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open	2024-02-02T10:36:49Z	null	https://api.github.com/repos/huggingface/datasets/issues/6639	null	{ "+1": 0, "-1": 0, "confused": 0, "eyes": 0, "heart": 0, "hooray": 0, "laugh": 0, "rocket": 0, "total_count": 0, "url": "https://api.github.com/repos/huggingface/datasets/issues/6639/reactions" }	true	https://api.github.com/repos/huggingface/datasets/issues/6639/labels{/name}	{ "avatar_url": "https://avatars.githubusercontent.com/u/42851186?v=4", "events_url": "https://api.github.com/users/lhoestq/events{/privacy}", "followers_url": "https://api.github.com/users/lhoestq/followers", "following_url": "https://api.github.com/users/lhoestq/following{/other_user}", "gists_url": "https://api.github.com/users/lhoestq/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/lhoestq", "id": 42851186, "login": "lhoestq", "node_id": "MDQ6VXNlcjQyODUxMTg2", "organizations_url": "https://api.github.com/users/lhoestq/orgs", "received_events_url": "https://api.github.com/users/lhoestq/received_events", "repos_url": "https://api.github.com/users/lhoestq/repos", "site_admin": false, "starred_url": "https://api.github.com/users/lhoestq/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/lhoestq/subscriptions", "type": "User", "url": "https://api.github.com/users/lhoestq" }	https://github.com/huggingface/datasets/pull/6639	[]	false	2024-02-02T10:40:47Z	null	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6639). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update." ]	null	[]	Run download_and_prepare if missing splits	MEMBER	https://api.github.com/repos/huggingface/datasets/issues/6639/timeline	A first step towards https://github.com/huggingface/datasets/issues/6529	https://api.github.com/repos/huggingface/datasets	{ "diff_url": "https://github.com/huggingface/datasets/pull/6639.diff", "html_url": "https://github.com/huggingface/datasets/pull/6639", "merged_at": null, "patch_url": "https://github.com/huggingface/datasets/pull/6639.patch", "url": "https://api.github.com/repos/huggingface/datasets/pulls/6639" }	2,114,620,200	https://api.github.com/repos/huggingface/datasets/issues/6639/comments	PR_kwDODunzps5l0KPG	null	6,639	https://api.github.com/repos/huggingface/datasets/issues/6639/events	true
closed	2024-02-01T19:41:42Z	null	https://api.github.com/repos/huggingface/datasets/issues/6638	null	{ "+1": 0, "-1": 0, "confused": 0, "eyes": 0, "heart": 0, "hooray": 0, "laugh": 0, "rocket": 0, "total_count": 0, "url": "https://api.github.com/repos/huggingface/datasets/issues/6638/reactions" }	null	https://api.github.com/repos/huggingface/datasets/issues/6638/labels{/name}	{ "avatar_url": "https://avatars.githubusercontent.com/u/81709031?v=4", "events_url": "https://api.github.com/users/vidyasiv/events{/privacy}", "followers_url": "https://api.github.com/users/vidyasiv/followers", "following_url": "https://api.github.com/users/vidyasiv/following{/other_user}", "gists_url": "https://api.github.com/users/vidyasiv/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/vidyasiv", "id": 81709031, "login": "vidyasiv", "node_id": "MDQ6VXNlcjgxNzA5MDMx", "organizations_url": "https://api.github.com/users/vidyasiv/orgs", "received_events_url": "https://api.github.com/users/vidyasiv/received_events", "repos_url": "https://api.github.com/users/vidyasiv/repos", "site_admin": false, "starred_url": "https://api.github.com/users/vidyasiv/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/vidyasiv/subscriptions", "type": "User", "url": "https://api.github.com/users/vidyasiv" }	https://github.com/huggingface/datasets/issues/6638	[]	false	2024-02-01T20:07:29Z	2024-02-01T20:07:29Z	null	[ "Looks like it works with latest datasets repository\r\n```\r\n- `datasets` version: 2.16.2.dev0\r\n- Platform: Linux-5.15.0-92-generic-x86_64-with-glibc2.29\r\n- Python version: 3.8.10\r\n- `huggingface_hub` version: 0.20.3\r\n- PyArrow version: 15.0.0\r\n- Pandas version: 2.0.1\r\n- `fsspec` version: 2023.10.0\r\n```\r\n\r\nCould you explain which is the minimum version that fixes this?\r\nEdit: Looks like that's 2.16.0, will close out issue" ]	completed	[]	Cannot download wmt16 dataset	NONE	https://api.github.com/repos/huggingface/datasets/issues/6638/timeline	### Describe the bug As of this morning (PST) 2/1/2024, seeing the wmt16 dataset is missing from opus , could you suggest an alternative? ``` Downloading data files: 0%\| \| 0/4 [00:00<?, ?it/s]Traceback (most recent call last): File "test.py", line 2, in <module> raw_datasets = load_dataset("wmt16","ro-en",split="train") File "/usr/local/lib/python3.8/dist-packages/datasets/load.py", line 2153, in load_dataset builder_instance.download_and_prepare( File "/usr/local/lib/python3.8/dist-packages/datasets/builder.py", line 954, in download_and_prepare self._download_and_prepare( File "/usr/local/lib/python3.8/dist-packages/datasets/builder.py", line 1717, in _download_and_prepare super()._download_and_prepare( File "/usr/local/lib/python3.8/dist-packages/datasets/builder.py", line 1027, in _download_and_prepare split_generators = self._split_generators(dl_manager, **split_generators_kwargs) File "/root/.cache/huggingface/modules/datasets_modules/datasets/wmt16/746749a11d25c02058042da7502d973ff410e73457f3d305fc1177dc0e8c4227/wmt_utils.py", line 754, in _split_generators downloaded_files = dl_manager.download_and_extract(urls_to_download) File "/usr/local/lib/python3.8/dist-packages/datasets/download/download_manager.py", line 565, in download_and_extract return self.extract(self.download(url_or_urls)) File "/usr/local/lib/python3.8/dist-packages/datasets/download/download_manager.py", line 428, in download downloaded_path_or_paths = map_nested( File "/usr/local/lib/python3.8/dist-packages/datasets/utils/py_utils.py", line 464, in map_nested mapped = [ File "/usr/local/lib/python3.8/dist-packages/datasets/utils/py_utils.py", line 465, in <listcomp> _single_map_nested((function, obj, types, None, True, None)) File "/usr/local/lib/python3.8/dist-packages/datasets/utils/py_utils.py", line 384, in _single_map_nested mapped = [_single_map_nested((function, v, types, None, True, None)) for v in pbar] File "/usr/local/lib/python3.8/dist-packages/datasets/utils/py_utils.py", line 384, in <listcomp> mapped = [_single_map_nested((function, v, types, None, True, None)) for v in pbar] File "/usr/local/lib/python3.8/dist-packages/datasets/utils/py_utils.py", line 367, in _single_map_nested return function(data_struct) File "/usr/local/lib/python3.8/dist-packages/datasets/download/download_manager.py", line 454, in _download return cached_path(url_or_filename, download_config=download_config) File "/usr/local/lib/python3.8/dist-packages/datasets/utils/file_utils.py", line 182, in cached_path output_path = get_from_cache( File "/usr/local/lib/python3.8/dist-packages/datasets/utils/file_utils.py", line 596, in get_from_cache raise FileNotFoundError(f"Couldn't find file at {url}") FileNotFoundError: Couldn't find file at https://opus.nlpl.eu/download.php?f=SETIMES/v2/tmx/en-ro.tmx.gz ``` ### Steps to reproduce the bug ``` from datasets import load_dataset raw_datasets = load_dataset("wmt16","ro-en",split="train") ``` ### Expected behavior Expect the dataset to be downloaded/ at least a clean exit with error explaining dataset is missing and a suggestion for next steps ### Environment info - `datasets` version: 2.14.7 - Platform: Linux-5.15.0-92-generic-x86_64-with-glibc2.29 - Python version: 3.8.10 - Huggingface_hub version: 0.17.3 - PyArrow version: 15.0.0 - Pandas version: 2.0.1	https://api.github.com/repos/huggingface/datasets	null	2,113,329,257	https://api.github.com/repos/huggingface/datasets/issues/6638/comments	I_kwDODunzps599thp	null	6,638	https://api.github.com/repos/huggingface/datasets/issues/6638/events	false
open	2024-02-01T17:16:54Z	null	https://api.github.com/repos/huggingface/datasets/issues/6637	null	{ "+1": 0, "-1": 0, "confused": 0, "eyes": 0, "heart": 0, "hooray": 0, "laugh": 0, "rocket": 0, "total_count": 0, "url": "https://api.github.com/repos/huggingface/datasets/issues/6637/reactions" }	null	https://api.github.com/repos/huggingface/datasets/issues/6637/labels{/name}	{ "avatar_url": "https://avatars.githubusercontent.com/u/22883190?v=4", "events_url": "https://api.github.com/users/tobycrisford/events{/privacy}", "followers_url": "https://api.github.com/users/tobycrisford/followers", "following_url": "https://api.github.com/users/tobycrisford/following{/other_user}", "gists_url": "https://api.github.com/users/tobycrisford/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/tobycrisford", "id": 22883190, "login": "tobycrisford", "node_id": "MDQ6VXNlcjIyODgzMTkw", "organizations_url": "https://api.github.com/users/tobycrisford/orgs", "received_events_url": "https://api.github.com/users/tobycrisford/received_events", "repos_url": "https://api.github.com/users/tobycrisford/repos", "site_admin": false, "starred_url": "https://api.github.com/users/tobycrisford/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/tobycrisford/subscriptions", "type": "User", "url": "https://api.github.com/users/tobycrisford" }	https://github.com/huggingface/datasets/issues/6637	[]	false	2024-02-01T17:16:54Z	null	null	[]	null	[]	'with_format' is extremely slow when used together with 'interleave_datasets' or 'shuffle' on IterableDatasets	NONE	https://api.github.com/repos/huggingface/datasets/issues/6637/timeline	### Describe the bug If you: 1. Interleave two iterable datasets together with the interleave_datasets function, or shuffle an iterable dataset 2. Set the output format to torch tensors with .with_format('torch') Then iterating through the dataset becomes over 100x slower than it is if you don't apply the torch formatting. ### Steps to reproduce the bug ```python import datasets import torch from tqdm import tqdm rand_a = torch.randn(3,224,224) rand_b = torch.randn(3,224,224) a = torch.stack([rand_a] * 1000) b = torch.stack([rand_b] * 1000) features = datasets.Features({"tensor": datasets.Array3D(shape=(3,224,224), dtype="float32")}) ds_a = datasets.Dataset.from_dict({"tensor": a}, features=features).to_iterable_dataset() ds_b = datasets.Dataset.from_dict({"tensor": b}, features=features).to_iterable_dataset() # Iterating through either dataset with torch formatting is really fast (2000it/s on my machine) for example in tqdm(ds_a.with_format('torch')): pass # Iterating through either dataset shuffled is also pretty fast (100it/s on my machine) for example in tqdm(ds_a.shuffle()): pass # Iterating through this interleaved dataset is pretty fast (200it/s on my machine) ds_fast = datasets.interleave_datasets([ds_a, ds_b]) for example in tqdm(ds_fast): pass # Iterating through either dataset with torch formatting after shuffling is really slow... (<2it/s on my machine) for example in tqdm(ds_a.shuffle().with_format('torch')): pass # Iterating through this torch formatted interleaved dataset is also really slow (<2it/s on my machine)... ds_slow = datasets.interleave_datasets([ds_a, ds_b]).with_format('torch') for example in tqdm(ds_slow): pass # Even doing this is way faster!! (70it/s on my machine) for example in tqdm(ds_fast): test = torch.tensor(example['tensor']) ``` ### Expected behavior Applying torch formatting to the interleaved dataset shouldn't increase the time taken to iterate through the dataset by very much, since even explicitly converting every example is over 70x faster than calling .with_format('torch'). ### Environment info - `datasets` version: 2.16.1 - Platform: Linux-6.5.0-15-generic-x86_64-with-glibc2.38 - Python version: 3.11.6 - `huggingface_hub` version: 0.20.3 - PyArrow version: 15.0.0 - Pandas version: 2.2.0 - `fsspec` version: 2023.10.0	https://api.github.com/repos/huggingface/datasets	null	2,113,025,975	https://api.github.com/repos/huggingface/datasets/issues/6637/comments	I_kwDODunzps598je3	null	6,637	https://api.github.com/repos/huggingface/datasets/issues/6637/events	false
open	2024-01-31T19:08:28Z	null	https://api.github.com/repos/huggingface/datasets/issues/6636	null	{ "+1": 0, "-1": 0, "confused": 0, "eyes": 0, "heart": 0, "hooray": 0, "laugh": 0, "rocket": 0, "total_count": 0, "url": "https://api.github.com/repos/huggingface/datasets/issues/6636/reactions" }	false	https://api.github.com/repos/huggingface/datasets/issues/6636/labels{/name}	{ "avatar_url": "https://avatars.githubusercontent.com/u/11325244?v=4", "events_url": "https://api.github.com/users/psmyth94/events{/privacy}", "followers_url": "https://api.github.com/users/psmyth94/followers", "following_url": "https://api.github.com/users/psmyth94/following{/other_user}", "gists_url": "https://api.github.com/users/psmyth94/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/psmyth94", "id": 11325244, "login": "psmyth94", "node_id": "MDQ6VXNlcjExMzI1MjQ0", "organizations_url": "https://api.github.com/users/psmyth94/orgs", "received_events_url": "https://api.github.com/users/psmyth94/received_events", "repos_url": "https://api.github.com/users/psmyth94/repos", "site_admin": false, "starred_url": "https://api.github.com/users/psmyth94/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/psmyth94/subscriptions", "type": "User", "url": "https://api.github.com/users/psmyth94" }	https://github.com/huggingface/datasets/pull/6636	[]	false	2024-02-01T20:03:27Z	null	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6636). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "Thanks @mariosasko, I made the changes. However, I did some tests with `map` and I still saw that it took ~3.5 minutes per batch on 6000 features when using `dataset.map(lambda x: x, batched=True)`. From the profile, the culprits were mainly with `ArrowWriter.write_batch` and `ArrowWriter._build_writer`. The slow down from `_build_writer` is due to updating existing features with the inferred ones. I don't think this can be optimized any further, but fortunately, I can avoid this by setting the `features` in `map`. On the other hand, `write_batch` selects cols based on intersection and difference between schema names and example keys using two for loops. The same exists in `ArrowWriter.write_examples_on_file`. Optimizing the column selection using set operations effectively brings it from 3.5 minutes per batch down to 6 seconds per batch. Can we add these changes along with this PR?" ]	null	[]	Faster column validation in set_format	NONE	https://api.github.com/repos/huggingface/datasets/issues/6636/timeline	I work with bioinformatics data and often these tables have thousands and even tens of thousands of features. These tables are also accompanied by metadata that I do not want to pass in the model. When I perform `set_format('pt', columns=large_column_list)` , it can take several minutes before it finishes. The culprit is when the following check is performed: `any(col not in self._data.column_names for col in columns)`. Replacing this by `set(columns) - (self._data.column_names)` is more efficient.	https://api.github.com/repos/huggingface/datasets	{ "diff_url": "https://github.com/huggingface/datasets/pull/6636.diff", "html_url": "https://github.com/huggingface/datasets/pull/6636", "merged_at": null, "patch_url": "https://github.com/huggingface/datasets/pull/6636.patch", "url": "https://api.github.com/repos/huggingface/datasets/pulls/6636" }	2,110,781,097	https://api.github.com/repos/huggingface/datasets/issues/6636/comments	PR_kwDODunzps5lm4zI	null	6,636	https://api.github.com/repos/huggingface/datasets/issues/6636/events	true
open	2024-01-31T17:55:21Z	null	https://api.github.com/repos/huggingface/datasets/issues/6635	null	{ "+1": 0, "-1": 0, "confused": 0, "eyes": 0, "heart": 0, "hooray": 0, "laugh": 0, "rocket": 0, "total_count": 0, "url": "https://api.github.com/repos/huggingface/datasets/issues/6635/reactions" }	true	https://api.github.com/repos/huggingface/datasets/issues/6635/labels{/name}	{ "avatar_url": "https://avatars.githubusercontent.com/u/42851186?v=4", "events_url": "https://api.github.com/users/lhoestq/events{/privacy}", "followers_url": "https://api.github.com/users/lhoestq/followers", "following_url": "https://api.github.com/users/lhoestq/following{/other_user}", "gists_url": "https://api.github.com/users/lhoestq/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/lhoestq", "id": 42851186, "login": "lhoestq", "node_id": "MDQ6VXNlcjQyODUxMTg2", "organizations_url": "https://api.github.com/users/lhoestq/orgs", "received_events_url": "https://api.github.com/users/lhoestq/received_events", "repos_url": "https://api.github.com/users/lhoestq/repos", "site_admin": false, "starred_url": "https://api.github.com/users/lhoestq/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/lhoestq/subscriptions", "type": "User", "url": "https://api.github.com/users/lhoestq" }	https://github.com/huggingface/datasets/pull/6635	[]	false	2024-01-31T17:59:34Z	null	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6635). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update." ]	null	[]	Fix missing info when loading some datasets from Parquet export	MEMBER	https://api.github.com/repos/huggingface/datasets/issues/6635/timeline	Fix getting the info for script-based datasets with Parquet export with a single config not named "default". E.g. ```python from datasets import load_dataset_builder b = load_dataset_builder("bookcorpus") print(b.info.features) # should print {'text': Value(dtype='string', id=None)} ``` I fixed this by setting the default config name when there is only one config.	https://api.github.com/repos/huggingface/datasets	{ "diff_url": "https://github.com/huggingface/datasets/pull/6635.diff", "html_url": "https://github.com/huggingface/datasets/pull/6635", "merged_at": null, "patch_url": "https://github.com/huggingface/datasets/pull/6635.patch", "url": "https://api.github.com/repos/huggingface/datasets/pulls/6635" }	2,110,659,519	https://api.github.com/repos/huggingface/datasets/issues/6635/comments	PR_kwDODunzps5lmeNO	null	6,635	https://api.github.com/repos/huggingface/datasets/issues/6635/events	true
open	2024-01-31T14:37:36Z	null	https://api.github.com/repos/huggingface/datasets/issues/6634	null	{ "+1": 0, "-1": 0, "confused": 0, "eyes": 0, "heart": 0, "hooray": 0, "laugh": 0, "rocket": 0, "total_count": 0, "url": "https://api.github.com/repos/huggingface/datasets/issues/6634/reactions" }	false	https://api.github.com/repos/huggingface/datasets/issues/6634/labels{/name}	{ "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/albertvillanova", "id": 8515462, "login": "albertvillanova", "node_id": "MDQ6VXNlcjg1MTU0NjI=", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "repos_url": "https://api.github.com/users/albertvillanova/repos", "site_admin": false, "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "type": "User", "url": "https://api.github.com/users/albertvillanova" }	https://github.com/huggingface/datasets/pull/6634	[]	false	2024-02-02T10:54:21Z	null	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6634). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "@huggingface/datasets, feel free to review this PR so that it can be included in the next release." ]	null	[]	Support data_dir parameter in push_to_hub	MEMBER	https://api.github.com/repos/huggingface/datasets/issues/6634/timeline	Support `data_dir` parameter in `push_to_hub`. This allows users to organize the data files according to their specific needs. For example, "wikimedia/wikipedia" files could be organized by year and/or date, e.g. "2024/20240101/20240101.en".	https://api.github.com/repos/huggingface/datasets	{ "diff_url": "https://github.com/huggingface/datasets/pull/6634.diff", "html_url": "https://github.com/huggingface/datasets/pull/6634", "merged_at": null, "patch_url": "https://github.com/huggingface/datasets/pull/6634.patch", "url": "https://api.github.com/repos/huggingface/datasets/pulls/6634" }	2,110,242,376	https://api.github.com/repos/huggingface/datasets/issues/6634/comments	PR_kwDODunzps5llB9a	null	6,634	https://api.github.com/repos/huggingface/datasets/issues/6634/events	true
closed	2024-01-31T13:41:54Z	null	https://api.github.com/repos/huggingface/datasets/issues/6633	null	{ "+1": 0, "-1": 0, "confused": 0, "eyes": 0, "heart": 0, "hooray": 0, "laugh": 0, "rocket": 0, "total_count": 0, "url": "https://api.github.com/repos/huggingface/datasets/issues/6633/reactions" }	false	https://api.github.com/repos/huggingface/datasets/issues/6633/labels{/name}	{ "avatar_url": "https://avatars.githubusercontent.com/u/1676121?v=4", "events_url": "https://api.github.com/users/severo/events{/privacy}", "followers_url": "https://api.github.com/users/severo/followers", "following_url": "https://api.github.com/users/severo/following{/other_user}", "gists_url": "https://api.github.com/users/severo/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/severo", "id": 1676121, "login": "severo", "node_id": "MDQ6VXNlcjE2NzYxMjE=", "organizations_url": "https://api.github.com/users/severo/orgs", "received_events_url": "https://api.github.com/users/severo/received_events", "repos_url": "https://api.github.com/users/severo/repos", "site_admin": false, "starred_url": "https://api.github.com/users/severo/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/severo/subscriptions", "type": "User", "url": "https://api.github.com/users/severo" }	https://github.com/huggingface/datasets/pull/6633	[]	false	2024-01-31T14:05:04Z	2024-01-31T13:59:01Z	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6633). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005172 / 0.011353 (-0.006181) \| 0.003694 / 0.011008 (-0.007314) \| 0.063098 / 0.038508 (0.024590) \| 0.028161 / 0.023109 (0.005052) \| 0.262288 / 0.275898 (-0.013610) \| 0.281867 / 0.323480 (-0.041613) \| 0.004088 / 0.007986 (-0.003898) \| 0.002745 / 0.004328 (-0.001583) \| 0.049071 / 0.004250 (0.044820) \| 0.040629 / 0.037052 (0.003577) \| 0.282766 / 0.258489 (0.024277) \| 0.297998 / 0.293841 (0.004157) \| 0.028057 / 0.128546 (-0.100489) \| 0.010878 / 0.075646 (-0.064768) \| 0.207410 / 0.419271 (-0.211861) \| 0.035600 / 0.043533 (-0.007933) \| 0.260157 / 0.255139 (0.005018) \| 0.273252 / 0.283200 (-0.009948) \| 0.017403 / 0.141683 (-0.124280) \| 1.150798 / 1.452155 (-0.301356) \| 1.200485 / 1.492716 (-0.292231) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.093783 / 0.018006 (0.075777) \| 0.302112 / 0.000490 (0.301622) \| 0.000225 / 0.000200 (0.000025) \| 0.000043 / 0.000054 (-0.000011) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.018254 / 0.037411 (-0.019158) \| 0.061083 / 0.014526 (0.046557) \| 0.074899 / 0.176557 (-0.101657) \| 0.119616 / 0.737135 (-0.617520) \| 0.075269 / 0.296338 (-0.221069) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.275878 / 0.215209 (0.060669) \| 2.694778 / 2.077655 (0.617123) \| 1.423810 / 1.504120 (-0.080310) \| 1.309444 / 1.541195 (-0.231750) \| 1.327898 / 1.468490 (-0.140592) \| 0.568621 / 4.584777 (-4.016155) \| 2.345849 / 3.745712 (-1.399863) \| 2.901281 / 5.269862 (-2.368580) \| 1.777959 / 4.565676 (-2.787717) \| 0.063539 / 0.424275 (-0.360736) \| 0.005011 / 0.007607 (-0.002596) \| 0.331212 / 0.226044 (0.105168) \| 3.200379 / 2.268929 (0.931451) \| 1.780766 / 55.444624 (-53.663859) \| 1.517178 / 6.876477 (-5.359299) \| 1.587307 / 2.142072 (-0.554765) \| 0.651939 / 4.805227 (-4.153288) \| 0.116646 / 6.500664 (-6.384018) \| 0.043325 / 0.075469 (-0.032144) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.996894 / 1.841788 (-0.844894) \| 11.495397 / 8.074308 (3.421089) \| 10.255784 / 10.191392 (0.064392) \| 0.129006 / 0.680424 (-0.551418) \| 0.013967 / 0.534201 (-0.520234) \| 0.284847 / 0.579283 (-0.294436) \| 0.265610 / 0.434364 (-0.168754) \| 0.320176 / 0.540337 (-0.220162) \| 0.429526 / 1.386936 (-0.957410) \|\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005582 / 0.011353 (-0.005771) \| 0.003867 / 0.011008 (-0.007142) \| 0.050416 / 0.038508 (0.011908) \| 0.030996 / 0.023109 (0.007887) \| 0.275987 / 0.275898 (0.000089) \| 0.289487 / 0.323480 (-0.033993) \| 0.005149 / 0.007986 (-0.002837) \| 0.002806 / 0.004328 (-0.001522) \| 0.049617 / 0.004250 (0.045366) \| 0.046949 / 0.037052 (0.009897) \| 0.281596 / 0.258489 (0.023107) \| 0.330948 / 0.293841 (0.037108) \| 0.049645 / 0.128546 (-0.078901) \| 0.010953 / 0.075646 (-0.064693) \| 0.058546 / 0.419271 (-0.360725) \| 0.034010 / 0.043533 (-0.009523) \| 0.270525 / 0.255139 (0.015386) \| 0.289749 / 0.283200 (0.006550) \| 0.018755 / 0.141683 (-0.122927) \| 1.163072 / 1.452155 (-0.289082) \| 1.213400 / 1.492716 (-0.279316) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.092397 / 0.018006 (0.074390) \| 0.299376 / 0.000490 (0.298886) \| 0.000211 / 0.000200 (0.000011) \| 0.000044 / 0.000054 (-0.000011) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.022496 / 0.037411 (-0.014916) \| 0.076886 / 0.014526 (0.062361) \| 0.087186 / 0.176557 (-0.089371) \| 0.126092 / 0.737135 (-0.611044) \| 0.088832 / 0.296338 (-0.207507) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.288885 / 0.215209 (0.073676) \| 2.839851 / 2.077655 (0.762196) \| 1.587556 / 1.504120 (0.083436) \| 1.470249 / 1.541195 (-0.070945) \| 1.518080 / 1.468490 (0.049590) \| 0.569646 / 4.584777 (-4.015131) \| 2.417574 / 3.745712 (-1.328138) \| 2.737368 / 5.269862 (-2.532494) \| 1.784419 / 4.565676 (-2.781257) \| 0.064104 / 0.424275 (-0.360171) \| 0.005138 / 0.007607 (-0.002469) \| 0.346214 / 0.226044 (0.120169) \| 3.439541 / 2.268929 (1.170612) \| 1.944792 / 55.444624 (-53.499832) \| 1.675762 / 6.876477 (-5.200714) \| 1.851871 / 2.142072 (-0.290201) \| 0.652932 / 4.805227 (-4.152295) \| 0.118953 / 6.500664 (-6.381711) \| 0.041011 / 0.075469 (-0.034459) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 1.017690 / 1.841788 (-0.824098) \| 12.610531 / 8.074308 (4.536223) \| 11.223165 / 10.191392 (1.031773) \| 0.131637 / 0.680424 (-0.548786) \| 0.016733 / 0.534201 (-0.517468) \| 0.288491 / 0.579283 (-0.290792) \| 0.275899 / 0.434364 (-0.158465) \| 0.331837 / 0.540337 (-0.208500) \| 0.421695 / 1.386936 (-0.965241) \|\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#5d9dfa9a8c077c783729a279623926faa9e2f3f1 \"CML watermark\")\n" ]	null	[]	dataset viewer requires no-script	CONTRIBUTOR	https://api.github.com/repos/huggingface/datasets/issues/6633/timeline	null	https://api.github.com/repos/huggingface/datasets	{ "diff_url": "https://github.com/huggingface/datasets/pull/6633.diff", "html_url": "https://github.com/huggingface/datasets/pull/6633", "merged_at": "2024-01-31T13:59:01Z", "patch_url": "https://github.com/huggingface/datasets/pull/6633.patch", "url": "https://api.github.com/repos/huggingface/datasets/pulls/6633" }	2,110,124,475	https://api.github.com/repos/huggingface/datasets/issues/6633/comments	PR_kwDODunzps5lknz9	null	6,633	https://api.github.com/repos/huggingface/datasets/issues/6633/events	true
open	2024-01-30T18:52:23Z	null	https://api.github.com/repos/huggingface/datasets/issues/6632	null	{ "+1": 0, "-1": 0, "confused": 0, "eyes": 0, "heart": 0, "hooray": 0, "laugh": 0, "rocket": 0, "total_count": 0, "url": "https://api.github.com/repos/huggingface/datasets/issues/6632/reactions" }	false	https://api.github.com/repos/huggingface/datasets/issues/6632/labels{/name}	{ "avatar_url": "https://avatars.githubusercontent.com/u/42851186?v=4", "events_url": "https://api.github.com/users/lhoestq/events{/privacy}", "followers_url": "https://api.github.com/users/lhoestq/followers", "following_url": "https://api.github.com/users/lhoestq/following{/other_user}", "gists_url": "https://api.github.com/users/lhoestq/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/lhoestq", "id": 42851186, "login": "lhoestq", "node_id": "MDQ6VXNlcjQyODUxMTg2", "organizations_url": "https://api.github.com/users/lhoestq/orgs", "received_events_url": "https://api.github.com/users/lhoestq/received_events", "repos_url": "https://api.github.com/users/lhoestq/repos", "site_admin": false, "starred_url": "https://api.github.com/users/lhoestq/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/lhoestq/subscriptions", "type": "User", "url": "https://api.github.com/users/lhoestq" }	https://github.com/huggingface/datasets/pull/6632	[]	false	2024-02-02T10:00:42Z	null	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6632). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update." ]	null	[]	Fix reload cache with data dir	MEMBER	https://api.github.com/repos/huggingface/datasets/issues/6632/timeline	The cache used to only check for the latest cache directory with a given config_name, but it was wrong (e.g. `default-data_dir=data%2Ffortran-data_dir=data%2Ffortran` instead of `default-data_dir=data%2Ffortran`) I fixed this by not passing the `config_kwargs` to the parent Builder `__init__`, and passing the config_id forged from the `config_kwargs` directly close https://github.com/huggingface/datasets/issues/6609	https://api.github.com/repos/huggingface/datasets	{ "diff_url": "https://github.com/huggingface/datasets/pull/6632.diff", "html_url": "https://github.com/huggingface/datasets/pull/6632", "merged_at": null, "patch_url": "https://github.com/huggingface/datasets/pull/6632.patch", "url": "https://api.github.com/repos/huggingface/datasets/pulls/6632" }	2,108,541,678	https://api.github.com/repos/huggingface/datasets/issues/6632/comments	PR_kwDODunzps5lfPuk	null	6,632	https://api.github.com/repos/huggingface/datasets/issues/6632/events	true
closed	2024-01-30T12:56:01Z	null	https://api.github.com/repos/huggingface/datasets/issues/6631	null	{ "+1": 0, "-1": 0, "confused": 0, "eyes": 0, "heart": 0, "hooray": 0, "laugh": 0, "rocket": 0, "total_count": 0, "url": "https://api.github.com/repos/huggingface/datasets/issues/6631/reactions" }	false	https://api.github.com/repos/huggingface/datasets/issues/6631/labels{/name}	{ "avatar_url": "https://avatars.githubusercontent.com/u/42851186?v=4", "events_url": "https://api.github.com/users/lhoestq/events{/privacy}", "followers_url": "https://api.github.com/users/lhoestq/followers", "following_url": "https://api.github.com/users/lhoestq/following{/other_user}", "gists_url": "https://api.github.com/users/lhoestq/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/lhoestq", "id": 42851186, "login": "lhoestq", "node_id": "MDQ6VXNlcjQyODUxMTg2", "organizations_url": "https://api.github.com/users/lhoestq/orgs", "received_events_url": "https://api.github.com/users/lhoestq/received_events", "repos_url": "https://api.github.com/users/lhoestq/repos", "site_admin": false, "starred_url": "https://api.github.com/users/lhoestq/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/lhoestq/subscriptions", "type": "User", "url": "https://api.github.com/users/lhoestq" }	https://github.com/huggingface/datasets/pull/6631	[]	false	2024-01-30T15:34:49Z	2024-01-30T15:28:37Z	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6631). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005076 / 0.011353 (-0.006277) \| 0.003665 / 0.011008 (-0.007343) \| 0.063602 / 0.038508 (0.025094) \| 0.029103 / 0.023109 (0.005993) \| 0.233133 / 0.275898 (-0.042765) \| 0.257000 / 0.323480 (-0.066480) \| 0.003059 / 0.007986 (-0.004926) \| 0.004007 / 0.004328 (-0.000321) \| 0.049804 / 0.004250 (0.045553) \| 0.039946 / 0.037052 (0.002893) \| 0.248003 / 0.258489 (-0.010486) \| 0.272729 / 0.293841 (-0.021112) \| 0.027542 / 0.128546 (-0.101004) \| 0.010745 / 0.075646 (-0.064901) \| 0.207686 / 0.419271 (-0.211586) \| 0.035438 / 0.043533 (-0.008095) \| 0.236864 / 0.255139 (-0.018275) \| 0.258610 / 0.283200 (-0.024590) \| 0.017225 / 0.141683 (-0.124458) \| 1.130894 / 1.452155 (-0.321261) \| 1.171266 / 1.492716 (-0.321450) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.092532 / 0.018006 (0.074525) \| 0.301650 / 0.000490 (0.301161) \| 0.000216 / 0.000200 (0.000016) \| 0.000045 / 0.000054 (-0.000010) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.018175 / 0.037411 (-0.019237) \| 0.061538 / 0.014526 (0.047012) \| 0.073673 / 0.176557 (-0.102884) \| 0.120676 / 0.737135 (-0.616460) \| 0.074753 / 0.296338 (-0.221586) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.283625 / 0.215209 (0.068416) \| 2.794903 / 2.077655 (0.717248) \| 1.485149 / 1.504120 (-0.018970) \| 1.361154 / 1.541195 (-0.180041) \| 1.371436 / 1.468490 (-0.097054) \| 0.580401 / 4.584777 (-4.004376) \| 2.457068 / 3.745712 (-1.288644) \| 2.760878 / 5.269862 (-2.508984) \| 1.725507 / 4.565676 (-2.840169) \| 0.063632 / 0.424275 (-0.360644) \| 0.005036 / 0.007607 (-0.002572) \| 0.337167 / 0.226044 (0.111122) \| 3.314508 / 2.268929 (1.045579) \| 1.863412 / 55.444624 (-53.581213) \| 1.621966 / 6.876477 (-5.254511) \| 1.600422 / 2.142072 (-0.541651) \| 0.647753 / 4.805227 (-4.157475) \| 0.117169 / 6.500664 (-6.383495) \| 0.042338 / 0.075469 (-0.033131) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.981818 / 1.841788 (-0.859969) \| 12.044657 / 8.074308 (3.970349) \| 10.654091 / 10.191392 (0.462699) \| 0.130693 / 0.680424 (-0.549731) \| 0.014733 / 0.534201 (-0.519468) \| 0.317432 / 0.579283 (-0.261851) \| 0.267196 / 0.434364 (-0.167168) \| 0.329310 / 0.540337 (-0.211028) \| 0.433379 / 1.386936 (-0.953557) \|\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005502 / 0.011353 (-0.005851) \| 0.003951 / 0.011008 (-0.007057) \| 0.050651 / 0.038508 (0.012143) \| 0.031802 / 0.023109 (0.008693) \| 0.281384 / 0.275898 (0.005485) \| 0.303900 / 0.323480 (-0.019580) \| 0.004451 / 0.007986 (-0.003534) \| 0.002801 / 0.004328 (-0.001527) \| 0.048688 / 0.004250 (0.044438) \| 0.044717 / 0.037052 (0.007664) \| 0.295017 / 0.258489 (0.036528) \| 0.328003 / 0.293841 (0.034162) \| 0.048421 / 0.128546 (-0.080125) \| 0.011254 / 0.075646 (-0.064392) \| 0.058223 / 0.419271 (-0.361048) \| 0.033915 / 0.043533 (-0.009618) \| 0.279893 / 0.255139 (0.024754) \| 0.297605 / 0.283200 (0.014405) \| 0.017115 / 0.141683 (-0.124568) \| 1.146966 / 1.452155 (-0.305189) \| 1.191650 / 1.492716 (-0.301066) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.092524 / 0.018006 (0.074518) \| 0.309332 / 0.000490 (0.308842) \| 0.000212 / 0.000200 (0.000012) \| 0.000044 / 0.000054 (-0.000011) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.022265 / 0.037411 (-0.015146) \| 0.075732 / 0.014526 (0.061206) \| 0.087340 / 0.176557 (-0.089217) \| 0.126079 / 0.737135 (-0.611056) \| 0.090349 / 0.296338 (-0.205990) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.288882 / 0.215209 (0.073673) \| 2.833046 / 2.077655 (0.755392) \| 1.602905 / 1.504120 (0.098785) \| 1.473110 / 1.541195 (-0.068085) \| 1.491300 / 1.468490 (0.022810) \| 0.557799 / 4.584777 (-4.026978) \| 2.439526 / 3.745712 (-1.306186) \| 2.669336 / 5.269862 (-2.600526) \| 1.719472 / 4.565676 (-2.846204) \| 0.062456 / 0.424275 (-0.361819) \| 0.005058 / 0.007607 (-0.002549) \| 0.343706 / 0.226044 (0.117662) \| 3.422397 / 2.268929 (1.153469) \| 1.983679 / 55.444624 (-53.460946) \| 1.673784 / 6.876477 (-5.202693) \| 1.785144 / 2.142072 (-0.356928) \| 0.643127 / 4.805227 (-4.162100) \| 0.115254 / 6.500664 (-6.385410) \| 0.041235 / 0.075469 (-0.034235) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 1.005448 / 1.841788 (-0.836340) \| 12.240100 / 8.074308 (4.165792) \| 11.051965 / 10.191392 (0.860573) \| 0.130438 / 0.680424 (-0.549986) \| 0.015918 / 0.534201 (-0.518283) \| 0.287468 / 0.579283 (-0.291815) \| 0.287699 / 0.434364 (-0.146665) \| 0.324561 / 0.540337 (-0.215777) \| 0.418820 / 1.386936 (-0.968116) \|\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#237a2a688155e23cfbcdfadd2d491ce1667fa494 \"CML watermark\")\n" ]	null	[]	Fix filelock: use current umask for filelock >= 3.10	MEMBER	https://api.github.com/repos/huggingface/datasets/issues/6631/timeline	reported in https://github.com/huggingface/evaluate/issues/542 cc @stas00 @williamberrios close https://github.com/huggingface/datasets/issues/6589	https://api.github.com/repos/huggingface/datasets	{ "diff_url": "https://github.com/huggingface/datasets/pull/6631.diff", "html_url": "https://github.com/huggingface/datasets/pull/6631", "merged_at": "2024-01-30T15:28:37Z", "patch_url": "https://github.com/huggingface/datasets/pull/6631.patch", "url": "https://api.github.com/repos/huggingface/datasets/pulls/6631" }	2,107,802,473	https://api.github.com/repos/huggingface/datasets/issues/6631/comments	PR_kwDODunzps5lcu9A	null	6,631	https://api.github.com/repos/huggingface/datasets/issues/6631/events	true
closed	2024-01-29T21:35:55Z	null	https://api.github.com/repos/huggingface/datasets/issues/6630	null	{ "+1": 0, "-1": 0, "confused": 0, "eyes": 0, "heart": 0, "hooray": 0, "laugh": 0, "rocket": 0, "total_count": 0, "url": "https://api.github.com/repos/huggingface/datasets/issues/6630/reactions" }	false	https://api.github.com/repos/huggingface/datasets/issues/6630/labels{/name}	{ "avatar_url": "https://avatars.githubusercontent.com/u/27844407?v=4", "events_url": "https://api.github.com/users/ringohoffman/events{/privacy}", "followers_url": "https://api.github.com/users/ringohoffman/followers", "following_url": "https://api.github.com/users/ringohoffman/following{/other_user}", "gists_url": "https://api.github.com/users/ringohoffman/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/ringohoffman", "id": 27844407, "login": "ringohoffman", "node_id": "MDQ6VXNlcjI3ODQ0NDA3", "organizations_url": "https://api.github.com/users/ringohoffman/orgs", "received_events_url": "https://api.github.com/users/ringohoffman/received_events", "repos_url": "https://api.github.com/users/ringohoffman/repos", "site_admin": false, "starred_url": "https://api.github.com/users/ringohoffman/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/ringohoffman/subscriptions", "type": "User", "url": "https://api.github.com/users/ringohoffman" }	https://github.com/huggingface/datasets/pull/6630	[]	false	2024-01-30T16:19:45Z	2024-01-30T15:12:25Z	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6630). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "Hmm these errors look pretty weird... can they be retried?", "Hi, thanks for working on this! To fix the errors, you also need to update [this file](https://github.com/huggingface/datasets/blob/main/src/datasets/utils/_dill.py) (by adding `version.parse(\"0.3.8\").release` to the lists)", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005068 / 0.011353 (-0.006285) \| 0.003657 / 0.011008 (-0.007351) \| 0.062914 / 0.038508 (0.024406) \| 0.027965 / 0.023109 (0.004855) \| 0.241804 / 0.275898 (-0.034094) \| 0.268069 / 0.323480 (-0.055411) \| 0.004066 / 0.007986 (-0.003920) \| 0.002704 / 0.004328 (-0.001624) \| 0.048745 / 0.004250 (0.044495) \| 0.042158 / 0.037052 (0.005106) \| 0.257670 / 0.258489 (-0.000819) \| 0.279419 / 0.293841 (-0.014422) \| 0.027193 / 0.128546 (-0.101353) \| 0.010379 / 0.075646 (-0.065267) \| 0.207009 / 0.419271 (-0.212262) \| 0.035494 / 0.043533 (-0.008039) \| 0.246025 / 0.255139 (-0.009114) \| 0.265906 / 0.283200 (-0.017294) \| 0.017335 / 0.141683 (-0.124348) \| 1.134052 / 1.452155 (-0.318103) \| 1.184668 / 1.492716 (-0.308049) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.093137 / 0.018006 (0.075130) \| 0.302279 / 0.000490 (0.301789) \| 0.000210 / 0.000200 (0.000010) \| 0.000047 / 0.000054 (-0.000008) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.018190 / 0.037411 (-0.019221) \| 0.061436 / 0.014526 (0.046910) \| 0.073102 / 0.176557 (-0.103454) \| 0.119782 / 0.737135 (-0.617354) \| 0.074292 / 0.296338 (-0.222046) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.285905 / 0.215209 (0.070696) \| 2.809051 / 2.077655 (0.731397) \| 1.470305 / 1.504120 (-0.033814) \| 1.350457 / 1.541195 (-0.190738) \| 1.349111 / 1.468490 (-0.119379) \| 0.568277 / 4.584777 (-4.016500) \| 2.353046 / 3.745712 (-1.392666) \| 2.805862 / 5.269862 (-2.463999) \| 1.750275 / 4.565676 (-2.815401) \| 0.062370 / 0.424275 (-0.361905) \| 0.004954 / 0.007607 (-0.002653) \| 0.335609 / 0.226044 (0.109564) \| 3.367200 / 2.268929 (1.098271) \| 1.829431 / 55.444624 (-53.615193) \| 1.545093 / 6.876477 (-5.331384) \| 1.571107 / 2.142072 (-0.570966) \| 0.640279 / 4.805227 (-4.164949) \| 0.116209 / 6.500664 (-6.384455) \| 0.042308 / 0.075469 (-0.033161) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.982972 / 1.841788 (-0.858816) \| 11.424370 / 8.074308 (3.350062) \| 10.427111 / 10.191392 (0.235719) \| 0.129477 / 0.680424 (-0.550946) \| 0.014166 / 0.534201 (-0.520035) \| 0.287597 / 0.579283 (-0.291686) \| 0.265588 / 0.434364 (-0.168776) \| 0.324007 / 0.540337 (-0.216330) \| 0.430766 / 1.386936 (-0.956170) \|\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005347 / 0.011353 (-0.006005) \| 0.003733 / 0.011008 (-0.007275) \| 0.049520 / 0.038508 (0.011011) \| 0.031177 / 0.023109 (0.008068) \| 0.281854 / 0.275898 (0.005956) \| 0.300937 / 0.323480 (-0.022543) \| 0.004385 / 0.007986 (-0.003601) \| 0.002841 / 0.004328 (-0.001488) \| 0.048661 / 0.004250 (0.044411) \| 0.044258 / 0.037052 (0.007205) \| 0.295651 / 0.258489 (0.037162) \| 0.322872 / 0.293841 (0.029031) \| 0.048924 / 0.128546 (-0.079622) \| 0.010742 / 0.075646 (-0.064905) \| 0.059327 / 0.419271 (-0.359944) \| 0.033938 / 0.043533 (-0.009595) \| 0.282235 / 0.255139 (0.027096) \| 0.297432 / 0.283200 (0.014233) \| 0.018295 / 0.141683 (-0.123388) \| 1.164459 / 1.452155 (-0.287696) \| 1.214511 / 1.492716 (-0.278205) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.091441 / 0.018006 (0.073435) \| 0.303023 / 0.000490 (0.302533) \| 0.000211 / 0.000200 (0.000011) \| 0.000051 / 0.000054 (-0.000004) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.022024 / 0.037411 (-0.015388) \| 0.075570 / 0.014526 (0.061044) \| 0.086761 / 0.176557 (-0.089796) \| 0.126437 / 0.737135 (-0.610698) \| 0.088354 / 0.296338 (-0.207984) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.289360 / 0.215209 (0.074151) \| 2.816433 / 2.077655 (0.738779) \| 1.561442 / 1.504120 (0.057322) \| 1.438168 / 1.541195 (-0.103027) \| 1.453398 / 1.468490 (-0.015092) \| 0.579474 / 4.584777 (-4.005303) \| 2.458640 / 3.745712 (-1.287072) \| 2.638572 / 5.269862 (-2.631290) \| 1.725218 / 4.565676 (-2.840458) \| 0.063550 / 0.424275 (-0.360725) \| 0.005220 / 0.007607 (-0.002387) \| 0.338883 / 0.226044 (0.112838) \| 3.353585 / 2.268929 (1.084656) \| 1.913186 / 55.444624 (-53.531438) \| 1.667445 / 6.876477 (-5.209032) \| 1.740085 / 2.142072 (-0.401987) \| 0.646369 / 4.805227 (-4.158859) \| 0.116737 / 6.500664 (-6.383927) \| 0.041052 / 0.075469 (-0.034417) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 1.023180 / 1.841788 (-0.818608) \| 12.078398 / 8.074308 (4.004090) \| 10.952012 / 10.191392 (0.760620) \| 0.131335 / 0.680424 (-0.549089) \| 0.015701 / 0.534201 (-0.518499) \| 0.289709 / 0.579283 (-0.289574) \| 0.270495 / 0.434364 (-0.163869) \| 0.331773 / 0.540337 (-0.208565) \| 0.417660 / 1.386936 (-0.969276) \|\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#3b21d74f5c0ab8a85838af04de8ad85e71b0ac4f \"CML watermark\")\n" ]	null	[]	Bump max range of dill to 0.3.8	CONTRIBUTOR	https://api.github.com/repos/huggingface/datasets/issues/6630/timeline	Release on Jan 27, 2024: https://pypi.org/project/dill/0.3.8/#history	https://api.github.com/repos/huggingface/datasets	{ "diff_url": "https://github.com/huggingface/datasets/pull/6630.diff", "html_url": "https://github.com/huggingface/datasets/pull/6630", "merged_at": "2024-01-30T15:12:25Z", "patch_url": "https://github.com/huggingface/datasets/pull/6630.patch", "url": "https://api.github.com/repos/huggingface/datasets/pulls/6630" }	2,106,478,275	https://api.github.com/repos/huggingface/datasets/issues/6630/comments	PR_kwDODunzps5lYPi3	null	6,630	https://api.github.com/repos/huggingface/datasets/issues/6630/events	true
open	2024-01-29T15:36:52Z	null	https://api.github.com/repos/huggingface/datasets/issues/6629	null	{ "+1": 1, "-1": 0, "confused": 0, "eyes": 0, "heart": 0, "hooray": 0, "laugh": 0, "rocket": 0, "total_count": 1, "url": "https://api.github.com/repos/huggingface/datasets/issues/6629/reactions" }	false	https://api.github.com/repos/huggingface/datasets/issues/6629/labels{/name}	{ "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/albertvillanova", "id": 8515462, "login": "albertvillanova", "node_id": "MDQ6VXNlcjg1MTU0NjI=", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "repos_url": "https://api.github.com/users/albertvillanova/repos", "site_admin": false, "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "type": "User", "url": "https://api.github.com/users/albertvillanova" }	https://github.com/huggingface/datasets/pull/6629	[]	false	2024-02-02T10:54:11Z	null	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6629). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "@huggingface/datasets, feel free to review this PR so that it can be included in the next release." ]	null	[]	Support push_to_hub without org/user to default to logged-in user	MEMBER	https://api.github.com/repos/huggingface/datasets/issues/6629/timeline	This behavior is aligned with: - the behavior of `datasets` before merging #6519 - the behavior described in the corresponding docstring - the behavior of `huggingface_hub.create_repo` Revert "Support push_to_hub canonical datasets (#6519)" - This reverts commit a887ee78835573f5d80f9e414e8443b4caff3541. Fix #6597.	https://api.github.com/repos/huggingface/datasets	{ "diff_url": "https://github.com/huggingface/datasets/pull/6629.diff", "html_url": "https://github.com/huggingface/datasets/pull/6629", "merged_at": null, "patch_url": "https://github.com/huggingface/datasets/pull/6629.patch", "url": "https://api.github.com/repos/huggingface/datasets/pulls/6629" }	2,105,774,482	https://api.github.com/repos/huggingface/datasets/issues/6629/comments	PR_kwDODunzps5lV0aF	null	6,629	https://api.github.com/repos/huggingface/datasets/issues/6629/events	true
open	2024-01-29T15:30:09Z	null	https://api.github.com/repos/huggingface/datasets/issues/6628	null	{ "+1": 0, "-1": 0, "confused": 0, "eyes": 0, "heart": 0, "hooray": 0, "laugh": 0, "rocket": 0, "total_count": 0, "url": "https://api.github.com/repos/huggingface/datasets/issues/6628/reactions" }	false	https://api.github.com/repos/huggingface/datasets/issues/6628/labels{/name}	{ "avatar_url": "https://avatars.githubusercontent.com/u/8515462?v=4", "events_url": "https://api.github.com/users/albertvillanova/events{/privacy}", "followers_url": "https://api.github.com/users/albertvillanova/followers", "following_url": "https://api.github.com/users/albertvillanova/following{/other_user}", "gists_url": "https://api.github.com/users/albertvillanova/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/albertvillanova", "id": 8515462, "login": "albertvillanova", "node_id": "MDQ6VXNlcjg1MTU0NjI=", "organizations_url": "https://api.github.com/users/albertvillanova/orgs", "received_events_url": "https://api.github.com/users/albertvillanova/received_events", "repos_url": "https://api.github.com/users/albertvillanova/repos", "site_admin": false, "starred_url": "https://api.github.com/users/albertvillanova/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/albertvillanova/subscriptions", "type": "User", "url": "https://api.github.com/users/albertvillanova" }	https://github.com/huggingface/datasets/pull/6628	[]	false	2024-02-02T10:54:06Z	null	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6628). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "@huggingface/datasets, feel free to review this PR so that it can be included in the next release." ]	null	[]	Make CLI test support multi-processing	MEMBER	https://api.github.com/repos/huggingface/datasets/issues/6628/timeline	Support passing `--num_proc` to CLI test. This was really useful recently to run the command on `pubmed`: https://huggingface.co/datasets/pubmed/discussions/11	https://api.github.com/repos/huggingface/datasets	{ "diff_url": "https://github.com/huggingface/datasets/pull/6628.diff", "html_url": "https://github.com/huggingface/datasets/pull/6628", "merged_at": null, "patch_url": "https://github.com/huggingface/datasets/pull/6628.patch", "url": "https://api.github.com/repos/huggingface/datasets/pulls/6628" }	2,105,760,502	https://api.github.com/repos/huggingface/datasets/issues/6628/comments	PR_kwDODunzps5lVxXU	null	6,628	https://api.github.com/repos/huggingface/datasets/issues/6628/events	true
closed	2024-01-29T15:18:21Z	null	https://api.github.com/repos/huggingface/datasets/issues/6627	null	{ "+1": 0, "-1": 0, "confused": 0, "eyes": 0, "heart": 0, "hooray": 0, "laugh": 0, "rocket": 0, "total_count": 0, "url": "https://api.github.com/repos/huggingface/datasets/issues/6627/reactions" }	false	https://api.github.com/repos/huggingface/datasets/issues/6627/labels{/name}	{ "avatar_url": "https://avatars.githubusercontent.com/u/47462742?v=4", "events_url": "https://api.github.com/users/mariosasko/events{/privacy}", "followers_url": "https://api.github.com/users/mariosasko/followers", "following_url": "https://api.github.com/users/mariosasko/following{/other_user}", "gists_url": "https://api.github.com/users/mariosasko/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/mariosasko", "id": 47462742, "login": "mariosasko", "node_id": "MDQ6VXNlcjQ3NDYyNzQy", "organizations_url": "https://api.github.com/users/mariosasko/orgs", "received_events_url": "https://api.github.com/users/mariosasko/received_events", "repos_url": "https://api.github.com/users/mariosasko/repos", "site_admin": false, "starred_url": "https://api.github.com/users/mariosasko/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/mariosasko/subscriptions", "type": "User", "url": "https://api.github.com/users/mariosasko" }	https://github.com/huggingface/datasets/pull/6627	[]	false	2024-01-29T15:47:34Z	2024-01-29T15:41:32Z	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6627). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.004944 / 0.011353 (-0.006409) \| 0.003279 / 0.011008 (-0.007729) \| 0.063041 / 0.038508 (0.024533) \| 0.029888 / 0.023109 (0.006779) \| 0.259138 / 0.275898 (-0.016760) \| 0.276907 / 0.323480 (-0.046573) \| 0.004015 / 0.007986 (-0.003970) \| 0.002647 / 0.004328 (-0.001682) \| 0.048944 / 0.004250 (0.044693) \| 0.039412 / 0.037052 (0.002360) \| 0.278069 / 0.258489 (0.019580) \| 0.299139 / 0.293841 (0.005298) \| 0.027272 / 0.128546 (-0.101274) \| 0.010445 / 0.075646 (-0.065202) \| 0.206925 / 0.419271 (-0.212347) \| 0.035589 / 0.043533 (-0.007944) \| 0.256805 / 0.255139 (0.001666) \| 0.275128 / 0.283200 (-0.008072) \| 0.017888 / 0.141683 (-0.123795) \| 1.136983 / 1.452155 (-0.315172) \| 1.167495 / 1.492716 (-0.325222) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.088167 / 0.018006 (0.070161) \| 0.297360 / 0.000490 (0.296871) \| 0.000231 / 0.000200 (0.000031) \| 0.000049 / 0.000054 (-0.000006) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.018114 / 0.037411 (-0.019297) \| 0.061217 / 0.014526 (0.046691) \| 0.072269 / 0.176557 (-0.104288) \| 0.120607 / 0.737135 (-0.616528) \| 0.073517 / 0.296338 (-0.222822) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.282580 / 0.215209 (0.067371) \| 2.758650 / 2.077655 (0.680995) \| 1.425125 / 1.504120 (-0.078995) \| 1.303182 / 1.541195 (-0.238013) \| 1.341035 / 1.468490 (-0.127455) \| 0.549485 / 4.584777 (-4.035292) \| 2.346297 / 3.745712 (-1.399415) \| 2.686457 / 5.269862 (-2.583405) \| 1.684789 / 4.565676 (-2.880888) \| 0.061279 / 0.424275 (-0.362996) \| 0.004902 / 0.007607 (-0.002705) \| 0.333089 / 0.226044 (0.107044) \| 3.297016 / 2.268929 (1.028087) \| 1.765614 / 55.444624 (-53.679010) \| 1.499314 / 6.876477 (-5.377162) \| 1.501275 / 2.142072 (-0.640797) \| 0.619039 / 4.805227 (-4.186189) \| 0.114284 / 6.500664 (-6.386380) \| 0.041481 / 0.075469 (-0.033988) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.973924 / 1.841788 (-0.867863) \| 11.268266 / 8.074308 (3.193958) \| 10.304738 / 10.191392 (0.113346) \| 0.129297 / 0.680424 (-0.551127) \| 0.014894 / 0.534201 (-0.519307) \| 0.287658 / 0.579283 (-0.291626) \| 0.266476 / 0.434364 (-0.167888) \| 0.322199 / 0.540337 (-0.218138) \| 0.419568 / 1.386936 (-0.967368) \|\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005220 / 0.011353 (-0.006133) \| 0.003310 / 0.011008 (-0.007698) \| 0.049707 / 0.038508 (0.011199) \| 0.031148 / 0.023109 (0.008039) \| 0.284644 / 0.275898 (0.008746) \| 0.302767 / 0.323480 (-0.020712) \| 0.004245 / 0.007986 (-0.003740) \| 0.002677 / 0.004328 (-0.001651) \| 0.049870 / 0.004250 (0.045620) \| 0.043922 / 0.037052 (0.006870) \| 0.294955 / 0.258489 (0.036466) \| 0.322144 / 0.293841 (0.028303) \| 0.047211 / 0.128546 (-0.081336) \| 0.010492 / 0.075646 (-0.065155) \| 0.058152 / 0.419271 (-0.361120) \| 0.033508 / 0.043533 (-0.010025) \| 0.281266 / 0.255139 (0.026127) \| 0.300010 / 0.283200 (0.016810) \| 0.017616 / 0.141683 (-0.124067) \| 1.124658 / 1.452155 (-0.327496) \| 1.167222 / 1.492716 (-0.325495) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.089085 / 0.018006 (0.071079) \| 0.297912 / 0.000490 (0.297423) \| 0.000211 / 0.000200 (0.000011) \| 0.000056 / 0.000054 (0.000002) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.021669 / 0.037411 (-0.015742) \| 0.075648 / 0.014526 (0.061123) \| 0.086054 / 0.176557 (-0.090503) \| 0.125236 / 0.737135 (-0.611899) \| 0.088146 / 0.296338 (-0.208192) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.295238 / 0.215209 (0.080029) \| 2.870002 / 2.077655 (0.792347) \| 1.582534 / 1.504120 (0.078414) \| 1.466710 / 1.541195 (-0.074485) \| 1.475352 / 1.468490 (0.006861) \| 0.554745 / 4.584777 (-4.030032) \| 2.412533 / 3.745712 (-1.333179) \| 2.583863 / 5.269862 (-2.685999) \| 1.689124 / 4.565676 (-2.876552) \| 0.061353 / 0.424275 (-0.362922) \| 0.005015 / 0.007607 (-0.002592) \| 0.338733 / 0.226044 (0.112688) \| 3.356710 / 2.268929 (1.087781) \| 1.932143 / 55.444624 (-53.512481) \| 1.660081 / 6.876477 (-5.216396) \| 1.764961 / 2.142072 (-0.377111) \| 0.640002 / 4.805227 (-4.165225) \| 0.115251 / 6.500664 (-6.385413) \| 0.040627 / 0.075469 (-0.034842) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.992296 / 1.841788 (-0.849492) \| 11.821259 / 8.074308 (3.746951) \| 10.715570 / 10.191392 (0.524178) \| 0.142934 / 0.680424 (-0.537489) \| 0.015680 / 0.534201 (-0.518521) \| 0.287435 / 0.579283 (-0.291848) \| 0.276817 / 0.434364 (-0.157547) \| 0.327823 / 0.540337 (-0.212515) \| 0.413404 / 1.386936 (-0.973532) \|\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#82c78b614d34ee42180d35a882875a28d6281db0 \"CML watermark\")\n" ]	null	[]	Disable `tqdm` bars in non-interactive environments	CONTRIBUTOR	https://api.github.com/repos/huggingface/datasets/issues/6627/timeline	Replace `disable=False` with `disable=None` in the `tqdm` bars to disable them in non-interactive environments (by default). For more info, see a [similar PR](https://github.com/huggingface/huggingface_hub/pull/2000) in `huggingface_hub`.	https://api.github.com/repos/huggingface/datasets	{ "diff_url": "https://github.com/huggingface/datasets/pull/6627.diff", "html_url": "https://github.com/huggingface/datasets/pull/6627", "merged_at": "2024-01-29T15:41:32Z", "patch_url": "https://github.com/huggingface/datasets/pull/6627.patch", "url": "https://api.github.com/repos/huggingface/datasets/pulls/6627" }	2,105,735,816	https://api.github.com/repos/huggingface/datasets/issues/6627/comments	PR_kwDODunzps5lVr-t	null	6,627	https://api.github.com/repos/huggingface/datasets/issues/6627/events	true
closed	2024-01-29T13:17:41Z	null	https://api.github.com/repos/huggingface/datasets/issues/6626	null	{ "+1": 0, "-1": 0, "confused": 0, "eyes": 0, "heart": 1, "hooray": 0, "laugh": 0, "rocket": 0, "total_count": 1, "url": "https://api.github.com/repos/huggingface/datasets/issues/6626/reactions" }	false	https://api.github.com/repos/huggingface/datasets/issues/6626/labels{/name}	{ "avatar_url": "https://avatars.githubusercontent.com/u/42851186?v=4", "events_url": "https://api.github.com/users/lhoestq/events{/privacy}", "followers_url": "https://api.github.com/users/lhoestq/followers", "following_url": "https://api.github.com/users/lhoestq/following{/other_user}", "gists_url": "https://api.github.com/users/lhoestq/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/lhoestq", "id": 42851186, "login": "lhoestq", "node_id": "MDQ6VXNlcjQyODUxMTg2", "organizations_url": "https://api.github.com/users/lhoestq/orgs", "received_events_url": "https://api.github.com/users/lhoestq/received_events", "repos_url": "https://api.github.com/users/lhoestq/repos", "site_admin": false, "starred_url": "https://api.github.com/users/lhoestq/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/lhoestq/subscriptions", "type": "User", "url": "https://api.github.com/users/lhoestq" }	https://github.com/huggingface/datasets/pull/6626	[]	false	2024-01-29T15:18:25Z	2024-01-29T15:12:18Z	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6626). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005085 / 0.011353 (-0.006268) \| 0.003592 / 0.011008 (-0.007417) \| 0.062591 / 0.038508 (0.024083) \| 0.031063 / 0.023109 (0.007954) \| 0.247029 / 0.275898 (-0.028869) \| 0.273706 / 0.323480 (-0.049774) \| 0.004034 / 0.007986 (-0.003951) \| 0.002672 / 0.004328 (-0.001657) \| 0.048407 / 0.004250 (0.044156) \| 0.049229 / 0.037052 (0.012177) \| 0.264316 / 0.258489 (0.005827) \| 0.284953 / 0.293841 (-0.008888) \| 0.027712 / 0.128546 (-0.100834) \| 0.010619 / 0.075646 (-0.065027) \| 0.210017 / 0.419271 (-0.209254) \| 0.035636 / 0.043533 (-0.007897) \| 0.252830 / 0.255139 (-0.002309) \| 0.278772 / 0.283200 (-0.004428) \| 0.017356 / 0.141683 (-0.124326) \| 1.140202 / 1.452155 (-0.311953) \| 1.204807 / 1.492716 (-0.287909) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.089130 / 0.018006 (0.071123) \| 0.300115 / 0.000490 (0.299626) \| 0.000213 / 0.000200 (0.000013) \| 0.000042 / 0.000054 (-0.000012) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.018352 / 0.037411 (-0.019059) \| 0.061431 / 0.014526 (0.046905) \| 0.073911 / 0.176557 (-0.102646) \| 0.121230 / 0.737135 (-0.615906) \| 0.074867 / 0.296338 (-0.221471) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.282272 / 0.215209 (0.067063) \| 2.737413 / 2.077655 (0.659759) \| 1.446651 / 1.504120 (-0.057469) \| 1.319686 / 1.541195 (-0.221508) \| 1.327479 / 1.468490 (-0.141011) \| 0.558003 / 4.584777 (-4.026774) \| 2.361623 / 3.745712 (-1.384089) \| 2.770436 / 5.269862 (-2.499425) \| 1.703450 / 4.565676 (-2.862227) \| 0.062034 / 0.424275 (-0.362241) \| 0.005070 / 0.007607 (-0.002537) \| 0.337265 / 0.226044 (0.111221) \| 3.299438 / 2.268929 (1.030509) \| 1.781273 / 55.444624 (-53.663351) \| 1.512743 / 6.876477 (-5.363734) \| 1.530995 / 2.142072 (-0.611077) \| 0.630210 / 4.805227 (-4.175017) \| 0.116219 / 6.500664 (-6.384445) \| 0.042220 / 0.075469 (-0.033249) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.946341 / 1.841788 (-0.895446) \| 11.462179 / 8.074308 (3.387871) \| 10.603314 / 10.191392 (0.411922) \| 0.128826 / 0.680424 (-0.551598) \| 0.013994 / 0.534201 (-0.520207) \| 0.288142 / 0.579283 (-0.291141) \| 0.266941 / 0.434364 (-0.167422) \| 0.329392 / 0.540337 (-0.210946) \| 0.431720 / 1.386936 (-0.955216) \|\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005303 / 0.011353 (-0.006050) \| 0.003587 / 0.011008 (-0.007422) \| 0.049437 / 0.038508 (0.010929) \| 0.031940 / 0.023109 (0.008831) \| 0.276651 / 0.275898 (0.000752) \| 0.297240 / 0.323480 (-0.026240) \| 0.004202 / 0.007986 (-0.003784) \| 0.002709 / 0.004328 (-0.001619) \| 0.048647 / 0.004250 (0.044397) \| 0.044147 / 0.037052 (0.007095) \| 0.291171 / 0.258489 (0.032682) \| 0.319297 / 0.293841 (0.025456) \| 0.048167 / 0.128546 (-0.080379) \| 0.010630 / 0.075646 (-0.065016) \| 0.058402 / 0.419271 (-0.360869) \| 0.033817 / 0.043533 (-0.009716) \| 0.300546 / 0.255139 (0.045407) \| 0.319396 / 0.283200 (0.036197) \| 0.017736 / 0.141683 (-0.123946) \| 1.159590 / 1.452155 (-0.292565) \| 1.191778 / 1.492716 (-0.300939) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.088971 / 0.018006 (0.070965) \| 0.299721 / 0.000490 (0.299231) \| 0.000219 / 0.000200 (0.000019) \| 0.000043 / 0.000054 (-0.000012) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.021895 / 0.037411 (-0.015516) \| 0.075388 / 0.014526 (0.060862) \| 0.087446 / 0.176557 (-0.089111) \| 0.126339 / 0.737135 (-0.610796) \| 0.089329 / 0.296338 (-0.207010) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.296642 / 0.215209 (0.081433) \| 2.916023 / 2.077655 (0.838368) \| 1.593180 / 1.504120 (0.089060) \| 1.470491 / 1.541195 (-0.070704) \| 1.485713 / 1.468490 (0.017223) \| 0.577204 / 4.584777 (-4.007573) \| 2.436463 / 3.745712 (-1.309249) \| 2.651004 / 5.269862 (-2.618858) \| 1.754026 / 4.565676 (-2.811651) \| 0.064943 / 0.424275 (-0.359332) \| 0.005115 / 0.007607 (-0.002492) \| 0.362082 / 0.226044 (0.136038) \| 3.498198 / 2.268929 (1.229270) \| 1.951936 / 55.444624 (-53.492688) \| 1.682027 / 6.876477 (-5.194450) \| 1.751768 / 2.142072 (-0.390304) \| 0.668479 / 4.805227 (-4.136748) \| 0.119934 / 6.500664 (-6.380730) \| 0.041419 / 0.075469 (-0.034050) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.978145 / 1.841788 (-0.863643) \| 11.984984 / 8.074308 (3.910676) \| 10.732377 / 10.191392 (0.540985) \| 0.141868 / 0.680424 (-0.538555) \| 0.015256 / 0.534201 (-0.518945) \| 0.288488 / 0.579283 (-0.290795) \| 0.276091 / 0.434364 (-0.158273) \| 0.330429 / 0.540337 (-0.209908) \| 0.423964 / 1.386936 (-0.962972) \|\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#bb8497b9dec2a3807c887b8184f902d1d8d7c25a \"CML watermark\")\n" ]	null	[]	Raise error on bad split name	MEMBER	https://api.github.com/repos/huggingface/datasets/issues/6626/timeline	e.g. dashes '-' are not allowed in split names This should add an error message on datasets with unsupported split names like https://huggingface.co/datasets/open-source-metrics/test cc @AndreaFrancis	https://api.github.com/repos/huggingface/datasets	{ "diff_url": "https://github.com/huggingface/datasets/pull/6626.diff", "html_url": "https://github.com/huggingface/datasets/pull/6626", "merged_at": "2024-01-29T15:12:18Z", "patch_url": "https://github.com/huggingface/datasets/pull/6626.patch", "url": "https://api.github.com/repos/huggingface/datasets/pulls/6626" }	2,105,482,522	https://api.github.com/repos/huggingface/datasets/issues/6626/comments	PR_kwDODunzps5lU0I2	null	6,626	https://api.github.com/repos/huggingface/datasets/issues/6626/events	true
open	2024-01-28T03:56:05Z	null	https://api.github.com/repos/huggingface/datasets/issues/6624	null	{ "+1": 0, "-1": 0, "confused": 0, "eyes": 0, "heart": 0, "hooray": 0, "laugh": 0, "rocket": 0, "total_count": 0, "url": "https://api.github.com/repos/huggingface/datasets/issues/6624/reactions" }	null	https://api.github.com/repos/huggingface/datasets/issues/6624/labels{/name}	{ "avatar_url": "https://avatars.githubusercontent.com/u/15981416?v=4", "events_url": "https://api.github.com/users/vanpersie32/events{/privacy}", "followers_url": "https://api.github.com/users/vanpersie32/followers", "following_url": "https://api.github.com/users/vanpersie32/following{/other_user}", "gists_url": "https://api.github.com/users/vanpersie32/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/vanpersie32", "id": 15981416, "login": "vanpersie32", "node_id": "MDQ6VXNlcjE1OTgxNDE2", "organizations_url": "https://api.github.com/users/vanpersie32/orgs", "received_events_url": "https://api.github.com/users/vanpersie32/received_events", "repos_url": "https://api.github.com/users/vanpersie32/repos", "site_admin": false, "starred_url": "https://api.github.com/users/vanpersie32/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/vanpersie32/subscriptions", "type": "User", "url": "https://api.github.com/users/vanpersie32" }	https://github.com/huggingface/datasets/issues/6624	[]	false	2024-01-29T15:30:03Z	null	null	[ "Hi, this dataset has been disabled by the authors, so unfortunately it's no longer possible to download it." ]	null	[]	How to download the laion-coco dataset	NONE	https://api.github.com/repos/huggingface/datasets/issues/6624/timeline	The laion coco dataset is not available now. How to download it https://huggingface.co/datasets/laion/laion-coco	https://api.github.com/repos/huggingface/datasets	null	2,103,950,718	https://api.github.com/repos/huggingface/datasets/issues/6624/comments	I_kwDODunzps59Z71-	null	6,624	https://api.github.com/repos/huggingface/datasets/issues/6624/events	false
open	2024-01-27T23:46:13Z	null	https://api.github.com/repos/huggingface/datasets/issues/6623	null	{ "+1": 0, "-1": 0, "confused": 0, "eyes": 0, "heart": 0, "hooray": 0, "laugh": 0, "rocket": 0, "total_count": 0, "url": "https://api.github.com/repos/huggingface/datasets/issues/6623/reactions" }	null	https://api.github.com/repos/huggingface/datasets/issues/6623/labels{/name}	{ "avatar_url": "https://avatars.githubusercontent.com/u/30778939?v=4", "events_url": "https://api.github.com/users/rohitgr7/events{/privacy}", "followers_url": "https://api.github.com/users/rohitgr7/followers", "following_url": "https://api.github.com/users/rohitgr7/following{/other_user}", "gists_url": "https://api.github.com/users/rohitgr7/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/rohitgr7", "id": 30778939, "login": "rohitgr7", "node_id": "MDQ6VXNlcjMwNzc4OTM5", "organizations_url": "https://api.github.com/users/rohitgr7/orgs", "received_events_url": "https://api.github.com/users/rohitgr7/received_events", "repos_url": "https://api.github.com/users/rohitgr7/repos", "site_admin": false, "starred_url": "https://api.github.com/users/rohitgr7/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/rohitgr7/subscriptions", "type": "User", "url": "https://api.github.com/users/rohitgr7" }	https://github.com/huggingface/datasets/issues/6623	[]	false	2024-02-02T09:42:10Z	null	null	[ "@mariosasko, @lhoestq, @albertvillanova\r\nhey guys! can anyone help? or can you guys suggest who can help with this?", "Hi ! \r\n\r\n1. When the dataset is running of of examples, the last batches received by the GPU can be incomplete or empty/missing. We haven't implemented yet a way to ignore the last batch. It might require the datasets to provide the number of examples per shard though, so that we can know when to stop.\r\n2. Samplers are not compatible with IterableDatasets in pytorch\r\n3. if `dataset.n_shards % world_size != 0` then all the nodes will read/stream the full dataset in order (possibly reading/streaming the same data multiple times), BUT will only yield one example out of `world_size` so that each example goes to one exactly one GPU.\r\n4. no, sharding should be down up-front and can take some time depending on the dataset size and format", "> if dataset.n_shards % world_size != 0 then all the nodes will read/stream the full dataset in order (possibly reading/streaming the same data multiple times), BUT will only yield one example out of world_size so that each example goes to one exactly one GPU.\r\n\r\nconsidering there's just 1 shard and 2 worker nodes, do you mean each worker node will load the whole dataset but still receive half of that shard while streaming?", "Yes both nodes will stream from the 1 shard, but each node will skip half of the examples. This way in total each example is seen once and exactly once during you distributed training.\r\n\r\nThough it terms of I/O, the dataset is effectively read/streamed twice.", "what if the number of samples in that shard % num_nodes != 0? it will break/get stuck? or is the data repeated in that case for gradient sync?", "In the case one at least one of the noes will get an empty/incomplete batch. The data is not repeated in that case. If the training loop doesn't take this into account it can lead to unexpected behaviors indeed.\r\n\r\nIn the future we'd like to add a feature that would allow the nodes to ignore the last batch, this way all the nodes would only have full batches." ]	null	[ { "color": "a2eeef", "default": true, "description": "New feature or request", "id": 1935892871, "name": "enhancement", "node_id": "MDU6TGFiZWwxOTM1ODkyODcx", "url": "https://api.github.com/repos/huggingface/datasets/labels/enhancement" } ]	streaming datasets doesn't work properly with multi-node	NONE	https://api.github.com/repos/huggingface/datasets/issues/6623/timeline	### Feature request Let’s say I have a dataset with 5 samples with values [1, 2, 3, 4, 5], with 2 GPUs (for DDP) and batch size of 2. This dataset is an `IterableDataset` since I am streaming it. Now I split the dataset using `split_dataset_by_node` to ensure it doesn’t get repeated. And since it’s already splitted, I don’t have to use `DistributedSampler` (also they don't work with iterable datasets anyway)? But in this case I noticed that the: First iteraton: first GPU will get → [1, 2] first GPU will get → [3, 4] Second iteraton: first GPU will get → [5] first GPU will get → Nothing which actually creates an issue since in case of `DistributedSampler`, the samples are repeated internally to ensure non of the GPUs at any iteration is missing any data for gradient sync. So my questions are: 1. Here since splitting is happening before hand, how to make sure each GPU get’s a batch at each iteration to avoid gradient sync issues? 2. Do we need to use `DistributedSampler`? If yes, how? 3. in the docstrings of `split_dataset_by_node`, this is mentioned: "If the dataset has a number of shards that is a factor of `world_size` (i.e. if `dataset.n_shards % world_size == 0`), then the shards are evenly assigned across the nodes, which is the most optimized. Otherwise, each node keeps 1 example out of `world_size`, skipping the other examples." Can you explain the last part here? 4. If `dataset.n_shards % world_size != 0`, is it possible to shard the streaming dataset on the fly to avoid the case where data is missing? ### Motivation Somehow streaming datasets should work with DDP since for big LLMs a lot of data is required and DDP/multi-node is mostly used to train such models and streaming can actually help solve the data part of it. ### Your contribution Yes, I can help in submitting the PR once we get mutual understanding on how it should behave.	https://api.github.com/repos/huggingface/datasets	null	2,103,870,123	https://api.github.com/repos/huggingface/datasets/issues/6623/comments	I_kwDODunzps59ZoKr	null	6,623	https://api.github.com/repos/huggingface/datasets/issues/6623/events	false
open	2024-01-27T20:06:08Z	null	https://api.github.com/repos/huggingface/datasets/issues/6622	null	{ "+1": 0, "-1": 0, "confused": 0, "eyes": 0, "heart": 0, "hooray": 0, "laugh": 0, "rocket": 0, "total_count": 0, "url": "https://api.github.com/repos/huggingface/datasets/issues/6622/reactions" }	null	https://api.github.com/repos/huggingface/datasets/issues/6622/labels{/name}	{ "avatar_url": "https://avatars.githubusercontent.com/u/17604849?v=4", "events_url": "https://api.github.com/users/kopyl/events{/privacy}", "followers_url": "https://api.github.com/users/kopyl/followers", "following_url": "https://api.github.com/users/kopyl/following{/other_user}", "gists_url": "https://api.github.com/users/kopyl/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/kopyl", "id": 17604849, "login": "kopyl", "node_id": "MDQ6VXNlcjE3NjA0ODQ5", "organizations_url": "https://api.github.com/users/kopyl/orgs", "received_events_url": "https://api.github.com/users/kopyl/received_events", "repos_url": "https://api.github.com/users/kopyl/repos", "site_admin": false, "starred_url": "https://api.github.com/users/kopyl/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/kopyl/subscriptions", "type": "User", "url": "https://api.github.com/users/kopyl" }	https://github.com/huggingface/datasets/issues/6622	[]	false	2024-01-27T20:06:08Z	null	null	[]	null	[]	multi-GPU map does not work	NONE	https://api.github.com/repos/huggingface/datasets/issues/6622/timeline	### Describe the bug Here is the code for single-GPU processing: https://pastebin.com/bfmEeK2y Here is the code for multi-GPU processing: https://pastebin.com/gQ7i5AQy Here is the video showing that the multi-GPU mapping does not work as expected (there are so many things wrong here, it's better to watch the 3-minute video than explain here): https://youtu.be/RNbdPkSppc4 ### Steps to reproduce the bug - ### Expected behavior - ### Environment info x2 RTX A4000	https://api.github.com/repos/huggingface/datasets	null	2,103,780,697	https://api.github.com/repos/huggingface/datasets/issues/6622/comments	I_kwDODunzps59ZSVZ	null	6,622	https://api.github.com/repos/huggingface/datasets/issues/6622/events	false
closed	2024-01-27T16:59:58Z	null	https://api.github.com/repos/huggingface/datasets/issues/6621	null	{ "+1": 0, "-1": 0, "confused": 0, "eyes": 0, "heart": 0, "hooray": 0, "laugh": 0, "rocket": 0, "total_count": 0, "url": "https://api.github.com/repos/huggingface/datasets/issues/6621/reactions" }	null	https://api.github.com/repos/huggingface/datasets/issues/6621/labels{/name}	{ "avatar_url": "https://avatars.githubusercontent.com/u/17604849?v=4", "events_url": "https://api.github.com/users/kopyl/events{/privacy}", "followers_url": "https://api.github.com/users/kopyl/followers", "following_url": "https://api.github.com/users/kopyl/following{/other_user}", "gists_url": "https://api.github.com/users/kopyl/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/kopyl", "id": 17604849, "login": "kopyl", "node_id": "MDQ6VXNlcjE3NjA0ODQ5", "organizations_url": "https://api.github.com/users/kopyl/orgs", "received_events_url": "https://api.github.com/users/kopyl/received_events", "repos_url": "https://api.github.com/users/kopyl/repos", "site_admin": false, "starred_url": "https://api.github.com/users/kopyl/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/kopyl/subscriptions", "type": "User", "url": "https://api.github.com/users/kopyl" }	https://github.com/huggingface/datasets/issues/6621	[]	false	2024-01-27T17:14:43Z	2024-01-27T17:14:43Z	null	[]	completed	[]	deleted	NONE	https://api.github.com/repos/huggingface/datasets/issues/6621/timeline	...	https://api.github.com/repos/huggingface/datasets	null	2,103,675,294	https://api.github.com/repos/huggingface/datasets/issues/6621/comments	I_kwDODunzps59Y4me	null	6,621	https://api.github.com/repos/huggingface/datasets/issues/6621/events	false
open	2024-01-27T01:00:09Z	null	https://api.github.com/repos/huggingface/datasets/issues/6620	null	{ "+1": 1, "-1": 0, "confused": 0, "eyes": 0, "heart": 0, "hooray": 0, "laugh": 0, "rocket": 0, "total_count": 1, "url": "https://api.github.com/repos/huggingface/datasets/issues/6620/reactions" }	null	https://api.github.com/repos/huggingface/datasets/issues/6620/labels{/name}	{ "avatar_url": "https://avatars.githubusercontent.com/u/101498700?v=4", "events_url": "https://api.github.com/users/kiehls90/events{/privacy}", "followers_url": "https://api.github.com/users/kiehls90/followers", "following_url": "https://api.github.com/users/kiehls90/following{/other_user}", "gists_url": "https://api.github.com/users/kiehls90/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/kiehls90", "id": 101498700, "login": "kiehls90", "node_id": "U_kgDOBgy_TA", "organizations_url": "https://api.github.com/users/kiehls90/orgs", "received_events_url": "https://api.github.com/users/kiehls90/received_events", "repos_url": "https://api.github.com/users/kiehls90/repos", "site_admin": false, "starred_url": "https://api.github.com/users/kiehls90/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/kiehls90/subscriptions", "type": "User", "url": "https://api.github.com/users/kiehls90" }	https://github.com/huggingface/datasets/issues/6620	[]	false	2024-01-27T01:00:09Z	null	null	[]	null	[]	wiki_dpr.py error (ID mismatch between lines {id} and vector {vec_id}	NONE	https://api.github.com/repos/huggingface/datasets/issues/6620/timeline	### Describe the bug I'm trying to run a rag example, and the dataset is wiki_dpr. wiki_dpr download and extracting have been completed successfully. However, at the generating train split stage, an error from wiki_dpr.py keeps popping up. Especially in "_generate_examples" : 1. The following error occurs in the line id, text, title = line.strip().split("\t") ValueError: not enough values to unpack (expected 3, got 2) -> This part handles exceptions so that even if an error occurs, it passes. 2. ID mismatch between lines {id} and vector {vec_id} This error seems to occur at the line " assert int(id) == int(vec_id),". After I handled the exception in the split error, generating train split progressed to 80%, but an id mismatch error occurred at about the 16200000th vector id. Debugging is even more difficult because it takes a long time to download and split wiki_dpr. I need help. thank you in advance!! ### Steps to reproduce the bug Occurs in the generating train split step when running the rag example in the transformers repository. Specifically, it is an error in wiki_dpr.py. ### Expected behavior . ### Environment info python 3.8	https://api.github.com/repos/huggingface/datasets	null	2,103,110,536	https://api.github.com/repos/huggingface/datasets/issues/6620/comments	I_kwDODunzps59WuuI	null	6,620	https://api.github.com/repos/huggingface/datasets/issues/6620/events	false
closed	2024-01-26T15:27:10Z	null	https://api.github.com/repos/huggingface/datasets/issues/6619	null	{ "+1": 0, "-1": 0, "confused": 0, "eyes": 0, "heart": 0, "hooray": 0, "laugh": 0, "rocket": 0, "total_count": 0, "url": "https://api.github.com/repos/huggingface/datasets/issues/6619/reactions" }	false	https://api.github.com/repos/huggingface/datasets/issues/6619/labels{/name}	{ "avatar_url": "https://avatars.githubusercontent.com/u/47462742?v=4", "events_url": "https://api.github.com/users/mariosasko/events{/privacy}", "followers_url": "https://api.github.com/users/mariosasko/followers", "following_url": "https://api.github.com/users/mariosasko/following{/other_user}", "gists_url": "https://api.github.com/users/mariosasko/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/mariosasko", "id": 47462742, "login": "mariosasko", "node_id": "MDQ6VXNlcjQ3NDYyNzQy", "organizations_url": "https://api.github.com/users/mariosasko/orgs", "received_events_url": "https://api.github.com/users/mariosasko/received_events", "repos_url": "https://api.github.com/users/mariosasko/repos", "site_admin": false, "starred_url": "https://api.github.com/users/mariosasko/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/mariosasko/subscriptions", "type": "User", "url": "https://api.github.com/users/mariosasko" }	https://github.com/huggingface/datasets/pull/6619	[]	false	2024-01-26T15:53:40Z	2024-01-26T15:47:32Z	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6619). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005066 / 0.011353 (-0.006287) \| 0.003678 / 0.011008 (-0.007330) \| 0.063057 / 0.038508 (0.024549) \| 0.031250 / 0.023109 (0.008140) \| 0.248856 / 0.275898 (-0.027042) \| 0.266932 / 0.323480 (-0.056548) \| 0.003814 / 0.007986 (-0.004172) \| 0.002843 / 0.004328 (-0.001485) \| 0.049210 / 0.004250 (0.044959) \| 0.041514 / 0.037052 (0.004462) \| 0.264874 / 0.258489 (0.006385) \| 0.288834 / 0.293841 (-0.005007) \| 0.027457 / 0.128546 (-0.101089) \| 0.011071 / 0.075646 (-0.064575) \| 0.206433 / 0.419271 (-0.212839) \| 0.035381 / 0.043533 (-0.008152) \| 0.246829 / 0.255139 (-0.008310) \| 0.271094 / 0.283200 (-0.012106) \| 0.017790 / 0.141683 (-0.123893) \| 1.134618 / 1.452155 (-0.317536) \| 1.182600 / 1.492716 (-0.310116) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.094970 / 0.018006 (0.076964) \| 0.306438 / 0.000490 (0.305949) \| 0.000212 / 0.000200 (0.000012) \| 0.000044 / 0.000054 (-0.000010) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.017786 / 0.037411 (-0.019625) \| 0.060652 / 0.014526 (0.046127) \| 0.072619 / 0.176557 (-0.103937) \| 0.119460 / 0.737135 (-0.617676) \| 0.073580 / 0.296338 (-0.222759) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.279304 / 0.215209 (0.064095) \| 2.747179 / 2.077655 (0.669524) \| 1.438291 / 1.504120 (-0.065829) \| 1.313405 / 1.541195 (-0.227789) \| 1.354569 / 1.468490 (-0.113921) \| 0.578375 / 4.584777 (-4.006402) \| 2.424576 / 3.745712 (-1.321136) \| 2.831513 / 5.269862 (-2.438348) \| 1.756062 / 4.565676 (-2.809614) \| 0.064460 / 0.424275 (-0.359815) \| 0.005065 / 0.007607 (-0.002542) \| 0.335003 / 0.226044 (0.108958) \| 3.310500 / 2.268929 (1.041571) \| 1.778017 / 55.444624 (-53.666607) \| 1.504743 / 6.876477 (-5.371734) \| 1.532843 / 2.142072 (-0.609229) \| 0.662110 / 4.805227 (-4.143118) \| 0.118239 / 6.500664 (-6.382425) \| 0.042135 / 0.075469 (-0.033335) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.945650 / 1.841788 (-0.896137) \| 11.623179 / 8.074308 (3.548871) \| 10.927315 / 10.191392 (0.735923) \| 0.131050 / 0.680424 (-0.549374) \| 0.014725 / 0.534201 (-0.519476) \| 0.290716 / 0.579283 (-0.288567) \| 0.272357 / 0.434364 (-0.162007) \| 0.323274 / 0.540337 (-0.217064) \| 0.426692 / 1.386936 (-0.960244) \|\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005478 / 0.011353 (-0.005875) \| 0.003618 / 0.011008 (-0.007390) \| 0.049599 / 0.038508 (0.011091) \| 0.030814 / 0.023109 (0.007705) \| 0.273663 / 0.275898 (-0.002235) \| 0.292099 / 0.323480 (-0.031381) \| 0.004196 / 0.007986 (-0.003790) \| 0.002779 / 0.004328 (-0.001550) \| 0.047812 / 0.004250 (0.043562) \| 0.045095 / 0.037052 (0.008043) \| 0.286288 / 0.258489 (0.027799) \| 0.314125 / 0.293841 (0.020284) \| 0.047940 / 0.128546 (-0.080606) \| 0.010714 / 0.075646 (-0.064932) \| 0.057453 / 0.419271 (-0.361819) \| 0.033482 / 0.043533 (-0.010051) \| 0.273391 / 0.255139 (0.018252) \| 0.284936 / 0.283200 (0.001736) \| 0.017805 / 0.141683 (-0.123878) \| 1.148303 / 1.452155 (-0.303852) \| 1.185268 / 1.492716 (-0.307448) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.092442 / 0.018006 (0.074436) \| 0.309908 / 0.000490 (0.309418) \| 0.000213 / 0.000200 (0.000013) \| 0.000043 / 0.000054 (-0.000012) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.022874 / 0.037411 (-0.014537) \| 0.078238 / 0.014526 (0.063712) \| 0.088844 / 0.176557 (-0.087713) \| 0.127054 / 0.737135 (-0.610081) \| 0.089809 / 0.296338 (-0.206530) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.292360 / 0.215209 (0.077151) \| 2.842700 / 2.077655 (0.765045) \| 1.571071 / 1.504120 (0.066951) \| 1.450773 / 1.541195 (-0.090422) \| 1.467090 / 1.468490 (-0.001400) \| 0.583529 / 4.584777 (-4.001248) \| 2.469284 / 3.745712 (-1.276428) \| 2.844426 / 5.269862 (-2.425435) \| 1.773336 / 4.565676 (-2.792341) \| 0.064585 / 0.424275 (-0.359690) \| 0.005098 / 0.007607 (-0.002509) \| 0.342816 / 0.226044 (0.116771) \| 3.363309 / 2.268929 (1.094381) \| 1.922834 / 55.444624 (-53.521790) \| 1.649702 / 6.876477 (-5.226774) \| 1.672727 / 2.142072 (-0.469345) \| 0.665015 / 4.805227 (-4.140212) \| 0.124764 / 6.500664 (-6.375900) \| 0.041564 / 0.075469 (-0.033905) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.988970 / 1.841788 (-0.852818) \| 12.148983 / 8.074308 (4.074675) \| 11.132697 / 10.191392 (0.941305) \| 0.131596 / 0.680424 (-0.548828) \| 0.015700 / 0.534201 (-0.518501) \| 0.288819 / 0.579283 (-0.290464) \| 0.276692 / 0.434364 (-0.157672) \| 0.330260 / 0.540337 (-0.210078) \| 0.421612 / 1.386936 (-0.965324) \|\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#d627fb8357f39d78d79e704712609c7b34bdeba4 \"CML watermark\")\n" ]	null	[]	Migrate from `setup.cfg` to `pyproject.toml`	CONTRIBUTOR	https://api.github.com/repos/huggingface/datasets/issues/6619/timeline	Based on https://github.com/huggingface/huggingface_hub/pull/1971 in `hfh`	https://api.github.com/repos/huggingface/datasets	{ "diff_url": "https://github.com/huggingface/datasets/pull/6619.diff", "html_url": "https://github.com/huggingface/datasets/pull/6619", "merged_at": "2024-01-26T15:47:32Z", "patch_url": "https://github.com/huggingface/datasets/pull/6619.patch", "url": "https://api.github.com/repos/huggingface/datasets/pulls/6619" }	2,102,407,478	https://api.github.com/repos/huggingface/datasets/issues/6619/comments	PR_kwDODunzps5lK2VY	null	6,619	https://api.github.com/repos/huggingface/datasets/issues/6619/events	true
open	2024-01-26T09:21:57Z	null	https://api.github.com/repos/huggingface/datasets/issues/6618	null	{ "+1": 0, "-1": 0, "confused": 0, "eyes": 0, "heart": 0, "hooray": 0, "laugh": 0, "rocket": 0, "total_count": 0, "url": "https://api.github.com/repos/huggingface/datasets/issues/6618/reactions" }	null	https://api.github.com/repos/huggingface/datasets/issues/6618/labels{/name}	{ "avatar_url": "https://avatars.githubusercontent.com/u/77973415?v=4", "events_url": "https://api.github.com/users/Era-cell/events{/privacy}", "followers_url": "https://api.github.com/users/Era-cell/followers", "following_url": "https://api.github.com/users/Era-cell/following{/other_user}", "gists_url": "https://api.github.com/users/Era-cell/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/Era-cell", "id": 77973415, "login": "Era-cell", "node_id": "MDQ6VXNlcjc3OTczNDE1", "organizations_url": "https://api.github.com/users/Era-cell/orgs", "received_events_url": "https://api.github.com/users/Era-cell/received_events", "repos_url": "https://api.github.com/users/Era-cell/repos", "site_admin": false, "starred_url": "https://api.github.com/users/Era-cell/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/Era-cell/subscriptions", "type": "User", "url": "https://api.github.com/users/Era-cell" }	https://github.com/huggingface/datasets/issues/6618	[]	false	2024-01-26T16:47:48Z	null	null	[ "Hi! Can you please share the error's stack trace so we can see where it comes from?" ]	null	[]	While importing load_dataset from datasets	NONE	https://api.github.com/repos/huggingface/datasets/issues/6618/timeline	### Describe the bug cannot import name 'DEFAULT_CIPHERS' from 'urllib3.util.ssl_' this is the error i received ### Steps to reproduce the bug from datasets import load_dataset ### Expected behavior No errors ### Environment info python 3.11.5	https://api.github.com/repos/huggingface/datasets	null	2,101,868,198	https://api.github.com/repos/huggingface/datasets/issues/6618/comments	I_kwDODunzps59R_am	null	6,618	https://api.github.com/repos/huggingface/datasets/issues/6618/events	false
closed	2024-01-25T13:57:41Z	null	https://api.github.com/repos/huggingface/datasets/issues/6617	null	{ "+1": 0, "-1": 0, "confused": 0, "eyes": 0, "heart": 0, "hooray": 0, "laugh": 0, "rocket": 0, "total_count": 0, "url": "https://api.github.com/repos/huggingface/datasets/issues/6617/reactions" }	false	https://api.github.com/repos/huggingface/datasets/issues/6617/labels{/name}	{ "avatar_url": "https://avatars.githubusercontent.com/u/42851186?v=4", "events_url": "https://api.github.com/users/lhoestq/events{/privacy}", "followers_url": "https://api.github.com/users/lhoestq/followers", "following_url": "https://api.github.com/users/lhoestq/following{/other_user}", "gists_url": "https://api.github.com/users/lhoestq/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/lhoestq", "id": 42851186, "login": "lhoestq", "node_id": "MDQ6VXNlcjQyODUxMTg2", "organizations_url": "https://api.github.com/users/lhoestq/orgs", "received_events_url": "https://api.github.com/users/lhoestq/received_events", "repos_url": "https://api.github.com/users/lhoestq/repos", "site_admin": false, "starred_url": "https://api.github.com/users/lhoestq/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/lhoestq/subscriptions", "type": "User", "url": "https://api.github.com/users/lhoestq" }	https://github.com/huggingface/datasets/pull/6617	[]	false	2024-01-26T14:56:46Z	2024-01-26T14:50:44Z	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6617). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.004774 / 0.011353 (-0.006579) \| 0.003397 / 0.011008 (-0.007611) \| 0.063862 / 0.038508 (0.025354) \| 0.029353 / 0.023109 (0.006244) \| 0.245921 / 0.275898 (-0.029977) \| 0.268414 / 0.323480 (-0.055066) \| 0.002834 / 0.007986 (-0.005152) \| 0.002606 / 0.004328 (-0.001723) \| 0.049690 / 0.004250 (0.045439) \| 0.041637 / 0.037052 (0.004585) \| 0.262526 / 0.258489 (0.004037) \| 0.288200 / 0.293841 (-0.005641) \| 0.027233 / 0.128546 (-0.101313) \| 0.010322 / 0.075646 (-0.065324) \| 0.213860 / 0.419271 (-0.205411) \| 0.034930 / 0.043533 (-0.008602) \| 0.249256 / 0.255139 (-0.005883) \| 0.270016 / 0.283200 (-0.013184) \| 0.019413 / 0.141683 (-0.122270) \| 1.124801 / 1.452155 (-0.327354) \| 1.166224 / 1.492716 (-0.326492) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.091641 / 0.018006 (0.073635) \| 0.299679 / 0.000490 (0.299189) \| 0.000209 / 0.000200 (0.000009) \| 0.000051 / 0.000054 (-0.000004) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.018084 / 0.037411 (-0.019327) \| 0.060143 / 0.014526 (0.045617) \| 0.072556 / 0.176557 (-0.104001) \| 0.118555 / 0.737135 (-0.618580) \| 0.073786 / 0.296338 (-0.222553) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.278193 / 0.215209 (0.062984) \| 2.707954 / 2.077655 (0.630300) \| 1.483575 / 1.504120 (-0.020545) \| 1.371939 / 1.541195 (-0.169256) \| 1.395009 / 1.468490 (-0.073481) \| 0.559949 / 4.584777 (-4.024828) \| 2.372529 / 3.745712 (-1.373183) \| 2.823641 / 5.269862 (-2.446221) \| 1.722999 / 4.565676 (-2.842678) \| 0.062535 / 0.424275 (-0.361741) \| 0.004970 / 0.007607 (-0.002637) \| 0.338625 / 0.226044 (0.112580) \| 3.317576 / 2.268929 (1.048648) \| 1.854552 / 55.444624 (-53.590073) \| 1.589323 / 6.876477 (-5.287154) \| 1.624630 / 2.142072 (-0.517442) \| 0.638388 / 4.805227 (-4.166839) \| 0.116675 / 6.500664 (-6.383989) \| 0.041850 / 0.075469 (-0.033619) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.938025 / 1.841788 (-0.903763) \| 11.450072 / 8.074308 (3.375764) \| 10.414943 / 10.191392 (0.223551) \| 0.128416 / 0.680424 (-0.552007) \| 0.013798 / 0.534201 (-0.520403) \| 0.287997 / 0.579283 (-0.291286) \| 0.259976 / 0.434364 (-0.174387) \| 0.320737 / 0.540337 (-0.219601) \| 0.424292 / 1.386936 (-0.962644) \|\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005107 / 0.011353 (-0.006246) \| 0.003374 / 0.011008 (-0.007634) \| 0.050067 / 0.038508 (0.011559) \| 0.031419 / 0.023109 (0.008310) \| 0.275303 / 0.275898 (-0.000595) \| 0.286736 / 0.323480 (-0.036744) \| 0.004177 / 0.007986 (-0.003808) \| 0.002742 / 0.004328 (-0.001586) \| 0.049011 / 0.004250 (0.044761) \| 0.044373 / 0.037052 (0.007321) \| 0.289189 / 0.258489 (0.030700) \| 0.320117 / 0.293841 (0.026276) \| 0.050154 / 0.128546 (-0.078392) \| 0.010541 / 0.075646 (-0.065106) \| 0.058318 / 0.419271 (-0.360954) \| 0.033090 / 0.043533 (-0.010443) \| 0.276820 / 0.255139 (0.021681) \| 0.290854 / 0.283200 (0.007654) \| 0.017268 / 0.141683 (-0.124415) \| 1.159345 / 1.452155 (-0.292809) \| 1.224829 / 1.492716 (-0.267887) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.092468 / 0.018006 (0.074462) \| 0.301176 / 0.000490 (0.300686) \| 0.000216 / 0.000200 (0.000017) \| 0.000043 / 0.000054 (-0.000012) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.021858 / 0.037411 (-0.015553) \| 0.074873 / 0.014526 (0.060347) \| 0.086238 / 0.176557 (-0.090318) \| 0.125555 / 0.737135 (-0.611580) \| 0.087791 / 0.296338 (-0.208547) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.292283 / 0.215209 (0.077073) \| 2.847306 / 2.077655 (0.769651) \| 1.600833 / 1.504120 (0.096713) \| 1.474253 / 1.541195 (-0.066942) \| 1.474871 / 1.468490 (0.006381) \| 0.576427 / 4.584777 (-4.008350) \| 2.380116 / 3.745712 (-1.365596) \| 2.782059 / 5.269862 (-2.487803) \| 1.730642 / 4.565676 (-2.835035) \| 0.063860 / 0.424275 (-0.360415) \| 0.005019 / 0.007607 (-0.002588) \| 0.343247 / 0.226044 (0.117202) \| 3.393427 / 2.268929 (1.124498) \| 1.935346 / 55.444624 (-53.509278) \| 1.680124 / 6.876477 (-5.196353) \| 1.665788 / 2.142072 (-0.476285) \| 0.648767 / 4.805227 (-4.156460) \| 0.121962 / 6.500664 (-6.378702) \| 0.040669 / 0.075469 (-0.034800) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.996535 / 1.841788 (-0.845252) \| 12.074553 / 8.074308 (4.000245) \| 10.812740 / 10.191392 (0.621348) \| 0.142690 / 0.680424 (-0.537734) \| 0.014977 / 0.534201 (-0.519224) \| 0.285619 / 0.579283 (-0.293664) \| 0.269401 / 0.434364 (-0.164963) \| 0.329882 / 0.540337 (-0.210456) \| 0.416169 / 1.386936 (-0.970767) \|\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#129b9e0565e7a2ceaca64b99dcbf39504661cfa9 \"CML watermark\")\n" ]	null	[]	Fix CI: pyarrow 15, pandas 2.2 and sqlachemy	MEMBER	https://api.github.com/repos/huggingface/datasets/issues/6617/timeline	this should fix the CI failures on `main` close https://github.com/huggingface/datasets/issues/5477	https://api.github.com/repos/huggingface/datasets	{ "diff_url": "https://github.com/huggingface/datasets/pull/6617.diff", "html_url": "https://github.com/huggingface/datasets/pull/6617", "merged_at": "2024-01-26T14:50:44Z", "patch_url": "https://github.com/huggingface/datasets/pull/6617.patch", "url": "https://api.github.com/repos/huggingface/datasets/pulls/6617" }	2,100,459,449	https://api.github.com/repos/huggingface/datasets/issues/6617/comments	PR_kwDODunzps5lEagV	null	6,617	https://api.github.com/repos/huggingface/datasets/issues/6617/events	true
closed	2024-01-25T11:01:14Z	null	https://api.github.com/repos/huggingface/datasets/issues/6616	null	{ "+1": 0, "-1": 0, "confused": 0, "eyes": 0, "heart": 0, "hooray": 0, "laugh": 0, "rocket": 0, "total_count": 0, "url": "https://api.github.com/repos/huggingface/datasets/issues/6616/reactions" }	false	https://api.github.com/repos/huggingface/datasets/issues/6616/labels{/name}	{ "avatar_url": "https://avatars.githubusercontent.com/u/42851186?v=4", "events_url": "https://api.github.com/users/lhoestq/events{/privacy}", "followers_url": "https://api.github.com/users/lhoestq/followers", "following_url": "https://api.github.com/users/lhoestq/following{/other_user}", "gists_url": "https://api.github.com/users/lhoestq/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/lhoestq", "id": 42851186, "login": "lhoestq", "node_id": "MDQ6VXNlcjQyODUxMTg2", "organizations_url": "https://api.github.com/users/lhoestq/orgs", "received_events_url": "https://api.github.com/users/lhoestq/received_events", "repos_url": "https://api.github.com/users/lhoestq/repos", "site_admin": false, "starred_url": "https://api.github.com/users/lhoestq/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/lhoestq/subscriptions", "type": "User", "url": "https://api.github.com/users/lhoestq" }	https://github.com/huggingface/datasets/pull/6616	[]	false	2024-01-26T16:25:24Z	2024-01-26T16:19:12Z	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6616). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005382 / 0.011353 (-0.005970) \| 0.003853 / 0.011008 (-0.007155) \| 0.062629 / 0.038508 (0.024121) \| 0.030344 / 0.023109 (0.007234) \| 0.245394 / 0.275898 (-0.030505) \| 0.266004 / 0.323480 (-0.057476) \| 0.003183 / 0.007986 (-0.004802) \| 0.002795 / 0.004328 (-0.001533) \| 0.048357 / 0.004250 (0.044107) \| 0.043834 / 0.037052 (0.006782) \| 0.255979 / 0.258489 (-0.002510) \| 0.280803 / 0.293841 (-0.013038) \| 0.028200 / 0.128546 (-0.100347) \| 0.010856 / 0.075646 (-0.064791) \| 0.207076 / 0.419271 (-0.212195) \| 0.036286 / 0.043533 (-0.007247) \| 0.246492 / 0.255139 (-0.008647) \| 0.265861 / 0.283200 (-0.017338) \| 0.018309 / 0.141683 (-0.123374) \| 1.155136 / 1.452155 (-0.297018) \| 1.214342 / 1.492716 (-0.278375) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.092530 / 0.018006 (0.074524) \| 0.344951 / 0.000490 (0.344461) \| 0.000207 / 0.000200 (0.000007) \| 0.000043 / 0.000054 (-0.000011) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.018324 / 0.037411 (-0.019087) \| 0.063137 / 0.014526 (0.048611) \| 0.074683 / 0.176557 (-0.101874) \| 0.120224 / 0.737135 (-0.616912) \| 0.083107 / 0.296338 (-0.213232) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.288631 / 0.215209 (0.073422) \| 2.817992 / 2.077655 (0.740337) \| 1.473609 / 1.504120 (-0.030511) \| 1.336610 / 1.541195 (-0.204585) \| 1.354807 / 1.468490 (-0.113683) \| 0.568776 / 4.584777 (-4.016001) \| 2.412607 / 3.745712 (-1.333105) \| 2.832816 / 5.269862 (-2.437045) \| 1.789899 / 4.565676 (-2.775778) \| 0.063602 / 0.424275 (-0.360673) \| 0.004993 / 0.007607 (-0.002615) \| 0.338830 / 0.226044 (0.112786) \| 3.302550 / 2.268929 (1.033621) \| 1.827907 / 55.444624 (-53.616717) \| 1.589857 / 6.876477 (-5.286620) \| 1.647746 / 2.142072 (-0.494326) \| 0.658461 / 4.805227 (-4.146766) \| 0.120360 / 6.500664 (-6.380304) \| 0.042989 / 0.075469 (-0.032480) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.945487 / 1.841788 (-0.896301) \| 11.846335 / 8.074308 (3.772027) \| 10.483199 / 10.191392 (0.291807) \| 0.131853 / 0.680424 (-0.548570) \| 0.014230 / 0.534201 (-0.519971) \| 0.288700 / 0.579283 (-0.290584) \| 0.276086 / 0.434364 (-0.158278) \| 0.326225 / 0.540337 (-0.214112) \| 0.422874 / 1.386936 (-0.964062) \|\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.006234 / 0.011353 (-0.005118) \| 0.004104 / 0.011008 (-0.006904) \| 0.049967 / 0.038508 (0.011459) \| 0.037157 / 0.023109 (0.014048) \| 0.261892 / 0.275898 (-0.014006) \| 0.284304 / 0.323480 (-0.039176) \| 0.004482 / 0.007986 (-0.003504) \| 0.002920 / 0.004328 (-0.001409) \| 0.048827 / 0.004250 (0.044577) \| 0.052258 / 0.037052 (0.015206) \| 0.277121 / 0.258489 (0.018632) \| 0.304177 / 0.293841 (0.010336) \| 0.053537 / 0.128546 (-0.075009) \| 0.011137 / 0.075646 (-0.064509) \| 0.058188 / 0.419271 (-0.361083) \| 0.034283 / 0.043533 (-0.009250) \| 0.261912 / 0.255139 (0.006773) \| 0.273851 / 0.283200 (-0.009348) \| 0.017824 / 0.141683 (-0.123859) \| 1.130454 / 1.452155 (-0.321701) \| 1.176834 / 1.492716 (-0.315882) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.102104 / 0.018006 (0.084098) \| 0.302873 / 0.000490 (0.302383) \| 0.000208 / 0.000200 (0.000008) \| 0.000052 / 0.000054 (-0.000003) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.022470 / 0.037411 (-0.014941) \| 0.076776 / 0.014526 (0.062250) \| 0.088220 / 0.176557 (-0.088337) \| 0.130030 / 0.737135 (-0.607105) \| 0.089955 / 0.296338 (-0.206383) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.284070 / 0.215209 (0.068861) \| 2.769130 / 2.077655 (0.691475) \| 1.546379 / 1.504120 (0.042259) \| 1.435849 / 1.541195 (-0.105346) \| 1.478616 / 1.468490 (0.010126) \| 0.569185 / 4.584777 (-4.015592) \| 2.504721 / 3.745712 (-1.240992) \| 2.778267 / 5.269862 (-2.491595) \| 1.860360 / 4.565676 (-2.705316) \| 0.073465 / 0.424275 (-0.350810) \| 0.005108 / 0.007607 (-0.002499) \| 0.335185 / 0.226044 (0.109140) \| 3.314799 / 2.268929 (1.045870) \| 1.934824 / 55.444624 (-53.509801) \| 1.656247 / 6.876477 (-5.220229) \| 1.785422 / 2.142072 (-0.356650) \| 0.673677 / 4.805227 (-4.131551) \| 0.117692 / 6.500664 (-6.382972) \| 0.041648 / 0.075469 (-0.033821) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.972143 / 1.841788 (-0.869645) \| 12.980353 / 8.074308 (4.906045) \| 11.056189 / 10.191392 (0.864797) \| 0.134592 / 0.680424 (-0.545832) \| 0.015972 / 0.534201 (-0.518229) \| 0.301691 / 0.579283 (-0.277593) \| 0.286332 / 0.434364 (-0.148032) \| 0.329025 / 0.540337 (-0.211312) \| 0.422585 / 1.386936 (-0.964351) \|\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#6eb492c7072f21cb417801957c087888f252d2d1 \"CML watermark\")\n" ]	null	[]	Use schema metadata only if it matches features	MEMBER	https://api.github.com/repos/huggingface/datasets/issues/6616/timeline	e.g. if we use `map` in arrow format and transform the table, the returned table might have new columns but the metadata might be wrong	https://api.github.com/repos/huggingface/datasets	{ "diff_url": "https://github.com/huggingface/datasets/pull/6616.diff", "html_url": "https://github.com/huggingface/datasets/pull/6616", "merged_at": "2024-01-26T16:19:12Z", "patch_url": "https://github.com/huggingface/datasets/pull/6616.patch", "url": "https://api.github.com/repos/huggingface/datasets/pulls/6616" }	2,100,125,709	https://api.github.com/repos/huggingface/datasets/issues/6616/comments	PR_kwDODunzps5lDSEL	null	6,616	https://api.github.com/repos/huggingface/datasets/issues/6616/events	true
closed	2024-01-24T19:37:03Z	null	https://api.github.com/repos/huggingface/datasets/issues/6615	null	{ "+1": 0, "-1": 0, "confused": 0, "eyes": 0, "heart": 0, "hooray": 0, "laugh": 0, "rocket": 0, "total_count": 0, "url": "https://api.github.com/repos/huggingface/datasets/issues/6615/reactions" }	null	https://api.github.com/repos/huggingface/datasets/issues/6615/labels{/name}	{ "avatar_url": "https://avatars.githubusercontent.com/u/22179777?v=4", "events_url": "https://api.github.com/users/ftkeys/events{/privacy}", "followers_url": "https://api.github.com/users/ftkeys/followers", "following_url": "https://api.github.com/users/ftkeys/following{/other_user}", "gists_url": "https://api.github.com/users/ftkeys/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/ftkeys", "id": 22179777, "login": "ftkeys", "node_id": "MDQ6VXNlcjIyMTc5Nzc3", "organizations_url": "https://api.github.com/users/ftkeys/orgs", "received_events_url": "https://api.github.com/users/ftkeys/received_events", "repos_url": "https://api.github.com/users/ftkeys/repos", "site_admin": false, "starred_url": "https://api.github.com/users/ftkeys/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/ftkeys/subscriptions", "type": "User", "url": "https://api.github.com/users/ftkeys" }	https://github.com/huggingface/datasets/issues/6615	[]	false	2024-01-24T19:42:30Z	2024-01-24T19:40:11Z	null	[ "Sorry I posted in the wrong repo, please delete.. thanks!" ]	not_planned	[]	...	NONE	https://api.github.com/repos/huggingface/datasets/issues/6615/timeline	...	https://api.github.com/repos/huggingface/datasets	null	2,098,951,409	https://api.github.com/repos/huggingface/datasets/issues/6615/comments	I_kwDODunzps59G3Tx	null	6,615	https://api.github.com/repos/huggingface/datasets/issues/6615/events	false
open	2024-01-24T18:52:10Z	null	https://api.github.com/repos/huggingface/datasets/issues/6614	null	{ "+1": 2, "-1": 0, "confused": 0, "eyes": 0, "heart": 0, "hooray": 0, "laugh": 0, "rocket": 0, "total_count": 2, "url": "https://api.github.com/repos/huggingface/datasets/issues/6614/reactions" }	null	https://api.github.com/repos/huggingface/datasets/issues/6614/labels{/name}	{ "avatar_url": "https://avatars.githubusercontent.com/u/10676103?v=4", "events_url": "https://api.github.com/users/stas00/events{/privacy}", "followers_url": "https://api.github.com/users/stas00/followers", "following_url": "https://api.github.com/users/stas00/following{/other_user}", "gists_url": "https://api.github.com/users/stas00/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/stas00", "id": 10676103, "login": "stas00", "node_id": "MDQ6VXNlcjEwNjc2MTAz", "organizations_url": "https://api.github.com/users/stas00/orgs", "received_events_url": "https://api.github.com/users/stas00/received_events", "repos_url": "https://api.github.com/users/stas00/repos", "site_admin": false, "starred_url": "https://api.github.com/users/stas00/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/stas00/subscriptions", "type": "User", "url": "https://api.github.com/users/stas00" }	https://github.com/huggingface/datasets/issues/6614	[]	false	2024-01-24T18:55:09Z	null	null	[]	null	[ { "color": "a2eeef", "default": true, "description": "New feature or request", "id": 1935892871, "name": "enhancement", "node_id": "MDU6TGFiZWwxOTM1ODkyODcx", "url": "https://api.github.com/repos/huggingface/datasets/labels/enhancement" } ]	`datasets/downloads` cleanup tool	CONTRIBUTOR	https://api.github.com/repos/huggingface/datasets/issues/6614/timeline	### Feature request Splitting off https://github.com/huggingface/huggingface_hub/issues/1997 - currently `huggingface-cli delete-cache` doesn't take care of cleaning `datasets` temp files e.g. I discovered having millions of files under `datasets/downloads` cache, I had to do: ``` sudo find /data/huggingface/datasets/downloads -type f -mtime +3 -exec rm {} \+ sudo find /data/huggingface/datasets/downloads -type d -empty -delete ``` could the cleanup be integrated into `huggingface-cli` or a different tool provided to keep the folders tidy and not consume inodes and space e.g. there were tens of thousands of `.lock` files - I don't know why they never get removed - lock files should be temporary for the duration of the operation requiring the lock and not remain after the operation finished, IMHO. Also I think one should be able to nuke `datasets/downloads` w/o hurting the cache, but I think there are some datasets that rely on files extracted under this dir - or at least they did in the past - which is very difficult to manage since one has no idea what is safe to delete and what not. Thank you @Wauplin (requested to be tagged)	https://api.github.com/repos/huggingface/datasets	null	2,098,884,520	https://api.github.com/repos/huggingface/datasets/issues/6614/comments	I_kwDODunzps59Gm-o	null	6,614	https://api.github.com/repos/huggingface/datasets/issues/6614/events	false
closed	2024-01-24T11:38:25Z	null	https://api.github.com/repos/huggingface/datasets/issues/6612	null	{ "+1": 0, "-1": 0, "confused": 0, "eyes": 0, "heart": 0, "hooray": 0, "laugh": 0, "rocket": 0, "total_count": 0, "url": "https://api.github.com/repos/huggingface/datasets/issues/6612/reactions" }	null	https://api.github.com/repos/huggingface/datasets/issues/6612/labels{/name}	{ "avatar_url": "https://avatars.githubusercontent.com/u/8274752?v=4", "events_url": "https://api.github.com/users/KeremZaman/events{/privacy}", "followers_url": "https://api.github.com/users/KeremZaman/followers", "following_url": "https://api.github.com/users/KeremZaman/following{/other_user}", "gists_url": "https://api.github.com/users/KeremZaman/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/KeremZaman", "id": 8274752, "login": "KeremZaman", "node_id": "MDQ6VXNlcjgyNzQ3NTI=", "organizations_url": "https://api.github.com/users/KeremZaman/orgs", "received_events_url": "https://api.github.com/users/KeremZaman/received_events", "repos_url": "https://api.github.com/users/KeremZaman/repos", "site_admin": false, "starred_url": "https://api.github.com/users/KeremZaman/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/KeremZaman/subscriptions", "type": "User", "url": "https://api.github.com/users/KeremZaman" }	https://github.com/huggingface/datasets/issues/6612	[]	false	2024-02-01T08:14:50Z	2024-02-01T08:14:50Z	null	[ "Hi ! We recently updated `cnn_dailymail` and now `datasets>=2.14` is needed to load it.\r\n\r\nYou can update `datasets` with\r\n\r\n```\r\npip install -U datasets\r\n```" ]	completed	[]	cnn_dailymail repeats itself	NONE	https://api.github.com/repos/huggingface/datasets/issues/6612/timeline	### Describe the bug When I try to load `cnn_dailymail` dataset, it takes longer than usual and when I checked the dataset it's 3x bigger than it's supposed to be. Check https://huggingface.co/datasets/cnn_dailymail: it says 287k rows for train. But when I check length of train split it says 861339. Also I checked data: ``` >>> ds['train']['highlights'][0] "Harry Potter star Daniel Radcliffe gets £20M fortune as he turns 18 Monday . Young actor says he has no plans to fritter his cash away . Radcliffe's earnings from first five Potter films have been held in trust fund ."```` >>> ds['train']['highlights'][0] "Harry Potter star Daniel Radcliffe gets £20M fortune as he turns 18 Monday . Young actor says he has no plans to fritter his cash away . Radcliffe's earnings from first five Potter films have been held in trust fund ."```` >>> ds['train']['highlights'][287113] "Harry Potter star Daniel Radcliffe gets £20M fortune as he turns 18 Monday .\nYoung actor says he has no plans to fritter his cash away .\nRadcliffe's earnings from first five Potter films have been held in trust fund ."```` >>> ds['train']['highlights'][574226] "Harry Potter star Daniel Radcliffe gets £20M fortune as he turns 18 Monday .\nYoung actor says he has no plans to fritter his cash away .\nRadcliffe's earnings from first five Potter films have been held in trust fund ." ``` The datasets seems to be updated 6 days ago to convert it to Parquet. Probably, there is some issue with backward compatability. ### Steps to reproduce the bug 1. ``` from datasets import load_dataset ds = load_dataset('cnn_dailymail', '3.0.0') len(ds['train']) ``` ### Expected behavior It should not repeat itself. ### Environment info datasets==2.13.2 Python==3.7.13	https://api.github.com/repos/huggingface/datasets	null	2,098,078,210	https://api.github.com/repos/huggingface/datasets/issues/6612/comments	I_kwDODunzps59DiIC	null	6,612	https://api.github.com/repos/huggingface/datasets/issues/6612/events	false
open	2024-01-23T12:37:57Z	null	https://api.github.com/repos/huggingface/datasets/issues/6611	null	{ "+1": 0, "-1": 0, "confused": 0, "eyes": 0, "heart": 0, "hooray": 0, "laugh": 0, "rocket": 0, "total_count": 0, "url": "https://api.github.com/repos/huggingface/datasets/issues/6611/reactions" }	null	https://api.github.com/repos/huggingface/datasets/issues/6611/labels{/name}	{ "avatar_url": "https://avatars.githubusercontent.com/u/15320635?v=4", "events_url": "https://api.github.com/users/zotroneneis/events{/privacy}", "followers_url": "https://api.github.com/users/zotroneneis/followers", "following_url": "https://api.github.com/users/zotroneneis/following{/other_user}", "gists_url": "https://api.github.com/users/zotroneneis/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/zotroneneis", "id": 15320635, "login": "zotroneneis", "node_id": "MDQ6VXNlcjE1MzIwNjM1", "organizations_url": "https://api.github.com/users/zotroneneis/orgs", "received_events_url": "https://api.github.com/users/zotroneneis/received_events", "repos_url": "https://api.github.com/users/zotroneneis/repos", "site_admin": false, "starred_url": "https://api.github.com/users/zotroneneis/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/zotroneneis/subscriptions", "type": "User", "url": "https://api.github.com/users/zotroneneis" }	https://github.com/huggingface/datasets/issues/6611	[]	false	2024-01-23T12:37:57Z	null	null	[]	null	[]	`load_from_disk` with large dataset from S3 runs into `botocore.exceptions.ClientError`	NONE	https://api.github.com/repos/huggingface/datasets/issues/6611/timeline	### Describe the bug When loading a large dataset (>1000GB) from S3 I run into the following error: ``` Traceback (most recent call last): File "/home/alp/.local/lib/python3.10/site-packages/s3fs/core.py", line 113, in _error_wrapper return await func(args, kwargs) File "/home/alp/.local/lib/python3.10/site-packages/aiobotocore/client.py", line 383, in _make_api_call raise error_class(parsed_response, operation_name) botocore.exceptions.ClientError: An error occurred (RequestTimeTooSkewed) when calling the GetObject operation: The difference between the request time and the current time is too large. The above exception was the direct cause of the following exception: Traceback (most recent call last): File "/home/alp/phoneme-classification.monorepo/aws_sagemaker/data_processing/inspect_final_dataset.py", line 13, in <module> dataset = load_from_disk("s3://speech-recognition-processed-data/whisper/de/train_data/", storage_options=storage_options) File "/home/alp/.local/lib/python3.10/site-packages/datasets/load.py", line 1902, in load_from_disk return Dataset.load_from_disk(dataset_path, keep_in_memory=keep_in_memory, storage_options=storage_options) File "/home/alp/.local/lib/python3.10/site-packages/datasets/arrow_dataset.py", line 1686, in load_from_disk fs.download(src_dataset_path, [dest_dataset_path.as](http://dest_dataset_path.as/)_posix(), recursive=True) File "/home/alp/.local/lib/python3.10/site-packages/fsspec/spec.py", line 1480, in download return self.get(rpath, lpath, recursive=recursive, kwargs) File "/home/alp/.local/lib/python3.10/site-packages/fsspec/asyn.py", line 121, in wrapper return sync(self.loop, func, args, *kwargs) File "/home/alp/.local/lib/python3.10/site-packages/fsspec/asyn.py", line 106, in sync raise return_result File "/home/alp/.local/lib/python3.10/site-packages/fsspec/asyn.py", line 61, in _runner result[0] = await coro File "/home/alp/.local/lib/python3.10/site-packages/fsspec/asyn.py", line 604, in _get return await _run_coros_in_chunks( File "/home/alp/.local/lib/python3.10/site-packages/fsspec/asyn.py", line 257, in _run_coros_in_chunks await asyncio.gather(chunk, return_exceptions=return_exceptions), File "/usr/lib/python3.10/asyncio/tasks.py", line 408, in wait_for return await fut File "/home/alp/.local/lib/python3.10/site-packages/s3fs/core.py", line 1193, in _get_file body, content_length = await _open_file(range=0) File "/home/alp/.local/lib/python3.10/site-packages/s3fs/core.py", line 1184, in _open_file resp = await self._call_s3( File "/home/alp/.local/lib/python3.10/site-packages/s3fs/core.py", line 348, in _call_s3 return await _error_wrapper( File "/home/alp/.local/lib/python3.10/site-packages/s3fs/core.py", line 140, in _error_wrapper raise err PermissionError: The difference between the request time and the current time is too large. ``` The usual problem for this error is that the time on my local machine is out of sync with the current time. However, this is not the case here. I checked the time and even reset it with no success. See resources here: - https://stackoverflow.com/questions/4770635/s3-error-the-difference-between-the-request-time-and-the-current-time-is-too-la - https://stackoverflow.com/questions/25964491/aws-s3-upload-fails-requesttimetooskewed The error does not appear when loading a smaller dataset (e.g. our test set) from the same s3 path. ### Steps to reproduce the bug 1. Create large dataset 2. Try loading it from s3 using: ``` dataset = load_from_disk("s3://...", storage_options=storage_options) ``` ### Expected behavior Load dataset without running into this error. ### Environment info - `datasets` version: 2.13.1 - Platform: Linux-5.15.0-91-generic-x86_64-with-glibc2.35 - Python version: 3.10.12 - Huggingface_hub version: 0.19.3 - PyArrow version: 12.0.1 - Pandas version: 2.0.3	https://api.github.com/repos/huggingface/datasets	null	2,096,004,858	https://api.github.com/repos/huggingface/datasets/issues/6611/comments	I_kwDODunzps587n76	null	6,611	https://api.github.com/repos/huggingface/datasets/issues/6611/events	false
closed	2024-01-23T09:32:32Z	null	https://api.github.com/repos/huggingface/datasets/issues/6610	null	{ "+1": 0, "-1": 0, "confused": 0, "eyes": 0, "heart": 0, "hooray": 0, "laugh": 0, "rocket": 0, "total_count": 0, "url": "https://api.github.com/repos/huggingface/datasets/issues/6610/reactions" }	null	https://api.github.com/repos/huggingface/datasets/issues/6610/labels{/name}	{ "avatar_url": "https://avatars.githubusercontent.com/u/16574677?v=4", "events_url": "https://api.github.com/users/neiblegy/events{/privacy}", "followers_url": "https://api.github.com/users/neiblegy/followers", "following_url": "https://api.github.com/users/neiblegy/following{/other_user}", "gists_url": "https://api.github.com/users/neiblegy/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/neiblegy", "id": 16574677, "login": "neiblegy", "node_id": "MDQ6VXNlcjE2NTc0Njc3", "organizations_url": "https://api.github.com/users/neiblegy/orgs", "received_events_url": "https://api.github.com/users/neiblegy/received_events", "repos_url": "https://api.github.com/users/neiblegy/repos", "site_admin": false, "starred_url": "https://api.github.com/users/neiblegy/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/neiblegy/subscriptions", "type": "User", "url": "https://api.github.com/users/neiblegy" }	https://github.com/huggingface/datasets/issues/6610	[]	false	2024-01-25T02:15:23Z	2024-01-25T02:15:23Z	null	[ "Hi! You are passing the wrong feature type to `cast_column`. This is the fixed call:\r\n```python\r\nais_dataset = ais_dataset.cast_column(\"my_labeled_bbox\", {\"bbox\": Sequence(Value(dtype=\"int64\")), \"label\": ClassLabel(names=[\"cat\", \"dog\"])})\r\n```", "> Hi! You are passing the wrong feature type to `cast_column`. This is the fixed call:\r\n> \r\n> ```python\r\n> ais_dataset = ais_dataset.cast_column(\"my_labeled_bbox\", {\"bbox\": Sequence(Value(dtype=\"int64\")), \"label\": ClassLabel(names=[\"cat\", \"dog\"])})\r\n> ```\r\n\r\nthanks" ]	completed	[]	cast_column to Sequence(subfeatures_dict) has err	NONE	https://api.github.com/repos/huggingface/datasets/issues/6610/timeline	### Describe the bug I am working with the following demo code: ``` from datasets import load_dataset from datasets.features import Sequence, Value, ClassLabel, Features ais_dataset = load_dataset("/data/ryan.gao/ais_dataset_cache/raw/1978/") ais_dataset = ais_dataset["train"] def add_class(example): example["my_labeled_bbox"] = {"bbox": [100,100,200,200], "label": "cat"} return example ais_dataset = ais_dataset.map(add_class, batched=False, num_proc=32) ais_dataset = ais_dataset.cast_column("my_labeled_bbox", Sequence( { "bbox": Sequence(Value(dtype="int64")), "label": ClassLabel(names=["cat", "dog"]) })) print(ais_dataset[0]) ``` However, executing this code results in an error: ``` File "/home/protoss.gao/.local/lib/python3.9/site-packages/datasets/table.py", line 2111, in cast_array_to_feature raise TypeError(f"Couldn't cast array of type\n{array.type}\nto\n{feature}") TypeError: Couldn't cast array of type int64 to Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None) ``` Upon examining the source code in datasets/table.py at line 2035: ``` if isinstance(feature, Sequence) and isinstance(feature.feature, dict): feature = { name: Sequence(subfeature, length=feature.length) for name, subfeature in feature.feature.items() } ``` I noticed that if subfeature is of type Sequence, the code results in Sequence(Sequence(...), ...) and Sequence(ClassLabel(...), ...), which appears to be the source of the error. ### Steps to reproduce the bug run my demo code ### Expected behavior no exception ### Environment info python 3.9 datasets: 2.16.1	https://api.github.com/repos/huggingface/datasets	null	2,095,643,711	https://api.github.com/repos/huggingface/datasets/issues/6610/comments	I_kwDODunzps586Pw_	null	6,610	https://api.github.com/repos/huggingface/datasets/issues/6610/events	false
open	2024-01-23T01:47:19Z	null	https://api.github.com/repos/huggingface/datasets/issues/6609	{ "avatar_url": "https://avatars.githubusercontent.com/u/42851186?v=4", "events_url": "https://api.github.com/users/lhoestq/events{/privacy}", "followers_url": "https://api.github.com/users/lhoestq/followers", "following_url": "https://api.github.com/users/lhoestq/following{/other_user}", "gists_url": "https://api.github.com/users/lhoestq/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/lhoestq", "id": 42851186, "login": "lhoestq", "node_id": "MDQ6VXNlcjQyODUxMTg2", "organizations_url": "https://api.github.com/users/lhoestq/orgs", "received_events_url": "https://api.github.com/users/lhoestq/received_events", "repos_url": "https://api.github.com/users/lhoestq/repos", "site_admin": false, "starred_url": "https://api.github.com/users/lhoestq/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/lhoestq/subscriptions", "type": "User", "url": "https://api.github.com/users/lhoestq" }	{ "+1": 0, "-1": 0, "confused": 0, "eyes": 0, "heart": 0, "hooray": 0, "laugh": 0, "rocket": 0, "total_count": 0, "url": "https://api.github.com/repos/huggingface/datasets/issues/6609/reactions" }	null	https://api.github.com/repos/huggingface/datasets/issues/6609/labels{/name}	{ "avatar_url": "https://avatars.githubusercontent.com/u/42117435?v=4", "events_url": "https://api.github.com/users/je-santos/events{/privacy}", "followers_url": "https://api.github.com/users/je-santos/followers", "following_url": "https://api.github.com/users/je-santos/following{/other_user}", "gists_url": "https://api.github.com/users/je-santos/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/je-santos", "id": 42117435, "login": "je-santos", "node_id": "MDQ6VXNlcjQyMTE3NDM1", "organizations_url": "https://api.github.com/users/je-santos/orgs", "received_events_url": "https://api.github.com/users/je-santos/received_events", "repos_url": "https://api.github.com/users/je-santos/repos", "site_admin": false, "starred_url": "https://api.github.com/users/je-santos/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/je-santos/subscriptions", "type": "User", "url": "https://api.github.com/users/je-santos" }	https://github.com/huggingface/datasets/issues/6609	[ { "avatar_url": "https://avatars.githubusercontent.com/u/42851186?v=4", "events_url": "https://api.github.com/users/lhoestq/events{/privacy}", "followers_url": "https://api.github.com/users/lhoestq/followers", "following_url": "https://api.github.com/users/lhoestq/following{/other_user}", "gists_url": "https://api.github.com/users/lhoestq/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/lhoestq", "id": 42851186, "login": "lhoestq", "node_id": "MDQ6VXNlcjQyODUxMTg2", "organizations_url": "https://api.github.com/users/lhoestq/orgs", "received_events_url": "https://api.github.com/users/lhoestq/received_events", "repos_url": "https://api.github.com/users/lhoestq/repos", "site_admin": false, "starred_url": "https://api.github.com/users/lhoestq/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/lhoestq/subscriptions", "type": "User", "url": "https://api.github.com/users/lhoestq" } ]	false	2024-01-31T15:11:26Z	null	null	[ "+1", "same error in 2.16.1", "@kongjiellx any luck with the issue?", "I opened https://github.com/huggingface/datasets/pull/6632 to fix this issue. Once it's merged we'll do a new release of `datasets`", "Thanks @lhoestq !" ]	null	[]	Wrong path for cache directory in offline mode	NONE	https://api.github.com/repos/huggingface/datasets/issues/6609/timeline	### Describe the bug Dear huggingfacers, I'm trying to use a subset of the-stack dataset. When I run the command the first time ``` dataset = load_dataset( path='bigcode/the-stack', data_dir='data/fortran', split='train' ) ``` It downloads the files and caches them normally. Nevertheless, since my compute nodes are not online (`HF_DATASETS_OFFLINE=1`) . Whenever I try to run the command again, the library is passing the wrong cache path: `Cache directory for the-stack doesn't exist at /Users/user/.cache/huggingface/datasets/bigcode___the-stack/default-data_dir=data%2Ffortran-data_dir=data%2Ffortran` when the right path is: `'/Users/user/.cache/huggingface/datasets/bigcode___the-stack/default-data_dir=data\%2Ffortran` Not sure why those redundancies are included in the path. If I try adding the correct path through the the cache_dir argument it throws an error: ConnectionError: Couldn't reach the Hugging Face Hub for dataset 'bigcode/the-stack': Offline mode is enabled. Your help with this issue is greatly appreciated. Thanks a lot for the great work. ### Steps to reproduce the bug 1: `dataset = load_dataset( path='bigcode/the-stack', data_dir='data/fortran', split='train' )` 2: `HF_DATASETS_OFFLINE=1` 3: `dataset = load_dataset( path='bigcode/the-stack', data_dir='data/fortran', split='train' )` ### Expected behavior being able to use the cached data ### Environment info several different systems	https://api.github.com/repos/huggingface/datasets	null	2,095,085,650	https://api.github.com/repos/huggingface/datasets/issues/6609/comments	I_kwDODunzps584HhS	null	6,609	https://api.github.com/repos/huggingface/datasets/issues/6609/events	false
closed	2024-01-22T15:19:16Z	null	https://api.github.com/repos/huggingface/datasets/issues/6608	null	{ "+1": 0, "-1": 0, "confused": 0, "eyes": 0, "heart": 0, "hooray": 0, "laugh": 0, "rocket": 0, "total_count": 0, "url": "https://api.github.com/repos/huggingface/datasets/issues/6608/reactions" }	false	https://api.github.com/repos/huggingface/datasets/issues/6608/labels{/name}	{ "avatar_url": "https://avatars.githubusercontent.com/u/47462742?v=4", "events_url": "https://api.github.com/users/mariosasko/events{/privacy}", "followers_url": "https://api.github.com/users/mariosasko/followers", "following_url": "https://api.github.com/users/mariosasko/following{/other_user}", "gists_url": "https://api.github.com/users/mariosasko/gists{/gist_id}", "gravatar_id": "", "html_url": "https://github.com/mariosasko", "id": 47462742, "login": "mariosasko", "node_id": "MDQ6VXNlcjQ3NDYyNzQy", "organizations_url": "https://api.github.com/users/mariosasko/orgs", "received_events_url": "https://api.github.com/users/mariosasko/received_events", "repos_url": "https://api.github.com/users/mariosasko/repos", "site_admin": false, "starred_url": "https://api.github.com/users/mariosasko/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/mariosasko/subscriptions", "type": "User", "url": "https://api.github.com/users/mariosasko" }	https://github.com/huggingface/datasets/pull/6608	[]	false	2024-01-29T16:43:11Z	2024-01-29T16:36:53Z	null	[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6608). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005376 / 0.011353 (-0.005977) \| 0.004691 / 0.011008 (-0.006317) \| 0.064061 / 0.038508 (0.025553) \| 0.030397 / 0.023109 (0.007288) \| 0.242656 / 0.275898 (-0.033242) \| 0.275586 / 0.323480 (-0.047894) \| 0.003460 / 0.007986 (-0.004526) \| 0.003125 / 0.004328 (-0.001203) \| 0.050496 / 0.004250 (0.046246) \| 0.045833 / 0.037052 (0.008781) \| 0.255222 / 0.258489 (-0.003267) \| 0.287303 / 0.293841 (-0.006538) \| 0.027755 / 0.128546 (-0.100791) \| 0.011251 / 0.075646 (-0.064396) \| 0.208456 / 0.419271 (-0.210816) \| 0.037219 / 0.043533 (-0.006314) \| 0.249592 / 0.255139 (-0.005547) \| 0.261243 / 0.283200 (-0.021957) \| 0.020735 / 0.141683 (-0.120948) \| 1.130017 / 1.452155 (-0.322137) \| 1.208558 / 1.492716 (-0.284158) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.098891 / 0.018006 (0.080885) \| 0.439042 / 0.000490 (0.438552) \| 0.000333 / 0.000200 (0.000133) \| 0.000045 / 0.000054 (-0.000010) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.018356 / 0.037411 (-0.019055) \| 0.062416 / 0.014526 (0.047891) \| 0.075613 / 0.176557 (-0.100944) \| 0.122009 / 0.737135 (-0.615126) \| 0.078195 / 0.296338 (-0.218144) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.273804 / 0.215209 (0.058595) \| 2.706480 / 2.077655 (0.628826) \| 1.456196 / 1.504120 (-0.047924) \| 1.353301 / 1.541195 (-0.187893) \| 1.378913 / 1.468490 (-0.089577) \| 0.556885 / 4.584777 (-4.027892) \| 2.358961 / 3.745712 (-1.386752) \| 2.871830 / 5.269862 (-2.398031) \| 1.765212 / 4.565676 (-2.800464) \| 0.062172 / 0.424275 (-0.362103) \| 0.004974 / 0.007607 (-0.002633) \| 0.330375 / 0.226044 (0.104331) \| 3.264550 / 2.268929 (0.995621) \| 1.824444 / 55.444624 (-53.620181) \| 1.561189 / 6.876477 (-5.315287) \| 1.671020 / 2.142072 (-0.471052) \| 0.633408 / 4.805227 (-4.171819) \| 0.116080 / 6.500664 (-6.384584) \| 0.044606 / 0.075469 (-0.030863) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.980757 / 1.841788 (-0.861031) \| 12.553534 / 8.074308 (4.479225) \| 10.517668 / 10.191392 (0.326276) \| 0.130528 / 0.680424 (-0.549896) \| 0.013960 / 0.534201 (-0.520241) \| 0.289615 / 0.579283 (-0.289668) \| 0.267277 / 0.434364 (-0.167087) \| 0.324139 / 0.540337 (-0.216198) \| 0.440325 / 1.386936 (-0.946611) \|\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n\| metric \| read_batch_formatted_as_numpy after write_array2d \| read_batch_formatted_as_numpy after write_flattened_sequence \| read_batch_formatted_as_numpy after write_nested_sequence \| read_batch_unformated after write_array2d \| read_batch_unformated after write_flattened_sequence \| read_batch_unformated after write_nested_sequence \| read_col_formatted_as_numpy after write_array2d \| read_col_formatted_as_numpy after write_flattened_sequence \| read_col_formatted_as_numpy after write_nested_sequence \| read_col_unformated after write_array2d \| read_col_unformated after write_flattened_sequence \| read_col_unformated after write_nested_sequence \| read_formatted_as_numpy after write_array2d \| read_formatted_as_numpy after write_flattened_sequence \| read_formatted_as_numpy after write_nested_sequence \| read_unformated after write_array2d \| read_unformated after write_flattened_sequence \| read_unformated after write_nested_sequence \| write_array2d \| write_flattened_sequence \| write_nested_sequence \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.005388 / 0.011353 (-0.005965) \| 0.004043 / 0.011008 (-0.006966) \| 0.050514 / 0.038508 (0.012005) \| 0.031413 / 0.023109 (0.008303) \| 0.275122 / 0.275898 (-0.000776) \| 0.307518 / 0.323480 (-0.015962) \| 0.004440 / 0.007986 (-0.003546) \| 0.003301 / 0.004328 (-0.001027) \| 0.049200 / 0.004250 (0.044949) \| 0.045704 / 0.037052 (0.008651) \| 0.285265 / 0.258489 (0.026776) \| 0.318942 / 0.293841 (0.025101) \| 0.053893 / 0.128546 (-0.074653) \| 0.011855 / 0.075646 (-0.063791) \| 0.060951 / 0.419271 (-0.358321) \| 0.034397 / 0.043533 (-0.009136) \| 0.276108 / 0.255139 (0.020969) \| 0.290981 / 0.283200 (0.007781) \| 0.019986 / 0.141683 (-0.121697) \| 1.205695 / 1.452155 (-0.246460) \| 1.255942 / 1.492716 (-0.236774) \|\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n\| metric \| get_batch_of\\_1024\\_random_rows \| get_batch_of\\_1024\\_rows \| get_first_row \| get_last_row \|\n\|--------\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.101910 / 0.018006 (0.083904) \| 0.320551 / 0.000490 (0.320061) \| 0.000299 / 0.000200 (0.000099) \| 0.000058 / 0.000054 (0.000004) \|\n\n### Benchmark: benchmark_indices_mapping.json\n\n\| metric \| select \| shard \| shuffle \| sort \| train_test_split \|\n\|--------\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.022387 / 0.037411 (-0.015024) \| 0.076380 / 0.014526 (0.061854) \| 0.090404 / 0.176557 (-0.086153) \| 0.127106 / 0.737135 (-0.610030) \| 0.089873 / 0.296338 (-0.206465) \|\n\n### Benchmark: benchmark_iterating.json\n\n\| metric \| read 5000 \| read 50000 \| read_batch 50000 10 \| read_batch 50000 100 \| read_batch 50000 1000 \| read_formatted numpy 5000 \| read_formatted pandas 5000 \| read_formatted tensorflow 5000 \| read_formatted torch 5000 \| read_formatted_batch numpy 5000 10 \| read_formatted_batch numpy 5000 1000 \| shuffled read 5000 \| shuffled read 50000 \| shuffled read_batch 50000 10 \| shuffled read_batch 50000 100 \| shuffled read_batch 50000 1000 \| shuffled read_formatted numpy 5000 \| shuffled read_formatted_batch numpy 5000 10 \| shuffled read_formatted_batch numpy 5000 1000 \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 0.288433 / 0.215209 (0.073223) \| 2.827005 / 2.077655 (0.749350) \| 1.548760 / 1.504120 (0.044640) \| 1.419545 / 1.541195 (-0.121650) \| 1.456531 / 1.468490 (-0.011959) \| 0.570254 / 4.584777 (-4.014523) \| 2.441318 / 3.745712 (-1.304394) \| 2.778647 / 5.269862 (-2.491215) \| 1.755255 / 4.565676 (-2.810422) \| 0.062581 / 0.424275 (-0.361694) \| 0.005205 / 0.007607 (-0.002402) \| 0.342189 / 0.226044 (0.116145) \| 3.401208 / 2.268929 (1.132279) \| 1.941447 / 55.444624 (-53.503178) \| 1.652578 / 6.876477 (-5.223899) \| 1.768558 / 2.142072 (-0.373514) \| 0.656537 / 4.805227 (-4.148690) \| 0.116901 / 6.500664 (-6.383763) \| 0.041408 / 0.075469 (-0.034061) \|\n\n### Benchmark: benchmark_map_filter.json\n\n\| metric \| filter \| map fast-tokenizer batched \| map identity \| map identity batched \| map no-op batched \| map no-op batched numpy \| map no-op batched pandas \| map no-op batched pytorch \| map no-op batched tensorflow \|\n\|--------\|---\|---\|---\|---\|---\|---\|---\|---\|---\|\n\| new / old (diff) \| 1.001715 / 1.841788 (-0.840073) \| 12.533073 / 8.074308 (4.458765) \| 11.086084 / 10.191392 (0.894692) \| 0.134368 / 0.680424 (-0.546055) \| 0.015255 / 0.534201 (-0.518946) \| 0.291769 / 0.579283 (-0.287514) \| 0.283311 / 0.434364 (-0.151053) \| 0.327857 / 0.540337 (-0.212481) \| 0.413854 / 1.386936 (-0.973083) \|\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#46931085bd8a3fdbc63b68b5ee4b8f62029c7557 \"CML watermark\")\n" ]	null	[]	Add `with_rank` param to `Dataset.filter`	CONTRIBUTOR	https://api.github.com/repos/huggingface/datasets/issues/6608/timeline	Fix #6564	https://api.github.com/repos/huggingface/datasets	{ "diff_url": "https://github.com/huggingface/datasets/pull/6608.diff", "html_url": "https://github.com/huggingface/datasets/pull/6608", "merged_at": "2024-01-29T16:36:53Z", "patch_url": "https://github.com/huggingface/datasets/pull/6608.patch", "url": "https://api.github.com/repos/huggingface/datasets/pulls/6608" }	2,094,153,292	https://api.github.com/repos/huggingface/datasets/issues/6608/comments	PR_kwDODunzps5ku_lN	null	6,608	https://api.github.com/repos/huggingface/datasets/issues/6608/events	true

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9.05 MB

Size of the auto-converted Parquet files:

9.05 MB

Number of rows:

5,000