huggingface_hub` version: 0.24.2 - PyArrow version: 17.0.0 - Pandas version: 2.2.2 - `fsspec` version: 2024.5.0
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2,432,275,393
PR_kwDODunzps52lTDe
7,076
🧪 Do not mock create_commit
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-26T13:44:42
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Update required soxr version from pre-release to release
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-26T11:24:35
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2024-07-26T11:40:49
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Update required `soxr` version from pre-release to release 0.4.0: https://github.com/dofuuz/python-soxr/releases/tag/v0.4.0
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Fix CI by temporarily marking test_convert_to_parquet as expected to fail
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-26T09:03:33
2024-07-26T09:23:33
2024-07-26T09:16:12
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As a hotfix for CI, temporarily mark test_convert_to_parquet as expected to fail. Fix #7073. Revert once root cause is fixed.
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7,073
CI is broken for convert_to_parquet: Invalid rev id: refs/pr/1 404 error causes RevisionNotFoundError
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-26T08:27:41
2024-07-27T05:48:02
2024-07-26T09:16:13
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See: https://github.com/huggingface/datasets/actions/runs/10095313567/job/27915185756 ``` FAILED tests/test_hub.py::test_convert_to_parquet - huggingface_hub.utils._errors.RevisionNotFoundError: 404 Client Error. (Request ID: Root=1-66a25839-31ce7b475e70e7db1e4d44c2;b0c8870f-d5ef-4bf2-a6ff-0191f3df0f64) Revision Not Found for url: https://hub-ci.huggingface.co/api/datasets/__DUMMY_TRANSFORMERS_USER__/test-dataset-5188a8-17219154347516/preupload/refs%2Fpr%2F1. Invalid rev id: refs/pr/1 ``` ``` /opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/datasets/hub.py:86: in convert_to_parquet dataset.push_to_hub( /opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/datasets/dataset_dict.py:1722: in push_to_hub split_additions, uploaded_size, dataset_nbytes = self[split]._push_parquet_shards_to_hub( /opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/datasets/arrow_dataset.py:5511: in _push_parquet_shards_to_hub api.preupload_lfs_files( /opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/huggingface_hub/hf_api.py:4231: in preupload_lfs_files _fetch_upload_modes( /opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/huggingface_hub/utils/_validators.py:118: in _inner_fn return fn(*args, **kwargs) /opt/hostedtoolcache/Python/3.8.18/x64/lib/python3.8/site-packages/huggingface_hub/_commit_api.py:507: in _fetch_upload_modes hf_raise_for_status(resp) ```
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-25T17:03:24
2024-07-25T20:36:11
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Filter hangs
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-25T15:29:05
2024-07-25T15:36:59
null
NONE
null
null
### Describe the bug When trying to filter my custom dataset, the process hangs, regardless of the lambda function used. It appears to be an issue with the way the Images are being handled. The dataset in question is a preprocessed version of https://huggingface.co/datasets/danaaubakirova/patfig where notably, I have converted the data to the Parquet format. ### Steps to reproduce the bug ```python from datasets import load_dataset ds = load_dataset('lcolonn/patfig', split='test') ds_filtered = ds.filter(lambda row: row['cpc_class'] != 'Y') ``` Eventually I ctrl+C and I obtain this stack trace: ``` >>> ds_filtered = ds.filter(lambda row: row['cpc_class'] != 'Y') Filter: 0%| | 0/998 [00:00<?, ? examples/s]Filter: 0%| | 0/998 [00:35<?, ? examples/s] Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/home/l-walewski/miniconda3/envs/patentqa/lib/python3.11/site-packages/datasets/arrow_dataset.py", line 567, in wrapper out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/l-walewski/miniconda3/envs/patentqa/lib/python3.11/site-packages/datasets/fingerprint.py", line 482, in wrapper out = func(dataset, *args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/l-walewski/miniconda3/envs/patentqa/lib/python3.11/site-packages/datasets/arrow_dataset.py", line 3714, in filter indices = self.map( ^^^^^^^^^ File "/home/l-walewski/miniconda3/envs/patentqa/lib/python3.11/site-packages/datasets/arrow_dataset.py", line 602, in wrapper out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/l-walewski/miniconda3/envs/patentqa/lib/python3.11/site-packages/datasets/arrow_dataset.py", line 567, in wrapper out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/l-walewski/miniconda3/envs/patentqa/lib/python3.11/site-packages/datasets/arrow_dataset.py", line 3161, in map for rank, done, content in Dataset._map_single(**dataset_kwargs): File "/home/l-walewski/miniconda3/envs/patentqa/lib/python3.11/site-packages/datasets/arrow_dataset.py", line 3552, in _map_single batch = apply_function_on_filtered_inputs( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/l-walewski/miniconda3/envs/patentqa/lib/python3.11/site-packages/datasets/arrow_dataset.py", line 3421, in apply_function_on_filtered_inputs processed_inputs = function(*fn_args, *additional_args, **fn_kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/l-walewski/miniconda3/envs/patentqa/lib/python3.11/site-packages/datasets/arrow_dataset.py", line 6478, in get_indices_from_mask_function num_examples = len(batch[next(iter(batch.keys()))]) ~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/l-walewski/miniconda3/envs/patentqa/lib/python3.11/site-packages/datasets/formatting/formatting.py", line 273, in __getitem__ value = self.format(key) ^^^^^^^^^^^^^^^^ File "/home/l-walewski/miniconda3/envs/patentqa/lib/python3.11/site-packages/datasets/formatting/formatting.py", line 376, in format return self.formatter.format_column(self.pa_table.select([key])) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/l-walewski/miniconda3/envs/patentqa/lib/python3.11/site-packages/datasets/formatting/formatting.py", line 443, in format_column column = self.python_features_decoder.decode_column(column, pa_table.column_names[0]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/l-walewski/miniconda3/envs/patentqa/lib/python3.11/site-packages/datasets/formatting/formatting.py", line 219, in decode_column return self.features.decode_column(column, column_name) if self.features else column ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/l-walewski/miniconda3/envs/patentqa/lib/python3.11/site-packages/datasets/features/features.py", line 2008, in decode_column [decode_nested_example(self[column_name], value) if value is not None else None for value in column] File "/home/l-walewski/miniconda3/envs/patentqa/lib/python3.11/site-packages/datasets/features/features.py", line 2008, in <listcomp> [decode_nested_example(self[column_name], value) if value is not None else None for value in column] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/l-walewski/miniconda3/envs/patentqa/lib/python3.11/site-packages/datasets/features/features.py", line 1351, in decode_nested_example return schema.decode_example(obj, token_per_repo_id=token_per_repo_id) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/l-walewski/miniconda3/envs/patentqa/lib/python3.11/site-packages/datasets/features/image.py", line 188, in decode_example image.load() # to avoid "Too many open files" errors ^^^^^^^^^^^^ File "/home/l-walewski/miniconda3/envs/patentqa/lib/python3.11/site-packages/PIL/ImageFile.py", line 293, in load n, err_code = decoder.decode(b) ^^^^^^^^^^^^^^^^^ KeyboardInterrupt ``` Warning! This can even seem to cause some computers to crash. ### Expected behavior Should return the filtered dataset ### Environment info - `datasets` version: 2.20.0 - Platform: Linux-6.5.0-41-generic-x86_64-with-glibc2.35 - Python version: 3.11.9 - `huggingface_hub` version: 0.24.0 - PyArrow version: 17.0.0 - Pandas version: 2.2.2 - `fsspec` version: 2024.5.0
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2,430,285,235
I_kwDODunzps6Q2zWz
7,070
how set_transform affects batch size?
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-25T15:19:34
2024-07-25T15:19:34
null
NONE
null
null
### Describe the bug I am trying to fine-tune w2v-bert for ASR task. Since my dataset is so big, I preferred to use the on-the-fly method with set_transform. So i change the preprocessing function to this: ``` def prepare_dataset(batch): input_features = processor(batch["audio"], sampling_rate=16000).input_features[0] input_length = len(input_features) labels = processor.tokenizer(batch["text"], padding=False).input_ids batch = { "input_features": [input_features], "input_length": [input_length], "labels": [labels] } return batch train_ds.set_transform(prepare_dataset) val_ds.set_transform(prepare_dataset) ``` After this, I also had to change the DataCollatorCTCWithPadding class like this: ``` @dataclass class DataCollatorCTCWithPadding: processor: Wav2Vec2BertProcessor padding: Union[bool, str] = True def __call__(self, features: List[Dict[str, Union[List[int], torch.Tensor]]]) -> Dict[str, torch.Tensor]: # Separate input_features and labels input_features = [{"input_features": feature["input_features"][0]} for feature in features] labels = [feature["labels"][0] for feature in features] # Pad input features batch = self.processor.pad( input_features, padding=self.padding, return_tensors="pt", ) # Pad and process labels label_features = self.processor.tokenizer.pad( {"input_ids": labels}, padding=self.padding, return_tensors="pt", ) labels = label_features["input_ids"] attention_mask = label_features["attention_mask"] # Replace padding with -100 to ignore these tokens during loss calculation labels = labels.masked_fill(attention_mask.ne(1), -100) batch["labels"] = labels return batch ``` But now a strange thing is happening, no matter how much I increase the batch size, the amount of V-RAM GPU usage does not change, while the number of total steps in the progress-bar (logging) changes. Is this normal or have I made a mistake? ### Steps to reproduce the bug i can share my code if needed ### Expected behavior Equal to the batch size value, the set_transform function is applied to the dataset and given to the model as a batch. ### Environment info all updated versions
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2,429,281,339
PR_kwDODunzps52betB
7,069
Fix push_to_hub by not calling create_branch if branch exists
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-25T07:50:04
2024-07-30T10:56:57
2024-07-30T10:51:01
MEMBER
false
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Fix push_to_hub by not calling create_branch if branch exists. Note that currently create_branch raises a 403 Forbidden error even if all these conditions are met: - exist_ok is passed - the branch already exists - the user does not have WRITE permission Fix #7067. Related issue: - https://github.com/huggingface/huggingface_hub/issues/2419
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2,426,657,434
PR_kwDODunzps52SwXS
7,068
Fix prepare_single_hop_path_and_storage_options
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-24T05:52:34
2024-07-29T07:02:07
2024-07-29T06:56:15
MEMBER
false
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Fix `_prepare_single_hop_path_and_storage_options`: - Do not pass HF authentication headers and HF user-agent to non-HF HTTP URLs - Do not overwrite passed `storage_options` nested values: - Before, when passed ```DownloadConfig(storage_options={"https": {"client_kwargs": {"raise_for_status": True}}})```, it was overwritten to ```{"https": {"client_kwargs": {"trust_env": True}}}``` - Now, the result combines both: ```{"https": {"client_kwargs": {"trust_env": True, "raise_for_status": True}}}```
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I_kwDODunzps6QkZXI
7,067
Convert_to_parquet fails for datasets with multiple configs
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-23T15:09:33
2024-07-30T10:51:02
2024-07-30T10:51:02
NONE
null
null
If the dataset has multiple configs, when using the `datasets-cli convert_to_parquet` command to avoid issues with the data viewer caused by loading scripts, the conversion process only successfully converts the data corresponding to the first config. When it starts converting the second config, it throws an error: ``` Traceback (most recent call last): File "/opt/anaconda3/envs/dl/bin/datasets-cli", line 8, in <module> sys.exit(main()) File "/opt/anaconda3/envs/dl/lib/python3.10/site-packages/datasets/commands/datasets_cli.py", line 41, in main service.run() File "/opt/anaconda3/envs/dl/lib/python3.10/site-packages/datasets/commands/convert_to_parquet.py", line 83, in run dataset.push_to_hub( File "/opt/anaconda3/envs/dl/lib/python3.10/site-packages/datasets/dataset_dict.py", line 1713, in push_to_hub api.create_branch(repo_id, branch=revision, token=token, repo_type="dataset", exist_ok=True) File "/opt/anaconda3/envs/dl/lib/python3.10/site-packages/huggingface_hub/utils/_validators.py", line 114, in _inner_fn return fn(*args, **kwargs) File "/opt/anaconda3/envs/dl/lib/python3.10/site-packages/huggingface_hub/hf_api.py", line 5503, in create_branch hf_raise_for_status(response) File "/opt/anaconda3/envs/dl/lib/python3.10/site-packages/huggingface_hub/utils/_errors.py", line 358, in hf_raise_for_status raise BadRequestError(message, response=response) from e huggingface_hub.utils._errors.BadRequestError: (Request ID: Root=1-669fc665-7c2e80d75f4337496ee95402;731fcdc7-0950-4eec-99cf-ce047b8d003f) Bad request: Invalid reference for a branch: refs/pr/1 ```
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2,425,125,160
I_kwDODunzps6QjHko
7,066
One subset per file in repo ?
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-23T12:43:59
2024-07-23T12:43:59
null
MEMBER
null
null
Right now we consider all the files of a dataset to be the same data, e.g. ``` single_subset_dataset/ ├── train0.jsonl ├── train1.jsonl └── train2.jsonl ``` but in cases like this, each file is actually a different subset of the dataset and should be loaded separately ``` many_subsets_dataset/ ├── animals.jsonl ├── trees.jsonl └── metadata.jsonl ``` It would be nice to detect those subsets automatically using a simple heuristic. For example we can group files together if their paths names are the same except some digits ?
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2,424,734,953
I_kwDODunzps6QhoTp
7,065
Cannot get item after loading from disk and then converting to iterable.
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-23T09:37:56
2024-07-23T09:37:56
null
NONE
null
null
### Describe the bug The dataset generated from local file works fine. ```py root = "/home/data/train" file_list1 = glob(os.path.join(root, "*part1.flac")) file_list2 = glob(os.path.join(root, "*part2.flac")) ds = ( Dataset.from_dict({"part1": file_list1, "part2": file_list2}) .cast_column("part1", Audio(sampling_rate=None, mono=False)) .cast_column("part2", Audio(sampling_rate=None, mono=False)) ) ids = ds.to_iterable_dataset(128) ids = ids.shuffle(buffer_size=10000, seed=42) dataloader = DataLoader(ids, num_workers=4, batch_size=8, persistent_workers=True) for batch in dataloader: break ``` But after saving it to disk and then loading it from disk, I cannot get data as expected. ```py root = "/home/data/train" file_list1 = glob(os.path.join(root, "*part1.flac")) file_list2 = glob(os.path.join(root, "*part2.flac")) ds = ( Dataset.from_dict({"part1": file_list1, "part2": file_list2}) .cast_column("part1", Audio(sampling_rate=None, mono=False)) .cast_column("part2", Audio(sampling_rate=None, mono=False)) ) ds.save_to_disk("./train") ds = datasets.load_from_disk("./train") ids = ds.to_iterable_dataset(128) ids = ids.shuffle(buffer_size=10000, seed=42) dataloader = DataLoader(ids, num_workers=4, batch_size=8, persistent_workers=True) for batch in dataloader: break ``` After a long time waiting, an error occurs: ``` Loading dataset from disk: 100%|█████████████████████████████████████████████████████████████████████████| 165/165 [00:00<00:00, 6422.18it/s] Traceback (most recent call last): File "/home/hanzerui/.conda/envs/mss/lib/python3.10/site-packages/torch/utils/data/dataloader.py", line 1133, in _try_get_data data = self._data_queue.get(timeout=timeout) File "/home/hanzerui/.conda/envs/mss/lib/python3.10/multiprocessing/queues.py", line 113, in get if not self._poll(timeout): File "/home/hanzerui/.conda/envs/mss/lib/python3.10/multiprocessing/connection.py", line 257, in poll return self._poll(timeout) File "/home/hanzerui/.conda/envs/mss/lib/python3.10/multiprocessing/connection.py", line 424, in _poll r = wait([self], timeout) File "/home/hanzerui/.conda/envs/mss/lib/python3.10/multiprocessing/connection.py", line 931, in wait ready = selector.select(timeout) File "/home/hanzerui/.conda/envs/mss/lib/python3.10/selectors.py", line 416, in select fd_event_list = self._selector.poll(timeout) File "/home/hanzerui/.conda/envs/mss/lib/python3.10/site-packages/torch/utils/data/_utils/signal_handling.py", line 66, in handler _error_if_any_worker_fails() RuntimeError: DataLoader worker (pid 3490529) is killed by signal: Killed. The above exception was the direct cause of the following exception: Traceback (most recent call last): File "/home/hanzerui/.conda/envs/mss/lib/python3.10/runpy.py", line 196, in _run_module_as_main return _run_code(code, main_globals, None, File "/home/hanzerui/.conda/envs/mss/lib/python3.10/runpy.py", line 86, in _run_code exec(code, run_globals) File "/home/hanzerui/.vscode-server/extensions/ms-python.debugpy-2024.9.12011011/bundled/libs/debugpy/adapter/../../debugpy/launcher/../../debugpy/__main__.py", line 39, in <module> cli.main() File "/home/hanzerui/.vscode-server/extensions/ms-python.debugpy-2024.9.12011011/bundled/libs/debugpy/adapter/../../debugpy/launcher/../../debugpy/../debugpy/server/cli.py", line 430, in main run() File "/home/hanzerui/.vscode-server/extensions/ms-python.debugpy-2024.9.12011011/bundled/libs/debugpy/adapter/../../debugpy/launcher/../../debugpy/../debugpy/server/cli.py", line 284, in run_file runpy.run_path(target, run_name="__main__") File "/home/hanzerui/.vscode-server/extensions/ms-python.debugpy-2024.9.12011011/bundled/libs/debugpy/_vendored/pydevd/_pydevd_bundle/pydevd_runpy.py", line 321, in run_path return _run_module_code(code, init_globals, run_name, File "/home/hanzerui/.vscode-server/extensions/ms-python.debugpy-2024.9.12011011/bundled/libs/debugpy/_vendored/pydevd/_pydevd_bundle/pydevd_runpy.py", line 135, in _run_module_code _run_code(code, mod_globals, init_globals, File "/home/hanzerui/.vscode-server/extensions/ms-python.debugpy-2024.9.12011011/bundled/libs/debugpy/_vendored/pydevd/_pydevd_bundle/pydevd_runpy.py", line 124, in _run_code exec(code, run_globals) File "/home/hanzerui/workspace/NetEase/test/test_datasets.py", line 60, in <module> for batch in dataloader: File "/home/hanzerui/.conda/envs/mss/lib/python3.10/site-packages/torch/utils/data/dataloader.py", line 631, in __next__ data = self._next_data() File "/home/hanzerui/.conda/envs/mss/lib/python3.10/site-packages/torch/utils/data/dataloader.py", line 1329, in _next_data idx, data = self._get_data() File "/home/hanzerui/.conda/envs/mss/lib/python3.10/site-packages/torch/utils/data/dataloader.py", line 1295, in _get_data success, data = self._try_get_data() File "/home/hanzerui/.conda/envs/mss/lib/python3.10/site-packages/torch/utils/data/dataloader.py", line 1146, in _try_get_data raise RuntimeError(f'DataLoader worker (pid(s) {pids_str}) exited unexpectedly') from e RuntimeError: DataLoader worker (pid(s) 3490529) exited unexpectedly ``` It seems that streaming is not supported by `laod_from_disk`, so does that mean I cannot convert it to iterable? ### Steps to reproduce the bug 1. Create a `Dataset` from local files with `from_dict` 2. Save it to disk with `save_to_disk` 3. Load it from disk with `load_from_disk` 4. Convert to iterable with `to_iterable_dataset` 5. Loop the dataset ### Expected behavior Get items faster than the original dataset generated from dict. ### Environment info - `datasets` version: 2.20.0 - Platform: Linux-6.5.0-41-generic-x86_64-with-glibc2.35 - Python version: 3.10.14 - `huggingface_hub` version: 0.23.2 - PyArrow version: 17.0.0 - Pandas version: 2.2.2 - `fsspec` version: 2024.5.0
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Add `batch` method to `Dataset` class
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-23T08:40:43
2024-07-25T13:51:25
2024-07-25T13:45:20
CONTRIBUTOR
false
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This PR introduces a new `batch` method to the `Dataset` class, aligning its functionality with the `IterableDataset.batch()` method (implemented in #7054). The implementation uses as well the existing `map` method for efficient batching of examples. Key changes: - Add `batch` method to `Dataset` class in `arrow_dataset.py` - Utilize `map` method for batching Closes #7063 Once the approach is approved, i will create the tests and update the documentation.
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Add `batch` method to `Dataset`
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-23T07:36:59
2024-07-25T13:45:21
2024-07-25T13:45:21
CONTRIBUTOR
null
null
### Feature request Add a `batch` method to the Dataset class, similar to the one recently implemented for `IterableDataset` in PR #7054. ### Motivation A batched iteration speeds up data loading significantly (see e.g. #6279) ### Your contribution I plan to open a PR to implement this.
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Avoid calling http_head for non-HTTP URLs
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-23T07:25:09
2024-07-23T14:28:27
2024-07-23T14:21:08
MEMBER
false
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Avoid calling `http_head` for non-HTTP URLs, by adding and `else` statement. Currently, it makes an unnecessary HTTP call (which adds latency) for non-HTTP protocols, like FTP, S3,... I discovered this while working in an unrelated issue.
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2,423,786,881
I_kwDODunzps6QeA2B
7,061
Custom Dataset | Still Raise Error while handling errors in _generate_examples
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-22T21:18:12
2024-07-22T21:18:12
null
NONE
null
null
### Describe the bug I follow this [example](https://discuss.huggingface.co/t/error-handling-in-iterabledataset/72827/3) to handle errors in custom dataset. I am writing a dataset script which read jsonl files and i need to handle errors and continue reading files without raising exception and exit the execution. ``` def _generate_examples(self, filepaths): errors=[] id_ = 0 for filepath in filepaths: try: with open(filepath, 'r') as f: for line in f: json_obj = json.loads(line) yield id_, json_obj id_ += 1 except Exception as exc: logger.error(f"error occur at filepath: {filepath}") errors.append(error) ``` seems the logger.error is printed but still exception is raised the the run is exit. ``` Downloading and preparing dataset custom_dataset/default to /home/myuser/.cache/huggingface/datasets/custom_dataset/default-a14cdd566afee0a6/1.0.0/acfcc9fb9c57034b580c4252841 ERROR: datasets_modules.datasets.custom_dataset.acfcc9fb9c57034b580c4252841bb890a5617cbd28678dd4be5e52b81188ad02.custom_dataset: 2024-07-22 10:47:42,167: error occur at filepath: '/home/myuser/ds/corrupted-file.jsonl Traceback (most recent call last): File "/home/myuser/.cache/huggingface/modules/datasets_modules/datasets/custom_dataset/ac..2/custom_dataset.py", line 48, in _generate_examples json_obj = json.loads(line) File "myenv/lib/python3.8/json/__init__.py", line 357, in loads return _default_decoder.decode(s) File "myenv/lib/python3.8/json/decoder.py", line 337, in decode obj, end = self.raw_decode(s, idx=_w(s, 0).end()) File "myenv/lib/python3.8/json/decoder.py", line 353, in raw_decode obj, end = self.scan_once(s, idx) json.decoder.JSONDecodeError: Invalid control character at: line 1 column 4 (char 3) Generating train split: 0 examples [00:06, ? examples/s]> RemoteTraceback: """ Traceback (most recent call last): File "myenv/lib/python3.8/site-packages/datasets/builder.py", line 1637, in _prepare_split_single num_examples, num_bytes = writer.finalize() File "myenv/lib/python3.8/site-packages/datasets/arrow_writer.py", line 594, in finalize raise SchemaInferenceError("Please pass `features` or at least one example when writing data") datasets.arrow_writer.SchemaInferenceError: Please pass `features` or at least one example when writing data The above exception was the direct cause of the following exception: Traceback (most recent call last): File "myenv/lib/python3.8/site-packages/multiprocess/pool.py", line 125, in worker result = (True, func(*args, **kwds)) File "myenv/lib/python3.8/site-packages/datasets/utils/py_utils.py", line 1353, in _write_generator_to_queue for i, result in enumerate(func(**kwargs)): File "myenv/lib/python3.8/site-packages/datasets/builder.py", line 1646, in _prepare_split_single raise DatasetGenerationError("An error occurred while generating the dataset") from e datasets.builder.DatasetGenerationError: An error occurred while generating the dataset """ The above exception was the direct cause of the following exception: │ │ │ myenv/lib/python3.8/site-packages/datasets/utils/py_utils. │ │ py:1377 in <listcomp> │ │ │ │ 1374 │ │ │ │ if all(async_result.ready() for async_result in async_results) and queue │ │ 1375 │ │ │ │ │ break │ │ 1376 │ │ # we get the result in case there's an error to raise │ │ ❱ 1377 │ │ [async_result.get() for async_result in async_results] │ │ 1378 │ │ │ │ ╭──────────────────────────────── locals ─────────────────────────────────╮ │ │ │ .0 = <list_iterator object at 0x7f2cc1f0ce20> │ │ │ │ async_result = <multiprocess.pool.ApplyResult object at 0x7f2cc1f79c10> │ │ │ ╰─────────────────────────────────────────────────────────────────────────╯ │ │ │ │ myenv/lib/python3.8/site-packages/multiprocess/pool.py:771 │ │ in get │ │ │ │ 768 │ │ if self._success: │ │ 769 │ │ │ return self._value │ │ 770 │ │ else: │ │ ❱ 771 │ │ │ raise self._value │ │ 772 │ │ │ 773 │ def _set(self, i, obj): │ │ 774 │ │ self._success, self._value = obj │ │ │ │ ╭────────────────────────────── locals ──────────────────────────────╮ │ │ │ self = <multiprocess.pool.ApplyResult object at 0x7f2cc1f79c10> │ │ │ │ timeout = None │ │ │ ╰────────────────────────────────────────────────────────────────────╯ │ DatasetGenerationError: An error occurred while generating the dataset ``` ### Steps to reproduce the bug same as above ### Expected behavior should handle error and continue reading remaining files ### Environment info python 3.9
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7,060
WebDataset BuilderConfig
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-22T15:41:07
2024-07-23T13:28:44
2024-07-23T13:28:44
NONE
false
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This PR adds `WebDatasetConfig`. Closes #7055
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I_kwDODunzps6QaWt0
7,059
None values are skipped when reading jsonl in subobjects
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-22T13:02:42
2024-07-22T13:02:53
null
NONE
null
null
### Describe the bug I have been fighting against my machine since this morning only to find out this is some kind of a bug. When loading a dataset composed of `metadata.jsonl`, if you have nullable values (Optional[str]), they can be ignored by the parser, shifting things around. E.g., let's take this example Here are two version of a same dataset: [not-buggy.tar.gz](https://github.com/user-attachments/files/16333532/not-buggy.tar.gz) [buggy.tar.gz](https://github.com/user-attachments/files/16333553/buggy.tar.gz) ### Steps to reproduce the bug 1. Load the `buggy.tar.gz` dataset 2. Print baseline of `dts = load_dataset("./data")["train"][0]["baselines]` 3. Load the `not-buggy.tar.gz` dataset 4. Print baseline of `dts = load_dataset("./data")["train"][0]["baselines]` ### Expected behavior Both should have 4 baseline entries: 1. Buggy should have None followed by three lists 2. Non-Buggy should have four lists, and the first one should be an empty list. One does not work, 2 works. Despite accepting None in another position than the first one. ### Environment info - `datasets` version: 2.19.1 - Platform: Linux-6.5.0-44-generic-x86_64-with-glibc2.35 - Python version: 3.10.12 - `huggingface_hub` version: 0.23.0 - PyArrow version: 16.1.0 - Pandas version: 2.2.2 - `fsspec` version: 2024.3.1
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New feature type: Document
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-22T10:49:20
2024-07-22T10:49:20
null
CONTRIBUTOR
null
null
It would be useful for PDF. https://github.com/huggingface/dataset-viewer/issues/2991#issuecomment-2242656069
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Update load_hub.mdx
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-22T10:17:46
2024-07-22T10:34:14
2024-07-22T10:28:10
CONTRIBUTOR
false
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7,056
Make `BufferShuffledExamplesIterable` resumable
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-22T07:50:02
2024-07-22T15:37:01
null
CONTRIBUTOR
false
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This PR aims to implement a resumable `BufferShuffledExamplesIterable`. Instead of saving the entire buffer content, which is very memory-intensive, the newly implemented `BufferShuffledExamplesIterable` saves only the minimal state necessary for recovery, e.g., the random generator states and the state of the first example in the buffer dict. The idea is that since the buffer size is limited, even if the entire buffer is discarded, we can rebuild it as long as the state of the oldest example is recorded. For buffer size $B$, the expected distance between when an example is pushed and when it is yielded is $d = \sum_{k=1}^{\infty} k\frac{1}{B} (1 - \frac{1}{B} )^{k-1} =B$. Simulation experiments support these claims: ```py from random import randint BUFFER_SIZE = 1024 dists = [] buffer = [] for i in range(10000000): if i < BUFFER_SIZE: buffer.append(i) else: index = randint(0, BUFFER_SIZE - 1) dists.append(i - buffer[index]) buffer[index] = i print(f"MIN DIST: {min(dists)}\nMAX DIST: {max(dists)}\nAVG DIST: {sum(dists) / len(dists):.2f}\n") ``` which produces the following output: ```py MIN DIST: 1 MAX DIST: 15136 AVG DIST: 1023.95 ``` The overall time for reconstructing the buffer and recovery should not be too long. The following code mimics the cases of resuming online tokenization by `datasets` and `StatefulDataLoader` under distributed scenarios, ```py import pickle import time from itertools import chain from typing import Any, Dict, List import torch from datasets import load_dataset from torchdata.stateful_dataloader import StatefulDataLoader from tqdm import tqdm from transformers import AutoTokenizer, DataCollatorForLanguageModeling tokenizer = AutoTokenizer.from_pretrained('fla-hub/gla-1.3B-100B') tokenizer.pad_token = tokenizer.eos_token data_collator = DataCollatorForLanguageModeling(tokenizer=tokenizer, mlm=False) torch.manual_seed(42) def tokenize(examples: Dict[str, List[Any]]) -> Dict[str, List[List[int]]]: input_ids = tokenizer(examples['text'])['input_ids'] input_ids = list(chain(*input_ids)) total_length = len(input_ids) chunk_size = 2048 total_length = (total_length // chunk_size) * chunk_size # the last chunk smaller than chunk_size will be discarded return {'input_ids': [input_ids[i: i+chunk_size] for i in range(0, total_length, chunk_size)]} batch_size = 16 num_workers = 5 context_length = 2048 rank = 1 world_size = 32 prefetch_factor = 2 steps = 2048 path = 'fla-hub/slimpajama-test' dataset = load_dataset( path=path, split='train', streaming=True, trust_remote_code=True ) dataset = dataset.map(tokenize, batched=True, remove_columns=next(iter(dataset)).keys()) dataset = dataset.shuffle(seed=42) loader = StatefulDataLoader(dataset=dataset, batch_size=batch_size, collate_fn=data_collator, num_workers=num_workers, persistent_workers=False, prefetch_factor=prefetch_factor) start = time.time() for i, batch in tqdm(enumerate(loader)): if i == 0: print(f'{i}\n{batch["input_ids"]}') if i == steps - 1: print(f'{i}\n{batch["input_ids"]}') state_dict = loader.state_dict() if i == steps: print(f'{i}\n{batch["input_ids"]}') break print(f"{time.time() - start:.2f}s elapsed") print(f"{len(pickle.dumps(state_dict)) / 1024**2:.2f}MB states in total") for worker in state_dict['_snapshot']['_worker_snapshots'].keys(): print(f"{worker} {len(pickle.dumps(state_dict['_snapshot']['_worker_snapshots'][worker])) / 1024**2:.2f}MB") print(state_dict['_snapshot']['_worker_snapshots']['worker_0']['dataset_state']) loader = StatefulDataLoader(dataset=dataset, batch_size=batch_size, collate_fn=data_collator, num_workers=num_workers, persistent_workers=False, prefetch_factor=prefetch_factor) print("Loading state dict") loader.load_state_dict(state_dict) start = time.time() for batch in loader: print(batch['input_ids']) break print(f"{time.time() - start:.2f}s elapsed") ``` and the outputs are ```py 0 tensor([[ 909, 395, 19082, ..., 13088, 16232, 395], [ 601, 28705, 28770, ..., 28733, 923, 288], [21753, 15071, 13977, ..., 9369, 28723, 415], ..., [21763, 28751, 20300, ..., 28781, 28734, 4775], [ 354, 396, 10214, ..., 298, 429, 28770], [ 333, 6149, 28768, ..., 2773, 340, 351]]) 2047 tensor([[28723, 415, 3889, ..., 272, 3065, 2609], [ 403, 3214, 3629, ..., 403, 21163, 16434], [28723, 13, 28749, ..., 28705, 28750, 28734], ..., [ 2778, 2251, 28723, ..., 354, 684, 429], [ 5659, 298, 1038, ..., 5290, 297, 22153], [ 938, 28723, 1537, ..., 9123, 28733, 12154]]) 2048 tensor([[ 769, 278, 12531, ..., 28721, 19309, 28739], [ 415, 23347, 622, ..., 3937, 2426, 28725], [28745, 4345, 28723, ..., 338, 28725, 583], ..., [ 1670, 28709, 5809, ..., 28734, 28760, 393], [ 340, 1277, 624, ..., 325, 28790, 1329], [ 523, 1144, 3409, ..., 359, 359, 17422]]) 65.97s elapsed 0.00MB states in total worker_0 0.00MB worker_1 0.00MB worker_2 0.00MB worker_3 0.00MB worker_4 0.00MB {'ex_iterable': {'ex_iterable': {'shard_idx': 0, 'shard_example_idx': 14000}, 'num_examples_since_previous_state': 166, 'previous_state_example_idx': 7394, 'previous_state': {'shard_idx': 0, 'shard_example_idx': 13000}}, 'num_taken': 6560, 'global_example_idx': 7560, 'buffer_state_dict': {'num_taken': 6560, 'global_example_idx': 356, 'index_offset': 0, 'first_state': {'ex_iterable': {'shard_idx': 0, 'shard_example_idx': 1000}, 'num_examples_since_previous_state': 356, 'previous_state_example_idx': 0, 'previous_state': {'shard_idx': 0, 'shard_example_idx': 0}}, 'bit_generator_state': {'state': {'state': 274674114334540486603088602300644985544, 'inc': 332724090758049132448979897138935081983}, 'bit_generator': 'PCG64', 'has_uint32': 0, 'uinteger': 0}}} Loading state dict tensor([[ 769, 278, 12531, ..., 28721, 19309, 28739], [ 415, 23347, 622, ..., 3937, 2426, 28725], [28745, 4345, 28723, ..., 338, 28725, 583], ..., [ 1670, 28709, 5809, ..., 28734, 28760, 393], [ 340, 1277, 624, ..., 325, 28790, 1329], [ 523, 1144, 3409, ..., 359, 359, 17422]]) 24.60s elapsed ``` Not sure if this PR complies with the `datasets` code style. Looking for your help @lhoestq, also very willing to further improve the code if any suggestions are given.
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7,055
WebDataset with different prefixes are unsupported
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-22T01:14:19
2024-07-24T13:26:30
2024-07-23T13:28:46
NONE
null
null
### Describe the bug Consider a WebDataset with multiple images for each item where the number of images may vary: [example](https://huggingface.co/datasets/bigdata-pw/fashion-150k) Due to this [code](https://github.com/huggingface/datasets/blob/87f4c2088854ff33e817e724e75179e9975c1b02/src/datasets/packaged_modules/webdataset/webdataset.py#L76-L80) an error is given. ``` The TAR archives of the dataset should be in WebDataset format, but the files in the archive don't share the same prefix or the same types. ``` The purpose of this check is unclear because PyArrow supports different keys. Removing the check allows the dataset to be loaded and there's no issue when iterating through the dataset. ``` >>> from datasets import load_dataset >>> path = "shards/*.tar" >>> dataset = load_dataset("webdataset", data_files={"train": path}, split="train", streaming=True) Resolving data files: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 152/152 [00:00<00:00, 56458.93it/s] >>> dataset IterableDataset({ features: ['__key__', '__url__', '1.jpg', '2.jpg', '3.jpg', '4.jpg', 'json'], n_shards: 152 }) ``` ### Steps to reproduce the bug ```python from datasets import load_dataset load_dataset("bigdata-pw/fashion-150k") ``` ### Expected behavior Dataset loads without error ### Environment info - `datasets` version: 2.20.0 - Platform: Linux-5.14.0-467.el9.x86_64-x86_64-with-glibc2.34 - Python version: 3.9.19 - `huggingface_hub` version: 0.23.4 - PyArrow version: 17.0.0 - Pandas version: 2.2.2 - `fsspec` version: 2024.5.0
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7,054
Add batching to `IterableDataset`
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-19T10:11:47
2024-07-23T13:25:13
2024-07-23T10:34:28
CONTRIBUTOR
false
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I've taken a try at implementing a batched `IterableDataset` as requested in issue #6279. This PR adds a new `BatchedExamplesIterable` class and a `.batch()` method to the `IterableDataset` class. The main changes are: 1. A new `BatchedExamplesIterable` that groups examples into batches. 2. A `.batch()` method for `IterableDataset` to easily create batched versions. 3. Support for shuffling and sharding to work with PyTorch DataLoader and multiple workers. I'm not sure if this is exactly what you had in mind and also have not fully tested it atm, so I'd really appreciate your feedback. Does this seem like it's heading in the right direction? I'm happy to make any changes or explore different approaches if needed. Pinging @lhoestq
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Datasets.datafiles resolve_pattern `TypeError: can only concatenate tuple (not "str") to tuple`
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-18T13:42:35
2024-07-18T15:17:42
2024-07-18T15:16:18
NONE
null
null
### Describe the bug in data_files.py, line 332, `fs, _, _ = get_fs_token_paths(pattern, storage_options=storage_options)` If we run the code on AWS, as fs.protocol will be a tuple like: `('file', 'local')` So, `isinstance(fs.protocol, str) == False` and `protocol_prefix = fs.protocol + "://" if fs.protocol != "file" else ""` will raise `TypeError: can only concatenate tuple (not "str") to tuple`. ### Steps to reproduce the bug Steps to reproduce: 1. Run on a cloud server like AWS, 2. `import datasets.data_files as datafile` 3. datafile.resolve_pattern('path/to/dataset', '.') 4. `TypeError: can only concatenate tuple (not "str") to tuple` ### Expected behavior Should return path of the dataset, with fs.protocol at the beginning ### Environment info - `datasets` version: 2.14.0 - Platform: Linux-3.10.0-1160.119.1.el7.x86_64-x86_64-with-glibc2.17 - Python version: 3.8.19 - Huggingface_hub version: 0.23.5 - PyArrow version: 16.1.0 - Pandas version: 1.1.5
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7,052
Adding `Music` feature for symbolic music modality (MIDI, abc)
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-16T17:26:04
2024-07-29T06:47:55
2024-07-29T06:47:55
NONE
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⚠️ (WIP) ⚠️ ### What this PR does This PR adds a `Music` feature for the symbolic music modality, in particular [MIDI](https://en.wikipedia.org/wiki/Musical_Instrument_Digital_Interface) and [abc](https://en.wikipedia.org/wiki/ABC_notation) files. ### Motivations These two file formats are widely used in the [Music Information Retrieval (MIR)](https://en.wikipedia.org/wiki/Music_information_retrieval) for tasks such as music generation, music transcription, music synthesis or music transcription. Having a dedicated feature in the datasets library would allow to both encourage researchers to share datasets of this modality as well as making them more easily usable for end users, benefitting from the perks of the library. These file formats are supported by [symusic](https://github.com/Yikai-Liao/symusic), a lightweight Python library with C bindings (using nanobind) allowing to efficiently read, write and manipulate them. The library is actively developed, and can in the future also implement other file formats such as [musicXML](https://en.wikipedia.org/wiki/MusicXML). As such, this PR relies on it. The music data can then easily be tokenized with appropriate tokenizers such as [MidiTok](https://github.com/Natooz/MidiTok) or converted to pianorolls matrices by symusic. **Jul 16th 2024:** * the tests for the `Music` feature are currently failing due to non-supported access to the LazyBatch in `test_dataset_with_music_feature_map` and `test_dataset_with_music_feature_map_resample_music` (see TODOs). I am a beginner with pyArrow, I'll take any advice to make this work; * additional tests including the `Music` feature with parquet and WebDataset should be implemented. As of right now, I am waiting for your feedback before taking further steps; * a `MusicFolder` should also be implemented to comply with the usages of the `Image` and `Audio` features, waiting for your feedback too. CCing @lhoestq and @albertvillanova
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2,409,353,929
I_kwDODunzps6Pm9LJ
7,051
How to set_epoch with interleave_datasets?
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-15T18:24:52
2024-07-22T16:52:07
null
NONE
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Let's say I have dataset A which has 100k examples, and dataset B which has 100m examples. I want to train on an interleaved dataset of A+B, with stopping_strategy='all_exhausted' so dataset B doesn't repeat any examples. But every time A is exhausted I want it to be reshuffled (eg. calling set_epoch) Of course I want to interleave as IterableDatasets / streaming mode so B doesn't have to get tokenized completely at the start. How could I achieve this? I was thinking something like, if I wrap dataset A in some new IterableDataset with from_generator() and manually call set_epoch before interleaving it? But I'm not sure how to keep the number of shards in that dataset... Something like ``` dataset_a = load_dataset(...) dataset_b = load_dataset(...) def epoch_shuffled_dataset(ds): # How to make this maintain the number of shards in ds?? for epoch in itertools.count(): ds.set_epoch(epoch) yield from iter(ds) shuffled_dataset_a = IterableDataset.from_generator(epoch_shuffled_dataset, gen_kwargs={'ds': dataset_a}) interleaved = interleave_datasets([shuffled_dataset_a, dataset_b], probs, stopping_strategy='all_exhausted') ```
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PR_kwDODunzps51Z1Yp
7,050
add checkpoint and resume title in docs
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-15T15:38:04
2024-07-15T16:06:15
2024-07-15T15:59:56
MEMBER
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(minor) just to make it more prominent in the docs page for the soon-to-be-released new torchdata
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7,049
Save nparray as list
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-15T11:36:11
2024-07-18T11:33:34
2024-07-18T11:33:34
NONE
null
null
### Describe the bug When I use the `map` function to convert images into features, datasets saves nparray as a list. Some people use the `set_format` function to convert the column back, but doesn't this lose precision? ### Steps to reproduce the bug the map function ```python def convert_image_to_features(inst, processor, image_dir): image_file = inst["image_url"] file = image_file.split("/")[-1] image_path = os.path.join(image_dir, file) image = Image.open(image_path) image = image.convert("RGBA") inst["pixel_values"] = processor(images=image, return_tensors="np")["pixel_values"] return inst ``` main function ```python map_fun = partial( convert_image_to_features, processor=processor, image_dir=image_dir ) ds = ds.map(map_fun, batched=False, num_proc=20) print(type(ds[0]["pixel_values"]) ``` ### Expected behavior (type < list>) ### Environment info - `datasets` version: 2.16.1 - Platform: Linux-4.19.91-009.ali4000.alios7.x86_64-x86_64-with-glibc2.35 - Python version: 3.11.5 - `huggingface_hub` version: 0.23.4 - PyArrow version: 14.0.2 - Pandas version: 2.1.4 - `fsspec` version: 2023.10.0
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7,048
ImportError: numpy.core.multiarray when using `filter`
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-15T11:21:04
2024-07-16T10:11:25
2024-07-16T10:11:25
NONE
null
null
### Describe the bug I can't apply the filter method on my dataset. ### Steps to reproduce the bug The following snippet generates a bug: ```python from datasets import load_dataset ami = load_dataset('kamilakesbi/ami', 'ihm') ami['train'].filter( lambda example: example["file_name"] == 'EN2001a' ) ``` I get the following error: `ImportError: numpy.core.multiarray failed to import (auto-generated because you didn't call 'numpy.import_array()' after cimporting numpy; use '<void>numpy._import_array' to disable if you are certain you don't need it).` ### Expected behavior It should work properly! ### Environment info - `datasets` version: 2.20.0 - Platform: Linux-5.15.0-67-generic-x86_64-with-glibc2.35 - Python version: 3.10.6 - `huggingface_hub` version: 0.23.4 - PyArrow version: 16.1.0 - Pandas version: 2.2.2 - `fsspec` version: 2024.5.0
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2,406,495,084
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7,047
Save Dataset as Sharded Parquet
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-12T23:47:51
2024-07-17T12:07:08
null
NONE
null
null
### Feature request `to_parquet` currently saves the dataset as one massive, monolithic parquet file, rather than as several small parquet files. It should shard large datasets automatically. ### Motivation This default behavior makes me very sad because a program I ran for 6 hours saved its results using `to_parquet`, putting the entire billion+ row dataset into a 171 GB *single shard parquet file* which pyarrow, apache spark, etc. all cannot work with without completely exhausting the memory of my system. I was previously able to work with larger-than-memory parquet files, but not this one. I *assume* the reason why this is happening is because it is a single shard. Making sharding the default behavior puts datasets in parity with other frameworks, such as spark, which automatically shard when a large dataset is saved as parquet. ### Your contribution I could change the logic here https://github.com/huggingface/datasets/blob/bf6f41e94d9b2f1c620cf937a2e85e5754a8b960/src/datasets/io/parquet.py#L109-L158 to use `pyarrow.dataset.write_dataset`, which seems to support sharding, or periodically open new files. We would only shard if the user passed in a path rather than file handle.
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2,405,485,582
PR_kwDODunzps51N05n
7,046
Support librosa and numpy 2.0 for Python 3.10
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-12T12:42:47
2024-07-12T13:04:40
2024-07-12T12:58:17
MEMBER
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Support librosa and numpy 2.0 for Python 3.10 by installing soxr 0.4.0b1 pre-release: - https://github.com/dofuuz/python-soxr/releases/tag/v0.4.0b1 - https://github.com/dofuuz/python-soxr/issues/28
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7,045
Fix tensorflow min version depending on Python version
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-12T12:20:23
2024-07-12T12:38:53
2024-07-12T12:33:00
MEMBER
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Fix tensorflow min version depending on Python version. Related to: - #6991
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7,044
Mark tests that require librosa
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-12T08:06:59
2024-07-12T09:06:32
2024-07-12T09:00:09
MEMBER
false
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Mark tests that require `librosa`. Note that `librosa` is an optional dependency (installed with `audio` option) and we should be able to test environments without that library installed. This is the case if we want to test Numpy 2.0, which is currently incompatible with `librosa` due to its dependency on `soxr`: - https://github.com/dofuuz/python-soxr/issues/28
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7,043
Add decorator as explicit test dependency
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-12T07:35:23
2024-07-12T08:12:55
2024-07-12T08:07:10
MEMBER
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Add decorator as explicit test dependency. We use `decorator` library in our CI test since PR: - #4845 However we did not add it as an explicit test requirement, and we depended on it indirectly through other libraries' dependencies. I discovered this while testing Numpy 2.0 and removing incompatible libraries.
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7,042
Improved the tutorial by adding a link for loading datasets
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-12T03:49:54
2024-07-12T03:49:54
null
NONE
false
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Improved the tutorial by letting readers know about loading datasets with common files and including a link. I left the local files section alone because the methods were already listed with code snippets.
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7,041
`sort` after `filter` unreasonably slow
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-12T03:29:27
2024-07-22T13:55:17
null
NONE
null
null
### Describe the bug as the tittle says ... ### Steps to reproduce the bug `sort` seems to be normal. ```python from datasets import Dataset import random nums = [{"k":random.choice(range(0,1000))} for _ in range(100000)] ds = Dataset.from_list(nums) print("start sort") ds = ds.sort("k") print("finish sort") ``` but `sort` after `filter` is extremely slow. ```python from datasets import Dataset import random nums = [{"k":random.choice(range(0,1000))} for _ in range(100000)] ds = Dataset.from_list(nums) ds = ds.filter(lambda x:x > 100, input_columns="k") print("start sort") ds = ds.sort("k") print("finish sort") ``` ### Expected behavior Is this a bug, or is it a misuse of the `sort` function? ### Environment info - `datasets` version: 2.20.0 - Platform: Linux-3.10.0-1127.19.1.el7.x86_64-x86_64-with-glibc2.17 - Python version: 3.10.13 - `huggingface_hub` version: 0.23.4 - PyArrow version: 16.1.0 - Pandas version: 2.2.2 - `fsspec` version: 2023.10.0
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I_kwDODunzps6POZ-_
7,040
load `streaming=True` dataset with downloaded cache
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-11T11:14:13
2024-07-11T14:11:56
null
NONE
null
null
### Describe the bug We build a dataset which contains several hdf5 files and write a script using `h5py` to generate the dataset. The hdf5 files are large and the processed dataset cache takes more disk space. So we hope to try streaming iterable dataset. Unfortunately, `h5py` can't convert a remote URL into a hdf5 file descriptor. So we use `fsspec` as an interface like below: ```python def _generate_examples(self, filepath, split): for file in filepath: with fsspec.open(file, "rb") as fs: with h5py.File(fs, "r") as fp: # for event_id in sorted(list(fp.keys())): event_ids = list(fp.keys()) ...... ``` ### Steps to reproduce the bug The `fsspec` works, but it takes 10+ min to print the first 10 examples, which is even longer than the downloading time. I'm not sure if it just caches the whole hdf5 file and generates the examples. ### Expected behavior So does the following make sense so far? 1. download the files ```python dataset = datasets.load('path/to/myscripts', split="train", name="event", trust_remote_code=True) ``` 2. load the iterable dataset faster (using the raw file cache at path `.cache/huggingface/datasets/downloads`) ```python dataset = datasets.load('path/to/myscripts', split="train", name="event", trust_remote_code=True, streaming=true) ``` I made some tests, but the code above can't get the expected result. I'm not sure if this is supported. I also find the issue #6327 . It seemed similar to mine, but I couldn't find a solution. ### Environment info - `datasets` = 2.18.0 - `h5py` = 3.10.0 - `fsspec` = 2023.10.0
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Fix export to JSON when dataset larger than batch size
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-11T06:52:22
2024-07-11T07:27:58
null
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Fix export to JSON (`files=False`) when dataset larger than batch size. Fix #7037.
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Yes, can definitely elaborate:
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-11T02:22:30
2024-07-11T05:28:39
2024-07-11T05:28:39
NONE
null
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Yes, can definitely elaborate: Say I want to use HF Trainer with an arbitrary PyTorch optimizer (`AdamW` here just as an example). Then I should intuitively extend `Trainer` like: ```python class CustomOptimizerTrainer(Trainer): @staticmethod def get_optimizer_cls_and_kwargs(args: HfTrainingArguments, model=None) -> tuple[type[torch.optim.Optimizer], dict[str, Any]]: optimizer = torch.optim.AdamW optimizer_kwargs = { "lr": 4e-3, "betas": (0.9, 0.999), "weight_decay": 0.05, } return optimizer, optimizer_kwargs ``` However, this won't take effect, because `Trainer.create_optimizer` hardcodes the `Trainer` class name when calling `get_optimizer_cls_and_kwargs`: https://github.com/huggingface/transformers/blob/6c1d0b069de22d7ed8aa83f733c25045eea0585d/src/transformers/trainer.py#L1076 `CustomOptimizerTrainer.get_optimizer_cls_and_kwargs` will never be called. So I could either: - also override the entire `create_optimizer` and rewrite `Trainer.get_optimizer_cls_and_kwargs` to `self.get_optimizer_cls_and_kwargs` (overkill) - or monkey-patch (not ideal): ```python class CustomOptimizerTrainer(Trainer): # def get_optimizer_cls_and_kwargs ... def create_optimizer(self): trainer_get_optimizer_fn = Trainer.get_optimizer_cls_and_kwargs Trainer.get_optimizer_cls_and_kwargs = self.get_optimizer_cls_and_kwargs optimizer = super().create_optimizer() Trainer.get_optimizer_cls_and_kwargs = trainer_get_optimizer_fn return optimizer ``` But I think the best fix is to change `Trainer.get_optimizer_cls_and_kwargs` to `self.get_optimizer_cls_and_kwargs` in the original source of `Trainer.create_optimizer`. I also made `get_optimizer_cls_and_kwargs` an instance method instead of a static method, but that probably doesn't matter as much and can be reverted. It breaks the syntax of the tests. Please let me know if that's clearer and if you agree! Thanks! _Originally posted by @apoorvkh in https://github.com/huggingface/transformers/issues/31875#issuecomment-2221491647_
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A bug of Dataset.to_json() function
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-10T09:11:22
2024-07-10T13:07:44
null
NONE
null
null
### Describe the bug When using the Dataset.to_json() function, an unexpected error occurs if the parameter is set to lines=False. The stored data should be in the form of a list, but it actually turns into multiple lists, which causes an error when reading the data again. The reason is that to_json() writes to the file in several segments based on the batch size. This is not a problem when lines=True, but it is incorrect when lines=False, because writing in several times will produce multiple lists(when len(dataset) > batch_size). ### Steps to reproduce the bug try this code: ```python from datasets import load_dataset import json train_dataset = load_dataset("Anthropic/hh-rlhf", data_dir="harmless-base")["train"] output_path = "./harmless-base_hftojs.json" print(len(train_dataset)) train_dataset.to_json(output_path, lines=False, force_ascii=False, indent=2) with open(output_path, encoding="utf-8") as f: data = json.loads(f.read()) ``` it raise error: json.decoder.JSONDecodeError: Extra data: line 4003 column 1 (char 1373709) Extra square brackets have appeared here: <img width="265" alt="image" src="https://github.com/huggingface/datasets/assets/26499566/81492332-386d-42e8-88d1-b6d4ae3682cc"> ### Expected behavior The code runs normally. ### Environment info datasets=2.20.0
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Fix doc generation when NamedSplit is used as parameter default value
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-10T07:58:46
2024-07-26T07:58:00
2024-07-26T07:51:52
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Fix doc generation when `NamedSplit` is used as parameter default value. Fix #7035.
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Docs are not generated when a parameter defaults to a NamedSplit value
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-10T07:51:24
2024-07-26T07:51:53
2024-07-26T07:51:53
MEMBER
null
null
While generating the docs, we get an error when some parameter defaults to a `NamedSplit` value, like: ```python def call_function(split=Split.TRAIN): ... ``` The error is: ValueError: Equality not supported between split train and <class 'inspect._empty'> See: https://github.com/huggingface/datasets/actions/runs/9869660902/job/27254359863?pr=7015 ``` Building the MDX files: 97%|█████████▋| 58/60 [00:00<00:00, 91.94it/s] Traceback (most recent call last): File "/home/runner/work/datasets/datasets/.venv/lib/python3.10/site-packages/doc_builder/build_doc.py", line 197, in build_mdx_files content, new_anchors, source_files, errors = resolve_autodoc( File "/home/runner/work/datasets/datasets/.venv/lib/python3.10/site-packages/doc_builder/build_doc.py", line 123, in resolve_autodoc doc = autodoc( File "/home/runner/work/datasets/datasets/.venv/lib/python3.10/site-packages/doc_builder/autodoc.py", line 499, in autodoc method_doc, check = document_object( File "/home/runner/work/datasets/datasets/.venv/lib/python3.10/site-packages/doc_builder/autodoc.py", line 395, in document_object signature = format_signature(obj) File "/home/runner/work/datasets/datasets/.venv/lib/python3.10/site-packages/doc_builder/autodoc.py", line 126, in format_signature if param.default != inspect._empty: File "/home/runner/work/datasets/datasets/.venv/lib/python3.10/site-packages/datasets/splits.py", line 136, in __ne__ return not self.__eq__(other) File "/home/runner/work/datasets/datasets/.venv/lib/python3.10/site-packages/datasets/splits.py", line 379, in __eq__ raise ValueError(f"Equality not supported between split {self} and {other}") ValueError: Equality not supported between split train and <class 'inspect._empty'> The above exception was the direct cause of the following exception: Traceback (most recent call last): File "/home/runner/work/datasets/datasets/.venv/bin/doc-builder", line 8, in <module> sys.exit(main()) File "/home/runner/work/datasets/datasets/.venv/lib/python3.10/site-packages/doc_builder/commands/doc_builder_cli.py", line 47, in main args.func(args) File "/home/runner/work/datasets/datasets/.venv/lib/python3.10/site-packages/doc_builder/commands/build.py", line 102, in build_command build_doc( File "/home/runner/work/datasets/datasets/.venv/lib/python3.10/site-packages/doc_builder/build_doc.py", line 367, in build_doc anchors_mapping, source_files_mapping = build_mdx_files( File "/home/runner/work/datasets/datasets/.venv/lib/python3.10/site-packages/doc_builder/build_doc.py", line 230, in build_mdx_files raise type(e)(f"There was an error when converting {file} to the MDX format.\n" + e.args[0]) from e ValueError: There was an error when converting ../datasets/docs/source/package_reference/main_classes.mdx to the MDX format. Equality not supported between split train and <class 'inspect._empty'> ```
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7,034
chore: fix typos in docs
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-09T08:35:05
2024-07-09T13:32:05
null
NONE
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2,397,419,768
I_kwDODunzps6O5bj4
7,033
`from_generator` does not allow to specify the split name
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-09T07:47:58
2024-07-26T12:56:16
2024-07-26T09:31:56
CONTRIBUTOR
null
null
### Describe the bug I'm building train, dev, and test using `from_generator`; however, in all three cases, the logger prints `Generating train split:` It's not possible to change the split name since it seems to be hardcoded: https://github.com/huggingface/datasets/blob/main/src/datasets/packaged_modules/generator/generator.py ### Steps to reproduce the bug ``` In [1]: from datasets import Dataset In [2]: def gen(): ...: yield {"pokemon": "bulbasaur", "type": "grass"} ...: In [3]: ds = Dataset.from_generator(gen) Generating train split: 1 examples [00:00, 133.89 examples/s] ``` ### Expected behavior It should be possible to specify any split name ### Environment info - `datasets` version: 2.19.2 - Platform: macOS-10.16-x86_64-i386-64bit - Python version: 3.8.5 - `huggingface_hub` version: 0.23.3 - PyArrow version: 15.0.0 - Pandas version: 2.0.3 - `fsspec` version: 2023.10.0
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7,032
Register `.zstd` extension for zstd-compressed files
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-08T12:39:50
2024-07-12T15:07:03
2024-07-12T15:07:03
CONTRIBUTOR
false
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For example, https://huggingface.co/datasets/mlfoundations/dclm-baseline-1.0 dataset files have `.zstd` extension which is currently ignored (only `.zst` is registered).
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7,031
CI quality is broken: use ruff check instead
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-08T11:42:24
2024-07-08T11:47:29
2024-07-08T11:47:29
MEMBER
null
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CI quality is broken: https://github.com/huggingface/datasets/actions/runs/9838873879/job/27159697027 ``` error: `ruff <path>` has been removed. Use `ruff check <path>` instead. ```
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I_kwDODunzps6OqJAv
7,030
Add option to disable progress bar when reading a dataset ("Loading dataset from disk")
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-06T05:43:37
2024-07-13T14:35:59
2024-07-13T14:35:59
NONE
null
null
### Feature request Add an option in load_from_disk to disable the progress bar even if the number of files is larger than 16. ### Motivation I am reading a lot of datasets that it creates lots of logs. <img width="1432" alt="image" src="https://github.com/huggingface/datasets/assets/57996478/8d4bbf03-6b89-44b6-937c-932f01b4eb2a"> ### Your contribution Seems like an easy fix to make. I can create a PR if necessary.
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2,391,366,696
I_kwDODunzps6OiVwo
7,029
load_dataset on AWS lambda throws OSError(30, 'Read-only file system') error
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-04T19:15:16
2024-07-17T12:44:03
null
NONE
null
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### Describe the bug I'm using AWS lambda to run a python application. I run the `load_dataset` function with cache_dir="/tmp" and is still throws the OSError(30, 'Read-only file system') error. Is even updated all the HF envs to point to /tmp dir but the issue still persists. I can confirm that the I can write to /tmp directory. ### Steps to reproduce the bug ```python d = load_dataset( path=hugging_face_link, split=split, token=token, cache_dir="/tmp/hugging_face_cache", ) ``` ### Expected behavior Everything written to the file system as part of the load_datasets function should be in the /tmp directory. ### Environment info datasets version: 2.16.1 Platform: Linux-5.10.216-225.855.amzn2.x86_64-x86_64-with-glibc2.26 Python version: 3.11.9 huggingface_hub version: 0.19.4 PyArrow version: 16.1.0 Pandas version: 2.2.2 fsspec version: 2023.10.0
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Fix ci
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-04T15:11:08
2024-07-04T15:26:35
2024-07-04T15:19:16
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...after last pr errors
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Missing line from previous pr
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-04T14:34:29
2024-07-04T14:40:46
2024-07-04T14:34:36
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2,390,983,889
PR_kwDODunzps50c8Mf
7,026
Fix check_library_imports
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-04T14:18:38
2024-07-04T14:28:36
2024-07-04T14:20:02
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move it to after the `trust_remote_code` check Note that it only affects local datasets that already exist on disk, not datasets loaded from HF directly
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2,390,488,546
PR_kwDODunzps50bSyD
7,025
feat: support non streamable arrow file binary format
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-04T10:11:12
2024-07-29T13:03:30
null
NONE
false
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Support Arrow files (`.arrow`) that are in non streamable binary file formats.
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I_kwDODunzps6Odqq6
7,024
Streaming dataset not returning data
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-04T07:21:47
2024-07-04T07:21:47
null
NONE
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### Describe the bug I'm deciding to post here because I'm still not sure what the issue is, or if I am using IterableDatasets wrongly. I'm following the guide on here https://huggingface.co/learn/cookbook/en/fine_tuning_code_llm_on_single_gpu pretty much to a tee and have verified that it works when I'm fine-tuning on the provided dataset. However, I'm doing some data preprocessing steps (filtering out entries), when I try to swap out the dataset for mine, it fails to train. However, I eventually fixed this by simply setting `stream=False` in `load_dataset`. Coud this be some sort of network / firewall issue I'm facing? ### Steps to reproduce the bug I made a post with greater description about how I reproduced this problem before I found my workaround: https://discuss.huggingface.co/t/problem-with-custom-iterator-of-streaming-dataset-not-returning-anything/94551 Here is the problematic dataset snippet, which works when streaming=False (and with buffer keyword removed from shuffle) ``` commitpackft = load_dataset( "chargoddard/commitpack-ft-instruct", split="train", streaming=True ).filter(lambda example: example["language"] == "Python") def form_template(example): """Forms a template for each example following the alpaca format for CommitPack""" example["content"] = ( "### Human: " + example["instruction"] + " " + example["input"] + " ### Assistant: " + example["output"] ) return example dataset = commitpackft.map( form_template, remove_columns=["id", "language", "license", "instruction", "input", "output"], ).shuffle( seed=42, buffer_size=10000 ) # remove everything since its all inside "content" now validation_data = dataset.take(4000) train_data = dataset.skip(4000) ``` The annoying part about this is that it only fails during training and I don't know when it will fail, except that it always fails during evaluation. ### Expected behavior The expected behavior is that I should be able to get something from the iterator when called instead of getting nothing / stuck in a loop somewhere. ### Environment info - `datasets` version: 2.20.0 - Platform: Linux-5.4.0-121-generic-x86_64-with-glibc2.31 - Python version: 3.11.7 - `huggingface_hub` version: 0.23.4 - PyArrow version: 16.1.0 - Pandas version: 2.2.2 - `fsspec` version: 2024.5.0
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Remove dead code for pyarrow < 15.0.0
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-03T09:05:03
2024-07-03T09:24:46
2024-07-03T09:17:35
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Remove dead code for pyarrow < 15.0.0. Code is dead since the merge of: - #6892 Fix #7022.
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There is dead code after we require pyarrow >= 15.0.0
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-03T08:52:57
2024-07-03T09:17:36
2024-07-03T09:17:36
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There are code lines specific for pyarrow versions < 15.0.0. However, we require pyarrow >= 15.0.0 since the merge of PR: - #6892 Those code lines are now dead code and should be removed.
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Fix casting list array to fixed size list
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-03T07:58:57
2024-07-03T08:47:49
2024-07-03T08:41:55
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Fix casting list array to fixed size list. This bug was introduced in [datasets-2.17.0](https://github.com/huggingface/datasets/releases/tag/2.17.0) by PR: https://github.com/huggingface/datasets/pull/6283/files#diff-1cb2b66aa9311d729cfd83013dad56cf5afcda35b39dfd0bfe9c3813a049eab0R1899 - #6283 Fix #7020.
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Casting list array to fixed size list raises error
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-03T07:54:49
2024-07-03T08:41:56
2024-07-03T08:41:56
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When trying to cast a list array to fixed size list, an AttributeError is raised: > AttributeError: 'pyarrow.lib.FixedSizeListType' object has no attribute 'length' Steps to reproduce the bug: ```python import pyarrow as pa from datasets.table import array_cast arr = pa.array([[0, 1]]) array_cast(arr, pa.list_(pa.int64(), 2)) ``` Stack trace: ``` --------------------------------------------------------------------------- AttributeError Traceback (most recent call last) <ipython-input-12-6cb90a1d8216> in <module> 3 4 arr = pa.array([[0, 1]]) ----> 5 array_cast(arr, pa.list_(pa.int64(), 2)) ~/huggingface/datasets/src/datasets/table.py in wrapper(array, *args, **kwargs) 1802 return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks]) 1803 else: -> 1804 return func(array, *args, **kwargs) 1805 1806 return wrapper ~/huggingface/datasets/src/datasets/table.py in array_cast(array, pa_type, allow_primitive_to_str, allow_decimal_to_str) 1920 else: 1921 array_values = array.values[ -> 1922 array.offset * pa_type.length : (array.offset + len(array)) * pa_type.length 1923 ] 1924 return pa.FixedSizeListArray.from_arrays(_c(array_values, pa_type.value_type), pa_type.list_size) AttributeError: 'pyarrow.lib.FixedSizeListType' object has no attribute 'length' ```
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Support pyarrow large_list
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-02T09:52:52
2024-07-30T14:17:38
null
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Allow Polars round trip by supporting pyarrow large list. Fix #6834, fix #6984. Supersede and close #4800, close #6835, close #6986.
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2,383,700,286
I_kwDODunzps6OFGE-
7,018
`load_dataset` fails to load dataset saved by `save_to_disk`
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-01T12:19:19
2024-07-23T09:09:17
null
NONE
null
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### Describe the bug This code fails to load the dataset it just saved: ```python from datasets import load_dataset from transformers import AutoTokenizer MODEL = "google-bert/bert-base-cased" tokenizer = AutoTokenizer.from_pretrained(MODEL) dataset = load_dataset("yelp_review_full") def tokenize_function(examples): return tokenizer(examples["text"], padding="max_length", truncation=True) tokenized_datasets = dataset.map(tokenize_function, batched=True) tokenized_datasets.save_to_disk("dataset") tokenized_datasets = load_dataset("dataset/") # raises ``` It raises `ValueError: Couldn't infer the same data file format for all splits. Got {NamedSplit('train'): ('arrow', {}), NamedSplit('test'): ('json', {})}`. I believe this bug is caused by the [logic that tries to infer dataset format](https://github.com/huggingface/datasets/blob/9af8dd3de7626183a9a9ec8973cebc672d690400/src/datasets/load.py#L556). It counts the most common file extension. However, a small dataset can fit in a single `.arrow` file and have two JSON metadata files, causing the format to be inferred as JSON: ```shell $ ls -l dataset/test -rw-r--r-- 1 sliedes sliedes 191498784 Jul 1 13:55 data-00000-of-00001.arrow -rw-r--r-- 1 sliedes sliedes 1730 Jul 1 13:55 dataset_info.json -rw-r--r-- 1 sliedes sliedes 249 Jul 1 13:55 state.json ``` ### Steps to reproduce the bug Execute the code above. ### Expected behavior The dataset is loaded successfully. ### Environment info - `datasets` version: 2.20.0 - Platform: Linux-6.9.3-arch1-1-x86_64-with-glibc2.39 - Python version: 3.12.4 - `huggingface_hub` version: 0.23.4 - PyArrow version: 16.1.0 - Pandas version: 2.2.2 - `fsspec` version: 2024.5.0
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Support fsspec 2024.6.1
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-01T11:57:15
2024-07-01T12:12:32
2024-07-01T12:06:24
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Support fsspec 2024.6.1.
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7,016
`drop_duplicates` method
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-01T09:01:06
2024-07-20T06:51:58
null
NONE
null
null
### Feature request `drop_duplicates` method for huggingface datasets (similiar in simplicity to the `pandas` one) ### Motivation Ease of use ### Your contribution I don't think i am good enough to help
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add split argument to Generator
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-01T08:09:25
2024-07-26T09:37:51
2024-07-26T09:31:56
CONTRIBUTOR
false
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## Actual When creating a multi-split dataset using generators like ```python datasets.DatasetDict({ "val": datasets.Dataset.from_generator( generator=generator_val, features=features ), "test": datasets.Dataset.from_generator( generator=generator_test, features=features, ) }) ``` It displays (for both test and val) ``` Generating train split ``` ## Expected I would like to be able to improve this behavior by doing ```python datasets.DatasetDict({ "val": datasets.Dataset.from_generator( generator=generator_val, features=features, split="val" ), "test": datasets.Dataset.from_generator( generator=generator_test, features=features, split="test" ) }) ``` It would display ``` Generating val split ``` and ``` Generating test split ``` ## Proposal Current PR is adding an explicit `split` argument and replace the implicit "train" split in the following classes/function : * Generator * from_generator * AbstractDatasetInputStream * GeneratorDatasetInputStream Please share your feedbacks
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Skip faiss tests on Windows to avoid running CI for 360 minutes
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-01T06:45:35
2024-07-01T07:16:36
2024-07-01T07:10:27
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Skip faiss tests on Windows to avoid running CI for 360 minutes. Fix #7013. Revert once the underlying issue is fixed.
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CI is broken for faiss tests on Windows: node down: Not properly terminated
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-07-01T06:40:03
2024-07-01T07:10:28
2024-07-01T07:10:28
MEMBER
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Faiss tests on Windows make the CI run indefinitely until maximum execution time (360 minutes) is reached. See: https://github.com/huggingface/datasets/actions/runs/9712659783 ``` test (integration, windows-latest, deps-minimum) The job running on runner GitHub Actions 60 has exceeded the maximum execution time of 360 minutes. test (integration, windows-latest, deps-latest) The job running on runner GitHub Actions 238 has exceeded the maximum execution time of 360 minutes. ``` ``` ____________________________ tests/test_search.py _____________________________ [gw1] win32 -- Python 3.8.10 C:\hostedtoolcache\windows\Python\3.8.10\x64\python.exe worker 'gw1' crashed while running 'tests/test_search.py::IndexableDatasetTest::test_add_faiss_index' ____________________________ tests/test_search.py _____________________________ [gw2] win32 -- Python 3.8.10 C:\hostedtoolcache\windows\Python\3.8.10\x64\python.exe worker 'gw2' crashed while running 'tests/test_search.py::IndexableDatasetTest::test_add_faiss_index' ``` ``` tests/test_search.py::IndexableDatasetTest::test_add_faiss_index [gw0] node down: Not properly terminated [gw0] FAILED tests/test_search.py::IndexableDatasetTest::test_add_faiss_index replacing crashed worker gw0 tests/test_search.py::IndexableDatasetTest::test_add_faiss_index [gw1] node down: Not properly terminated [gw1] FAILED tests/test_search.py::IndexableDatasetTest::test_add_faiss_index replacing crashed worker gw1 tests/test_search.py::IndexableDatasetTest::test_add_faiss_index [gw2] node down: Not properly terminated [gw2] FAILED tests/test_search.py::IndexableDatasetTest::test_add_faiss_index replacing crashed worker gw2 ```
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Raise an error when a nested object is expected to be a mapping that displays the object
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-06-28T18:10:59
2024-07-11T02:06:16
2024-07-11T02:06:16
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Re-enable raising error from huggingface-hub FutureWarning in CI
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-06-28T07:28:32
2024-06-28T12:25:25
2024-06-28T12:19:28
MEMBER
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Re-enable raising error from huggingface-hub FutureWarning in tests, once that the fix in transformers - https://github.com/huggingface/transformers/pull/31007 was just released yesterday in transformers-4.42.0: https://github.com/huggingface/transformers/releases/tag/v4.42.0 Fix #7010.
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Re-enable raising error from huggingface-hub FutureWarning in CI
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-06-28T07:23:40
2024-06-28T12:19:30
2024-06-28T12:19:29
MEMBER
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Re-enable raising error from huggingface-hub FutureWarning in CI, which was disabled by PR: - #6876 Note that this can only be done once transformers releases the fix: - https://github.com/huggingface/transformers/pull/31007
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Support ruff 0.5.0 in CI
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-06-28T05:37:36
2024-06-28T07:17:26
2024-06-28T07:11:17
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Support ruff 0.5.0 in CI and revert: - #7007 Fix #7008.
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Support ruff 0.5.0 in CI
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-06-28T05:11:26
2024-06-28T07:11:18
2024-06-28T07:11:18
MEMBER
null
null
Support ruff 0.5.0 in CI. Also revert: - #7007
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7,007
Fix CI by temporarily pinning ruff < 0.5.0
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-06-28T05:09:17
2024-06-28T05:31:21
2024-06-28T05:25:17
MEMBER
false
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As a hotfix for CI, temporarily pin ruff upper version < 0.5.0. Fix #7006. Revert once root cause is fixed.
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I_kwDODunzps6N1Yhn
7,006
CI is broken after ruff-0.5.0: E721
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-06-28T05:03:28
2024-06-28T05:25:18
2024-06-28T05:25:18
MEMBER
null
null
After ruff-0.5.0 release (https://github.com/astral-sh/ruff/releases/tag/0.5.0), our CI is broken due to E721 rule. See: https://github.com/huggingface/datasets/actions/runs/9707641618/job/26793170961?pr=6983 > src/datasets/features/features.py:844:12: E721 Use `is` and `is not` for type comparisons, or `isinstance()` for isinstance checks
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2,378,424,349
I_kwDODunzps6Nw-Ad
7,005
EmptyDatasetError: The directory at /metadata.jsonl doesn't contain any data files
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-06-27T15:08:26
2024-06-28T09:56:19
2024-06-28T09:56:19
NONE
null
null
### Describe the bug while trying to load custom dataset from jsonl file, I get the error: "metadata.jsonl doesn't contain any data files" ### Steps to reproduce the bug This is my [metadata_v2.jsonl](https://github.com/user-attachments/files/16016011/metadata_v2.json) file. I have this file in the folder with all images mentioned in that json(l) file. Through below mentioned command I am trying to load_dataset so that I can upload it as mentioned here on the [official website](https://huggingface.co/docs/datasets/en/image_dataset#upload-dataset-to-the-hub). ```` from datasets import load_dataset dataset = load_dataset("imagefolder", data_dir="path/to/jsonl/metadata.jsonl") ```` error: ```` EmptyDatasetError Traceback (most recent call last) Cell In[18], line 3 1 from datasets import load_dataset ----> 3 dataset = load_dataset("imagefolder", 4 data_dir="path/to/jsonl/file/metadata.jsonl") 5 dataset[0]["objects"] File ~/anaconda3/envs/lvis/lib/python3.11/site-packages/datasets/load.py:2594, in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, verification_mode, ignore_verifications, keep_in_memory, save_infos, revision, token, use_auth_token, task, streaming, num_proc, storage_options, trust_remote_code, **config_kwargs) 2589 verification_mode = VerificationMode( 2590 (verification_mode or VerificationMode.BASIC_CHECKS) if not save_infos else VerificationMode.ALL_CHECKS 2591 ) 2593 # Create a dataset builder -> 2594 builder_instance = load_dataset_builder( 2595 path=path, 2596 name=name, 2597 data_dir=data_dir, 2598 data_files=data_files, 2599 cache_dir=cache_dir, 2600 features=features, 2601 download_config=download_config, 2602 download_mode=download_mode, 2603 revision=revision, 2604 token=token, 2605 storage_options=storage_options, 2606 trust_remote_code=trust_remote_code, 2607 _require_default_config_name=name is None, 2608 **config_kwargs, 2609 ) 2611 # Return iterable dataset in case of streaming 2612 if streaming: File ~/anaconda3/envs/lvis/lib/python3.11/site-packages/datasets/load.py:2266, in load_dataset_builder(path, name, data_dir, data_files, cache_dir, features, download_config, download_mode, revision, token, use_auth_token, storage_options, trust_remote_code, _require_default_config_name, **config_kwargs) 2264 download_config = download_config.copy() if download_config else DownloadConfig() 2265 download_config.storage_options.update(storage_options) -> 2266 dataset_module = dataset_module_factory( 2267 path, 2268 revision=revision, 2269 download_config=download_config, 2270 download_mode=download_mode, 2271 data_dir=data_dir, 2272 data_files=data_files, 2273 cache_dir=cache_dir, 2274 trust_remote_code=trust_remote_code, 2275 _require_default_config_name=_require_default_config_name, 2276 _require_custom_configs=bool(config_kwargs), 2277 ) 2278 # Get dataset builder class from the processing script 2279 builder_kwargs = dataset_module.builder_kwargs File ~/anaconda3/envs/lvis/lib/python3.11/site-packages/datasets/load.py:1805, in dataset_module_factory(path, revision, download_config, download_mode, dynamic_modules_path, data_dir, data_files, cache_dir, trust_remote_code, _require_default_config_name, _require_custom_configs, **download_kwargs) 1782 # We have several ways to get a dataset builder: 1783 # 1784 # - if path is the name of a packaged dataset module (...) 1796 1797 # Try packaged 1798 if path in _PACKAGED_DATASETS_MODULES: 1799 return PackagedDatasetModuleFactory( 1800 path, 1801 data_dir=data_dir, 1802 data_files=data_files, 1803 download_config=download_config, 1804 download_mode=download_mode, -> 1805 ).get_module() 1806 # Try locally 1807 elif path.endswith(filename): File ~/anaconda3/envs/lvis/lib/python3.11/site-packages/datasets/load.py:1140, in PackagedDatasetModuleFactory.get_module(self) 1135 def get_module(self) -> DatasetModule: 1136 base_path = Path(self.data_dir or "").expanduser().resolve().as_posix() 1137 patterns = ( 1138 sanitize_patterns(self.data_files) 1139 if self.data_files is not None -> 1140 else get_data_patterns(base_path, download_config=self.download_config) 1141 ) 1142 data_files = DataFilesDict.from_patterns( 1143 patterns, 1144 download_config=self.download_config, 1145 base_path=base_path, 1146 ) 1147 supports_metadata = self.name in _MODULE_SUPPORTS_METADATA File ~/anaconda3/envs/lvis/lib/python3.11/site-packages/datasets/data_files.py:503, in get_data_patterns(base_path, download_config) 501 return _get_data_files_patterns(resolver) 502 except FileNotFoundError: --> 503 raise EmptyDatasetError(f"The directory at {base_path} doesn't contain any data files") from None EmptyDatasetError: The directory at path/to/jsonl/file/metadata.jsonl doesn't contain any data files` ``` ### Expected behavior It should be able load the whole file in a format of "dataset" inside the dataset variable. But it gives error "The directory at "path/to/jsonl/metadata.jsonl" doesn't contain any data files." ### Environment info I am using conda environment.
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2,376,064,264
PR_kwDODunzps5zrIYR
7,004
Fix WebDatasets KeyError for user-defined Features when a field is missing in an example
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-06-26T18:58:05
2024-06-29T00:15:49
2024-06-28T09:30:12
CONTRIBUTOR
false
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Fixes: https://github.com/huggingface/datasets/issues/6900 Not sure if this needs any addition stuff before merging
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7,003
minor fix for bfloat16
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-06-25T16:10:04
2024-06-25T16:16:11
2024-06-25T16:10:10
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PR_kwDODunzps5zhBld
7,002
Fix dump of bfloat16 torch tensor
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-06-25T15:38:09
2024-06-25T16:10:16
2024-06-25T15:51:52
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close https://github.com/huggingface/datasets/issues/7000
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I_kwDODunzps6NcA0_
7,001
Datasetbuilder Local Download FileNotFoundError
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-06-25T15:02:34
2024-06-25T15:21:19
null
NONE
null
null
### Describe the bug So I was trying to download a dataset and save it as parquet and I follow the [tutorial](https://huggingface.co/docs/datasets/filesystems#download-and-prepare-a-dataset-into-a-cloud-storage) of Huggingface. However, during the excution I face a FileNotFoundError. I debug the code and it seems there is a bug there: So first it creates a .incomplete folder and before moving its contents the following code deletes the directory [Code](https://github.com/huggingface/datasets/blob/98fdc9e78e6d057ca66e58a37f49d6618aab8130/src/datasets/builder.py#L984) hence as a result I face with: ``` FileNotFoundError: [Errno 2] No such file or directory: '~/data/Parquet/.incomplete '``` ### Steps to reproduce the bug ``` from datasets import load_dataset_builder from pathlib import Path parquet_dir = "~/data/Parquet/" Path(parquet_dir).mkdir(parents=True, exist_ok=True) builder = load_dataset_builder( "rotten_tomatoes", ) builder.download_and_prepare(parquet_dir, file_format="parquet") ``` ### Expected behavior Downloads the files and saves as parquet ### Environment info Ubuntu, Python 3.10 ``` datasets 2.19.1 ```
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7,000
IterableDataset: Unsupported ScalarType BFloat16
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-06-25T14:43:26
2024-06-25T16:04:00
2024-06-25T15:51:53
NONE
null
null
### Describe the bug `IterableDataset.from_generator` crashes when using BFloat16: ``` File "/usr/local/lib/python3.11/site-packages/datasets/utils/_dill.py", line 169, in _save_torchTensor args = (obj.detach().cpu().numpy(),) ^^^^^^^^^^^^^^^^^^^^^^^^^^ TypeError: Got unsupported ScalarType BFloat16 ``` ### Steps to reproduce the bug ```python import torch from datasets import IterableDataset def demo(x): yield {"x": x} x = torch.tensor([1.], dtype=torch.bfloat16) dataset = IterableDataset.from_generator( demo, gen_kwargs=dict(x=x), ) example = next(iter(dataset)) print(example) ``` ### Expected behavior Code sample should print: ```python {'x': tensor([1.], dtype=torch.bfloat16)} ``` ### Environment info ``` datasets==2.20.0 torch==2.2.2 ```
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6,999
Remove tasks
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-06-25T09:06:16
2024-07-03T12:01:42
null
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Remove tasks, as part of the 3.0 release.
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Fix tests using hf-internal-testing/librispeech_asr_dummy
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-06-25T07:59:44
2024-06-25T08:22:38
2024-06-25T08:13:42
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Fix tests using hf-internal-testing/librispeech_asr_dummy once that dataset has been converted to Parquet. Fix #6997.
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6,997
CI is broken for tests using hf-internal-testing/librispeech_asr_dummy
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-06-25T07:55:44
2024-06-25T08:13:43
2024-06-25T08:13:43
MEMBER
null
null
CI is broken: https://github.com/huggingface/datasets/actions/runs/9657882317/job/26637998686?pr=6996 ``` FAILED tests/test_inspect.py::test_get_dataset_config_names[hf-internal-testing/librispeech_asr_dummy-expected4] - AssertionError: assert ['clean'] == ['clean', 'other'] Right contains one more item: 'other' Full diff: [ 'clean', - 'other', ] FAILED tests/test_inspect.py::test_get_dataset_default_config_name[hf-internal-testing/librispeech_asr_dummy-None] - AssertionError: assert 'clean' is None ``` Note that repository was recently converted to Parquet: https://huggingface.co/datasets/hf-internal-testing/librispeech_asr_dummy/commit/5be91486e11a2d616f4ec5db8d3fd248585ac07a
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PR_kwDODunzps5zdAg0
6,996
Remove deprecated code
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-06-25T06:54:40
2024-07-01T12:36:59
null
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Remove deprecated code, as part of the 3.0 release. First merge: - [x] #6983 - [x] #6987 - [ ] #6999
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2,370,713,475
I_kwDODunzps6NTjeD
6,995
ImportError when importing datasets.load_dataset
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-06-24T17:07:22
2024-07-16T17:51:06
2024-06-25T06:11:37
NONE
null
null
### Describe the bug I encountered an ImportError while trying to import `load_dataset` from the `datasets` module in Hugging Face. The error message indicates a problem with importing 'CommitInfo' from 'huggingface_hub'. ### Steps to reproduce the bug 1. pip install git+https://github.com/huggingface/datasets 2. from datasets import load_dataset ### Expected behavior ImportError Traceback (most recent call last) Cell In[7], [line 1](vscode-notebook-cell:?execution_count=7&line=1) ----> [1](vscode-notebook-cell:?execution_count=7&line=1) from datasets import load_dataset [3](vscode-notebook-cell:?execution_count=7&line=3) train_set = load_dataset("mispeech/speechocean762", split="train") [4](vscode-notebook-cell:?execution_count=7&line=4) test_set = load_dataset("mispeech/speechocean762", split="test") File d:\Anaconda3\envs\CS224S\Lib\site-packages\datasets\__init__.py:[1](file:///D:/Anaconda3/envs/CS224S/Lib/site-packages/datasets/__init__.py:1)7 1 # Copyright 2020 The HuggingFace Datasets Authors and the TensorFlow Datasets Authors. [2](file:///D:/Anaconda3/envs/CS224S/Lib/site-packages/datasets/__init__.py:2) # [3](file:///D:/Anaconda3/envs/CS224S/Lib/site-packages/datasets/__init__.py:3) # Licensed under the Apache License, Version 2.0 (the "License"); (...) [12](file:///D:/Anaconda3/envs/CS224S/Lib/site-packages/datasets/__init__.py:12) # See the License for the specific language governing permissions and [13](file:///D:/Anaconda3/envs/CS224S/Lib/site-packages/datasets/__init__.py:13) # limitations under the License. [15](file:///D:/Anaconda3/envs/CS224S/Lib/site-packages/datasets/__init__.py:15) __version__ = "2.20.1.dev0" ---> [17](file:///D:/Anaconda3/envs/CS224S/Lib/site-packages/datasets/__init__.py:17) from .arrow_dataset import Dataset [18](file:///D:/Anaconda3/envs/CS224S/Lib/site-packages/datasets/__init__.py:18) from .arrow_reader import ReadInstruction [19](file:///D:/Anaconda3/envs/CS224S/Lib/site-packages/datasets/__init__.py:19) from .builder import ArrowBasedBuilder, BeamBasedBuilder, BuilderConfig, DatasetBuilder, GeneratorBasedBuilder File d:\Anaconda3\envs\CS224S\Lib\site-packages\datasets\arrow_dataset.py:63 [61](file:///D:/Anaconda3/envs/CS224S/Lib/site-packages/datasets/arrow_dataset.py:61) import pyarrow.compute as pc [62](file:///D:/Anaconda3/envs/CS224S/Lib/site-packages/datasets/arrow_dataset.py:62) from fsspec.core import url_to_fs ---> [63](file:///D:/Anaconda3/envs/CS224S/Lib/site-packages/datasets/arrow_dataset.py:63) from huggingface_hub import ( [64](file:///D:/Anaconda3/envs/CS224S/Lib/site-packages/datasets/arrow_dataset.py:64) CommitInfo, [65](file:///D:/Anaconda3/envs/CS224S/Lib/site-packages/datasets/arrow_dataset.py:65) CommitOperationAdd, ... [70](file:///D:/Anaconda3/envs/CS224S/Lib/site-packages/datasets/arrow_dataset.py:70) ) [71](file:///D:/Anaconda3/envs/CS224S/Lib/site-packages/datasets/arrow_dataset.py:71) from huggingface_hub.hf_api import RepoFile [72](file:///D:/Anaconda3/envs/CS224S/Lib/site-packages/datasets/arrow_dataset.py:72) from multiprocess import Pool ImportError: cannot import name 'CommitInfo' from 'huggingface_hub' (d:\Anaconda3\envs\CS224S\Lib\site-packages\huggingface_hub\__init__.py) Output is truncated. View as a [scrollable element](command:cellOutput.enableScrolling?580889ab-0f61-4f37-9214-eaa2b3807f85) or open in a [text editor](command:workbench.action.openLargeOutput?580889ab-0f61-4f37-9214-eaa2b3807f85). Adjust cell output [settings](command:workbench.action.openSettings?%5B%22%40tag%3AnotebookOutputLayout%22%5D)... ### Environment info Leo@DESKTOP-9NHUAMI MSYS /d/Anaconda3/envs/CS224S/Lib/site-packages/huggingface_hub $ datasets-cli env Traceback (most recent call last): File "<frozen runpy>", line 198, in _run_module_as_main File "<frozen runpy>", line 88, in _run_code File "D:\Anaconda3\envs\CS224S\Scripts\datasets-cli.exe\__main__.py", line 4, in <module> File "D:\Anaconda3\envs\CS224S\Lib\site-packages\datasets\__init__.py", line 17, in <module> from .arrow_dataset import Dataset File "D:\Anaconda3\envs\CS224S\Lib\site-packages\datasets\arrow_dataset.py", line 63, in <module> from huggingface_hub import ( ImportError: cannot import name 'CommitInfo' from 'huggingface_hub' (D:\Anaconda3\envs\CS224S\Lib\site-packages\huggingface_hub\__init__.py) (CS224S)
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2,370,491,689
PR_kwDODunzps5zYYXr
6,994
Fix incorrect rank value in data splitting
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-06-24T15:07:47
2024-06-26T04:37:35
2024-06-25T16:19:17
CONTRIBUTOR
false
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Fix #6990.
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PR_kwDODunzps5zYN7P
6,993
less script docs
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-06-24T14:45:28
2024-07-08T13:10:53
2024-06-27T09:31:21
MEMBER
false
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+ mark as legacy in some parts of the docs since we'll not build new features for script datasets
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Dataset with streaming doesn't work with proxy
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-06-22T16:12:08
2024-06-25T15:43:05
null
NONE
null
null
### Describe the bug I'm currently trying to stream data using dataset since the dataset is too big but it hangs indefinitely without loading the first batch. I use AIMOS which is a supercomputer that uses proxy to connect to the internet. I assume it has to do with the network configurations. I've already set up both HTTP_PROXY and HTTPS_PROXY. streaming = False works fine. ### Steps to reproduce the bug use load_dataset with streaming = True in AIMOS ### Expected behavior does not hang indefinitely and loads batches to start training run ### Environment info _libgcc_mutex 0.1 conda_forge conda-forge _openmp_mutex 4.5 2_gnu conda-forge _pytorch_select 2.0 cuda_2 https://ftp.osuosl.org/pub/open-ce/1.10.0 abseil-cpp 20220623.0 h9888cd1_6 conda-forge absl-py 1.0.0 py311h399429b_0 https://ftp.osuosl.org/pub/open-ce/1.10.0 aiofiles 23.2.1 pyhd8ed1ab_0 conda-forge aiohttp 3.8.6 py311hf118e41_0 aiosignal 1.2.0 pyhd3eb1b0_0 archspec 0.2.3 pyhd8ed1ab_0 conda-forge arrow-cpp 11.0.0 ha3edaa6_5_cpu conda-forge async-timeout 4.0.2 py311h6ffa863_0 attrs 23.1.0 py311h6ffa863_0 av 10.0.0 py311he6153ed_2 https://ftp.osuosl.org/pub/open-ce/1.10.0 aws-c-auth 0.6.24 hb81f6d7_5 conda-forge aws-c-cal 0.5.20 h3c2b4d9_6 conda-forge aws-c-common 0.8.11 h4194056_0 conda-forge aws-c-compression 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Unblock NumPy 2.0
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-06-22T09:19:53
2024-07-12T12:11:18
2024-07-12T12:04:53
CONTRIBUTOR
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Fixes https://github.com/huggingface/datasets/issues/6980
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6,990
Problematic rank after calling `split_dataset_by_node` twice
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-06-21T14:25:26
2024-06-25T16:19:19
2024-06-25T16:19:19
CONTRIBUTOR
null
null
### Describe the bug I'm trying to split `IterableDataset` by `split_dataset_by_node`. But when doing split on a already split dataset, the resulting `rank` is greater than `world_size`. ### Steps to reproduce the bug Here is the minimal code for reproduction: ```py >>> from datasets import load_dataset >>> from datasets.distributed import split_dataset_by_node >>> dataset = load_dataset('fla-hub/slimpajama-test', split='train', streaming=True) >>> dataset = split_dataset_by_node(dataset, 1, 32) >>> dataset._distributed DistributedConfig(rank=1, world_size=32) >>> dataset = split_dataset_by_node(dataset, 1, 15) >>> dataset._distributed DistributedConfig(rank=481, world_size=480) ``` As you can see, the second rank 481 > 480, which is problematic. ### Expected behavior I think this error comes from this line @lhoestq https://github.com/huggingface/datasets/blob/a6ccf944e42c1a84de81bf326accab9999b86c90/src/datasets/iterable_dataset.py#L2943-L2944 We may need to obtain the rank first. Then the above code gives ```py >>> dataset._distributed DistributedConfig(rank=16, world_size=480) ``` ### Environment info datasets==2.20.0
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I_kwDODunzps6M_4bh
6,989
cache in nfs error
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-06-21T02:09:22
2024-06-21T02:12:55
null
NONE
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### Describe the bug - When reading dataset, a cache will be generated to the ~/. cache/huggingface/datasets directory - When using .map and .filter operations, runtime cache will be generated to the /tmp/hf_datasets-* directory - The default is to use the path of tempfile.tempdir - If I modify this path to the NFS disk, an error will be reported, but the program will continue to run - https://github.com/huggingface/datasets/blob/main/src/datasets/config.py#L257 ``` Traceback (most recent call last): File "/home/wzp/miniconda3/envs/dask/lib/python3.8/site-packages/multiprocess/process.py", line 315, in _bootstrap self.run() File "/home/wzp/miniconda3/envs/dask/lib/python3.8/site-packages/multiprocess/process.py", line 108, in run self._target(*self._args, **self._kwargs) File "/home/wzp/miniconda3/envs/dask/lib/python3.8/site-packages/multiprocess/managers.py", line 616, in _run_server server.serve_forever() File "/home/wzp/miniconda3/envs/dask/lib/python3.8/site-packages/multiprocess/managers.py", line 182, in serve_forever sys.exit(0) SystemExit: 0 During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/home/wzp/miniconda3/envs/dask/lib/python3.8/site-packages/multiprocess/util.py", line 300, in _run_finalizers finalizer() File "/home/wzp/miniconda3/envs/dask/lib/python3.8/site-packages/multiprocess/util.py", line 224, in __call__ res = self._callback(*self._args, **self._kwargs) File "/home/wzp/miniconda3/envs/dask/lib/python3.8/site-packages/multiprocess/util.py", line 133, in _remove_temp_dir rmtree(tempdir) File "/home/wzp/miniconda3/envs/dask/lib/python3.8/shutil.py", line 718, in rmtree _rmtree_safe_fd(fd, path, onerror) File "/home/wzp/miniconda3/envs/dask/lib/python3.8/shutil.py", line 675, in _rmtree_safe_fd onerror(os.unlink, fullname, sys.exc_info()) File "/home/wzp/miniconda3/envs/dask/lib/python3.8/shutil.py", line 673, in _rmtree_safe_fd os.unlink(entry.name, dir_fd=topfd) OSError: [Errno 16] Device or resource busy: '.nfs000000038330a012000030b4' Traceback (most recent call last): File "/home/wzp/miniconda3/envs/dask/lib/python3.8/site-packages/multiprocess/process.py", line 315, in _bootstrap self.run() File "/home/wzp/miniconda3/envs/dask/lib/python3.8/site-packages/multiprocess/process.py", line 108, in run self._target(*self._args, **self._kwargs) File "/home/wzp/miniconda3/envs/dask/lib/python3.8/site-packages/multiprocess/managers.py", line 616, in _run_server server.serve_forever() File "/home/wzp/miniconda3/envs/dask/lib/python3.8/site-packages/multiprocess/managers.py", line 182, in serve_forever sys.exit(0) SystemExit: 0 During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/home/wzp/miniconda3/envs/dask/lib/python3.8/site-packages/multiprocess/util.py", line 300, in _run_finalizers finalizer() File "/home/wzp/miniconda3/envs/dask/lib/python3.8/site-packages/multiprocess/util.py", line 224, in __call__ res = self._callback(*self._args, **self._kwargs) File "/home/wzp/miniconda3/envs/dask/lib/python3.8/site-packages/multiprocess/util.py", line 133, in _remove_temp_dir rmtree(tempdir) File "/home/wzp/miniconda3/envs/dask/lib/python3.8/shutil.py", line 718, in rmtree _rmtree_safe_fd(fd, path, onerror) File "/home/wzp/miniconda3/envs/dask/lib/python3.8/shutil.py", line 675, in _rmtree_safe_fd onerror(os.unlink, fullname, sys.exc_info()) File "/home/wzp/miniconda3/envs/dask/lib/python3.8/shutil.py", line 673, in _rmtree_safe_fd os.unlink(entry.name, dir_fd=topfd) OSError: [Errno 16] Device or resource busy: '.nfs0000000400064d4a000030e5' ``` ### Steps to reproduce the bug ``` import os import time import tempfile from datasets import load_dataset def add_column(sample): # print(type(sample)) # time.sleep(0.1) sample['__ds__stats__'] = {'data': 123} return sample def filt_column(sample): # print(type(sample)) if len(sample['content']) > 10: return True else: return False if __name__ == '__main__': input_dir = '/mnt/temp/CN/small' # some json dataset dataset = load_dataset('json', data_dir=input_dir) temp_dir = '/media/release/release/temp/temp' # a nfs folder os.makedirs(temp_dir, exist_ok=True) # change huggingface-datasets runtime cache in nfs(default in /tmp) tempfile.tempdir = temp_dir aa = dataset.map(add_column, num_proc=64) aa = aa.filter(filt_column, num_proc=64) print(aa) ``` ### Expected behavior no error occur ### Environment info datasets==2.18.0 ubuntu 20.04
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[`feat`] Move dataset card creation to method for easier overriding
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-06-20T10:47:57
2024-06-21T16:04:58
null
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Hello! ## Pull Request overview * Move dataset card creation to method for easier overriding ## Details It's common for me to fully automatically download, reformat, and upload a dataset (e.g. see https://huggingface.co/datasets?other=sentence-transformers), but one aspect that I cannot easily automate is the dataset card generation. This is because during `push_to_hub`, the dataset card is created in 3 lines of code in a much larger method. To automatically generate a dataset card, I need to either: 1. Subclass `Dataset`/`DatasetDict`, copy the entire `push_to_hub` method to override the ~3 lines used to generate the dataset card. This is not viable as the method is likely to change over time. 2. Use `push_to_hub` normally, then separately download the pushed (but empty) dataset card, update it, and reupload the modified dataset. This works fine, but prevents me from being able to return a `Dataset` to my users which will automatically use a nice dataset card. So, in this PR I'm proposing to move the dataset generation into another method so that it can be overridden more easily. For example, imagine the following use case: ````python import json from typing import Any, Dict, Optional from datasets import Dataset, load_dataset from datasets.info import DatasetInfosDict, DatasetInfo from datasets.utils.metadata import MetadataConfigs from huggingface_hub import DatasetCardData, DatasetCard TEMPLATE = r"""--- {dataset_card_data} --- # Dataset Card for {source_dataset_name} with mined hard negatives This dataset is a collection of {column_one}-{column_two}-negative triplets from the {source_dataset_name} dataset. See [{source_dataset_name}](https://huggingface.co/datasets/{source_dataset_id}) for additional information. This dataset can be used directly with Sentence Transformers to train embedding models. ## Mining Parameters The negative samples have been mined using the following parameters: - `range_min`: {range_min}, i.e. we skip the {range_min} most similar samples - `range_max`: {range_max}, i.e. we only look at the top {range_max} most similar samples - `margin`: {margin}, i.e. we require negative similarity + margin < positive similarity, so negative samples can't be more similar than the known true answer - `sampling_strategy`: {sampling_strategy}, i.e. whether to randomly sample from the candidate negatives or take the "top" negatives - `num_negatives`: {num_negatives}, i.e. we mine {num_negatives} negatives per question-answer pair ## Dataset Format - Columns: {column_one}, {column_two}, negative - Column types: str, str, str - Example: ```python {example} ``` """ class HNMDataset(Dataset): @classmethod def from_dict(cls, *args, mining_kwargs: Dict[str, Any], **kwargs) -> "HNMDataset": dataset = super().from_dict(*args, **kwargs) dataset.mining_kwargs = mining_kwargs return dataset def _create_dataset_card( self, dataset_card_data: DatasetCardData, dataset_card: Optional[DatasetCard], config_name: str, info_to_dump: DatasetInfo, metadata_config_to_dump: MetadataConfigs, ) -> DatasetCard: if dataset_card: return dataset_card DatasetInfosDict({config_name: info_to_dump}).to_dataset_card_data(dataset_card_data) MetadataConfigs({config_name: metadata_config_to_dump}).to_dataset_card_data(dataset_card_data) dataset_card_data.tags = ["sentence-transformers"] dataset_name = self.mining_kwargs["source_dataset"].info.dataset_name # Very messy, just as an example: dataset_id = list(self.mining_kwargs["source_dataset"].info.download_checksums.keys())[0].removeprefix("hf://datasets/").split("@")[0] content = TEMPLATE.format(**{ "dataset_card_data": str(dataset_card_data), "source_dataset_name": dataset_name, "source_dataset_id": dataset_id, "range_min": self.mining_kwargs["range_min"], "range_max": self.mining_kwargs["range_max"], "margin": self.mining_kwargs["margin"], "sampling_strategy": self.mining_kwargs["sampling_strategy"], "num_negatives": self.mining_kwargs["num_negatives"], "column_one": self.column_names[0], "column_two": self.column_names[1], "example": json.dumps(self[0], indent=4), }) return DatasetCard(content) source_dataset = load_dataset("sentence-transformers/gooaq", split="train[:100]") dataset = HNMDataset.from_dict({ "query": source_dataset["question"], "answer": source_dataset["answer"], # "negative": ... <- In my case, this column would be 'mined' automatically with these parameters }, mining_kwargs={ "range_min": 10, "range_max": 20, "max_score": 0.9, "margin": 0.1, "sampling_strategy": "random", "num_negatives": 3, "source_dataset": source_dataset, }) dataset.push_to_hub("tomaarsen/mining_demo", private=True) ```` In this script, I've created a subclass which stores some additional information about how the dataset was generated. It's a bit hacky (e.g. setting a `mining_kwargs` parameter in `from_dict` that wasn't created in `__init__`, but that's just a consequence of how the `from_...` methods don't accept kwargs), but it allows me to create a "hard negatives mining" function that returns a dataset which people can use locally like normal, but if they choose to upload it, then it'll automatically include some information, e.g.: https://huggingface.co/datasets/tomaarsen/mining_demo This allows others to actually find this dataset (e.g. via the `sentence-transformers` tag) and get an idea of the quality, source, etc. by looking at the model card. ## Note I'm not fixed on this solution whatsoever: I am also completely fine with other solutions, e.g. a `dataset.set_dataset_card_creator` method that allows me to provide a function without even having to subclass anything. I'm open to all ideas :) cc @albertvillanova @lhoestq cc @LysandreJik - Tom Aarsen
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Remove beam
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-06-20T07:27:14
2024-06-26T19:41:55
2024-06-26T19:35:42
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Remove beam, as part of the 3.0 release.
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Add large_list type support in string_to_arrow
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-06-19T14:54:25
2024-07-18T08:29:17
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add large_list type support in string_to_arrow() and _arrow_to_datasets_dtype() in features.py Fix #6984
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AttributeError: module 'pyarrow.lib' has no attribute 'ListViewType'
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-06-19T13:22:28
2024-07-29T07:45:21
2024-06-25T05:40:51
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### Describe the bug I have been struggling with this for two days, any help would be appreciated. Python 3.10 ``` from setfit import SetFitModel from huggingface_hub import login access_token_read = "cccxxxccc" # Authenticate with the Hugging Face Hub login(token=access_token_read) # Load the models from the Hugging Face Hub trainer_relv = SetFitModel.from_pretrained("snowdere/trainer_relevance") trainer_trust = SetFitModel.from_pretrained("snowdere/trainer_trust") trainer_sent = SetFitModel.from_pretrained("snowdere/trainer_sent") trainer_topic = SetFitModel.from_pretrained("snowdere/trainer_topic") ``` ``` --------------------------------------------------------------------------- AttributeError Traceback (most recent call last) Cell In[6], line 1 ----> 1 from setfit import SetFitModel 2 from huggingface_hub import login 4 access_token_read = "ccsddsds" File /opt/conda/lib/python3.10/site-packages/setfit/__init__.py:7 4 import os 5 import warnings ----> 7 from .data import get_templated_dataset, sample_dataset 8 from .model_card import SetFitModelCardData 9 from .modeling import SetFitHead, SetFitModel File /opt/conda/lib/python3.10/site-packages/setfit/data.py:5 3 import pandas as pd 4 import torch ----> 5 from datasets import Dataset, DatasetDict, load_dataset 6 from torch.utils.data import Dataset as TorchDataset 8 from . import logging File /opt/conda/lib/python3.10/site-packages/datasets/__init__.py:18 1 # ruff: noqa 2 # Copyright 2020 The HuggingFace Datasets Authors and the TensorFlow Datasets Authors. 3 # (...) 13 # See the License for the specific language governing permissions and 14 # limitations under the License. 16 __version__ = "2.19.0" ---> 18 from .arrow_dataset import Dataset 19 from .arrow_reader import ReadInstruction 20 from .builder import ArrowBasedBuilder, BeamBasedBuilder, BuilderConfig, DatasetBuilder, GeneratorBasedBuilder File /opt/conda/lib/python3.10/site-packages/datasets/arrow_dataset.py:76 73 from tqdm.contrib.concurrent import thread_map 75 from . import config ---> 76 from .arrow_reader import ArrowReader 77 from .arrow_writer import ArrowWriter, OptimizedTypedSequence 78 from .data_files import sanitize_patterns File /opt/conda/lib/python3.10/site-packages/datasets/arrow_reader.py:29 26 from typing import TYPE_CHECKING, List, Optional, Union 28 import pyarrow as pa ---> 29 import pyarrow.parquet as pq 30 from tqdm.contrib.concurrent import thread_map 32 from .download.download_config import DownloadConfig File /opt/conda/lib/python3.10/site-packages/pyarrow/parquet/__init__.py:20 1 # Licensed to the Apache Software Foundation (ASF) under one 2 # or more contributor license agreements. See the NOTICE file 3 # distributed with this work for additional information (...) 17 18 # flake8: noqa ---> 20 from .core import * File /opt/conda/lib/python3.10/site-packages/pyarrow/parquet/core.py:33 30 import pyarrow as pa 32 try: ---> 33 import pyarrow._parquet as _parquet 34 except ImportError as exc: 35 raise ImportError( 36 "The pyarrow installation is not built with support " 37 f"for the Parquet file format ({str(exc)})" 38 ) from None File /opt/conda/lib/python3.10/site-packages/pyarrow/_parquet.pyx:1, in init pyarrow._parquet() AttributeError: module 'pyarrow.lib' has no attribute 'ListViewType' ``` setfit: 1.0.3 transformers: 4.41.2 lingua-language-detector: 2.0.2 polars: 0.20.31 lightning: None google-cloud-bigquery: 3.24.0 shapely: 2.0.4 pyarrow: 16.0.0 ### Steps to reproduce the bug I have tried all version combinations for Dataset and Pyarrow, the all have the same error since a few days ago. This is accross multiple scripts I have. ### Expected behavior Just ron normally. ### Environment info 3.10
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I_kwDODunzps6My3NC
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Convert polars DataFrame back to datasets
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-06-19T11:38:48
2024-07-01T12:48:18
null
NONE
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### Feature request This returns error. ```python from datasets import Dataset dsdf = Dataset.from_dict({"x": [[1, 2], [3, 4, 5]], "y": ["a", "b"]}) Dataset.from_polars(dsdf.to_polars()) ``` ValueError: Arrow type large_list<item: int64> does not have a datasets dtype equivalent. ### Motivation When datasets contain Sequence data type, it will be converted to Arrow type large_list. However, the reverse (from large_list to Sequence) does not work. ### Your contribution No
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Remove metrics
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[ "@albertvillanova my tests are failing here:\r\n```\r\ndataset_name = 'gooaq'\r\n\r\n def test_load_dataset(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True, use_local_dummy_data=True)\r\n\r\ntests/test_dataset_common.py:234: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:187: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\nWhen I try loading dataset on local machine it works fine. Any suggestions on how can I avoid this error?", "Thanks for the help, @albertvillanova! All tests are passing now." ]
2024-06-19T09:08:55
2024-06-28T06:57:38
2024-06-28T06:51:30
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Remove all metrics, as part of the 3.0 release. Note they are deprecated since 2.5.0 version.
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