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fix conda release worlflow
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Set dev version
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Release: 3.1.0
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The dataset viewer should be available soon. Please retry later.
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### Describe the bug After waiting for 2 hours, it still presents ``The dataset viewer should be available soon. Please retry later.'' ### Steps to reproduce the bug dataset link: https://huggingface.co/datasets/BryanW/HI_EDIT ### Expected behavior Present the dataset viewer. ### Environment info NA
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Disallow video push_to_hub
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fix docs relative links
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7,263
Small addition to video docs
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7,262
Allow video with disabeld decoding without decord
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for the viewer, this way it can use Video(decode=False) and doesn't need decord (which causes segfaults)
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7,259
Don't embed videos
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don't include video bytes when running download_and_prepare(format="parquet") this also affects push_to_hub which will just upload the local paths of the videos though
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7,258
Always set non-null writer batch size
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bug introduced in #7230, it was preventing the Viewer limit writes to work
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fix ci for pyarrow 18
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as reported in https://github.com/huggingface/datasets/issues/6843
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fix decord import
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delay the import until Video() is instantiated + also import duckdb first (otherwise importing duckdb later causes a segfault)
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7,252
Add IterableDataset.shard()
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2024-10-25T11:07:12
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Will be useful to distribute a dataset across workers (other than pytorch) like spark I also renamed `.n_shards` -> `.num_shards` for consistency and kept the old name for backward compatibility. And a few changes in internal functions for consistency as well (rank, world_size -> num_shards, index) Breaking change: the new default for `contiguous` in `Dataset.shard()` is `True`, but imo not a big deal since I couldn't find any usage of `contiguous=False` internally (we always do contiguous=True for map-style datasets since its more optimized) or in the wild
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7,251
Missing video docs
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Basic XML support (mostly copy pasted from text)
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enable the viewer for datasets like https://huggingface.co/datasets/FrancophonIA/e-calm (there will be more and more apparently)
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Set dev version
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Release: 3.0.2
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use huggingface_hub offline mode
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and better handling of LocalEntryNotfoundError cc @Wauplin follow up to #7234
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7,241
`push_to_hub` overwrite argument
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2024-10-20T03:23:26
2024-10-24T17:39:08
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### Feature request Add an `overwrite` argument to the `push_to_hub` method. ### Motivation I want to overwrite a repo without deleting it on Hugging Face. Is this possible? I couldn't find anything in the documentation or tutorials. ### Your contribution I can create a PR.
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2,597,358,525
PR_kwDODunzps5_GIvw
7,236
[MINOR:TYPO] Update arrow_dataset.py
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2024-10-18T12:10:03
2024-10-24T15:06:43
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Fix wrong link. csv kwargs docstring link was pointing to pandas json docs.
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7,234
No need for dataset_info
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2024-10-17T09:54:03
2024-10-22T12:30:40
2024-10-21T16:44:34
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save a useless call to /api/datasets/repo_id
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https://api.github.com/repos/huggingface/datasets/issues/7232
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PR_kwDODunzps5-62rY
7,232
(Super tiny doc update) Mention to_polars
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2024-10-17T06:08:53
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polars is also quite popular now, thus this tiny update can tell users polars is supported
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2,592,011,737
PR_kwDODunzps5-1jP8
7,231
Fix typo in image dataset docs
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Fix typo in image dataset docs. Typo reported by @datavistics.
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Video support
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2024-10-15T18:17:29
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(wip and experimental) adding the `Video` type based on `VideoReader` from `decord` ```python >>>from datasets import load_dataset >>> ds = load_dataset("path/to/videos", split="train").with_format("torch") >>> print(ds[0]["video"]) <decord.video_reader.VideoReader object at 0x337a47910> >>> print(ds[0]["video"][0]) tensor([[[73, 73, 73], [73, 73, 73], [73, 73, 73], ..., [23, 23, 23], [23, 23, 23], [23, 23, 23]]], dtype=torch.uint8) ``` the storage is the same as for audio and images: `{"path": pa.string(), "bytes": pa.binary()}` and I did a small to keep the hf:// URL in the "path" field if possible, this way the viewer can link to fiels on the hub if possible
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8 days, 22:22:21
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handle config_name=None in push_to_hub
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This caught me out - thought it might be better to explicitly handle None?
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bump fsspec
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Preserve features in iterable dataset.filter
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Fixes example in #7208 - I'm not sure what other checks I should do? @lhoestq I also haven't thought hard about the concatenate / interleaving example iterables but think this might work assuming that features are either all identical or None?
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Iterable dataset.filter should not override features
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### Describe the bug When calling filter on an iterable dataset, the features get set to None ### Steps to reproduce the bug import numpy as np import time from datasets import Dataset, Features, Array3D ```python features=Features(**{"array0": Array3D((None, 10, 10), dtype="float32"), "array1": Array3D((None,10,10), dtype="float32")}) dataset = Dataset.from_dict({f"array{i}": [np.zeros((x,10,10), dtype=np.float32) for x in [2000,1000]*25] for i in range(2)}, features=features) ds = dataset.to_iterable_dataset() orig_column_names = ds.column_names ds = ds.filter(lambda x: True) assert ds.column_names == orig_column_names ``` ### Expected behavior Filter should preserve features information ### Environment info 3.0.2
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we're not using the benchmarks anymore + they were not working anyway due to token permissions I keep the code in case we ever want to re-run the benchmark manually
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Fixes the bug when applying map to an arrow-formatted iterable dataset described here: https://github.com/huggingface/datasets/issues/6833#issuecomment-2399903885 ```python from datasets import load_dataset ds = load_dataset("rotten_tomatoes", split="train", streaming=True) ds = ds.with_format("arrow").map(lambda x: x) for ex in ds: pass ``` @lhoestq
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with_format docstring
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2024-10-08T13:05:19
2024-10-08T13:13:12
2024-10-08T13:13:05
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reported at https://github.com/huggingface/datasets/issues/3444
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Fix the environment variable for huggingface cache
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2024-10-05T11:54:35
2024-10-30T23:10:27
2024-10-08T15:45:18
CONTRIBUTOR
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Resolve #6256. As far as I tested, `HF_DATASETS_CACHE` was ignored and I could not specify the cache directory at all except for the default one by this environment variable. `HF_HOME` has worked. Perhaps the recent change on file downloading by `huggingface_hub` could affect this bug. In my testing, I could not specify the cache directory even by `load_dataset("dataset_name" cache_dir="...")`. It might be another issue. I also welcome any advice to solve this issue.
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datasets.exceptions.DatasetNotFoundError for private dataset
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2024-10-03T07:49:36
2024-10-03T10:09:28
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### Describe the bug The following Python code tries to download a private dataset and fails with the error `datasets.exceptions.DatasetNotFoundError: Dataset 'ClimatePolicyRadar/all-document-text-data-weekly' doesn't exist on the Hub or cannot be accessed.`. Downloading a public dataset doesn't work. ``` py from datasets import load_dataset _ = load_dataset("ClimatePolicyRadar/all-document-text-data-weekly") ``` This seems to be just an issue with my machine config as the code above works with a colleague's machine. So far I have tried: - logging back out and in from the Huggingface CLI using `huggingface-cli logout` - manually removing the token cache at `/Users/kalyan/.cache/huggingface/token` (found using `huggingface-cli env`) - manually passing a token in `load_dataset` My output of `huggingface-cli whoami`: ``` kdutia orgs: ClimatePolicyRadar ``` ### Steps to reproduce the bug ``` python Python 3.12.2 (main, Feb 6 2024, 20:19:44) [Clang 15.0.0 (clang-1500.1.0.2.5)] on darwin Type "help", "copyright", "credits" or "license" for more information. >>> from datasets import load_dataset >>> _ = load_dataset("ClimatePolicyRadar/all-document-text-data-weekly") Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/Users/kalyan/Library/Caches/pypoetry/virtualenvs/open-data-cnKQNmjn-py3.12/lib/python3.12/site-packages/datasets/load.py", line 2074, in load_dataset builder_instance = load_dataset_builder( ^^^^^^^^^^^^^^^^^^^^^ File "/Users/kalyan/Library/Caches/pypoetry/virtualenvs/open-data-cnKQNmjn-py3.12/lib/python3.12/site-packages/datasets/load.py", line 1795, in load_dataset_builder dataset_module = dataset_module_factory( ^^^^^^^^^^^^^^^^^^^^^^^ File "/Users/kalyan/Library/Caches/pypoetry/virtualenvs/open-data-cnKQNmjn-py3.12/lib/python3.12/site-packages/datasets/load.py", line 1659, in dataset_module_factory raise e1 from None File "/Users/kalyan/Library/Caches/pypoetry/virtualenvs/open-data-cnKQNmjn-py3.12/lib/python3.12/site-packages/datasets/load.py", line 1597, in dataset_module_factory raise DatasetNotFoundError(f"Dataset '{path}' doesn't exist on the Hub or cannot be accessed.") from e datasets.exceptions.DatasetNotFoundError: Dataset 'ClimatePolicyRadar/all-document-text-data-weekly' doesn't exist on the Hub or cannot be accessed. >>> ``` ### Expected behavior The dataset downloads successfully. ### Environment info From `huggingface-cli env`: ``` - huggingface_hub version: 0.25.1 - Platform: macOS-14.2.1-arm64-arm-64bit - Python version: 3.12.2 - Running in iPython ?: No - Running in notebook ?: No - Running in Google Colab ?: No - Running in Google Colab Enterprise ?: No - Token path ?: /Users/kalyan/.cache/huggingface/token - Has saved token ?: True - Who am I ?: kdutia - Configured git credential helpers: osxkeychain - FastAI: N/A - Tensorflow: N/A - Torch: N/A - Jinja2: 3.1.4 - Graphviz: N/A - keras: N/A - Pydot: N/A - Pillow: N/A - hf_transfer: N/A - gradio: N/A - tensorboard: N/A - numpy: 2.1.1 - pydantic: N/A - aiohttp: 3.10.8 - ENDPOINT: https://huggingface.co - HF_HUB_CACHE: /Users/kalyan/.cache/huggingface/hub - HF_ASSETS_CACHE: /Users/kalyan/.cache/huggingface/assets - HF_TOKEN_PATH: /Users/kalyan/.cache/huggingface/token - HF_HUB_OFFLINE: False - HF_HUB_DISABLE_TELEMETRY: False - HF_HUB_DISABLE_PROGRESS_BARS: None - HF_HUB_DISABLE_SYMLINKS_WARNING: False - HF_HUB_DISABLE_EXPERIMENTAL_WARNING: False - HF_HUB_DISABLE_IMPLICIT_TOKEN: False - HF_HUB_ENABLE_HF_TRANSFER: False - HF_HUB_ETAG_TIMEOUT: 10 - HF_HUB_DOWNLOAD_TIMEOUT: 10 ``` from `datasets-cli env`: ``` - `datasets` version: 3.0.1 - Platform: macOS-14.2.1-arm64-arm-64bit - Python version: 3.12.2 - `huggingface_hub` version: 0.25.1 - PyArrow version: 17.0.0 - Pandas version: 2.2.3 - `fsspec` version: 2024.6.1 ```
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Pin multiprocess<0.70.1 to align with dill<0.3.9
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2024-10-02T05:40:18
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Pin multiprocess<0.70.1 to align with dill<0.3.9. Note that multiprocess-0.70.1 requires dill-0.3.9: https://github.com/uqfoundation/multiprocess/releases/tag/0.70.17 Fix #7186.
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pinning `dill<0.3.9` without pinning `multiprocess`
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2024-10-01T22:29:32
2024-10-02T06:08:24
2024-10-02T06:08:24
NONE
null
null
null
### Describe the bug The [latest `multiprocess` release](https://github.com/uqfoundation/multiprocess/releases/tag/0.70.17) requires `dill>=0.3.9` which causes issues when installing `datasets` without backtracking during package version resolution. Is it possible to add a pin for multiprocess so something like `multiprocess<=0.70.16` so that the `dill` version is compatible? ### Steps to reproduce the bug NA ### Expected behavior NA ### Environment info NA
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CI benchmarks are broken
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2024-10-01T08:16:08
2024-10-09T16:07:48
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Since Aug 30, 2024, CI benchmarks are broken: https://github.com/huggingface/datasets/actions/runs/11108421214/job/30861323975 ``` {"level":"error","message":"Resource not accessible by integration","name":"HttpError","request":{"body":"{\"body\":\"<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 | ... "headers":{"accept":"application/vnd.github.v3+json","authorization":"token [REDACTED]","content-type":"application/json; charset=utf-8","user-agent":"octokit-rest.js/18.0.0 octokit-core.js/3.6.0 Node.js/16.20.2 (linux; x64)"},"method":"POST","request":{"agent":{"_events":{},"_eventsCount":2,"cache": ... "response":{"data":{"documentation_url":"https://docs.github.com/rest/issues/comments#create-an-issue-comment","message":"Resource not accessible by integration","status":"403"}, ... "stack":"HttpError: Resource not accessible by integration\n at /usr/lib/node_modules/@dvcorg/cml/node_modules/@octokit/request/dist-node/index.js:86:21\n at processTicksAndRejections (node:internal/process/task_queues:96:5)\n at async Job.doExecute (/usr/lib/node_modules/@dvcorg/cml/node_modules/bottleneck/light.js:405:18)","status":403} ```
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Pin dill<0.3.9 to fix CI
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2024-09-30T14:26:25
2024-09-30T14:38:59
2024-09-30T14:38:57
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Pin dill<0.3.9 to fix CI for deps-latest. Note that dill-0.3.9 was released yesterday Sep 29, 2024: - https://pypi.org/project/dill/0.3.9/ - https://github.com/uqfoundation/dill/releases/tag/0.3.9 Fix #7183.
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CI is broken for deps-latest
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2024-09-30T14:38:58
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See: https://github.com/huggingface/datasets/actions/runs/11106149906/job/30853879890 ``` =========================== short test summary info ============================ FAILED tests/test_arrow_dataset.py::BaseDatasetTest::test_filter_caching_on_disk - AssertionError: Lists differ: [{'fi[44 chars] {'filename': '/tmp/tmp6xcyyjs4/cache-9533fe2601cd3e48.arrow'}] != [{'fi[44 chars] {'filename': '/tmp/tmp6xcyyjs4/cache-e6e0a8b830976289.arrow'}] First differing element 1: {'filename': '/tmp/tmp6xcyyjs4/cache-9533fe2601cd3e48.arrow'} {'filename': '/tmp/tmp6xcyyjs4/cache-e6e0a8b830976289.arrow'} [{'filename': '/tmp/tmp6xcyyjs4/dataset0.arrow'}, - {'filename': '/tmp/tmp6xcyyjs4/cache-9533fe2601cd3e48.arrow'}] ? ^^^^^ -------- + {'filename': '/tmp/tmp6xcyyjs4/cache-e6e0a8b830976289.arrow'}] ? ++++++++++ ^^ + FAILED tests/test_arrow_dataset.py::BaseDatasetTest::test_map_caching_on_disk - AssertionError: Lists differ: [{'filename': '/tmp/tmp5gxrti_n/cache-e58d327daec8626f.arrow'}] != [{'filename': '/tmp/tmp5gxrti_n/cache-d87234c5763e54a3.arrow'}] First differing element 0: {'filename': '/tmp/tmp5gxrti_n/cache-e58d327daec8626f.arrow'} {'filename': '/tmp/tmp5gxrti_n/cache-d87234c5763e54a3.arrow'} - [{'filename': '/tmp/tmp5gxrti_n/cache-e58d327daec8626f.arrow'}] ? ^^ ----------- + [{'filename': '/tmp/tmp5gxrti_n/cache-d87234c5763e54a3.arrow'}] ? +++++++++++ ^^ FAILED tests/test_fingerprint.py::TokenizersHashTest::test_hash_regex - NameError: name 'log' is not defined FAILED tests/test_fingerprint.py::RecurseHashTest::test_hash_ignores_line_definition_of_function - AssertionError: '52e56ee04ad92499' != '0a4f75cec280f634' - 52e56ee04ad92499 + 0a4f75cec280f634 FAILED tests/test_fingerprint.py::RecurseHashTest::test_hash_ipython_function - AssertionError: 'a6bd2041ca63d6c0' != '517bf36b7eecdef5' - a6bd2041ca63d6c0 + 517bf36b7eecdef5 FAILED tests/test_fingerprint.py::HashingTest::test_hash_tiktoken_encoding - NameError: name 'log' is not defined FAILED tests/test_fingerprint.py::HashingTest::test_hash_torch_compiled_module - NameError: name 'log' is not defined FAILED tests/test_fingerprint.py::HashingTest::test_hash_torch_generator - NameError: name 'log' is not defined FAILED tests/test_fingerprint.py::HashingTest::test_hash_torch_tensor - NameError: name 'log' is not defined FAILED tests/test_fingerprint.py::HashingTest::test_set_doesnt_depend_on_order - NameError: name 'log' is not defined FAILED tests/test_fingerprint.py::HashingTest::test_set_stable - NameError: name 'log' is not defined ERROR tests/test_iterable_dataset.py::test_iterable_dataset_from_file - NameError: name 'log' is not defined = 11 failed, 2850 passed, 3 skipped, 23 warnings, 1 error in 191.06s (0:03:11) = ```
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Support features in metadata configs
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Support features in metadata configs, like: ``` configs: - config_name: default features: - name: id dtype: int64 - name: name dtype: string - name: score dtype: float64 ``` This will allow to avoid inference of data types. Currently, we allow passing this information in the `dataset_info` (instead of `configs`) field, but this is not intuitive and it is not properly documented. TODO: - [ ] Document usage
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PR_kwDODunzps59Br4E
7,181
Fix datasets export to JSON
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I_kwDODunzps6YPq6O
7,180
Memory leak when wrapping datasets into PyTorch Dataset without explicit deletion
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2024-09-30T12:07:56
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### Describe the bug I've encountered a memory leak when wrapping the HuggingFace dataset into a PyTorch Dataset. The RAM usage constantly increases during iteration if items are not explicitly deleted after use. ### Steps to reproduce the bug Steps to reproduce: Create a PyTorch Dataset wrapper for 'nebula/cc12m': ```` from torch.utils.data import Dataset from tqdm import tqdm from datasets import load_dataset from torchvision import transforms Image.MAX_IMAGE_PIXELS = None class CC12M(Dataset): def __init__(self, path_or_name='nebula/cc12m', split='train', transform=None, single_caption=True): self.raw_dataset = load_dataset(path_or_name)[split] if transform is None: self.transform = transforms.Compose([ transforms.Resize((224, 224)), transforms.CenterCrop(224), transforms.ToTensor(), transforms.Normalize( mean=[0.48145466, 0.4578275, 0.40821073], std=[0.26862954, 0.26130258, 0.27577711] ) ]) else: self.transform = transforms.Compose(transform) self.single_caption = single_caption self.length = len(self.raw_dataset) def __len__(self): return self.length def __getitem__(self, index): item = self.raw_dataset[index] caption = item['txt'] with io.BytesIO(item['webp']) as buffer: image = Image.open(buffer).convert('RGB') if self.transform: image = self.transform(image) # del item # Uncomment this line to prevent the memory leak return image, caption ```` Iterate through the dataset without the del item line in __getitem__. Observe RAM usage increasing constantly. Add del item at the end of __getitem__: ``` def __getitem__(self, index): item = self.raw_dataset[index] caption = item['txt'] with io.BytesIO(item['webp']) as buffer: image = Image.open(buffer).convert('RGB') if self.transform: image = self.transform(image) del item # This line prevents the memory leak return image, caption ``` Iterate through the dataset again and observe that RAM usage remains stable. ### Expected behavior Expected behavior: RAM usage should remain stable during iteration without needing to explicitly delete items. Actual behavior: RAM usage constantly increases unless items are explicitly deleted after use ### Environment info - `datasets` version: 2.21.0 - Platform: Linux-4.18.0-513.5.1.el8_9.x86_64-x86_64-with-glibc2.28 - Python version: 3.12.4 - `huggingface_hub` version: 0.24.6 - PyArrow version: 17.0.0 - Pandas version: 2.2.2 - `fsspec` version: 2024.6.1
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Support Python 3.11
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Support Python 3.11. Fix #7178.
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Support Python 3.11
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Support Python 3.11: https://peps.python.org/pep-0664/
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Fix release instructions
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Fix release instructions. During last release, I had to make this additional update.
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[FSTimeoutError] load_dataset
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2024-09-26T15:42:29
2024-10-26T16:12:57
2024-09-30T17:28:35
NONE
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null
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### Describe the bug When using `load_dataset`to load [HuggingFaceM4/VQAv2](https://huggingface.co/datasets/HuggingFaceM4/VQAv2), I am getting `FSTimeoutError`. ### Error ``` TimeoutError: The above exception was the direct cause of the following exception: FSTimeoutError Traceback (most recent call last) [/usr/local/lib/python3.10/dist-packages/fsspec/asyn.py](https://klh9mr78js-496ff2e9c6d22116-0-colab.googleusercontent.com/outputframe.html?vrz=colab_20240924-060116_RC00_678132060#) in sync(loop, func, timeout, *args, **kwargs) 99 if isinstance(return_result, asyncio.TimeoutError): 100 # suppress asyncio.TimeoutError, raise FSTimeoutError --> 101 raise FSTimeoutError from return_result 102 elif isinstance(return_result, BaseException): 103 raise return_result FSTimeoutError: ``` It usually fails around 5-6 GB. <img width="847" alt="Screenshot 2024-09-26 at 9 10 19 PM" src="https://github.com/user-attachments/assets/ff91995a-fb55-4de6-8214-94025d6c8470"> ### Steps to reproduce the bug To reproduce it, run this in colab notebook: ``` !pip install -q -U datasets from datasets import load_dataset ds = load_dataset('HuggingFaceM4/VQAv2', split="train[:10%]") ``` ### Expected behavior It should download properly. ### Environment info Using Colab Notebook.
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