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OSCAR unshuffled_original_ko: NonMatchingSplitsSizesError
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NONE
## Describe the bug Cannot download OSCAR `unshuffled_original_ko` due to `NonMatchingSplitsSizesError`. ## Steps to reproduce the bug ```python >>> dataset = datasets.load_dataset('oscar', 'unshuffled_original_ko') NonMatchingSplitsSizesError: [{'expected': SplitInfo(name='train', num_bytes=25292102197, num_examples=7345075, dataset_name='oscar'), 'recorded': SplitInfo(name='train', num_bytes=25284578514, num_examples=7344907, dataset_name='oscar')}] ``` ## Expected results Loading is successful. ## Actual results Loading throws above error. ## Environment info - `datasets` version: 1.12.1 - Platform: Linux-5.4.0-81-generic-x86_64-with-glibc2.29 - Python version: 3.8.10 - PyArrow version: 5.0.0
2022-01-19T14:10:07Z
https://github.com/huggingface/datasets/issues/2941
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add swedish_medical_ner dataset
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2021-09-17T20:03:05Z
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CONTRIBUTOR
Adding the Swedish Medical NER dataset, listed in "Biomedical Datasets - BigScience Workshop 2021"
2021-10-05T12:13:34Z
https://github.com/huggingface/datasets/pull/2940
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MENYO-20k repo has moved, updating URL
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CONTRIBUTOR
Dataset repo moved to https://github.com/uds-lsv/menyo-20k_MT, now editing URL to match. https://github.com/uds-lsv/menyo-20k_MT/blob/master/data/train.tsv is the file we're looking for
2021-09-21T15:31:37Z
https://github.com/huggingface/datasets/pull/2939
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2021-09-29T13:01:31Z
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Take namespace into account in caching
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2021-09-17T16:57:33Z
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MEMBER
Loading a dataset "username/dataset_name" hosted by a user on the hub used to cache the dataset only taking into account the dataset name, and ignorign the username. Because of this, if a user later loads "dataset_name" without specifying the username, it would reload the dataset from the cache instead of failing. I changed the dataset cache and module cache mechanism to include the username in the name of the cache directory that is used: <s> `~/.cache/huggingface/datasets/username/dataset_name` for the data `~/.cache/huggingface/modules/datasets_modules/datasets/username/dataset_name` for the python files </s> EDIT: actually using three underscores: `~/.cache/huggingface/datasets/username___dataset_name` for the data `~/.cache/huggingface/modules/datasets_modules/datasets/username___dataset_name` for the python files This PR should fix the issue https://github.com/huggingface/datasets/issues/2842 cc @stas00
2021-12-17T10:52:18Z
https://github.com/huggingface/datasets/pull/2938
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load_dataset using default cache on Windows causes PermissionError: [WinError 5] Access is denied
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2021-09-17T16:52:10Z
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NONE
## Describe the bug Standard process to download and load the wiki_bio dataset causes PermissionError in Windows 10 and 11. ## Steps to reproduce the bug ```python from datasets import load_dataset ds = load_dataset('wiki_bio') ``` ## Expected results It is expected that the dataset downloads without any errors. ## Actual results PermissionError see trace below: ``` Using custom data configuration default Downloading and preparing dataset wiki_bio/default (download: 318.53 MiB, generated: 736.94 MiB, post-processed: Unknown size, total: 1.03 GiB) to C:\Users\username\.cache\huggingface\datasets\wiki_bio\default\1.1.0\5293ce565954ba965dada626f1e79684e98172d950371d266bf3caaf87e911c9... Traceback (most recent call last): File "<stdin>", line 1, in <module> File "C:\Users\username\.conda\envs\hf\lib\site-packages\datasets\load.py", line 1112, in load_dataset builder_instance.download_and_prepare( File "C:\Users\username\.conda\envs\hf\lib\site-packages\datasets\builder.py", line 644, in download_and_prepare self._save_info() File "C:\Users\username\.conda\envs\hf\lib\contextlib.py", line 120, in __exit__ next(self.gen) File "C:\Users\username\.conda\envs\hf\lib\site-packages\datasets\builder.py", line 598, in incomplete_dir os.rename(tmp_dir, dirname) PermissionError: [WinError 5] Access is denied: 'C:\\Users\\username\\.cache\\huggingface\\datasets\\wiki_bio\\default\\1.1.0\\5293ce565954ba965dada626f1e79684e98172d950371d266bf3caaf87e911c9.incomplete' -> 'C:\\Users\\username\\.cache\\huggingface\\datasets\\wiki_bio\\default\\1.1.0\\5293ce565954ba965dada626f1e79684e98172d950371d266bf3caaf87e911c9' ``` By commenting out the os.rename() [L604](https://github.com/huggingface/datasets/blob/master/src/datasets/builder.py#L604) and the shutil.rmtree() [L607](https://github.com/huggingface/datasets/blob/master/src/datasets/builder.py#L607) lines, in my virtual environment, I was able to get the load process to complete, rename the directory manually and then rerun the `load_dataset('wiki_bio')` to get what I needed. It seems that os.rename() in the `incomplete_dir` content manager is the culprit. Here's another project [Conan](https://github.com/conan-io/conan/issues/6560) with similar issue with os.rename() if it helps debug this issue. ## Environment info - `datasets` version: 1.12.1 - Platform: Windows-10-10.0.22449-SP0 - Python version: 3.8.12 - PyArrow version: 5.0.0
2022-08-24T13:09:08Z
https://github.com/huggingface/datasets/issues/2937
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2021-09-21T09:39:04Z
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Check that array is not Float as nan != nan
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2021-09-17T16:16:41Z
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CONTRIBUTOR
The Exception wants to check for issues with StructArrays/ListArrays but catches FloatArrays with value nan as nan != nan. Pass on FloatArrays as we should not raise an Exception for them.
2021-09-21T09:39:05Z
https://github.com/huggingface/datasets/pull/2936
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2021-09-24T10:41:52Z
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Add Jigsaw unintended Bias
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CONTRIBUTOR
Hi, Here's a first attempt at this dataset. Would be great if it could be merged relatively quickly as it is needed for Bigscience-related stuff. This requires manual download, and I had some trouble generating dummy_data in this setting, so welcoming feedback there.
2021-09-24T10:41:52Z
https://github.com/huggingface/datasets/pull/2935
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to_tf_dataset keeps a reference to the open data somewhere, causing issues on windows
https://api.github.com/repos/huggingface/datasets/issues/2934/events
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2021-09-17T15:26:53Z
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999,477,413
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https://api.github.com/repos/huggingface/datasets/issues/2934
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To reproduce: ```python import datasets as ds import weakref import gc d = ds.load_dataset("mnist", split="train") ref = weakref.ref(d._data.table) tfd = d.to_tf_dataset("image", batch_size=1, shuffle=False, label_cols="label") del tfd, d gc.collect() assert ref() is None, "Error: there is at least one reference left" ``` This causes issues because the table holds a reference to an open arrow file that should be closed. So on windows it's not possible to delete or move the arrow file afterwards. Moreover the CI test of the `to_tf_dataset` method isn't able to clean up the temporary arrow files because of this. cc @Rocketknight1
2021-10-13T09:03:23Z
https://github.com/huggingface/datasets/issues/2934
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2021-09-20T09:52:10Z
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Replace script_version with revision
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2021-09-17T14:04:39Z
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As discussed in https://github.com/huggingface/datasets/pull/2718#discussion_r707013278, the parameter name `script_version` is no longer applicable to datasets without loading script (i.e., datasets only with raw data files). This PR replaces the parameter name `script_version` with `revision`. This way, we are also aligned with: - Transformers: `AutoTokenizer.from_pretrained(..., revision=...)` - Hub: `HfApi.dataset_info(..., revision=...)`, `HfApi.upload_file(..., revision=...)`
2021-09-20T09:52:10Z
https://github.com/huggingface/datasets/pull/2933
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2021-09-21T15:31:10Z
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Conda build fails
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2021-09-17T12:49:22Z
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999,317,750
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https://api.github.com/repos/huggingface/datasets/issues/2932
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MEMBER
## Describe the bug Current `datasets` version in conda is 1.9 instead of 1.12. The build of the conda package fails.
2021-09-21T15:31:10Z
https://github.com/huggingface/datasets/issues/2932
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2021-09-16T17:01:37Z
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Fix bug in to_tf_dataset
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2021-09-16T15:08:03Z
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998,326,359
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Replace `set_format()` to `with_format()` so that we don't alter the original dataset in `to_tf_dataset()`
2021-09-16T17:01:38Z
https://github.com/huggingface/datasets/pull/2931
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2021-09-16T13:50:53Z
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Mutable columns argument breaks set_format
https://api.github.com/repos/huggingface/datasets/issues/2930/events
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2021-09-16T12:27:22Z
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998,154,311
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https://api.github.com/repos/huggingface/datasets/issues/2930
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## Describe the bug If you pass a mutable list to the `columns` argument of `set_format` and then change the list afterwards, the returned columns also change. ## Steps to reproduce the bug ```python from datasets import load_dataset dataset = load_dataset("glue", "cola") column_list = ["idx", "label"] dataset.set_format("python", columns=column_list) column_list[1] = "foo" # Change the list after we call `set_format` dataset['train'][:4].keys() ``` ## Expected results ```python dict_keys(['idx', 'label']) ``` ## Actual results ```python dict_keys(['idx']) ```
2021-09-16T13:50:53Z
https://github.com/huggingface/datasets/issues/2930
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2021-09-17T08:23:59Z
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Add regression test for null Sequence
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2021-09-16T08:58:33Z
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Relates to #2892 and #2900.
2021-09-17T08:23:59Z
https://github.com/huggingface/datasets/pull/2929
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2021-09-16T12:35:34Z
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Update BibTeX entry
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2021-09-16T08:39:20Z
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Update BibTeX entry.
2021-09-16T12:35:34Z
https://github.com/huggingface/datasets/pull/2928
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Datasets 1.12 dataset.filter TypeError: get_indices_from_mask_function() got an unexpected keyword argument
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## Describe the bug Upgrading to 1.12 caused `dataset.filter` call to fail with > get_indices_from_mask_function() got an unexpected keyword argument valid_rel_labels ## Steps to reproduce the bug ```pythondef filter_good_rows( ex: Dict, valid_rel_labels: Set[str], valid_ner_labels: Set[str], tokenizer: PreTrainedTokenizerFast, ) -> bool: """Get the good rows""" encoding = get_encoding_for_text(text=ex["text"], tokenizer=tokenizer) ex["encoding"] = encoding for relation in ex["relations"]: if not is_valid_relation(relation, valid_rel_labels): return False for span in ex["spans"]: if not is_valid_span(span, valid_ner_labels, encoding): return False return True def get_dataset(): loader_path = str(Path(__file__).parent / "prodigy_dataset_builder.py") ds = load_dataset( loader_path, name="prodigy-dataset", data_files=sorted(file_paths), cache_dir=cache_dir, )["train"] valid_ner_labels = set(vocab.ner_category) valid_relations = set(vocab.relation_types.keys()) ds = ds.filter( filter_good_rows, fn_kwargs=dict( valid_rel_labels=valid_relations, valid_ner_labels=valid_ner_labels, tokenizer=vocab.tokenizer, ), keep_in_memory=True, num_proc=num_proc, ) ``` `ds` is a `DatasetDict` produced by a jsonl dataset. This runs fine on 1.11 but fails on 1.12 **Stack Trace** ## Expected results I expect 1.12 datasets filter to filter the dataset without raising as it does on 1.11 ## Actual results ``` tf_ner_rel_lib/dataset.py:695: in load_prodigy_arrow_datasets_from_jsonl ds = ds.filter( ../../../../.pyenv/versions/tf_ner_rel_lib/lib/python3.8/site-packages/datasets/arrow_dataset.py:185: in wrapper out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs) ../../../../.pyenv/versions/tf_ner_rel_lib/lib/python3.8/site-packages/datasets/fingerprint.py:398: in wrapper out = func(self, *args, **kwargs) ../../../../.pyenv/versions/tf_ner_rel_lib/lib/python3.8/site-packages/datasets/arrow_dataset.py:2169: in filter indices = self.map( ../../../../.pyenv/versions/tf_ner_rel_lib/lib/python3.8/site-packages/datasets/arrow_dataset.py:1686: in map return self._map_single( ../../../../.pyenv/versions/tf_ner_rel_lib/lib/python3.8/site-packages/datasets/arrow_dataset.py:185: in wrapper out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs) ../../../../.pyenv/versions/tf_ner_rel_lib/lib/python3.8/site-packages/datasets/fingerprint.py:398: in wrapper out = func(self, *args, **kwargs) ../../../../.pyenv/versions/tf_ner_rel_lib/lib/python3.8/site-packages/datasets/arrow_dataset.py:2048: in _map_single batch = apply_function_on_filtered_inputs( _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ inputs = {'_input_hash': [2108817714, 1477695082, -1021597032, 2130671338, -1260483858, -1203431639, ...], '_task_hash': [18070...ons', 'relations', 'relations', ...], 'answer': ['accept', 'accept', 'accept', 'accept', 'accept', 'accept', ...], ...} indices = [0, 1, 2, 3, 4, 5, ...], check_same_num_examples = False, offset = 0 def apply_function_on_filtered_inputs(inputs, indices, check_same_num_examples=False, offset=0): """Utility to apply the function on a selection of columns.""" nonlocal update_data fn_args = [inputs] if input_columns is None else [inputs[col] for col in input_columns] if offset == 0: effective_indices = indices else: effective_indices = [i + offset for i in indices] if isinstance(indices, list) else indices + offset processed_inputs = ( > function(*fn_args, effective_indices, **fn_kwargs) if with_indices else function(*fn_args, **fn_kwargs) ) E TypeError: get_indices_from_mask_function() got an unexpected keyword argument 'valid_rel_labels' ../../../../.pyenv/versions/tf_ner_rel_lib/lib/python3.8/site-packages/datasets/arrow_dataset.py:1939: TypeError ``` ## Environment info <!-- You can run the command `datasets-cli env` and copy-and-paste its output below. --> - `datasets` version: 1.12.1 - Platform: Mac - Python version: 3.8.9 - PyArrow version: pyarrow==5.0.0
2021-09-20T16:23:22Z
https://github.com/huggingface/datasets/issues/2927
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Error when downloading datasets to non-traditional cache directories
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2021-09-15T19:59:46Z
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## Describe the bug When the cache directory is linked (soft link) to a directory on a NetApp device, the download fails. ## Steps to reproduce the bug ```bash ln -s /path/to/netapp/.cache ~/.cache ``` ```python load_dataset("imdb") ``` ## Expected results Successfully loading IMDB dataset ## Actual results ``` datasets.utils.info_utils.NonMatchingSplitsSizesError: [{'expected': SplitInfo(name='train', num_bytes=33432835, num_examples=25000, dataset_name='imdb'), 'recorded': SplitInfo(name='train', num_bytes=0, num_examples=0, dataset_name='imdb')}, {'expected': SplitInfo(name='test', num_bytes=32650697, num_examples=25000, dataset_name='imdb'), 'recorded': SplitInfo(name='test', num_bytes=659932, num_examples=503, dataset_name='imdb')}, {'expected': SplitInfo(name='unsupervised', num_bytes=67106814, num_examples=50000, dataset_name='imdb'), 'recorded': SplitInfo(name='unsupervised', num_bytes=0, num_examples=0, dataset_name='imdb')}] ``` ## Environment info <!-- You can run the command `datasets-cli env` and copy-and-paste its output below. --> - `datasets` version: 1.1.2 - Platform: Ubuntu - Python version: 3.8 ## Extra notes Stranger yet, trying to debug the phenomenon, I found the range of results to vary a lot without clear direction: - With `cache_dir="/path/to/netapp/.cache"` the same thing happens. - However, when linking `~/netapp/` to `/path/to/netapp` *and* setting `cache_dir="~/netapp/.cache/huggingface/datasets"` - it does work - On the other hand, when linking `~/.cache` to `~/netapp/.cache` without using `cache_dir`, it does work anymore. While I could test it only for a NetApp device, it might have to do with any other mounted FS. Thanks :)
2021-11-24T21:42:31Z
https://github.com/huggingface/datasets/issues/2926
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Add tutorial for no-code dataset upload
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This PR is for a tutorial for uploading a dataset to the Hub. It relies on the Hub UI elements to upload a dataset, introduces the online tagging tool for creating tags, and the Dataset card template to get a head start on filling it out. The addition of this tutorial should make it easier for beginners to upload a dataset without accessing the terminal or knowing Git.
2021-09-27T17:51:55Z
https://github.com/huggingface/datasets/pull/2925
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"File name too long" error for file locks
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## Describe the bug Getting the following error when calling `load_dataset("gar1t/test")`: ``` OSError: [Errno 36] File name too long: '<user>/.cache/huggingface/datasets/_home_garrett_.cache_huggingface_datasets_csv_test-7c856aea083a7043_0.0.0_9144e0a4e8435090117cea53e6c7537173ef2304525df4a077c435d8ee7828ff.incomplete.lock' ``` ## Steps to reproduce the bug Where the user cache dir (e.g. `~/.cache`) is on a file system that limits filenames to 255 chars (e.g. ext4): ```python from datasets import load_dataset load_dataset("gar1t/test") ``` ## Expected results Expect the function to return without an error. ## Actual results ``` Traceback (most recent call last): File "<stdin>", line 1, in <module> File "<python_venv>/lib/python3.9/site-packages/datasets/load.py", line 1112, in load_dataset builder_instance.download_and_prepare( File "<python_venv>/lib/python3.9/site-packages/datasets/builder.py", line 644, in download_and_prepare self._save_info() File "<python_venv>/lib/python3.9/site-packages/datasets/builder.py", line 765, in _save_info with FileLock(lock_path): File "<python_venv>/lib/python3.9/site-packages/datasets/utils/filelock.py", line 323, in __enter__ self.acquire() File "<python_venv>/lib/python3.9/site-packages/datasets/utils/filelock.py", line 272, in acquire self._acquire() File "<python_venv>/lib/python3.9/site-packages/datasets/utils/filelock.py", line 403, in _acquire fd = os.open(self._lock_file, open_mode) OSError: [Errno 36] File name too long: '<user>/.cache/huggingface/datasets/_home_garrett_.cache_huggingface_datasets_csv_test-7c856aea083a7043_0.0.0_9144e0a4e8435090117cea53e6c7537173ef2304525df4a077c435d8ee7828ff.incomplete.lock' ``` ## Environment info - `datasets` version: 1.12.1 - Platform: Linux-5.11.0-27-generic-x86_64-with-glibc2.31 - Python version: 3.9.7 - PyArrow version: 5.0.0
2023-12-08T13:39:51Z
https://github.com/huggingface/datasets/issues/2924
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Loading an autonlp dataset raises in normal mode but not in streaming mode
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2021-09-15T17:44:38Z
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CONTRIBUTOR
## Describe the bug The same dataset (from autonlp) raises an error in normal mode, but does not raise in streaming mode ## Steps to reproduce the bug ```python from datasets import load_dataset load_dataset("severo/autonlp-data-sentiment_detection-3c8bcd36", split="train", streaming=False) ## raises an error load_dataset("severo/autonlp-data-sentiment_detection-3c8bcd36", split="train", streaming=True) ## does not raise an error ``` ## Expected results Both calls should raise the same error ## Actual results Call with streaming=False: ``` 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 5825.42it/s] Using custom data configuration autonlp-data-sentiment_detection-3c8bcd36-fe30267462d1d42b Downloading and preparing dataset json/autonlp-data-sentiment_detection-3c8bcd36 to /home/slesage/.cache/huggingface/datasets/json/autonlp-data-sentiment_detection-3c8bcd36-fe30267462d1d42b/0.0.0/d75ead8d5cfcbe67495df0f89bd262f0023257fbbbd94a730313295f3d756d50... 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 5/5 [00:00<00:00, 15923.71it/s] 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 5/5 [00:00<00:00, 3346.88it/s] Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/datasets/load.py", line 1112, in load_dataset builder_instance.download_and_prepare( File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/datasets/builder.py", line 636, in download_and_prepare self._download_and_prepare( File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/datasets/builder.py", line 726, in _download_and_prepare self._prepare_split(split_generator, **prepare_split_kwargs) File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/datasets/builder.py", line 1187, in _prepare_split writer.write_table(table) File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/datasets/arrow_writer.py", line 418, in write_table pa_table = pa.Table.from_arrays([pa_table[name] for name in self._schema.names], schema=self._schema) File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/datasets/arrow_writer.py", line 418, in <listcomp> pa_table = pa.Table.from_arrays([pa_table[name] for name in self._schema.names], schema=self._schema) File "pyarrow/table.pxi", line 1249, in pyarrow.lib.Table.__getitem__ File "pyarrow/table.pxi", line 1825, in pyarrow.lib.Table.column File "pyarrow/table.pxi", line 1800, in pyarrow.lib.Table._ensure_integer_index KeyError: 'Field "splits" does not exist in table schema' ``` Call with `streaming=False`: ``` 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 6000.43it/s] Using custom data configuration autonlp-data-sentiment_detection-3c8bcd36-fe30267462d1d42b 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 5/5 [00:00<00:00, 46916.15it/s] 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 5/5 [00:00<00:00, 148734.18it/s] ``` ## Environment info - `datasets` version: 1.12.1.dev0 - Platform: Linux-5.11.0-1017-aws-x86_64-with-glibc2.29 - Python version: 3.8.11 - PyArrow version: 4.0.1
2022-04-12T10:09:40Z
https://github.com/huggingface/datasets/issues/2923
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Fix conversion of multidim arrays in list to arrow
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Arrow only supports 1-dim arrays. Previously we were converting all the numpy arrays to python list before instantiating arrow arrays to workaround this limitation. However in #2361 we started to keep numpy arrays in order to keep their dtypes. It works when we pass any multi-dim numpy array (the conversion to arrow has been added on our side), but not for lists of multi-dim numpy arrays. In this PR I added two strategies: - one that takes a list of multi-dim numpy arrays on returns an arrow array in an optimized way (more common case) - one that takes a list of possibly very nested data (lists, dicts, tuples) containing multi-dim arrays. This one is less optimized since it converts all the multi-dim numpy arrays into lists of 1-d arrays for compatibility with arrow. This strategy is simpler that just trying to create the arrow array from a possibly very nested data structure, but in the future we can improve it if needed. Fix https://github.com/huggingface/datasets/issues/2921
2021-09-15T17:22:52Z
https://github.com/huggingface/datasets/pull/2922
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Using a list of multi-dim numpy arrays raises an error "can only convert 1-dimensional array values"
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2021-09-15T17:12:11Z
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MEMBER
This error has been introduced in https://github.com/huggingface/datasets/pull/2361 To reproduce: ```python import numpy as np from datasets import Dataset d = Dataset.from_dict({"a": [np.zeros((2, 2))]}) ``` raises ```python Traceback (most recent call last): File "playground/ttest.py", line 5, in <module> d = Dataset.from_dict({"a": [np.zeros((2, 2))]}).with_format("torch") File "/Users/quentinlhoest/Desktop/hf/nlp/src/datasets/arrow_dataset.py", line 458, in from_dict pa_table = InMemoryTable.from_pydict(mapping=mapping) File "/Users/quentinlhoest/Desktop/hf/nlp/src/datasets/table.py", line 365, in from_pydict return cls(pa.Table.from_pydict(*args, **kwargs)) File "pyarrow/table.pxi", line 1639, in pyarrow.lib.Table.from_pydict File "pyarrow/array.pxi", line 332, in pyarrow.lib.asarray File "pyarrow/array.pxi", line 223, in pyarrow.lib.array File "pyarrow/array.pxi", line 110, in pyarrow.lib._handle_arrow_array_protocol File "/Users/quentinlhoest/Desktop/hf/nlp/src/datasets/arrow_writer.py", line 107, in __arrow_array__ out = pa.array(self.data, type=type) File "pyarrow/array.pxi", line 306, in pyarrow.lib.array File "pyarrow/array.pxi", line 39, in pyarrow.lib._sequence_to_array File "pyarrow/error.pxi", line 143, in pyarrow.lib.pyarrow_internal_check_status File "pyarrow/error.pxi", line 99, in pyarrow.lib.check_status pyarrow.lib.ArrowInvalid: Can only convert 1-dimensional array values
2021-09-15T17:21:45Z
https://github.com/huggingface/datasets/issues/2921
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2021-09-15T17:18:24Z
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Fix unwanted tqdm bar when accessing examples
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A change in #2814 added bad progress bars in `map_nested`. Now they're disabled by default Fix #2919
2021-09-15T17:18:24Z
https://github.com/huggingface/datasets/pull/2920
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Unwanted progress bars when accessing examples
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2021-09-15T14:05:10Z
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When accessing examples from a dataset formatted for pytorch, some progress bars appear when accessing examples: ```python In [1]: import datasets as ds In [2]: d = ds.Dataset.from_dict({"a": [0, 1, 2]}).with_format("torch") In [3]: d[0] 100%|████████████████████████████████| 1/1 [00:00<00:00, 3172.70it/s] Out[3]: {'a': tensor(0)} ``` This is because the pytorch formatter calls `map_nested` that uses progress bars cc @sgugger
2021-09-15T17:21:49Z
https://github.com/huggingface/datasets/issues/2919
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`Can not decode content-encoding: gzip` when loading `scitldr` dataset with streaming
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2021-09-15T13:06:07Z
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## Describe the bug Trying to load the `"FullText"` config of the `"scitldr"` dataset with `streaming=True` raises an error from `aiohttp`: ```python ClientPayloadError: 400, message='Can not decode content-encoding: gzip' ``` cc @lhoestq ## Steps to reproduce the bug ```python from datasets import load_dataset iter_dset = iter( load_dataset("scitldr", name="FullText", split="test", streaming=True) ) next(iter_dset) ``` ## Expected results Returns the first sample of the dataset ## Actual results Calling `__next__` crashes with the following Traceback: ```python ----> 1 next(dset_iter) ~\miniconda3\envs\datasets\lib\site-packages\datasets\iterable_dataset.py in __iter__(self) 339 340 def __iter__(self): --> 341 for key, example in self._iter(): 342 if self.features: 343 # we encode the example for ClassLabel feature types for example ~\miniconda3\envs\datasets\lib\site-packages\datasets\iterable_dataset.py in _iter(self) 336 else: 337 ex_iterable = self._ex_iterable --> 338 yield from ex_iterable 339 340 def __iter__(self): ~\miniconda3\envs\datasets\lib\site-packages\datasets\iterable_dataset.py in __iter__(self) 76 77 def __iter__(self): ---> 78 for key, example in self.generate_examples_fn(**self.kwargs): 79 yield key, example 80 ~\.cache\huggingface\modules\datasets_modules\datasets\scitldr\72d6e2195786c57e1d343066fb2cc4f93ea39c5e381e53e6ae7c44bbfd1f05ef\scitldr.py in _generate_examples(self, filepath, split) 162 163 with open(filepath, encoding="utf-8") as f: --> 164 for id_, row in enumerate(f): 165 data = json.loads(row) 166 if self.config.name == "AIC": ~\miniconda3\envs\datasets\lib\site-packages\fsspec\implementations\http.py in read(self, length) 496 else: 497 length = min(self.size - self.loc, length) --> 498 return super().read(length) 499 500 async def async_fetch_all(self): ~\miniconda3\envs\datasets\lib\site-packages\fsspec\spec.py in read(self, length) 1481 # don't even bother calling fetch 1482 return b"" -> 1483 out = self.cache._fetch(self.loc, self.loc + length) 1484 self.loc += len(out) 1485 return out ~\miniconda3\envs\datasets\lib\site-packages\fsspec\caching.py in _fetch(self, start, end) 378 elif start < self.start: 379 if self.end - end > self.blocksize: --> 380 self.cache = self.fetcher(start, bend) 381 self.start = start 382 else: ~\miniconda3\envs\datasets\lib\site-packages\fsspec\asyn.py in wrapper(*args, **kwargs) 86 def wrapper(*args, **kwargs): 87 self = obj or args[0] ---> 88 return sync(self.loop, func, *args, **kwargs) 89 90 return wrapper ~\miniconda3\envs\datasets\lib\site-packages\fsspec\asyn.py in sync(loop, func, timeout, *args, **kwargs) 67 raise FSTimeoutError 68 if isinstance(result[0], BaseException): ---> 69 raise result[0] 70 return result[0] 71 ~\miniconda3\envs\datasets\lib\site-packages\fsspec\asyn.py in _runner(event, coro, result, timeout) 23 coro = asyncio.wait_for(coro, timeout=timeout) 24 try: ---> 25 result[0] = await coro 26 except Exception as ex: 27 result[0] = ex ~\miniconda3\envs\datasets\lib\site-packages\fsspec\implementations\http.py in async_fetch_range(self, start, end) 538 if r.status == 206: 539 # partial content, as expected --> 540 out = await r.read() 541 elif "Content-Length" in r.headers: 542 cl = int(r.headers["Content-Length"]) ~\miniconda3\envs\datasets\lib\site-packages\aiohttp\client_reqrep.py in read(self) 1030 if self._body is None: 1031 try: -> 1032 self._body = await self.content.read() 1033 for trace in self._traces: 1034 await trace.send_response_chunk_received( ~\miniconda3\envs\datasets\lib\site-packages\aiohttp\streams.py in read(self, n) 342 async def read(self, n: int = -1) -> bytes: 343 if self._exception is not None: --> 344 raise self._exception 345 346 # migration problem; with DataQueue you have to catch ClientPayloadError: 400, message='Can not decode content-encoding: gzip' ``` ## Environment info - `datasets` version: 1.12.0 - Platform: Windows-10-10.0.19041-SP0 - Python version: 3.8.5 - PyArrow version: 2.0.0 - aiohttp version: 3.7.4.post0
2021-12-01T08:15:00Z
https://github.com/huggingface/datasets/issues/2918
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2021-09-16T17:17:48Z
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windows download abnormal
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2021-09-15T12:45:35Z
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## Describe the bug The script clearly exists (accessible from the browser), but the script download fails on windows. Then I tried it again and it can be downloaded normally on linux. why?? ## Steps to reproduce the bug ```python3.7 + windows ![image](https://user-images.githubusercontent.com/52347799/133436174-4303f847-55d5-434f-a749-08da3bb9b654.png) # Sample code to reproduce the bug ``` ## Expected results It can be downloaded normally. ## Actual results it cann't ## Environment info <!-- You can run the command `datasets-cli env` and copy-and-paste its output below. --> - `datasets` version:1.11.0 - Platform:windows - Python version:3.7 - PyArrow version:
2021-09-16T17:17:48Z
https://github.com/huggingface/datasets/issues/2917
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2021-11-12T14:19:50Z
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Add OpenAI's pass@k code evaluation metric
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2021-09-15T12:05:43Z
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MEMBER
This PR introduces the `code_eval` metric which implements [OpenAI's code evaluation harness](https://github.com/openai/human-eval) introduced in the [Codex paper](https://arxiv.org/abs/2107.03374). It is heavily based on the original implementation and just adapts the interface to follow the `predictions`/`references` convention. The addition of this metric should enable the evaluation against the code evaluation datasets added in #2897 and #2893. A few open questions: - The implementation makes heavy use of multiprocessing which this PR does not touch. Is this conflicting with multiprocessing natively integrated in `datasets`? - This metric executes generated Python code and as such it poses dangers of executing malicious code. OpenAI addresses this issue by 1) commenting the `exec` call in the code so the user has to actively uncomment it and read the warning and 2) suggests using a sandbox environment (gVisor container). Should we add a similar safeguard? E.g. a prompt that needs to be answered when initialising the metric? Or at least a warning message? - Naming: the implementation sticks to the `predictions`/`references` naming, however, the references are not reference solutions but unittest to test the solution. While reference solutions are also available they are not used. Should the naming be adapted?
2021-11-12T14:19:51Z
https://github.com/huggingface/datasets/pull/2916
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2021-09-15T11:35:24Z
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Fix fsspec AbstractFileSystem access
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2021-09-15T09:39:20Z
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CONTRIBUTOR
This addresses the issue from #2914 by changing the way fsspec's AbstractFileSystem is accessed.
2021-09-15T11:35:24Z
https://github.com/huggingface/datasets/pull/2915
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2021-09-15T16:49:16Z
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Having a dependency defining fsspec entrypoint raises an AttributeError when importing datasets
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2021-09-15T07:54:06Z
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CONTRIBUTOR
## Describe the bug In one of my project, I defined a custom fsspec filesystem with an entrypoint. My guess is that by doing so, a variable named `spec` is created in the module `fsspec` (created by entering a for loop as there are entrypoints defined, see the loop in question [here](https://github.com/intake/filesystem_spec/blob/0589358d8a029ed6b60d031018f52be2eb721291/fsspec/__init__.py#L55)). So that `fsspec.spec`, that was previously referring to the `spec` submodule, is now referring to that `spec` variable. This make the import of datasets failing as it is using that `fsspec.spec`. ## Steps to reproduce the bug I could reproduce the bug with a dummy poetry project. Here is the pyproject.toml: ```toml [tool.poetry] name = "debug-datasets" version = "0.1.0" description = "" authors = ["Pierre Godard"] [tool.poetry.dependencies] python = "^3.8" datasets = "^1.11.0" [tool.poetry.dev-dependencies] [build-system] requires = ["poetry-core>=1.0.0"] build-backend = "poetry.core.masonry.api" [tool.poetry.plugins."fsspec.specs"] "file2" = "fsspec.implementations.local.LocalFileSystem" ``` The only other file being a `debug_datasets/__init__.py` empty file. The overall structure of the project is as follows: ``` . ├── pyproject.toml └── debug_datasets └── __init__.py ``` Then, within the project folder run: ``` poetry install poetry run python ``` And in the python interpreter, try to import `datasets`: ``` import datasets ``` ## Expected results The import should run successfully. ## Actual results Here is the trace of the error I get: ``` Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/home/godarpi/.cache/pypoetry/virtualenvs/debug-datasets-JuFzTKL--py3.8/lib/python3.8/site-packages/datasets/__init__.py", line 33, in <module> from .arrow_dataset import Dataset, concatenate_datasets File "/home/godarpi/.cache/pypoetry/virtualenvs/debug-datasets-JuFzTKL--py3.8/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 48, in <module> from .filesystems import extract_path_from_uri, is_remote_filesystem File "/home/godarpi/.cache/pypoetry/virtualenvs/debug-datasets-JuFzTKL--py3.8/lib/python3.8/site-packages/datasets/filesystems/__init__.py", line 30, in <module> def is_remote_filesystem(fs: fsspec.spec.AbstractFileSystem) -> bool: AttributeError: 'EntryPoint' object has no attribute 'AbstractFileSystem' ``` ## Suggested fix `datasets/filesystems/__init__.py`, line 30, replace: ``` def is_remote_filesystem(fs: fsspec.spec.AbstractFileSystem) -> bool: ``` by: ``` def is_remote_filesystem(fs: fsspec.AbstractFileSystem) -> bool: ``` I will come up with a PR soon if this effectively solves the issue. ## Environment info <!-- You can run the command `datasets-cli env` and copy-and-paste its output below. --> - `datasets` version: 1.11.0 - Platform: WSL2 (Ubuntu 20.04.1 LTS) - Python version: 3.8.5 - PyArrow version: 5.0.0 - `fsspec` version: 2021.8.1
2021-09-15T16:49:17Z
https://github.com/huggingface/datasets/issues/2914
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2021-09-15T08:05:18Z
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timit_asr dataset only includes one text phrase
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2021-09-14T21:06:07Z
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## Describe the bug The dataset 'timit_asr' only includes one text phrase. It only includes the transcription "Would such an act of refusal be useful?" multiple times rather than different phrases. ## Steps to reproduce the bug Note: I am following the tutorial https://huggingface.co/blog/fine-tune-wav2vec2-english 1. Install the dataset and other packages ```python !pip install datasets>=1.5.0 !pip install transformers==4.4.0 !pip install soundfile !pip install jiwer ``` 2. Load the dataset ```python from datasets import load_dataset, load_metric timit = load_dataset("timit_asr") ``` 3. Remove columns that we don't want ```python timit = timit.remove_columns(["phonetic_detail", "word_detail", "dialect_region", "id", "sentence_type", "speaker_id"]) ``` 4. Write a short function to display some random samples of the dataset. ```python from datasets import ClassLabel import random import pandas as pd from IPython.display import display, HTML def show_random_elements(dataset, num_examples=10): assert num_examples <= len(dataset), "Can't pick more elements than there are in the dataset." picks = [] for _ in range(num_examples): pick = random.randint(0, len(dataset)-1) while pick in picks: pick = random.randint(0, len(dataset)-1) picks.append(pick) df = pd.DataFrame(dataset[picks]) display(HTML(df.to_html())) show_random_elements(timit["train"].remove_columns(["file"])) ``` ## Expected results 10 random different transcription phrases. ## Actual results 10 of the same transcription phrase "Would such an act of refusal be useful?" ## Environment info <!-- You can run the command `datasets-cli env` and copy-and-paste its output below. --> - `datasets` version: 1.4.1 - Platform: macOS-10.15.7-x86_64-i386-64bit - Python version: 3.8.5 - PyArrow version: not listed
2021-09-15T08:05:19Z
https://github.com/huggingface/datasets/issues/2913
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Update link to Blog in docs footer
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2021-09-14T17:23:14Z
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Update link.
2021-09-15T07:59:23Z
https://github.com/huggingface/datasets/pull/2912
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Fix exception chaining
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2021-09-14T16:19:29Z
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Fix exception chaining to avoid tracebacks with message: `During handling of the above exception, another exception occurred:`
2021-09-16T15:04:44Z
https://github.com/huggingface/datasets/pull/2911
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feat: 🎸 pass additional arguments to get private configs + info
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2021-09-14T15:24:19Z
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`use_auth_token` can now be passed to the functions to get the configs or infos of private datasets on the hub
2021-09-15T16:19:09Z
https://github.com/huggingface/datasets/pull/2910
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2021-10-13T11:27:49Z
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fix anli splits
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2021-09-14T13:10:35Z
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I can't run the tests for dummy data, facing this error `ImportError while loading conftest '/home/zaid/tmp/fix_anli_splits/datasets/tests/conftest.py'. tests/conftest.py:10: in <module> from datasets import config E ImportError: cannot import name 'config' from 'datasets' (unknown location)`
2021-10-13T11:27:49Z
https://github.com/huggingface/datasets/pull/2909
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Update Zenodo metadata with creator names and affiliation
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This PR helps in prefilling author data when automatically generating the DOI after each release.
2021-09-14T14:29:25Z
https://github.com/huggingface/datasets/pull/2908
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add story_cloze dataset
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2021-09-14T12:36:53Z
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@lhoestq I have spent some time but I still I can't succeed in correctly testing the dummy_data.
2021-10-08T21:41:42Z
https://github.com/huggingface/datasets/pull/2907
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feat: 🎸 add a function to get a dataset config's split names
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2021-09-14T12:31:22Z
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Also: pass additional arguments (use_auth_token) to get private configs + info of private datasets on the hub Questions: - [x] I'm not sure how the versions work: I changed 1.12.1.dev0 to 1.12.1.dev1, was it correct? -> no: reverted - [x] Should I add a section in https://github.com/huggingface/datasets/blob/master/docs/source/load_hub.rst? (there is no section for get_dataset_infos) -> yes: added
2021-10-04T09:55:38Z
https://github.com/huggingface/datasets/pull/2906
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Update BibTeX entry
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2021-09-14T10:16:17Z
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Update BibTeX entry.
2021-09-14T12:25:37Z
https://github.com/huggingface/datasets/pull/2905
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FORCE_REDOWNLOAD does not work
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2021-09-14T09:45:26Z
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NONE
## Describe the bug With GenerateMode.FORCE_REDOWNLOAD, the documentation says +------------------------------------+-----------+---------+ | | Downloads | Dataset | +====================================+===========+=========+ | `REUSE_DATASET_IF_EXISTS` (default)| Reuse | Reuse | +------------------------------------+-----------+---------+ | `REUSE_CACHE_IF_EXISTS` | Reuse | Fresh | +------------------------------------+-----------+---------+ | `FORCE_REDOWNLOAD` | Fresh | Fresh | +------------------------------------+-----------+---------+ However, the old dataset is loaded even when FORCE_REDOWNLOAD is chosen. ## Steps to reproduce the bug ```python import pandas as pd from datasets import load_dataset, GenerateMode pd.DataFrame(range(5), columns=['numbers']).to_csv('/tmp/test.tsv.gz', index=False) ee = load_dataset('csv', data_files=['/tmp/test.tsv.gz'], delimiter='\t', split='train', download_mode=GenerateMode.FORCE_REDOWNLOAD) print(ee) pd.DataFrame(range(10), columns=['numerals']).to_csv('/tmp/test.tsv.gz', index=False) ee = load_dataset('csv', data_files=['/tmp/test.tsv.gz'], delimiter='\t', split='train', download_mode=GenerateMode.FORCE_REDOWNLOAD) print(ee) ``` ## Expected results Dataset({ features: ['numbers'], num_rows: 5 }) Dataset({ features: ['numerals'], num_rows: 10 }) ## Actual results Dataset({ features: ['numbers'], num_rows: 5 }) Dataset({ features: ['numbers'], num_rows: 5 }) ## Environment info <!-- You can run the command `datasets-cli env` and copy-and-paste its output below. --> - `datasets` version: 1.8.0 - Platform: Linux-4.14.181-108.257.amzn1.x86_64-x86_64-with-glibc2.10 - Python version: 3.7.10 - PyArrow version: 3.0.0
2021-10-06T09:37:19Z
https://github.com/huggingface/datasets/issues/2904
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Fix xpathopen to accept positional arguments
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2021-09-14T08:02:50Z
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Fix `xpathopen()` so that it also accepts positional arguments. Fix #2901.
2021-09-14T08:51:21Z
https://github.com/huggingface/datasets/pull/2903
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Add WIT Dataset
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CONTRIBUTOR
## Adding a Dataset - **Name:** *WIT* - **Description:** *Wikipedia-based Image Text Dataset* - **Paper:** *[WIT: Wikipedia-based Image Text Dataset for Multimodal Multilingual Machine Learning ](https://arxiv.org/abs/2103.01913)* - **Data:** *https://github.com/google-research-datasets/wit* - **Motivation:** (excerpt from their Github README.md) > - The largest multimodal dataset (publicly available at the time of this writing) by the number of image-text examples. > - A massively multilingual dataset (first of its kind) with coverage for over 100+ languages. > - A collection of diverse set of concepts and real world entities. > - Brings forth challenging real-world test sets. Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
2022-06-01T17:28:40Z
https://github.com/huggingface/datasets/issues/2902
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Incompatibility with pytest
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2021-09-13T19:12:17Z
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CONTRIBUTOR
## Describe the bug pytest complains about xpathopen / path.open("w") ## Steps to reproduce the bug Create a test file, `test.py`: ```python import datasets as ds def load_dataset(): ds.load_dataset("counter", split="train", streaming=True) ``` And launch it with pytest: ```bash python -m pytest test.py ``` ## Expected results It should give something like: ``` collected 1 item test.py . [100%] ======= 1 passed in 3.15s ======= ``` ## Actual results ``` ============================================================================================================================= test session starts ============================================================================================================================== platform linux -- Python 3.8.11, pytest-6.2.5, py-1.10.0, pluggy-1.0.0 rootdir: /home/slesage/hf/datasets-preview-backend, configfile: pyproject.toml plugins: anyio-3.3.1 collected 1 item tests/queries/test_rows.py . [100%]Traceback (most recent call last): File "/home/slesage/.pyenv/versions/3.8.11/lib/python3.8/runpy.py", line 194, in _run_module_as_main return _run_code(code, main_globals, None, File "/home/slesage/.pyenv/versions/3.8.11/lib/python3.8/runpy.py", line 87, in _run_code exec(code, run_globals) File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/pytest/__main__.py", line 5, in <module> raise SystemExit(pytest.console_main()) File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/_pytest/config/__init__.py", line 185, in console_main code = main() File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/_pytest/config/__init__.py", line 162, in main ret: Union[ExitCode, int] = config.hook.pytest_cmdline_main( File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/pluggy/_hooks.py", line 265, in __call__ return self._hookexec(self.name, self.get_hookimpls(), kwargs, firstresult) File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/pluggy/_manager.py", line 80, in _hookexec return self._inner_hookexec(hook_name, methods, kwargs, firstresult) File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/pluggy/_callers.py", line 60, in _multicall return outcome.get_result() File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/pluggy/_result.py", line 60, in get_result raise ex[1].with_traceback(ex[2]) File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/pluggy/_callers.py", line 39, in _multicall res = hook_impl.function(*args) File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/_pytest/main.py", line 316, in pytest_cmdline_main return wrap_session(config, _main) File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/_pytest/main.py", line 304, in wrap_session config.hook.pytest_sessionfinish( File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/pluggy/_hooks.py", line 265, in __call__ return self._hookexec(self.name, self.get_hookimpls(), kwargs, firstresult) File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/pluggy/_manager.py", line 80, in _hookexec return self._inner_hookexec(hook_name, methods, kwargs, firstresult) File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/pluggy/_callers.py", line 55, in _multicall gen.send(outcome) File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/_pytest/terminal.py", line 803, in pytest_sessionfinish outcome.get_result() File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/pluggy/_result.py", line 60, in get_result raise ex[1].with_traceback(ex[2]) File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/pluggy/_callers.py", line 39, in _multicall res = hook_impl.function(*args) File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/_pytest/cacheprovider.py", line 428, in pytest_sessionfinish config.cache.set("cache/nodeids", sorted(self.cached_nodeids)) File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/_pytest/cacheprovider.py", line 188, in set f = path.open("w") TypeError: xpathopen() takes 1 positional argument but 2 were given ``` ## Environment info - `datasets` version: 1.12.0 - Platform: Linux-5.11.0-1017-aws-x86_64-with-glibc2.29 - Python version: 3.8.11 - PyArrow version: 4.0.1
2021-09-14T08:40:47Z
https://github.com/huggingface/datasets/issues/2901
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Fix null sequence encoding
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2021-09-13T13:55:08Z
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The Sequence feature encoding was failing when a `None` sequence was used in a dataset. Fix https://github.com/huggingface/datasets/issues/2892
2021-09-13T14:17:43Z
https://github.com/huggingface/datasets/pull/2900
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Dataset
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## Adding a Dataset - **Name:** *name of the dataset* - **Description:** *short description of the dataset (or link to social media or blog post)* - **Paper:** *link to the dataset paper if available* - **Data:** *link to the Github repository or current dataset location* - **Motivation:** *what are some good reasons to have this dataset* Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
2021-09-12T16:12:15Z
https://github.com/huggingface/datasets/issues/2899
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Hug emoji
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## Adding a Dataset - **Name:** *name of the dataset* - **Description:** *short description of the dataset (or link to social media or blog post)* - **Paper:** *link to the dataset paper if available* - **Data:** *link to the Github repository or current dataset location* - **Motivation:** *what are some good reasons to have this dataset* Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
2021-09-12T16:13:13Z
https://github.com/huggingface/datasets/issues/2898
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Add OpenAI's HumanEval dataset
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2021-09-11T09:37:47Z
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This PR adds OpenAI's [HumanEval](https://github.com/openai/human-eval) dataset. The dataset consists of 164 handcrafted programming problems with solutions and unittests to verify solution. This dataset is useful to evaluate code generation models.
2021-09-16T15:02:11Z
https://github.com/huggingface/datasets/pull/2897
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2021-10-26T16:00:42Z
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add multi-proc in `to_csv`
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2021-09-10T21:35:09Z
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993,613,113
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CONTRIBUTOR
This PR extends the multi-proc method used in #2747 for`to_json` to `to_csv` as well. Results on my machine post benchmarking on `ascent_kb` dataset (giving ~45% improvement when compared to num_proc = 1): ``` Time taken on 1 num_proc, 10000 batch_size 674.2055702209473 Time taken on 4 num_proc, 10000 batch_size 425.6553490161896 Time taken on 1 num_proc, 50000 batch_size 623.5897650718689 Time taken on 4 num_proc, 50000 batch_size 380.0402421951294 Time taken on 4 num_proc, 100000 batch_size 361.7168130874634 ``` This is a WIP as writing tests is pending for this PR. I'm also exploring [this](https://arrow.apache.org/docs/python/csv.html#incremental-writing) approach for which I'm using `pyarrow-5.0.0`.
2021-10-28T05:47:33Z
https://github.com/huggingface/datasets/pull/2896
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2021-09-21T08:18:35Z
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Use pyarrow.Table.replace_schema_metadata instead of pyarrow.Table.cast
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2021-09-10T17:56:57Z
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CONTRIBUTOR
This PR partially addresses #2252. ``update_metadata_with_features`` uses ``Table.cast`` which slows down ``load_from_disk`` (and possibly other methods that use it) for very large datasets. Since ``update_metadata_with_features`` is only updating the schema metadata, it makes more sense to use ``pyarrow.Table.replace_schema_metadata`` which is much faster. This PR adds a ``replace_schema_metadata`` method to all table classes, and modifies ``update_metadata_with_features`` to use it instead of ``cast``.
2021-09-21T22:50:01Z
https://github.com/huggingface/datasets/pull/2895
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Fix COUNTER dataset
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2021-09-10T16:07:29Z
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Fix filename generating `FileNotFoundError`. Related to #2866. CC: @severo.
2021-09-10T16:27:45Z
https://github.com/huggingface/datasets/pull/2894
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add mbpp dataset
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2021-09-10T15:27:30Z
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This PR adds the mbpp dataset introduced by Google [here](https://github.com/google-research/google-research/tree/master/mbpp) as mentioned in #2816. The dataset contain two versions: a full and a sanitized one. They have a slightly different schema and it is current state the loading preserves the original schema. An open question is whether to harmonize the two schemas when loading the dataset or to preserve the original one. Since not all fields are overlapping the schema will not be exactly the same.
2021-09-16T09:35:42Z
https://github.com/huggingface/datasets/pull/2893
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Error when encoding a dataset with None objects with a Sequence feature
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2021-09-10T14:11:43Z
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There is an error when encoding a dataset with None objects with a Sequence feature To reproduce: ```python from datasets import Dataset, Features, Value, Sequence data = {"a": [[0], None]} features = Features({"a": Sequence(Value("int32"))}) dataset = Dataset.from_dict(data, features=features) ``` raises ```python --------------------------------------------------------------------------- TypeError Traceback (most recent call last) <ipython-input-24-40add67f8751> in <module> 2 data = {"a": [[0], None]} 3 features = Features({"a": Sequence(Value("int32"))}) ----> 4 dataset = Dataset.from_dict(data, features=features) [...] ~/datasets/features.py in encode_nested_example(schema, obj) 888 if isinstance(obj, str): # don't interpret a string as a list 889 raise ValueError("Got a string but expected a list instead: '{}'".format(obj)) --> 890 return [encode_nested_example(schema.feature, o) for o in obj] 891 # Object with special encoding: 892 # ClassLabel will convert from string to int, TranslationVariableLanguages does some checks TypeError: 'NoneType' object is not iterable ``` Instead, if should run without error, as if the `features` were not passed
2021-09-13T14:18:13Z
https://github.com/huggingface/datasets/issues/2892
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2021-10-29T09:37:17Z
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Allow dynamic first dimension for ArrayXD
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2021-09-10T11:52:52Z
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Add support for dynamic first dimension for ArrayXD features. See issue [#887](https://github.com/huggingface/datasets/issues/887). Following changes allow for `to_pylist` method of `ArrayExtensionArray` to return a list of numpy arrays where fist dimension can vary. @lhoestq Could you suggest how you want to extend test suit. For now I added only very limited testing.
2021-11-23T15:33:13Z
https://github.com/huggingface/datasets/pull/2891
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## Adding a Dataset - **Name:** *name of the dataset* - **Description:** *short description of the dataset (or link to social media or blog post)* - **Paper:** *link to the dataset paper if available* - **Data:** *link to the Github repository or current dataset location* - **Motivation:** *what are some good reasons to have this dataset* Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
2021-09-10T11:45:29Z
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## Adding a Dataset - **Name:** *name of the dataset* - **Description:** *short description of the dataset (or link to social media or blog post)* - **Paper:** *link to the dataset paper if available* - **Data:** *link to the Github repository or current dataset location* - **Motivation:** *what are some good reasons to have this dataset* Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
2021-09-10T11:45:54Z
https://github.com/huggingface/datasets/issues/2889
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v1.11.1 release date
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Hello, i need to use latest features in one of my packages but there have been no new datasets release since 2 months ago. When do you plan to publush v1.11.1 release?
2021-09-12T20:18:35Z
https://github.com/huggingface/datasets/issues/2888
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#2837 Use cache folder for lockfile
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Fixes #2837 Use a cache folder directory to store the FileLock. The issue was that the lock file was in a readonly folder.
2021-10-05T17:58:22Z
https://github.com/huggingface/datasets/pull/2887
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Adding an Elastic Search index to a Dataset
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## Describe the bug When trying to index documents from the squad dataset, the connection to ElasticSearch seems to break: Reusing dataset squad (/Users/andreasmotz/.cache/huggingface/datasets/squad/plain_text/1.0.0/d6ec3ceb99ca480ce37cdd35555d6cb2511d223b9150cce08a837ef62ffea453) 90%|████████████████████████████████████████████▉ | 9501/10570 [00:01<00:00, 6335.61docs/s] No error is thrown, but the indexing breaks ~90%. ## Steps to reproduce the bug ```python # Sample code to reproduce the bug from datasets import load_dataset from elasticsearch import Elasticsearch es = Elasticsearch() squad = load_dataset('squad', split='validation') index_name = "corpus" es_config = { "settings": { "number_of_shards": 1, "analysis": {"analyzer": {"stop_standard": {"type": "standard", " stopwords": "_english_"}}}, }, "mappings": { "properties": { "idx" : {"type" : "keyword"}, "title" : {"type" : "keyword"}, "text": { "type": "text", "analyzer": "standard", "similarity": "BM25" }, } }, } class IndexBuilder: """ Elastic search indexing of a corpus """ def __init__( self, *args, #corpus : None, dataset : squad, index_name = str, query = str, config = dict, **kwargs, ): #instantiate HuggingFace dataset self.dataset = dataset #instantiate ElasticSearch config self.config = config self.es = Elasticsearch() self.index_name = index_name self.query = query def elastic_index(self): print(self.es.info) self.es.indices.delete(index=self.index_name, ignore=[400, 404]) search_index = self.dataset.add_elasticsearch_index(column='context', host='localhost', port='9200', es_index_name=self.index_name, es_index_config=self.config) return search_index def exact_match_method(self, index): scores, retrieved_examples = index.get_nearest_examples('context', query=self.query, k=1) return scores, retrieved_examples if __name__ == "__main__": print(type(squad)) Index = IndexBuilder(dataset=squad, index_name='corpus_index', query='Where was Chopin born?', config=es_config) search_index = Index.elastic_index() scores, examples = Index.exact_match_method(search_index) print(scores, examples) for name in squad.column_names: print(type(squad[name])) ``` ## Environment info We run the code in Poetry. This might be the issue, since the script runs successfully in our local environment. Poetry: - Python version: 3.8 - PyArrow: 4.0.1 - Elasticsearch: 7.13.4 - datasets: 1.10.2 Local: - Python version: 3.8 - PyArrow: 3.0.0 - Elasticsearch: 7.7.1 - datasets: 1.7.0
2021-10-20T18:57:11Z
https://github.com/huggingface/datasets/issues/2885
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Add IC, SI, ER tasks to SUPERB
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This PR adds 3 additional classification tasks to SUPERB #### Intent Classification Dataset URL seems to be down at the moment :( See the note below. S3PRL source: https://github.com/s3prl/s3prl/blob/master/s3prl/downstream/fluent_commands/dataset.py Instructions: https://github.com/s3prl/s3prl/tree/master/s3prl/downstream#ic-intent-classification---fluent-speech-commands #### Speaker Identification Manual download script: ``` mkdir VoxCeleb1 cd VoxCeleb1 wget https://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox1_dev_wav_partaa wget https://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox1_dev_wav_partab wget https://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox1_dev_wav_partac wget https://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox1_dev_wav_partad cat vox1_dev* > vox1_dev_wav.zip unzip vox1_dev_wav.zip wget https://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox1_test_wav.zip unzip vox1_test_wav.zip # download the official SUPERB train-dev-test split wget https://raw.githubusercontent.com/s3prl/s3prl/master/s3prl/downstream/voxceleb1/veri_test_class.txt ``` S3PRL source: https://github.com/s3prl/s3prl/blob/master/s3prl/downstream/voxceleb1/dataset.py Instructions: https://github.com/s3prl/s3prl/tree/master/s3prl/downstream#sid-speaker-identification #### Intent Classification Manual download requires going through a slow application process, see the note below. S3PRL source: https://github.com/s3prl/s3prl/blob/master/s3prl/downstream/emotion/IEMOCAP_preprocess.py Instructions: https://github.com/s3prl/s3prl/tree/master/s3prl/downstream#er-emotion-recognition #### :warning: Note These datasets either require manual downloads or have broken/unstable links. You can get all necessary archives in this repo: https://huggingface.co/datasets/anton-l/superb_source_data_dumps/tree/main
2021-09-20T09:17:58Z
https://github.com/huggingface/datasets/pull/2884
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Fix data URLs and metadata in DocRED dataset
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The host of `docred` dataset has updated the `dev` data file. This PR: - Updates the dev URL - Updates dataset metadata This PR also fixes the URL of the `train_distant` split, which was wrong. Fix #2882.
2021-09-13T11:24:31Z
https://github.com/huggingface/datasets/pull/2883
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`load_dataset('docred')` results in a `NonMatchingChecksumError`
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2021-09-09T05:55:02Z
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## Describe the bug I get consistent `NonMatchingChecksumError: Checksums didn't match for dataset source files` errors when trying to execute `datasets.load_dataset('docred')`. ## Steps to reproduce the bug It is quasi only this code: ```python import datasets data = datasets.load_dataset('docred') ``` ## Expected results The DocRED dataset should be loaded without any problems. ## Actual results ``` NonMatchingChecksumError Traceback (most recent call last) <ipython-input-4-b1b83f25a16c> in <module> ----> 1 d = datasets.load_dataset('docred') ~/anaconda3/lib/python3.8/site-packages/datasets/load.py in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, ignore_verifications, keep_in_memory, save_infos, script_version, use_auth_token, task, streaming, **config_kwargs) 845 846 # Download and prepare data --> 847 builder_instance.download_and_prepare( 848 download_config=download_config, 849 download_mode=download_mode, ~/anaconda3/lib/python3.8/site-packages/datasets/builder.py in download_and_prepare(self, download_config, download_mode, ignore_verifications, try_from_hf_gcs, dl_manager, base_path, use_auth_token, **download_and_prepare_kwargs) 613 logger.warning("HF google storage unreachable. Downloading and preparing it from source") 614 if not downloaded_from_gcs: --> 615 self._download_and_prepare( 616 dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs 617 ) ~/anaconda3/lib/python3.8/site-packages/datasets/builder.py in _download_and_prepare(self, dl_manager, verify_infos, **prepare_split_kwargs) 673 # Checksums verification 674 if verify_infos: --> 675 verify_checksums( 676 self.info.download_checksums, dl_manager.get_recorded_sizes_checksums(), "dataset source files" 677 ) ~/anaconda3/lib/python3.8/site-packages/datasets/utils/info_utils.py in verify_checksums(expected_checksums, recorded_checksums, verification_name) 38 if len(bad_urls) > 0: 39 error_msg = "Checksums didn't match" + for_verification_name + ":\n" ---> 40 raise NonMatchingChecksumError(error_msg + str(bad_urls)) 41 logger.info("All the checksums matched successfully" + for_verification_name) 42 NonMatchingChecksumError: Checksums didn't match for dataset source files: ['https://drive.google.com/uc?export=download&id=1fDmfUUo5G7gfaoqWWvK81u08m71TK2g7'] ``` ## Environment info - `datasets` version: 1.11.0 - Platform: Linux-5.11.0-7633-generic-x86_64-with-glibc2.10 - Python version: 3.8.5 - PyArrow version: 5.0.0 This error also happened on my Windows-partition, after freshly installing python 3.9 and `datasets`. ## Remarks - I have already called `rm -rf /home/<user>/.cache/huggingface`, i.e., I have tried clearing the cache. - The problem does not exist for other datasets, i.e., it seems to be DocRED-specific.
2021-09-13T11:24:30Z
https://github.com/huggingface/datasets/issues/2882
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Add BIOSSES dataset
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Adding the biomedical semantic sentence similarity dataset, BIOSSES, listed in "Biomedical Datasets - BigScience Workshop 2021"
2021-09-13T14:20:40Z
https://github.com/huggingface/datasets/pull/2881
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2021-09-09T13:13:29Z
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Extend support for streaming datasets that use pathlib.Path stem/suffix
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2021-09-08T08:42:43Z
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This PR extends the support in streaming mode for datasets that use `pathlib`, by patching the properties `pathlib.Path.stem` and `pathlib.Path.suffix`. Related to #2876, #2874, #2866. CC: @severo
2021-09-09T13:13:29Z
https://github.com/huggingface/datasets/pull/2880
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In v1.4.1, all TIMIT train transcripts are "Would such an act of refusal be useful?"
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2021-09-07T18:53:45Z
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## Describe the bug Using version 1.4.1 of `datasets`, TIMIT transcripts are all the same. ## Steps to reproduce the bug I was following this tutorial - https://huggingface.co/blog/fine-tune-wav2vec2-english But here's a distilled repro: ```python !pip install datasets==1.4.1 from datasets import load_dataset timit = load_dataset("timit_asr", cache_dir="./temp") unique_transcripts = set(timit["train"]["text"]) print(unique_transcripts) assert len(unique_transcripts) > 1 ``` ## Expected results Expected the correct TIMIT data. Or an error saying that this version of `datasets` can't produce it. ## Actual results Every train transcript was "Would such an act of refusal be useful?" Every test transcript was "The bungalow was pleasantly situated near the shore." ## Environment info - `datasets` version: 1.4.1 - Platform: Darwin-18.7.0-x86_64-i386-64bit - Python version: 3.7.9 - PyTorch version (GPU?): 1.9.0 (False) - Tensorflow version (GPU?): not installed (NA) - Using GPU in script?: tried both - Using distributed or parallel set-up in script?: no -
2021-09-08T16:55:19Z
https://github.com/huggingface/datasets/issues/2879
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## Describe the bug Trying to load saved dataset or dataset directory from Amazon S3 on a Windows machine fails. Performing the same operation succeeds on non-windows environment (AWS Sagemaker). ## Steps to reproduce the bug ```python # Followed https://huggingface.co/docs/datasets/filesystems.html#loading-a-processed-dataset-from-s3 from datasets import load_from_disk from datasets.filesystems import S3FileSystem s3_file = "output of save_to_disk" s3_filesystem = S3FileSystem() load_from_disk(s3_file, fs=s3_filesystem) ``` ## Expected results load_from_disk succeeds without error ## Actual results Seems like it succeeds in pulling the file into a windows temp directory, as it exists in my system, but fails to process it. ``` Exception ignored in: <finalize object at 0x26409231ce0; dead> Traceback (most recent call last): File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\weakref.py", line 566, in __call__ return info.func(*info.args, **(info.kwargs or {})) File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\tempfile.py", line 817, in _cleanup cls._rmtree(name) File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\tempfile.py", line 813, in _rmtree _shutil.rmtree(name, onerror=onerror) File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 740, in rmtree return _rmtree_unsafe(path, onerror) File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 613, in _rmtree_unsafe _rmtree_unsafe(fullname, onerror) File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 613, in _rmtree_unsafe _rmtree_unsafe(fullname, onerror) File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 613, in _rmtree_unsafe _rmtree_unsafe(fullname, onerror) [Previous line repeated 2 more times] File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 618, in _rmtree_unsafe onerror(os.unlink, fullname, sys.exc_info()) File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\tempfile.py", line 805, in onerror cls._rmtree(path) File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\tempfile.py", line 813, in _rmtree _shutil.rmtree(name, onerror=onerror) File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 740, in rmtree return _rmtree_unsafe(path, onerror) File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 599, in _rmtree_unsafe onerror(os.scandir, path, sys.exc_info()) File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 596, in _rmtree_unsafe with os.scandir(path) as scandir_it: NotADirectoryError: [WinError 267] The directory name is invalid: 'C:\\Users\\grassycup\\AppData\\Local\\Temp\\tmp45f_qbma\\tests3bucket\\output\\test_output\\train\\dataset.arrow' Exception ignored in: <finalize object at 0x264091c7880; dead> Traceback (most recent call last): File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\weakref.py", line 566, in __call__ return info.func(*info.args, **(info.kwargs or {})) File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\tempfile.py", line 817, in _cleanup cls._rmtree(name) File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\tempfile.py", line 813, in _rmtree _shutil.rmtree(name, onerror=onerror) File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 740, in rmtree return _rmtree_unsafe(path, onerror) File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 613, in _rmtree_unsafe _rmtree_unsafe(fullname, onerror) File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 613, in _rmtree_unsafe _rmtree_unsafe(fullname, onerror) File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 613, in _rmtree_unsafe _rmtree_unsafe(fullname, onerror) [Previous line repeated 2 more times] File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 618, in _rmtree_unsafe onerror(os.unlink, fullname, sys.exc_info()) File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\tempfile.py", line 805, in onerror cls._rmtree(path) File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\tempfile.py", line 813, in _rmtree _shutil.rmtree(name, onerror=onerror) File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 740, in rmtree return _rmtree_unsafe(path, onerror) File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 599, in _rmtree_unsafe onerror(os.scandir, path, sys.exc_info()) File "C:\Users\grassycup\Anaconda3\envs\hello.world\lib\shutil.py", line 596, in _rmtree_unsafe with os.scandir(path) as scandir_it: NotADirectoryError: [WinError 267] The directory name is invalid: 'C:\\Users\\grassycup\\AppData\\Local\\Temp\\tmp45f_qbma\\tests3bucket\\output\\test_output\\train\\dataset.arrow' ``` ## Environment info <!-- You can run the command `datasets-cli env` and copy-and-paste its output below. --> - `datasets` version: 1.11.0 - Platform: Windows-10-10.0.19042-SP0 - Python version: 3.8.11 - PyArrow version: 3.0.0
2021-09-07T15:15:05Z
https://github.com/huggingface/datasets/issues/2878
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Don't keep the dummy data folder or dataset_infos.json when resolving data files
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2021-09-07T14:09:04Z
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When there's no dataset script, all the data files of a folder or a repository on the Hub are loaded as data files. There are already a few exceptions: - files starting with "." are ignored - the dataset card "README.md" is ignored - any file named "config.json" is ignored (currently it isn't used anywhere, but it could be used in the future to define splits or configs for example, but not 100% sure) However any data files in a folder named "dummy" should be ignored as well as they should only be used to test the dataset. Same for "dataset_infos.json" which should only be used to get the `dataset.info`
2021-09-29T09:05:38Z
https://github.com/huggingface/datasets/issues/2877
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2021-09-10T09:50:48Z
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Extend support for streaming datasets that use pathlib.Path.glob
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2021-09-07T13:43:45Z
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This PR extends the support in streaming mode for datasets that use `pathlib`, by patching the method `pathlib.Path.glob`. Related to #2874, #2866. CC: @severo
2021-09-10T09:50:49Z
https://github.com/huggingface/datasets/pull/2876
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Add Congolese Swahili speech datasets
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2021-09-07T12:13:50Z
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https://api.github.com/repos/huggingface/datasets/issues/2875
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MEMBER
## Adding a Dataset - **Name:** Congolese Swahili speech corpora - **Data:** https://gamayun.translatorswb.org/data/ Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md). Also related: https://mobile.twitter.com/OktemAlp/status/1435196393631764482
2021-09-07T12:13:50Z
https://github.com/huggingface/datasets/issues/2875
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2021-09-07T11:41:15Z
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Support streaming datasets that use pathlib
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2021-09-07T07:35:49Z
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This PR extends the support in streaming mode for datasets that use `pathlib.Path`. Related to: #2866. CC: @severo
2021-09-07T18:25:22Z
https://github.com/huggingface/datasets/pull/2874
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2021-09-17T20:47:37Z
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adding swedish_medical_ner
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2021-09-07T04:44:53Z
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CONTRIBUTOR
Adding the Swedish Medical NER dataset, listed in "Biomedical Datasets - BigScience Workshop 2021" Code refactored
2021-09-17T20:47:37Z
https://github.com/huggingface/datasets/pull/2873
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adding swedish_medical_ner
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2021-09-06T22:00:52Z
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Adding the Swedish Medical NER dataset, listed in "Biomedical Datasets - BigScience Workshop 2021"
2021-09-07T04:36:32Z
https://github.com/huggingface/datasets/pull/2872
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datasets.config.PYARROW_VERSION has no attribute 'major'
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CONTRIBUTOR
In the test_dataset_common.py script, line 288-289 ``` if datasets.config.PYARROW_VERSION.major < 3: packaged_datasets = [pd for pd in packaged_datasets if pd["dataset_name"] != "parquet"] ``` which throws the error below. `datasets.config.PYARROW_VERSION` itself return the string '4.0.1'. I have tested this on both datasets.__version_=='1.11.0' and '1.9.0'. I am using Mac OS. ``` import datasets datasets.config.PYARROW_VERSION.major --------------------------------------------------------------------------- AttributeError Traceback (most recent call last) /var/folders/1f/0wqmlgp90qjd5mpj53fnjq440000gn/T/ipykernel_73361/2547517336.py in <module> 1 import datasets ----> 2 datasets.config.PYARROW_VERSION.major AttributeError: 'str' object has no attribute 'major' ``` ## Environment info - `datasets` version: 1.11.0 - Platform: Darwin-20.6.0-x86_64-i386-64bit - Python version: 3.7.11 - PyArrow version: 4.0.1
2021-09-08T08:51:52Z
https://github.com/huggingface/datasets/issues/2871
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Fix three typos in two files for documentation
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2021-09-04T11:49:43Z
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CONTRIBUTOR
Changed "bacth_size" to "batch_size" (2x) Changed "intsructions" to "instructions"
2021-09-06T08:21:21Z
https://github.com/huggingface/datasets/pull/2870
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TypeError: 'NoneType' object is not callable
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2021-09-03T11:27:39Z
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NONE
## Describe the bug TypeError: 'NoneType' object is not callable ## Steps to reproduce the bug ```python from datasets import load_dataset, load_metric dataset = datasets.load_dataset("glue", 'cola') ``` ## Expected results A clear and concise description of the expected results. ## Actual results Specify the actual results or traceback. ## Environment info <!-- You can run the command `datasets-cli env` and copy-and-paste its output below. --> - `datasets` version: 1.11.0 - Platform: - Python version: 3.7 - PyArrow version:
2022-03-30T05:30:38Z
https://github.com/huggingface/datasets/issues/2869
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Add Common Objects in 3D (CO3D)
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2021-09-02T20:36:12Z
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987,139,146
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CONTRIBUTOR
## Adding a Dataset - **Name:** *Common Objects in 3D (CO3D)* - **Description:** *See blog post [here](https://ai.facebook.com/blog/common-objects-in-3d-dataset-for-3d-reconstruction)* - **Paper:** *[link to paper](https://arxiv.org/abs/2109.00512)* - **Data:** *[link to data](https://ai.facebook.com/datasets/co3d-downloads/)* - **Motivation:** *excerpt from above blog post:* > As the first data set of its kind, CO3D will aptly enable reconstruction of real-life 3D objects. Indeed, CO3D already provides training data to enable our NeRFormer to tackle the new-view synthesis (NVS) task. Here, photorealistic NVS is a major step on the path to fully immersive AR/VR effects, where objects can be virtually transported across different environments, which will allow connecting users by sharing or recollecting their experiences. > > Besides practical applications in AR/VR, we hope that the data set will become a standard testbed for the recent proliferation of methods (including NeRFormer, Implicit Differentiable Renderer, NeRF, and others) that reconstruct 3D scenes by means of an implicit shape model. > Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
2024-01-17T12:03:59Z
https://github.com/huggingface/datasets/issues/2868
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2021-09-16T09:23:44Z
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Add CaSiNo dataset
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2021-09-02T17:06:23Z
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CONTRIBUTOR
Hi. I request you to add our dataset to the repository. This data was recently published at NAACL 2021: https://aclanthology.org/2021.naacl-main.254.pdf
2021-09-16T15:12:54Z
https://github.com/huggingface/datasets/pull/2867
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"counter" dataset raises an error in normal mode, but not in streaming mode
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CONTRIBUTOR
## Describe the bug `counter` dataset raises an error on `load_dataset()`, but simply returns an empty iterator in streaming mode. ## Steps to reproduce the bug ```python >>> import datasets as ds >>> a = ds.load_dataset('counter', split="train", streaming=False) Using custom data configuration default Downloading and preparing dataset counter/default (download: 1.29 MiB, generated: 2.48 MiB, post-processed: Unknown size, total: 3.77 MiB) to /home/slesage/.cache/huggingface/datasets/counter/default/1.0.0/9f84962fa0f35bec5a34fe0bdff8681838d497008c457f7856c48654476ec0e9... Traceback (most recent call last): File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/datasets/builder.py", line 726, in _download_and_prepare self._prepare_split(split_generator, **prepare_split_kwargs) File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/datasets/builder.py", line 1124, in _prepare_split for key, record in utils.tqdm( File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/tqdm/std.py", line 1185, in __iter__ for obj in iterable: File "/home/slesage/.cache/huggingface/modules/datasets_modules/datasets/counter/9f84962fa0f35bec5a34fe0bdff8681838d497008c457f7856c48654476ec0e9/counter.py", line 161, in _generate_examples with derived_file.open(encoding="utf-8") as f: File "/home/slesage/.pyenv/versions/3.8.11/lib/python3.8/pathlib.py", line 1222, in open return io.open(self, mode, buffering, encoding, errors, newline, File "/home/slesage/.pyenv/versions/3.8.11/lib/python3.8/pathlib.py", line 1078, in _opener return self._accessor.open(self, flags, mode) FileNotFoundError: [Errno 2] No such file or directory: '/home/slesage/.cache/huggingface/datasets/downloads/extracted/b57aa6db5601a738e57b95c1fd8cced54ff28fc540efcdaf0f6c4f1bb5dfe211/COUNTER/0032p.xml' During handling of the above exception, another exception occurred: Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/datasets/load.py", line 1112, in load_dataset builder_instance.download_and_prepare( File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/datasets/builder.py", line 636, in download_and_prepare self._download_and_prepare( File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/datasets/builder.py", line 728, in _download_and_prepare raise OSError( OSError: Cannot find data file. Original error: [Errno 2] No such file or directory: '/home/slesage/.cache/huggingface/datasets/downloads/extracted/b57aa6db5601a738e57b95c1fd8cced54ff28fc540efcdaf0f6c4f1bb5dfe211/COUNTER/0032p.xml' ``` ```python >>> import datasets as ds >>> b = ds.load_dataset('counter', split="train", streaming=True) Using custom data configuration default >>> list(b) [] ``` ## Expected results An exception should be raised in streaming mode ## Actual results No exception is raised in streaming mode: there is no way to tell if something has broken or if the dataset is simply empty. ## Environment info - `datasets` version: 1.11.1.dev0 - Platform: Linux-5.11.0-1016-aws-x86_64-with-glibc2.29 - Python version: 3.8.11 - PyArrow version: 4.0.1
2021-10-14T09:24:09Z
https://github.com/huggingface/datasets/issues/2866
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2021-09-10T11:50:06Z
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Add MultiEURLEX dataset
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2021-09-02T09:42:24Z
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CONTRIBUTOR
**Add new MultiEURLEX Dataset** MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource). Each EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU. As with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels); this is multi-label classification task (given the text, predict multiple labels).
2021-09-10T11:50:06Z
https://github.com/huggingface/datasets/pull/2865
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Fix data URL in ToTTo dataset
https://api.github.com/repos/huggingface/datasets/issues/2864/events
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2021-09-02T05:25:08Z
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Data source host changed their data URL: google-research-datasets/ToTTo@cebeb43. Fix #2860.
2021-09-02T06:47:40Z
https://github.com/huggingface/datasets/pull/2864
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Update dataset URL
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2021-09-02T05:22:18Z
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2021-09-02T08:10:50Z
https://github.com/huggingface/datasets/pull/2863
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2021-09-02T09:52:03Z
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fix: 🐛 be more specific when catching exceptions
https://api.github.com/repos/huggingface/datasets/issues/2861/events
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2021-09-01T12:18:12Z
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The same specific exception is catched in other parts of the same function.
2021-09-02T09:53:36Z
https://github.com/huggingface/datasets/pull/2861
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Cannot download TOTTO dataset
https://api.github.com/repos/huggingface/datasets/issues/2860/events
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2021-09-01T11:04:10Z
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Error: Couldn't find file at https://storage.googleapis.com/totto/totto_data.zip `datasets version: 1.11.0` # How to reproduce: ```py from datasets import load_dataset dataset = load_dataset('totto') ```
2021-09-02T06:47:40Z
https://github.com/huggingface/datasets/issues/2860
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Loading allenai/c4 in streaming mode does too many HEAD requests
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2021-08-31T21:11:04Z
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This does 60,000+ HEAD requests to get all the ETags of all the data files: ```python from datasets import load_dataset load_dataset("allenai/c4", streaming=True) ``` It makes loading the dataset completely impractical. The ETags are used to compute the config id (it must depend on the data files being used). Instead of using the ETags, we could simply use the commit hash of the dataset repository on the hub, as well and the glob pattern used to resolve the files (here it's `*` by default, to load all the files of the repository)
2021-10-12T07:35:52Z
https://github.com/huggingface/datasets/issues/2859
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2021-08-31T21:29:51Z
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Fix s3fs version in CI
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2021-08-31T18:05:43Z
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The latest s3fs version has new constrains on aiobotocore, and therefore on boto3 and botocore This PR changes the constrains to avoid the new conflicts In particular it pins the version of s3fs.
2021-09-06T13:33:35Z
https://github.com/huggingface/datasets/pull/2858
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2021-09-07T09:44:32Z
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Update: Openwebtext - update size
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2021-08-31T17:11:03Z
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Update the size of the Openwebtext dataset I also regenerated the dataset_infos.json but the data file checksum didn't change, and the number of examples either (8013769 examples) Close #2839, close #726.
2022-02-15T10:38:03Z
https://github.com/huggingface/datasets/pull/2857
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2021-08-31T14:22:12Z
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fix: 🐛 remove URL's query string only if it's ?dl=1
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2021-08-31T13:40:07Z
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CONTRIBUTOR
A lot of URL use the query strings, for example http://opus.nlpl.eu/download.php?f=Bianet/v1/moses/en-ku.txt.zip, we must not remove it when trying to detect the protocol. We thus remove it only in the case of the query string being ?dl=1 which occurs on dropbox and dl.orangedox.com. Also: add unit tests. See https://github.com/huggingface/datasets/pull/2843 for the original discussion.
2021-08-31T14:22:12Z
https://github.com/huggingface/datasets/pull/2856
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2021-08-31T13:35:33Z
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Fix windows CI CondaError
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2021-08-31T13:22:02Z
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MEMBER
From this thread: https://github.com/conda/conda/issues/6057 We can fix the conda error ``` CondaError: Cannot link a source that does not exist. C:\Users\...\Anaconda3\Scripts\conda.exe ``` by doing ```bash conda update conda ``` before doing any install in the windows CI
2021-08-31T13:35:34Z
https://github.com/huggingface/datasets/pull/2855
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2021-08-31T13:13:36Z
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Fix caching when moving script
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2021-08-31T10:58:35Z
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When caching the result of a `map` function, the hash that is computed depends on many properties of this function, such as all the python objects it uses, its code and also the location of this code. Using the full path of the python script for the location of the code makes the hash change if a script like `run_mlm.py` is moved. I changed this by simply using the base name of the script instead of the full path. Note that this change also affects the hash of the code used from imported modules, but I think it's fine. Indeed it hashes the code of the imported modules anyway, so the location of the python files of the imported modules doesn't matter when computing the hash. Close https://github.com/huggingface/datasets/issues/2825
2021-08-31T13:13:36Z
https://github.com/huggingface/datasets/pull/2854
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2021-09-29T09:19:19Z
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Add AMI dataset
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2021-08-31T10:19:01Z
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This is an initial commit for AMI dataset
2021-09-29T09:19:19Z
https://github.com/huggingface/datasets/pull/2853
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Fix: linnaeus - fix url
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2021-08-31T08:51:13Z
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The url was causing a `ConnectionError` because of the "/" at the end Close https://github.com/huggingface/datasets/issues/2821
2021-08-31T13:12:10Z
https://github.com/huggingface/datasets/pull/2852
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Update `column_names` showed as `:func:` in exploring.st
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2021-08-30T13:21:46Z
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Hi, One mention of `column_names` in exploring.st was showing it as `:func:` instead of `:attr:`.
2021-09-01T08:42:11Z
https://github.com/huggingface/datasets/pull/2851
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Wound segmentation datasets
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2021-08-30T10:44:32Z
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## Adding a Dataset - **Name:** Wound segmentation datasets - **Description:** annotated wound image dataset - **Paper:** https://www.nature.com/articles/s41598-020-78799-w - **Data:** https://github.com/uwm-bigdata/wound-segmentation - **Motivation:** Interesting simple image dataset, useful for segmentation, with visibility due to http://www.miccai.org/special-interest-groups/challenges/ and https://fusc.grand-challenge.org/ Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
2021-12-08T12:02:00Z
https://github.com/huggingface/datasets/issues/2850
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Add Open Catalyst Project Dataset
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## Adding a Dataset - **Name:** Open Catalyst 2020 (OC20) Dataset - **Website:** https://opencatalystproject.org/ - **Data:** https://github.com/Open-Catalyst-Project/ocp/blob/master/DATASET.md Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
2021-08-30T10:14:39Z
https://github.com/huggingface/datasets/issues/2849
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Update README.md
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2021-08-28T23:58:26Z
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Changed 'Tain' to 'Train'.
2021-09-07T09:40:32Z
https://github.com/huggingface/datasets/pull/2848
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fix regex to accept negative timezone
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fix #2846
2021-09-13T20:39:50Z
https://github.com/huggingface/datasets/pull/2847
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Negative timezone
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2021-08-27T20:50:33Z
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## Describe the bug The load_dataset method do not accept a parquet file with a negative timezone, as it has the following regex: ``` "^(s|ms|us|ns),\s*tz=([a-zA-Z0-9/_+:]*)$" ``` So a valid timestap ```timestamp[us, tz=-03:00]``` returns an error when loading parquet files. ## Steps to reproduce the bug ```python # Where the timestamp column has a tz of -03:00 datasets = load_dataset('parquet', data_files={'train': train_files, 'validation': validation_files, 'test': test_files}, cache_dir="./cache_teste/") ``` ## Expected results The -03:00 is a valid tz so the regex should accept this without raising an error. ## Actual results As this regex disaproves a valid tz it raises the following error: ```python raise ValueError( f"{datasets_dtype} is not a validly formatted string representation of a pyarrow timestamp." f"Examples include timestamp[us] or timestamp[us, tz=America/New_York]" f"See: https://arrow.apache.org/docs/python/generated/pyarrow.timestamp.html#pyarrow.timestamp" ) ``` ## Environment info <!-- You can run the command `datasets-cli env` and copy-and-paste its output below. --> - `datasets` version: 1.11.0 - Platform: Ubuntu 20.04 - Python version: 3.8 - PyArrow version: 5.0.0
2021-09-10T11:51:07Z
https://github.com/huggingface/datasets/issues/2846
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[feature request] adding easy to remember `datasets.cache_dataset()` + `datasets.is_dataset_cached()`
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2021-08-27T18:21:51Z
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Often, there is a need to prepare a dataset but not use it immediately, e.g. think tests suite setup, so it'd be really useful to be able to do: ``` if not datasets.is_dataset_cached(ds): datasets.cache_dataset(ds) ``` This can already be done with: ``` builder = load_dataset_builder(ds) if not os.path.idsir(builder.cache_dir): builder.download_and_prepare() ``` but the current way is a way less intuitive and much harder to remember than the proposed API, IMHO. One more way is to do: ``` _ = load_dataset(ds) ``` but it wastes resources loading the dataset when it's not needed. this has been discussed at https://huggingface.slack.com/archives/C01229B19EX/p1630021912025800 Thank you! @lhoestq
2021-08-27T18:24:05Z
https://github.com/huggingface/datasets/issues/2845
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Fix: wikicorpus - fix keys
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2021-08-27T15:56:06Z
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As mentioned in https://github.com/huggingface/datasets/issues/2552, there is a duplicate keys error in `wikicorpus`. I fixed that by taking into account the file index in the keys
2021-09-06T14:07:28Z
https://github.com/huggingface/datasets/pull/2844
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Fix extraction protocol inference from urls with params
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Previously it was unable to infer the compression protocol for files at URLs like ``` https://foo.bar/train.json.gz?dl=1 ``` because of the query parameters. I fixed that, this should allow 10+ datasets to work in streaming mode: ``` "discovery", "emotion", "grail_qa", "guardian_authorship", "pragmeval", "simple_questions_v2", "versae/adobo", "w-nicole/childes_data", "w-nicole/childes_data_no_tags_", "w-nicole/childes_data_with_tags", "w-nicole/childes_data_with_tags_" ``` cc @severo
2021-08-30T17:11:49Z
https://github.com/huggingface/datasets/pull/2843
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always requiring the username in the dataset name when there is one
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2021-08-26T23:31:53Z
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https://api.github.com/repos/huggingface/datasets/issues/2842
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CONTRIBUTOR
Me and now another person have been bitten by the `datasets`'s non-strictness on requiring a dataset creator's username when it's due. So both of us started with `stas/openwebtext-10k`, somewhere along the lines lost `stas/` and continued using `openwebtext-10k` and it all was good until we published the software and things broke, since there is no `openwebtext-10k` So this feature request is asking to tighten the checking and not allow dataset loading if it was downloaded with the user prefix, but then attempted to be used w/o it. The same in code: ``` # first run python -c "from datasets import load_dataset; load_dataset('stas/openwebtext-10k')" # now run immediately python -c "from datasets import load_dataset; load_dataset('openwebtext-10k')" # the second command should fail, but it doesn't fail now. ``` Please let me know if I explained myself clearly. Thank you!
2021-10-22T09:43:35Z
https://github.com/huggingface/datasets/issues/2842
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Adding GLUECoS Hinglish and Spanglish code-switching bemchmark
https://api.github.com/repos/huggingface/datasets/issues/2841/events
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2021-08-26T17:47:39Z
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https://api.github.com/repos/huggingface/datasets/issues/2841
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MEMBER
## Adding a Dataset - **Name:** GLUECoS - **Description:** a Microsoft Benchmark to evaluate code-switching for only two language pairs but a variety of tasks - **Paper:** https://aclanthology.org/2020.acl-main.329/ - **Data:** https://github.com/microsoft/GLUECoS - **Motivation:** We currently only have [one other](https://huggingface.co/datasets/lince) dataset for code-switching Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
2021-10-20T18:41:20Z
https://github.com/huggingface/datasets/issues/2841
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