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Remove links in docs to old dataset viewer
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[ "_The documentation is not available anymore as the PR was closed or merged._" ]
2022-05-19T13:24:39Z
2022-05-20T15:24:28Z
2022-05-20T15:16:05Z
CONTRIBUTOR
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Remove the links in the docs to the no longer maintained dataset viewer.
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3,969
Cannot preview cnn_dailymail dataset
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[ "I guess the cache got corrupted due to a previous issue with Google Drive service.\r\n\r\nThe cache should be regenerated, e.g. by passing `download_mode=\"force_redownload\"`.\r\n\r\nCC: @severo ", "Note that the dataset preview uses its own cache, not `datasets`' cache. So `download_mode=\"force_redownload\"` ...
2022-03-19T14:08:57Z
2022-04-20T15:52:49Z
2022-04-20T15:52:49Z
NONE
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## Dataset viewer issue for '*cnn_dailymail*' **Link:** https://huggingface.co/datasets/cnn_dailymail *short description of the issue* Am I the one who added this dataset ? Yes-No
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from datasets import MoleculeDataset, GEOMDataset
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2021-03-06T15:50:19Z
2021-03-06T16:13:26Z
2021-03-06T16:13:26Z
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I met the ImportError: cannot import name 'MoleculeDataset' from 'datasets'. Have anyone met the similar issues? Thanks!
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ASSIN2 dataset checksum bug
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[ "Using latest code, I am still facing the issue.\r\n\r\n```python\r\n(base) vimos@vimosmu ➜ ~ ipython\r\nPython 3.6.7 | packaged by conda-forge | (default, Nov 6 2019, 16:19:42) \r\nType 'copyright', 'credits' or 'license' for more information\r\nIPython 7.11.1 -- An enhanced Interactive Python. Type '?' for help...
2022-03-24T10:08:50Z
2022-04-27T14:14:45Z
2022-03-28T13:56:39Z
CONTRIBUTOR
null
null
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## Describe the bug Checksum error after trying to load the [ASSIN 2 dataset](https://huggingface.co/datasets/assin2). `NonMatchingChecksumError` triggered by calling `load_dataset("assin2")`. Similar to #3952 , #3942 , #3941 , etc. ``` --------------------------------------------------------------------------- NonMatchingChecksumError Traceback (most recent call last) [<ipython-input-13-c664a92ad5e7>](https://localhost:8080/#) in <module>() ----> 1 load_dataset('assin2') 4 frames [/usr/local/lib/python3.7/dist-packages/datasets/utils/info_utils.py](https://localhost:8080/#) 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/u/0/uc?id=1Q9j1a83CuKzsHCGaNulSkNxBm7Dkn7Ln&export=download'] ``` ## Steps to reproduce the bug ```python from datasets import load_dataset load_dataset("assin2") ``` ## Expected results Load the dataset. ## Actual results The dataset won't load. ## Environment info - `datasets` version: 2.0.1.dev0 - Platform: Google Colab - Python version: 3.7.12 - PyArrow version: 6.0.1
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3,031
Align tqdm control with cache control
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[ "Could you add this function to the documentation please ?\r\n\r\nYou can add it in `main_classes.rst`, and maybe add a `Tip` section in the `map` section in the `process.rst`" ]
2021-10-05T15:18:49Z
2021-10-18T15:00:21Z
2021-10-18T14:59:30Z
CONTRIBUTOR
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Currently, once disabled with `disable_progress_bar`, progress bars cannot be re-enabled again. To overcome this limitation, this PR introduces the `set_progress_bar_enabled` function that accepts a boolean indicating whether to display progress bars. The goal is to provide a similar API to the existing cache control API. Following the Zen of Python (😄), there should be one and preferably only one obvious way to do it, so I'm also deprecating the aforementioned `disable_progress_bar` function. Additionally, I justify the deprecation with the fact that this function has never been in the docs. Moreover, similar API changes have recently been introduced to [`tfds`](https://github.com/tensorflow/datasets/blob/a1e8b98f45b0214082b546cc967c67c43fffda55/tensorflow_datasets/core/utils/tqdm_utils.py#L98-L112). Considering the popularity of the [comment](https://github.com/huggingface/datasets/issues/1627#issuecomment-751383559) I made a while ago, this API (`set_progress_bar_enabled` and `is_progress_bar_enabled`) should be mentioned in the docs, but I'm not sure where to put it exactly. Maybe we can replace the `logging_methods` page under `package_reference` with `utility_methods` and then introduce two subsections on that page: `Logging methods` and `tqdm control`. Additionally, this PR: * adds the `disable_tqdm` keyword arg of `Dataset._map_single` to the `ignore_kwargs` list to ignore it when computing the fingerprint (forgot to add it in #2696) * deletes the unused components in `tqdm_utils.py`, which seem to be inherited from `tfds` * disables the tqdm output in the test suite. As I see it, this output doesn't seem informative, but let me know if this is not a good idea
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Add non-commercial licensing info for datasets for which we removed tags
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[ "yep plus `license_details` also makes sense for this IMO" ]
2022-07-04T14:32:43Z
2022-07-08T14:27:29Z
null
MEMBER
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We removed several YAML tags saying that certain datasets can't be used for commercial purposes: https://github.com/huggingface/datasets/pull/4613#discussion_r911919753 Reason for this is that we only allow tags that are part of our [supported list of licenses](https://github.com/huggingface/datasets/blob/84fc3ad73c85de4eda5d152dfede7671491449cb/src/datasets/utils/resources/standard_licenses.tsv) We should update the Licensing Information section of the concerned dataset cards, now that the non-commercial tag doesn't exist anymore for certain datasets
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1,400,530,412
I_kwDODunzps5TemXs
5,088
load_datasets("json", ...) don't read local .json.gz properly
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[ "Hi @junwang-wish, thanks for reporting.\r\n\r\nUnfortunately, I'm not able to reproduce the bug. Which version of `datasets` are you using? Does the problem persist if you update `datasets`?\r\n```shell\r\npip install -U datasets\r\n``` ", "Thanks @albertvillanova I updated `datasets` from `2.5.1` to `2.5.2` and...
2022-10-07T02:16:58Z
2022-10-07T14:43:16Z
null
NONE
null
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## Describe the bug I have a local file `*.json.gz` and it can be read by `pandas.read_json(lines=True)`, but cannot be read by `load_datasets("json")` (resulting in 0 lines) ## Steps to reproduce the bug ```python fpath = '/data/junwang/.cache/general/57b6f2314cbe0bc45dda5b78f0871df2/test.json.gz' ds_panda = DatasetDict( test=Dataset.from_pandas( pd.read_json(fpath, lines=True) ) ) ds_direct = load_dataset( 'json', data_files={ 'test': fpath }, features=Features( text_input=Value(dtype="string", id=None), text_output=Value(dtype="string", id=None) ) ) len(ds_panda['test']), len(ds_direct['test']) ``` ## Expected results Lines of `ds_panda['test']` and `ds_direct['test']` should match. ## Actual results ``` Using custom data configuration default-c0ef2598760968aa Downloading and preparing dataset json/default to /data/junwang/.cache/huggingface/datasets/json/default-c0ef2598760968aa/0.0.0/e6070c77f18f01a5ad4551a8b7edfba20b8438b7cad4d94e6ad9378022ce4aab... Dataset json downloaded and prepared to /data/junwang/.cache/huggingface/datasets/json/default-c0ef2598760968aa/0.0.0/e6070c77f18f01a5ad4551a8b7edfba20b8438b7cad4d94e6ad9378022ce4aab. Subsequent calls will reuse this data. (62087, 0) ``` ## Environment info <!-- You can run the command `datasets-cli env` and copy-and-paste its output below. --> - `datasets` version: - Platform: Ubuntu 18.04.4 LTS - Python version: 3.8.13 - PyArrow version: 9.0.0
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change user permissions to -rw-r--r--
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[ "I tried this with `ade_corpus_v2` dataset. `ade_corpus_v2-train.arrow` (downloaded dataset) and `cache-25d41a4d3c2d8a25.arrow` (ran a mapping function on the dataset) both had file permission with octal value of `0644`. " ]
2021-03-19T18:14:56Z
2021-03-24T13:59:04Z
2021-03-24T13:59:04Z
CONTRIBUTOR
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Fix for #2065
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Add API code examples for Builder classes
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2022-05-10T22:22:32Z
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This PR adds API code examples for the Builder classes.
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Release 2.5.0 breaks transformers CI
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[ "Shall we revert https://github.com/huggingface/datasets/pull/4971 @mariosasko ?\r\n\r\nAnd for consistency we can update IterableDataset.map later" ]
2022-09-21T13:39:19Z
2022-09-21T14:11:57Z
2022-09-21T14:11:57Z
MEMBER
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## Describe the bug As reported by @lhoestq: > see https://app.circleci.com/pipelines/github/huggingface/transformers/47634/workflows/b491886b-e66e-4edb-af96-8b459e72aa25/jobs/564563 this is used here: [https://github.com/huggingface/transformers/blob/3b19c0317b6909e2d7f11b5053895ac55[…]torch/speech-pretraining/run_wav2vec2_pretraining_no_trainer.py](https://github.com/huggingface/transformers/blob/3b19c0317b6909e2d7f11b5053895ac55250e7da/examples/pytorch/speech-pretraining/run_wav2vec2_pretraining_no_trainer.py#L482-L488)
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init commit for MultiReQA for third PR with all issues fixed
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[ "good dataset card as well :) ", "@lhoestq Thank you :) " ]
2020-12-09T22:57:41Z
2020-12-11T13:37:08Z
2020-12-11T13:37:08Z
CONTRIBUTOR
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3rd PR w.r.t. PR #1349 with all the issues fixed. As #1349 had uploaded other files along with the multi_re_qa dataset
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[CI] Fix some warnings
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[ "_The documentation is not available anymore as the PR was closed or merged._", "There is a CI failure only related to the missing content of the universal_dependencies dataset card, we can ignore this failure in this PR", "good catch, I thought I resolved them all sorry", "Alright it should be good now" ]
2022-06-23T10:10:49Z
2022-06-28T14:10:57Z
2022-06-28T13:59:54Z
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There are some warnings in the CI that are annoying, I tried to remove most of them
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3863). All of your documentation changes will be reflected on that endpoint." ]
2022-03-08T15:34:43Z
2022-03-09T16:45:30Z
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Following https://github.com/huggingface/datasets/pull/3860#issuecomment-1061756712 and https://github.com/huggingface/datasets/pull/3690 we need to update the code blocks to use markdown instead of sphinx
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Add column type guessing from map return function
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[ "Thanks for working on this. However, having thought about this issue a bit more, supporting this doesn't seem like a good idea - it's better to be explicit than implicit, according to the Zen of Python 🙂. Also, I don't think many users would use this, so this raises the question of whether this is something we wa...
2023-07-25T00:34:17Z
2023-07-26T15:13:45Z
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As discussed [here](https://github.com/huggingface/datasets/issues/5965), there are some cases where datasets is unable to automatically promote columns during mapping. The fix is to explicitly provide a `features` definition so pyarrow can configure itself with the right column types from the outset. This PR provides an alternative approach, which is functionally equivalent to specifying features but a bit cleaner within a larger mapping pipeline. It allows clients to typehint the return variable coming from the mapper function - if we find one of these type annotations specified, and no explicit features have been passed in, we'll try to convert it into a Features map. If the map function runs and casting is unable to succeed, it will raise a DatasetTransformationNotAllowedError that indicates the typehint may be to blame. It works for batched and non-batched mapping functions. Currently supported column types: - builtins primitives: string, int, float, bool - dictionaries, lists (nested and one-deep) - Optional types and None-Unions (synonymous with optional types) It's used like: ```python class DatasetTyped(TypedDict): texts: list[str] def dataset_typed_map(batch) -> DatasetTyped: return {"texts": [text.split() for text in batch["raw_text"]]} dataset = {"raw_text": ["", "This is a test", "This is another test"]} with Dataset.from_dict(dataset) as dset: new_dataset = dset.map( dataset_typed_map, batched=True, batch_size=1, num_proc=1, ) ``` Open questions: - Should logging indicate we have automatically guessed these types? Or proceed quietly until we hit an error (as is the current implementation).
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add openwebtext2
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[ "It seems we need to `pip install jsonlines` to pass the checks ?", "Hi ! Do you really need `jsonlines` ? I think it simply uses `json.loads` under the hood.\r\n\r\nCurrently the test are failing because `jsonlines` is not part of the extra requirements `TESTS_REQUIRE` in setup.py\r\n\r\nSo either you can replac...
2021-08-14T07:09:03Z
2021-08-23T14:06:14Z
2021-08-23T14:06:14Z
CONTRIBUTOR
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openwebtext2 is part of EleutherAI/The Pile, but AFAIK, The Pile dataset blend all sub datasets together thus we are not able to use just one of its sub dataset from The Pile data. So I create an independent dataset using The Pile preliminary components. When I was creating dataset card. I found there is room for creating / editing dataset card. I've made it an issue. #2797 Also I am wondering whether the import of The Pile dataset is actively undertaken (because I may need it recently)? #1675
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Out of memory error on workers while running Beam+Dataflow
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[ "Some naive ideas to cope with this:\r\n- enable more RAM on each worker\r\n- force the spanning of more workers\r\n- others?", "@albertvillanova We were finally able to process the full NQ dataset on our machines using 600 gb with 5 workers. Maybe these numbers will work for you as well.", "Thanks a lot for th...
2022-06-20T07:28:12Z
2022-06-30T09:33:57Z
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## Describe the bug While running the preprocessing of the natural_question dataset (see PR #4368), there is an issue for the "default" config (train+dev files). Previously we ran the preprocessing for the "dev" config (only dev files) with success. Train data files are larger than dev ones and apparently workers run out of memory while processing them. Any help/hint is welcome! Error message: ``` Data channel closed, unable to receive additional data from SDK sdk-0-0 ``` Info from the Diagnostics tab: ``` Out of memory: Killed process 1882 (python) total-vm:6041764kB, anon-rss:3290928kB, file-rss:0kB, shmem-rss:0kB, UID:0 pgtables:9520kB oom_score_adj:900 The worker VM had to shut down one or more processes due to lack of memory. ``` ## Additional information ### Stack trace ``` Traceback (most recent call last): File "/home/albert_huggingface_co/natural_questions/venv/bin/datasets-cli", line 8, in <module> sys.exit(main()) File "/home/albert_huggingface_co/natural_questions/venv/lib/python3.9/site-packages/datasets/commands/datasets_cli.py", line 39, in main service.run() File "/home/albert_huggingface_co/natural_questions/venv/lib/python3.9/site-packages/datasets/commands/run_beam.py", line 127, in run builder.download_and_prepare( File "/home/albert_huggingface_co/natural_questions/venv/lib/python3.9/site-packages/datasets/builder.py", line 704, in download_and_prepare self._download_and_prepare( File "/home/albert_huggingface_co/natural_questions/venv/lib/python3.9/site-packages/datasets/builder.py", line 1389, in _download_and_prepare pipeline_results.wait_until_finish() File "/home/albert_huggingface_co/natural_questions/venv/lib/python3.9/site-packages/apache_beam/runners/dataflow/dataflow_runner.py", line 1667, in wait_until_finish raise DataflowRuntimeException( apache_beam.runners.dataflow.dataflow_runner.DataflowRuntimeException: Dataflow pipeline failed. State: FAILED, Error: Data channel closed, unable to receive additional data from SDK sdk-0-0 ``` ### Logs ``` Error message from worker: Data channel closed, unable to receive additional data from SDK sdk-0-0 Workflow failed. Causes: S30:train/ReadAllFromText/ReadAllFiles/Reshard/ReshufflePerKey/GroupByKey/Read+train/ReadAllFromText/ReadAllFiles/Reshard/ReshufflePerKey/GroupByKey/GroupByWindow+train/ReadAllFromText/ReadAllFiles/Reshard/ReshufflePerKey/FlatMap(restore_timestamps)+train/ReadAllFromText/ReadAllFiles/Reshard/RemoveRandomKeys+train/ReadAllFromText/ReadAllFiles/ReadRange+train/Map(_parse_example)+train/Encode+train/Count N. Examples+train/Get values/Values+train/Save to parquet/Write/WriteImpl/WindowInto(WindowIntoFn)+train/Save to parquet/Write/WriteImpl/WriteBundles+train/Save to parquet/Write/WriteImpl/Pair+train/Save to parquet/Write/WriteImpl/GroupByKey/Write failed., The job failed because a work item has failed 4 times. Look in previous log entries for the cause of each one of the 4 failures. For more information, see https://cloud.google.com/dataflow/docs/guides/common-errors. The work item was attempted on these workers: beamapp-alberthuggingface-06170554-5p23-harness-t4v9 Root cause: Data channel closed, unable to receive additional data from SDK sdk-0-0, beamapp-alberthuggingface-06170554-5p23-harness-t4v9 Root cause: The worker lost contact with the service., beamapp-alberthuggingface-06170554-5p23-harness-bwsj Root cause: The worker lost contact with the service., beamapp-alberthuggingface-06170554-5p23-harness-5052 Root cause: The worker lost contact with the service. ```
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Fix to_pandas for boolean ArrayXD
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[ "Thanks!" ]
2021-02-18T16:30:46Z
2021-02-18T17:10:03Z
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As noticed in #1887 the conversion of a dataset with a boolean ArrayXD feature types fails because of the underlying ListArray conversion to numpy requires `zero_copy_only=False`. zero copy is available for all primitive types except booleans see https://arrow.apache.org/docs/python/generated/pyarrow.Array.html#pyarrow.Array.to_numpy and https://issues.apache.org/jira/browse/ARROW-2871?jql=text%20~%20%22boolean%20to_numpy%22 cc @SBrandeis
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Add rmse and mae metrics.
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3844). All of your documentation changes will be reflected on that endpoint.", "@dnaveenr This PR is in pretty good shape, so feel free to reopen it." ]
2022-03-07T17:06:38Z
2022-03-07T17:24:32Z
2022-03-07T17:15:06Z
CONTRIBUTOR
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This PR adds RMSE - Root Mean Squared Error and MAE - Mean Absolute Error to the metrics API. Both implementations are based on usage of sciket-learn. Feature request here : Add support for continuous metrics (RMSE, MAE) [#3608](https://github.com/huggingface/datasets/issues/3608) Any suggestions and changes required will be helpful.
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Getting Value Error while loading a dataset..
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[ "Hi! I can't reproduce this error locally (Mac) or in Colab. What version of `datasets` are you using?", "Hi [mariosasko](https://github.com/mariosasko), the datasets version is '2.8.0'.", "@valmetisrinivas you get that error because you imported `datasets` (and thus `fsspec`) before installing `zstandard`.\r\n...
2022-12-23T08:16:43Z
2022-12-29T08:36:33Z
2022-12-27T17:59:09Z
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### Describe the bug I am trying to load a dataset using Hugging Face Datasets load_dataset method. I am getting the value error as show below. Can someone help with this? I am using Windows laptop and Google Colab notebook. ``` WARNING:datasets.builder:Using custom data configuration default-a1d9e8eaedd958cd --------------------------------------------------------------------------- ValueError Traceback (most recent call last) [<ipython-input-12-5b4fdcb8e6d5>](https://localhost:8080/#) in <module> 6 ) 7 ----> 8 next(iter(law_dataset_streamed)) 17 frames [/usr/local/lib/python3.8/dist-packages/fsspec/core.py](https://localhost:8080/#) in get_compression(urlpath, compression) 485 compression = infer_compression(urlpath) 486 if compression is not None and compression not in compr: --> 487 raise ValueError("Compression type %s not supported" % compression) 488 return compression 489 ValueError: Compression type zstd not supported ``` ### Steps to reproduce the bug ``` !pip install zstandard from datasets import load_dataset lds = load_dataset( "json", data_files="https://the-eye.eu/public/AI/pile_preliminary_components/FreeLaw_Opinions.jsonl.zst", split="train", streaming=True, ) ``` ### Expected behavior I expect an iterable object as the output 'lds' to be created. ### Environment info Windows laptop with Google Colab notebook
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OpenSLR 25: ASR data for Amharic, Swahili and Wolof
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[ "Whoever handles this just needs to: \r\n\r\n- [ ] fork the HuggingFace Datasets repo\r\n- [ ] update the [existing dataset script](https://github.com/huggingface/datasets/blob/master/datasets/openslr/openslr.py) to add SLR25. Lots of copypasting from other sections of the script should make that easy. \r\nAmharic ...
2021-09-28T15:04:36Z
2021-09-29T17:25:14Z
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CONTRIBUTOR
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## Adding a Dataset - **Name:** *SLR25* - **Description:** *Subset 25 from OpenSLR. Other subsets have been added to https://huggingface.co/datasets/openslr, 25 covers Amharic, Swahili and Wolof data* - **Paper:** *https://www.openslr.org/25/ has citations for each of the three subsubsets. * - **Data:** *Currently the three links to the .tar.bz2 files can be found a thttps://www.openslr.org/25/* - **Motivation:** *Increase ASR data for underrepresented African languages. Also, other subsets of OpenSLR speech recognition have been uploaded, so this would be easy.* https://github.com/huggingface/datasets/blob/master/datasets/openslr/openslr.py already has been created for various other OpenSLR subsets, this should be relatively straightforward to do.
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984,093,938
MDExOlB1bGxSZXF1ZXN0NzIzNTY5OTE4
2,857
Update: Openwebtext - update size
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[ "merging since the CI error in unrelated to this PR and fixed on master" ]
2021-08-31T17:11:03Z
2022-02-15T10:38:03Z
2021-09-07T09:44:32Z
MEMBER
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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.
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I_kwDODunzps5w_nNw
6,240
Dataloader stuck on multiple GPUs
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[ "What type of dataset are you using in this script? `torch.utils.data.Dataset` or `datasets.Dataset`? Please share the `datasets` package version if it's the latter. Otherwise, it's better to move this issue to the `accelerate` repo.", "Very sorry, I thought I had a repo in `accelerate!`\r\nI will close this issu...
2023-09-14T05:30:30Z
2023-09-14T23:54:42Z
2023-09-14T23:54:42Z
NONE
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### Describe the bug I am trying to get CLIP to fine-tuning with my code. When I tried to run it on multiple GPUs using accelerate, I encountered the following phenomenon. - Validation dataloader stuck in 2nd epoch only on multi-GPU Specifically, when the "for inputs in valid_loader:" process is finished, it does not proceed to the next step. train_loader process is completed. Also, both train and valid are working correctly in the first epoch. The accelerate command at that time is as follows. `accelerate launch --multi_gpu --num_processes=2 {script_name.py} {--arg1} {--arg2} ...` - This will not happen when single GPU is used. `CUDA_VISIBLE_DEVICES="0" accelerate launch {script_name.py} --arg1 --arg2 ...` - Setting num_workers=0 in dataloader did not change the result. ### Steps to reproduce the bug 1. The codes for fine-tuning the regular CLIP were updated for accelerate. 2. Run the code with the accelerate command as `accelerate launch --multi_gpu --num_processes=2 {script_name.py} {--arg1} {--arg2} ...` and the above problem will occur. 3. CUDA_VISIBLE_DEVICES="0" accelerate launch {script_name.py} --arg1 --arg2 ...` , it works fine. ### Expected behavior It Should end normally as if it was run on a single GPU. ### Environment info Since `datasets-cli env` did not work, the environment is described below. - OS: Ubuntu 22.04 with Docker - Docker: 24.0.5, build ced0996 - Python: 3.10.12 - torch==2.0.1 - accelerate==0.21.0 - transformers==4.33.1
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I_kwDODunzps5JAyc2
4,275
CommonSenseQA has missing and inconsistent field names
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[ "Thanks for reporting, @vblagoje.\r\n\r\nI'm opening a PR to address this. " ]
2022-05-04T05:38:59Z
2022-05-04T11:41:18Z
null
CONTRIBUTOR
null
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## Describe the bug In short, CommonSenseQA implementation is inconsistent with the original dataset. More precisely, we need to: 1. Add the dataset matching "id" field. The current dataset, instead, regenerates monotonically increasing id. 2. The [“question”][“stem”] field is flattened into "question". We should match the original dataset and unflatten it 3. Add the missing "question_concept" field in the question tree node 4. Anything else? Go over the data structure of the newly repaired CommonSenseQA and make sure it matches the original ## Expected results Every data item of the CommonSenseQA should structurally and data-wise match the original CommonSenseQA dataset. ## Actual results TBD ## Environment info - `datasets` version: 2.1.0 - Platform: macOS-10.15.7-x86_64-i386-64bit - Python version: 3.8.13 - PyArrow version: 7.0.0 - Pandas version: 1.4.2
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785,606,286
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1,737
update link in TLC to be github links
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[ "Thanks for updating this!" ]
2021-01-14T02:49:21Z
2021-01-14T10:25:24Z
2021-01-14T10:25:24Z
CONTRIBUTOR
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Base on this issue https://github.com/huggingface/datasets/issues/1064, I can now use the official links.
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Hendrycks Checksum
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[ "Thanks for reporting, @DanielHesslow. We are fixing it. ", "@albertvillanova thanks for taking care of this so quickly!", "The dataset metadata is fixed. You can download it normally." ]
2022-09-29T06:56:20Z
2022-09-29T10:23:30Z
2022-09-29T10:04:20Z
NONE
null
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null
Hi, The checksum for [hendrycks_test](https://huggingface.co/datasets/hendrycks_test) does not compare correctly, I guess it has been updated on the remote. ``` datasets.utils.info_utils.NonMatchingChecksumError: Checksums didn't match for dataset source files: ['https://people.eecs.berkeley.edu/~hendrycks/data.tar'] ```
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Map is slow and processes batches one after another
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[ "Hi @villmow, thanks for reporting.\r\n\r\nCould you please try with the Datasets version 1.6? We released it yesterday and it fixes some issues about the processing speed. You can see the fix implemented by @lhoestq here: #2122.\r\n\r\nOnce you update Datasets, please confirm if the problem persists.", "Hi @albe...
2021-04-20T14:58:20Z
2021-05-03T17:54:33Z
2021-05-03T17:54:32Z
NONE
null
null
null
## Describe the bug I have a somewhat unclear bug to me, where I can't figure out what the problem is. The code works as expected on a small subset of my dataset (2000 samples) on my local machine, but when I execute the same code with a larger dataset (1.4 million samples) this problem occurs. Thats why I can't give exact steps to reproduce, I'm sorry. I process a large dataset in a two step process. I first call map on a dataset I load from disk and create a new dataset from it. This works like expected and `map` uses all workers I started it with. Then I process the dataset created by the first step, again with `map`, which is really slow and starting only one or two process at a time. Number of processes is the same for both steps. pseudo code: ```python ds = datasets.load_from_disk("path") new_dataset = ds.map(work, batched=True, ...) # fast uses all processes final_dataset = new_dataset.map(work2, batched=True, ...) # slow starts one process after another ``` ## Expected results Second stage should be as fast as the first stage. ## Versions Paste the output of the following code: - Datasets: 1.5.0 - Python: 3.8.8 (default, Feb 24 2021, 21:46:12) - Platform: Linux-5.4.0-60-generic-x86_64-with-glibc2.10 Do you guys have any idea? Thanks a lot!
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Use a config id in the cache directory names for custom configs
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2021-01-20T11:11:00Z
2021-01-25T09:12:07Z
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As noticed by @JetRunner there was some issues when trying to generate a dataset using a custom config that is based on an existing config. For example in the following code the `mnli_custom` would reuse the cache used to create `mnli` instead of generating a new dataset with the new label classes: ```python from datasets import load_dataset mnli = load_dataset("glue", "mnli") mnli_custom = load_dataset("glue", "mnli", label_classes=["contradiction", "entailment", "neutral"]) ``` I fixed that by extending the cache directory definition of a dataset that is being generated. Instead of using the config name in the cache directory name, I switched to using a `config_id`. By default it is equal to the config name. However the name of a config is not sufficent to have a unique identifier for the dataset being generated since it doesn't take into account: - the config kwargs that can be used to overwrite attributes - the custom features used to write the dataset - the data_files for json/text/csv/pandas datasets Therefore the config id is just the config name with an optional suffix based on these. In particular taking into account the config kwargs fixes the issue with the `label_classes` above. I completed the current test cases by adding the case that was missing: overwriting an already existing config.
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4,385
Test dill
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[ "_The documentation is not available anymore as the PR was closed or merged._", "I should point out that the hash will be the same if computed twice with the same code on the same version of dill (after adding huggingface's code that removes line numbers and file names, and sorts globals.) My changes in dill 0.3....
2022-05-21T08:57:43Z
2022-05-25T08:30:13Z
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Regression test for future releases of `dill`. Related to #4379.
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Tilde (~) is not supported
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2023-04-16T11:48:10Z
2023-04-20T15:30:51Z
2023-04-20T15:30:51Z
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### Describe the bug It seems that `~` is not recognized correctly in local paths. Whenever I try to use it I get an exception ### Steps to reproduce the bug ```python load_dataset("imagefolder", data_dir="~/data/my_dataset") ``` Will generate the following error: ``` EmptyDatasetError: The directory at /path/to/cwd/~/data/datasets/clementine_tagged_per_cam doesn't contain any data files ``` ### Expected behavior Load the dataset. ### Environment info datasets==2.11.0
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Improve error message for missing function parameters
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2023-09-11T19:11:58Z
2023-09-15T18:07:56Z
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The error message in the fingerprint module was missing the f-string 'f' symbol, so the error message returned by fingerprint.py, line 469 was literally "function {func} is missing parameters {fingerprint_names} in signature." This has been fixed.
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2021-09-12T07:38:53Z
2021-09-12T16:12:15Z
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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).
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Fix map suffix_template
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2023-02-21T15:26:26Z
2023-02-21T17:21:37Z
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#5455 introduced a small bug that lead `map` to ignore the `suffix_template` argument and not put suffixes to cached files in multiprocessing. I fixed this and also improved a few things: - regarding logging: "Loading cached processed dataset" is now logged only once even in multiprocessing (it used to be logged `num_proc` times) - regarding new_fingerprint: I made sure that the returned dataset satisfies `ds._fingerprint==new_fingerprint` if `new_fingerprint` is passed to `map`
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Update `dataset_infos.json` with new split info in `Dataset.push_to_hub` to avoid verification error
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2022-05-27T17:03:42Z
2022-06-07T12:42:25Z
2022-06-07T12:33:52Z
CONTRIBUTOR
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Update `dataset_infos.json` when pushing splits one by one via `Dataset.push_to_hub` to avoid the splits verification error. TODO: ~~- [ ] handle token + `{Audio, Image}.embed_storage`~~ - [x] tests
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6,262
Fix CI 404 errors
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[ "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_a...
2023-09-27T07:40:18Z
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Currently our CI usually raises 404 errors when trying to delete temporary repositories. See, e.g.: https://github.com/huggingface/datasets/actions/runs/6314980985/job/17146507884 ``` FAILED tests/test_upstream_hub.py::TestPushToHub::test_push_dataset_dict_to_hub_multiple_files_with_max_shard_size - huggingface_hub.utils._errors.RepositoryNotFoundError: 404 Client Error. (Request ID: Root=1-6512fb99-4a52c561752ece3d77eb6d57;2b61cae4-613d-4a73-bbb1-2faf9e32b02d) Repository Not Found for url: https://hub-ci.huggingface.co/api/repos/delete. Please make sure you specified the correct `repo_id` and `repo_type`. If you are trying to access a private or gated repo, make sure you are authenticated. FAILED tests/test_upstream_hub.py::TestPushToHub::test_push_dataset_to_hub_custom_features_audio - huggingface_hub.utils._errors.RepositoryNotFoundError: 404 Client Error. (Request ID: Root=1-6512fbb2-0333dd666d42f0e173c2bb68;dfdc4271-b49b-4008-8c49-f05cf7c1d53d) Repository Not Found for url: https://hub-ci.huggingface.co/api/repos/delete. Please make sure you specified the correct `repo_id` and `repo_type`. If you are trying to access a private or gated repo, make sure you are authenticated. FAILED tests/test_upstream_hub.py::TestPushToHub::test_push_dataset_dict_to_hub_custom_splits - huggingface_hub.utils._errors.RepositoryNotFoundError: 404 Client Error. (Request ID: Root=1-6512fbca-167690694f39770a5b3a444e;baeaa905-0a57-4585-ac97-9aaae12dd47d) Repository Not Found for url: https://hub-ci.huggingface.co/api/repos/delete. Please make sure you specified the correct `repo_id` and `repo_type`. If you are trying to access a private or gated repo, make sure you are authenticated. ``` I think this can be caused by collisions in temporary repository IDs because we create them in multiprocessing: ```python with temporary_repo(f"{CI_HUB_USER}/test-{int(time.time() * 10e3)}") as ds_name: ``` This can also be caused when there is another issue that does not allow the creation of the repository, thus making it impossible to delete it. This PR tries to fix this issue by increasing the precision of the number on the repository ID: `10e6` instead of `10e3`. Additionally, this PR catches RepositoryNotFoundError.
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2022-06-06T02:24:32Z
2022-06-06T15:44:50Z
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import android.content.DialogInterface; import android.database.Cursor; import android.os.Bundle; import android.view.View; import android.widget.ArrayAdapter; import android.widget.Button; import android.widget.EditText; import android.widget.Toast; import androidx.appcompat.app.AlertDialog; import androidx.appcompat.app.AppCompatActivity; public class MainActivity extends AppCompatActivity { private EditText editTextID; private EditText editTextName; private EditText editTextNum; private String name; private int number; private String ID; private dbHelper db; @Override protected void onCreate(Bundle savedInstanceState) { super.onCreate(savedInstanceState); setContentView(R.layout.activity_main); db = new dbHelper(this); editTextID = findViewById(R.id.editText1); editTextName = findViewById(R.id.editText2); editTextNum = findViewById(R.id.editText3); Button buttonSave = findViewById(R.id.button); Button buttonRead = findViewById(R.id.button2); Button buttonUpdate = findViewById(R.id.button3); Button buttonDelete = findViewById(R.id.button4); Button buttonSearch = findViewById(R.id.button5); Button buttonDeleteAll = findViewById(R.id.button6); buttonSave.setOnClickListener(new View.OnClickListener() { @Override public void onClick(View v) { name = editTextName.getText().toString(); String num = editTextNum.getText().toString(); if (name.isEmpty() || num.isEmpty()) { Toast.makeText(MainActivity.this, "Cannot Submit Empty Fields", Toast.LENGTH_SHORT).show(); } else { number = Integer.parseInt(num); try { // Insert Data db.insertData(name, number); // Clear the fields editTextID.getText().clear(); editTextName.getText().clear(); editTextNum.getText().clear(); } catch (Exception e) { e.printStackTrace(); } } } }); buttonRead.setOnClickListener(new View.OnClickListener() { @Override public void onClick(View v) { final ArrayAdapter<String> adapter = new ArrayAdapter<>(MainActivity.this, android.R.layout.simple_list_item_1); String name; String num; String id; try { Cursor cursor = db.readData(); if (cursor != null && cursor.getCount() > 0) { while (cursor.moveToNext()) { id = cursor.getString(0); // get data in column index 0 name = cursor.getString(1); // get data in column index 1 num = cursor.getString(2); // get data in column index 2 // Add SQLite data to listView adapter.add("ID :- " + id + "\n" + "Name :- " + name + "\n" + "Number :- " + num + "\n\n"); } } else { adapter.add("No Data"); } cursor.close(); } catch (Exception e) { e.printStackTrace(); } // show the saved data in alertDialog AlertDialog.Builder builder = new AlertDialog.Builder(MainActivity.this); builder.setTitle("SQLite saved data"); builder.setIcon(R.mipmap.app_icon_foreground); builder.setAdapter(adapter, new DialogInterface.OnClickListener() { @Override public void onClick(DialogInterface dialog, int which) { } }); builder.setPositiveButton("OK", new DialogInterface.OnClickListener() { @Override public void onClick(DialogInterface dialog, int which) { dialog.cancel(); } }); AlertDialog dialog = builder.create(); dialog.show(); } }); buttonUpdate.setOnClickListener(new View.OnClickListener() { @Override public void onClick(View v) { name = editTextName.getText().toString(); String num = editTextNum.getText().toString(); ID = editTextID.getText().toString(); if (name.isEmpty() || num.isEmpty() || ID.isEmpty()) { Toast.makeText(MainActivity.this, "Cannot Submit Empty Fields", Toast.LENGTH_SHORT).show(); } else { number = Integer.parseInt(num); try { // Update Data db.updateData(ID, name, number); // Clear the fields editTextID.getText().clear(); editTextName.getText().clear(); editTextNum.getText().clear(); } catch (Exception e) { e.printStackTrace(); } } } }); buttonDelete.setOnClickListener(new View.OnClickListener() { @Override public void onClick(View v) { ID = editTextID.getText().toString(); if (ID.isEmpty()) { Toast.makeText(MainActivity.this, "Please enter the ID", Toast.LENGTH_SHORT).show(); } else { try { // Delete Data db.deleteData(ID); // Clear the fields editTextID.getText().clear(); editTextName.getText().clear(); editTextNum.getText().clear(); } catch (Exception e) { e.printStackTrace(); } } } }); buttonDeleteAll.setOnClickListener(new View.OnClickListener() { @Override public void onClick(View v) { // Delete all data // You can simply delete all the data by calling this method --> db.deleteAllData(); // You can try this also AlertDialog.Builder builder = new AlertDialog.Builder(MainActivity.this); builder.setIcon(R.mipmap.app_icon_foreground); builder.setTitle("Delete All Data"); builder.setCancelable(false); builder.setMessage("Do you really need to delete your all data ?"); builder.setPositiveButton("Yes", new DialogInterface.OnClickListener() { @Override public void onClick(DialogInterface dialog, int which) { // User confirmed , now you can delete the data db.deleteAllData(); // Clear the fields editTextID.getText().clear(); editTextName.getText().clear(); editTextNum.getText().clear(); } }); builder.setNegativeButton("No", new DialogInterface.OnClickListener() { @Override public void onClick(DialogInterface dialog, int which) { // user not confirmed dialog.cancel(); } }); AlertDialog dialog = builder.create(); dialog.show(); } }); buttonSearch.setOnClickListener(new View.OnClickListener() { @Override public void onClick(View v) { ID = editTextID.getText().toString(); if (ID.isEmpty()) { Toast.makeText(MainActivity.this, "Please enter the ID", Toast.LENGTH_SHORT).show(); } else { try { // Search data Cursor cursor = db.searchData(ID); if (cursor.moveToFirst()) { editTextName.setText(cursor.getString(1)); editTextNum.setText(cursor.getString(2)); Toast.makeText(MainActivity.this, "Data successfully searched", Toast.LENGTH_SHORT).show(); } else { Toast.makeText(MainActivity.this, "ID not found", Toast.LENGTH_SHORT).show(); editTextNum.setText("ID Not found"); editTextName.setText("ID not found"); } cursor.close(); } catch (Exception e) { e.printStackTrace(); } } } }); } }
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Fix bugs in NewsQA dataset
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2022-02-16T13:51:28Z
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Fix #3733.
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Allow dataset streaming from private a private source when loading a dataset with a dataset loading script
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[ "Hi ! What kind of private source ? We're exploring adding support for cloud storage and URIs like s3://, gs:// etc. with authentication in the download manager", "Hello! It's a google cloud storage, so gs://, but I'm using it with https.\r\nBeing able to provide a file system like [here](https://huggingface.co/d...
2022-11-15T16:02:10Z
2022-11-23T14:02:30Z
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### Feature request Add arguments to the function _get_authentication_headers_for_url_ like custom_endpoint and custom_token in order to add flexibility when downloading files from a private source. It should also be possible to provide these arguments from the dataset loading script, maybe giving them to the dl_manager ### Motivation It is possible to share a dataset hosted on another platform by writing a dataset loading script. It works perfectly for publicly available resources. For resources that require authentication, you can provide a [download_custom](https://huggingface.co/docs/datasets/package_reference/builder_classes#datasets.DownloadManager) method to the download_manager. Unfortunately, this function doesn't work with **dataset streaming**. A solution so as to allow dataset streaming from private sources would be a more flexible _get_authentication_headers_for_url_ function. ### Your contribution Would you be interested in this improvement ? If so I could provide a PR. I've got something working locally, but it's not very clean, I'd need some guidance regarding integration.
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Fix inferring module for unsupported data files
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[ "_The documentation is not available anymore as the PR was closed or merged._", "I think you can revert the last commit - it should fail if data_files={} IMO", "The validation of non-empty data_files is addressed in this PR:\r\n- #5802", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<det...
2023-04-24T10:44:50Z
2023-04-27T13:06:01Z
2023-04-27T12:57:28Z
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This PR raises a FileNotFoundError instead: ``` FileNotFoundError: No (supported) data files or dataset script found in <dataset_name> ``` Fix #5785.
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BioASQ AttributeError: 'BuilderConfig' object has no attribute 'schema'
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[ "Following worked:\r\n\r\n```\r\ndata_dir = \"/Users/dlituiev/repos/datasets/bioasq/\"\r\nbioasq_task_b = load_dataset(\"aps/bioasq_task_b\", data_dir=data_dir, name=\"bioasq_9b_source\")\r\n```\r\n\r\nWould maintainers be open to one of the following:\r\n- automating this with a latest default config (e.g. `bioas...
2022-09-09T16:06:43Z
2022-09-13T08:51:03Z
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## Describe the bug I am trying to load a dataset from drive and running into an error. ## Steps to reproduce the bug ```python data_dir = "/Users/dlituiev/repos/datasets/bioasq/BioASQ-training9b" bioasq_task_b = load_dataset("aps/bioasq_task_b", data_dir=data_dir) ``` ## Actual results `AttributeError: 'BuilderConfig' object has no attribute 'schema'` <details> ``` Using custom data configuration default-a1ca3e05be5abf2f --------------------------------------------------------------------------- AttributeError Traceback (most recent call last) Input In [8], in <cell line: 2>() 1 data_dir = "/Users/dlituiev/repos/datasets/bioasq/BioASQ-training9b" ----> 2 bioasq_task_b = load_dataset("aps/bioasq_task_b", data_dir=data_dir) File ~/opt/anaconda3/envs/spacy3/lib/python3.10/site-packages/datasets/load.py:1723, in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, ignore_verifications, keep_in_memory, save_infos, revision, use_auth_token, task, streaming, **config_kwargs) 1720 ignore_verifications = ignore_verifications or save_infos 1722 # Create a dataset builder -> 1723 builder_instance = load_dataset_builder( 1724 path=path, 1725 name=name, 1726 data_dir=data_dir, 1727 data_files=data_files, 1728 cache_dir=cache_dir, 1729 features=features, 1730 download_config=download_config, 1731 download_mode=download_mode, 1732 revision=revision, 1733 use_auth_token=use_auth_token, 1734 **config_kwargs, 1735 ) 1737 # Return iterable dataset in case of streaming 1738 if streaming: File ~/opt/anaconda3/envs/spacy3/lib/python3.10/site-packages/datasets/load.py:1526, in load_dataset_builder(path, name, data_dir, data_files, cache_dir, features, download_config, download_mode, revision, use_auth_token, **config_kwargs) 1523 raise ValueError(error_msg) 1525 # Instantiate the dataset builder -> 1526 builder_instance: DatasetBuilder = builder_cls( 1527 cache_dir=cache_dir, 1528 config_name=config_name, 1529 data_dir=data_dir, 1530 data_files=data_files, 1531 hash=hash, 1532 features=features, 1533 use_auth_token=use_auth_token, 1534 **builder_kwargs, 1535 **config_kwargs, 1536 ) 1538 return builder_instance File ~/opt/anaconda3/envs/spacy3/lib/python3.10/site-packages/datasets/builder.py:1154, in GeneratorBasedBuilder.__init__(self, writer_batch_size, *args, **kwargs) 1153 def __init__(self, *args, writer_batch_size=None, **kwargs): -> 1154 super().__init__(*args, **kwargs) 1155 # Batch size used by the ArrowWriter 1156 # It defines the number of samples that are kept in memory before writing them 1157 # and also the length of the arrow chunks 1158 # None means that the ArrowWriter will use its default value 1159 self._writer_batch_size = writer_batch_size or self.DEFAULT_WRITER_BATCH_SIZE File ~/opt/anaconda3/envs/spacy3/lib/python3.10/site-packages/datasets/builder.py:307, in DatasetBuilder.__init__(self, cache_dir, config_name, hash, base_path, info, features, use_auth_token, repo_id, data_files, data_dir, name, **config_kwargs) 305 if info is None: 306 info = self.get_exported_dataset_info() --> 307 info.update(self._info()) 308 info.builder_name = self.name 309 info.config_name = self.config.name File ~/.cache/huggingface/modules/datasets_modules/datasets/aps--bioasq_task_b/3d54b1213f7e8001eef755af92877f9efa44161ee83c2a70d5d649defa95759e/bioasq_task_b.py:477, in BioasqTaskBDataset._info(self) 474 def _info(self): 475 476 # BioASQ Task B source schema --> 477 if self.config.schema == "source": 478 features = datasets.Features( 479 { 480 "id": datasets.Value("string"), (...) 504 } 505 ) 506 # simplified schema for QA tasks AttributeError: 'BuilderConfig' object has no attribute 'schema' ``` </details> ## Environment info - `datasets` version: 2.4.0 - Platform: macOS-10.16-x86_64-i386-64bit - Python version: 3.10.4 - PyArrow version: 9.0.0 - Pandas version: 1.4.3
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1,735,313,549
I_kwDODunzps5nbsiN
5,918
File not found for audio dataset
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[ "load_dataset () did not work for loading local files either " ]
2023-06-01T02:15:29Z
2023-06-11T06:02:25Z
null
NONE
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### Describe the bug After loading an audio dataset, and looking at a sample entry, the `path` element, which is supposed to be the path to the audio file, doesn't actually exist. ### Steps to reproduce the bug Run bug.py: ```py import os.path from datasets import load_dataset def run() -> None: cv13 = load_dataset( "mozilla-foundation/common_voice_13_0", "hi", split="train", ) print(cv13[0]) audio_file = cv13[0]["path"] if not os.path.exists(audio_file): raise ValueError(f'File {audio_file} does not exist.') if __name__ == "__main__": run() ``` The result (on my machine): ```json {'client_id': '0f018a99663f33afbb7d38aee281fb1afcfd07f9e7acd00383f604e1e17c38d6ed8adf1bd2ccbf927a52c5adefb8ac4b158ce27a7c2ed9581e71202eb302dfb3', 'path': 'C:\\Users\\rober\\.cache\\huggingface\\datasets\\downloads\\extracted\\8d1479bc09b4609bc2675bd02d6869a4d5e09f7e6616f540bd55eacef46c6e2b\\common_voice_hi_26008353.mp3', 'audio': {'path': 'C:\\Users\\rober\\.cache\\huggingface\\datasets\\downloads\\extracted\\8d1479bc09b4609bc2675bd02d6869a4d5e09f7e6616f540bd55eacef46c6e2b\\common_voice_hi_26008353.mp3', 'array': array([ 6.46234854e-26, -1.35709319e-25, -8.07793567e-26, ..., 1.06425944e-07, 4.46417090e-08, 2.61451660e-09]), 'sampling_rate': 48000}, 'sentence': 'हमने उसका जन्मदिन मनाया।', 'up_votes': 2, 'down_votes': 0, 'age': '', 'gender': '', 'accent': '', 'locale': 'hi', 'segment': '' ', 'variant': ''} ``` ```txt Traceback (most recent call last): File "F:\eo-reco\bug.py", line 18, in <module> run() File "F:\eo-reco\bug.py", line 15, in run raise ValueError(f'File {audio_file} does not exist.') ValueError: File C:\Users\rober\.cache\huggingface\datasets\downloads\extracted\8d1479bc09b4609bc2675bd02d6869a4d5e09f7e6616f540bd55eacef46c6e2b\common_voice_hi_26008353.mp3 does not exist. ``` ### Expected behavior The `path` element points to the correct file, which happens to be: ``` C:\Users\rober\.cache\huggingface\datasets\downloads\extracted\8d1479bc09b4609bc2675bd02d6869a4d5e09f7e6616f540bd55eacef46c6e2b\hi_train_0\common_voice_hi_26008353.mp3 ``` That is, there's an extra directory `hi_train_0` that is not in the `path` element. ### Environment info - `datasets` version: 2.12.0 - Platform: Windows-10-10.0.22621-SP0 - Python version: 3.11.3 - Huggingface_hub version: 0.14.1 - PyArrow version: 12.0.0 - Pandas version: 2.0.1 -
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4,824
Fix titles in dataset cards
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[ "_The documentation is not available anymore as the PR was closed or merged._", "The non-passing tests are caused by other missing information in the dataset cards." ]
2022-08-11T11:27:48Z
2022-08-11T13:46:11Z
2022-08-11T12:56:49Z
MEMBER
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Fix all the titles in the dataset cards, so that they conform to the required format.
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MDExOlB1bGxSZXF1ZXN0NTY4NTkwNDM2
1,828
Add CelebA Dataset
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[ "Hi @gchhablani! Thanks for all the contributions! We definitely want more image datasets, but Face datasets are tricky in general, in this one includes predicting attributes such as Attractiveness, Gender, or Race, which can be pretty problematic.\r\n\r\nWould you be up for starting with only object classification...
2021-02-05T20:20:55Z
2021-02-18T14:17:07Z
2021-02-18T14:17:07Z
CONTRIBUTOR
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Trying to add CelebA Dataset. Need help with testing. Loading examples takes a lot of time so I am unable to generate the `dataset_infos.json` and unable to test. Also, need help with creating `dummy_data.zip`. Additionally, trying to load a few examples using `load_dataset('./datasets/celeb_a',split='train[10:20]')` still loads all the examples (doesn't stop at 10).
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4,358
Missing dataset tags and sections in some dataset cards
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[ "@lhoestq I can take this issue. Please can you point out to me where I can find the other positional arguments?", "Hi @RohitRathore1 :)\r\n\r\nYou can find all the YAML tags in the tagging app here: https://hf.co/spaces/huggingface/datasets-tagging). They're all passed as arguments to a DatasetMetadata object us...
2022-05-16T13:18:16Z
2022-05-30T15:36:52Z
null
NONE
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Summary of CircleCI errors for different dataset metadata: - **BoolQ**: missing 8 required positional arguments: 'annotations_creators', 'language_creators', 'licenses', 'multilinguality', 'size_categories', 'source_datasets', 'task_categories', and 'task_ids' - **Conllpp**: expected some content in section `Citation Information` but it is empty. - **GLUE**: 'annotations_creators', 'language_creators', 'source_datasets' :['unknown'] are not registered tags - **ConLL2003**: field 'task_ids': ['part-of-speech-tagging'] are not registered tags for 'task_ids' - **Hate_speech18:** Expected some content in section `Data Instances` but it is empty, Expected some content in section `Data Splits` but it is empty - **Jjigsaw_toxicity_pred**: `Citation Information` but it is empty. - **LIAR** : `Data Instances`,`Data Fields`, `Data Splits`, `Citation Information` are empty. - **MSRA NER** : Dataset Summary`, `Data Instances`, `Data Fields`, `Data Splits`, `Citation Information` are empty. - **sem_eval_2010_task_8**: missing 8 required positional arguments: 'annotations_creators', 'language_creators', 'licenses', 'multilinguality', 'size_categories', 'source_datasets', 'task_categories', and 'task_ids' - **sms_spam**: `Data Instances` and`Data Splits` are empty. - **Quora** : Expected some content in section `Citation Information` but it is empty, missing 8 required positional arguments: 'annotations_creators', 'language_creators', 'licenses', 'multilinguality', 'size_categories', 'source_datasets', 'task_categories', and 'task_ids' - **sentiment140**: missing 8 required positional arguments: 'annotations_creators', 'language_creators', 'licenses', 'multilinguality', 'size_categories', 'source_datasets', 'task_categories', and 'task_ids'
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Issue when wanting to split in memory a cached dataset
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[ "Hi ! Good catch, this is wrong indeed and thanks for opening a PR :)" ]
2023-04-03T17:00:07Z
2023-04-04T16:52:42Z
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### Describe the bug **In the 'train_test_split' method of the Dataset class** (defined datasets/arrow_dataset.py), **if 'self.cache_files' is not empty**, then, **regarding the input parameters 'train_indices_cache_file_name' and 'test_indices_cache_file_name', if they are None**, we modify them to make them not None, to see if we can just provide back / work from cached data. But if we can't provide cached data, we move on with the call to the method, except those two values are not None anymore, which will conflict with the use of the 'keep_in_memory' parameter down the line. Indeed, at some point we end up calling the 'select' method, **and if 'keep_in_memory' is True**, since the value of this method's parameter 'indices_cache_file_name' is now not None anymore, **an exception is raised, whose message is "Please use either 'keep_in_memory' or 'indices_cache_file_name' but not both.".** Because of that, it's impossible to perform a train / test split of a cached dataset while requesting that the result not be cached. Which is inconvenient when one is just performing experiments, with no intention of caching the result. Aside from this being inconvenient, **the code which lead up to that situation seems simply wrong** to me: the input variable should not be modified so as to change the user's intention just to perform a test, if that test can fail and respecting the user's intention is necessary to proceed in that case. To fix this, I suggest to use other variables / other variable names, in order to host the value(s) needed to perform the test, so as not to change the originally input values needed by the rest of the method's code. Also, **I don't see why an exception should be raised when the 'select' method is called with both 'keep_in_memory'=True and 'indices_cache_file_name'!=None**: should the use of 'keep_in_memory' not prevail anyway, specifying that the user does not want to perform caching, and so making irrelevant the value of 'indices_cache_file_name'? This is indeed what happens when we look further in the code, in the '\_select_with_indices_mapping' method: when 'keep_in_memory' is True, then the value of indices_cache_file_name does not matter, the data will be written to a stream buffer anyway. Hence I suggest to remove the raising of exception in those circumstances. Notably, to remove the raising of it in the 'select', '\_select_with_indices_mapping', 'shuffle' and 'map' methods. ### Steps to reproduce the bug ```python import datasets def generate_examples(): for i in range(10): yield {"id": i} dataset_ = datasets.Dataset.from_generator( generate_examples, keep_in_memory=False, ) dataset_.train_test_split( test_size=3, shuffle=False, keep_in_memory=True, train_indices_cache_file_name=None, test_indices_cache_file_name=None, ) ``` ### Expected behavior The result of the above code should be a DatasetDict instance. Instead, we get the following exception stack: ```python --------------------------------------------------------------------------- ValueError Traceback (most recent call last) Cell In[3], line 1 ----> 1 dataset_.train_test_split( 2 test_size=3, 3 shuffle=False, 4 keep_in_memory=True, 5 train_indices_cache_file_name=None, 6 test_indices_cache_file_name=None, 7 ) File ~/Work/Developments/datasets/src/datasets/arrow_dataset.py:528, in transmit_format.<locals>.wrapper(*args, **kwargs) 521 self_format = { 522 "type": self._format_type, 523 "format_kwargs": self._format_kwargs, 524 "columns": self._format_columns, 525 "output_all_columns": self._output_all_columns, 526 } 527 # apply actual function --> 528 out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs) 529 datasets: List["Dataset"] = list(out.values()) if isinstance(out, dict) else [out] 530 # re-apply format to the output File ~/Work/Developments/datasets/src/datasets/fingerprint.py:511, in fingerprint_transform.<locals>._fingerprint.<locals>.wrapper(*args, **kwargs) 507 validate_fingerprint(kwargs[fingerprint_name]) 509 # Call actual function --> 511 out = func(dataset, *args, **kwargs) 513 # Update fingerprint of in-place transforms + update in-place history of transforms 515 if inplace: # update after calling func so that the fingerprint doesn't change if the function fails File ~/Work/Developments/datasets/src/datasets/arrow_dataset.py:4428, in Dataset.train_test_split(self, test_size, train_size, shuffle, stratify_by_column, seed, generator, keep_in_memory, load_from_cache_file, train_indices_cache_file_name, test_indices_cache_file_name, writer_batch_size, train_new_fingerprint, test_new_fingerprint) 4425 test_indices = permutation[:n_test] 4426 train_indices = permutation[n_test : (n_test + n_train)] -> 4428 train_split = self.select( 4429 indices=train_indices, 4430 keep_in_memory=keep_in_memory, 4431 indices_cache_file_name=train_indices_cache_file_name, 4432 writer_batch_size=writer_batch_size, 4433 new_fingerprint=train_new_fingerprint, 4434 ) 4435 test_split = self.select( 4436 indices=test_indices, 4437 keep_in_memory=keep_in_memory, (...) 4440 new_fingerprint=test_new_fingerprint, 4441 ) 4443 return DatasetDict({"train": train_split, "test": test_split}) File ~/Work/Developments/datasets/src/datasets/arrow_dataset.py:528, in transmit_format.<locals>.wrapper(*args, **kwargs) 521 self_format = { 522 "type": self._format_type, 523 "format_kwargs": self._format_kwargs, 524 "columns": self._format_columns, 525 "output_all_columns": self._output_all_columns, 526 } 527 # apply actual function --> 528 out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs) 529 datasets: List["Dataset"] = list(out.values()) if isinstance(out, dict) else [out] 530 # re-apply format to the output File ~/Work/Developments/datasets/src/datasets/fingerprint.py:511, in fingerprint_transform.<locals>._fingerprint.<locals>.wrapper(*args, **kwargs) 507 validate_fingerprint(kwargs[fingerprint_name]) 509 # Call actual function --> 511 out = func(dataset, *args, **kwargs) 513 # Update fingerprint of in-place transforms + update in-place history of transforms 515 if inplace: # update after calling func so that the fingerprint doesn't change if the function fails File ~/Work/Developments/datasets/src/datasets/arrow_dataset.py:3679, in Dataset.select(self, indices, keep_in_memory, indices_cache_file_name, writer_batch_size, new_fingerprint) 3645 """Create a new dataset with rows selected following the list/array of indices. 3646 3647 Args: (...) 3676 ``` 3677 """ 3678 if keep_in_memory and indices_cache_file_name is not None: -> 3679 raise ValueError("Please use either `keep_in_memory` or `indices_cache_file_name` but not both.") 3681 if len(self.list_indexes()) > 0: 3682 raise DatasetTransformationNotAllowedError( 3683 "Using `.select` on a dataset with attached indexes is not allowed. You can first run `.drop_index() to remove your index and then re-add it." 3684 ) ValueError: Please use either `keep_in_memory` or `indices_cache_file_name` but not both. ``` ### Environment info - `datasets` version: 2.11.1.dev0 - Platform: Linux-5.4.236-1-MANJARO-x86_64-with-glibc2.2.5 - Python version: 3.8.12 - Huggingface_hub version: 0.13.3 - PyArrow version: 11.0.0 - Pandas version: 2.0.0 *** *** EDIT: Now with a pull request to fix this [here](https://github.com/huggingface/datasets/pull/5700)
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Fix CLI run_beam namespace
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[ "_The documentation is not available anymore as the PR was closed or merged._" ]
2022-05-11T12:21:00Z
2022-05-11T13:13:00Z
2022-05-11T13:05:08Z
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Currently, it raises TypeError: ``` TypeError: __init__() got an unexpected keyword argument 'namespace' ```
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Add a guide for semantic segmentation
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[ "Sure this sounds great! Would this be pure torchvision, albumentations, or something else?", "I am considering `torchvision` and `albumentations`. Also [works with TensorFlow](https://github.com/deep-diver/segformer-tf-transformers/blob/main/notebooks/TFSegFormer_Finetune.ipynb). \r\n\r\nI am assigning the issue...
2022-11-01T07:54:50Z
2022-11-04T18:23:36Z
2022-11-04T18:23:36Z
MEMBER
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Currently, we have these guides for object detection and image classification: * https://huggingface.co/docs/datasets/object_detection * https://huggingface.co/docs/datasets/image_classification I am proposing adding a similar guide for semantic segmentation. I am happy to contribute a PR for it. Cc: @osanseviero @nateraw
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PR_kwDODunzps4vISGy
3,335
add Speech commands dataset
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[ "@anton-l ping", "@lhoestq \r\nHi Quentin! Thank you for your feedback and suggestions! 🤗\r\n\r\nYes, that was actually what I wanted to do next - I mean the steaming stuff :)\r\nAlso, I need to make some changes to the readme (to account for the updated features set).\r\n\r\nHopefully, I will be done by tomorro...
2021-11-29T13:52:47Z
2021-12-10T10:37:21Z
2021-12-10T10:30:15Z
CONTRIBUTOR
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closes #3283
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MDU6SXNzdWU3OTMyNzM3NzA=
1,777
GPT2 MNLI training using run_glue.py
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2021-01-25T10:53:52Z
2021-01-25T11:12:53Z
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Edit: I'm closing this because I actually meant to post this in `transformers `not `datasets` Running this on Google Colab, ``` !python run_glue.py \ --model_name_or_path gpt2 \ --task_name mnli \ --do_train \ --do_eval \ --max_seq_length 128 \ --per_gpu_train_batch_size 10 \ --gradient_accumulation_steps 32\ --learning_rate 2e-5 \ --num_train_epochs 3.0 \ --output_dir models/gpt2/mnli/ ``` I get the following error, ``` "Asking to pad but the tokenizer does not have a padding token. " ValueError: Asking to pad but the tokenizer does not have a padding token. Please select a token to use as `pad_token` `(tokenizer.pad_token = tokenizer.eos_token e.g.)` or add a new pad token via `tokenizer.add_special_tokens({'pad_token': '[PAD]'})`. ``` Do I need to modify the trainer to work with GPT2 ?
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Dataset Viewer issue for pn_summary
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[ "linked to https://github.com/huggingface/datasets/issues/4580#issuecomment-1168373066?", "Note that I refreshed twice this dataset, and I still have (another) error on one of the splits\r\n\r\n```\r\nStatus code: 400\r\nException: ClientResponseError\r\nMessage: 403, message='Forbidden', url=URL('htt...
2022-06-27T20:56:12Z
2022-06-28T14:42:03Z
2022-06-28T14:42:03Z
MEMBER
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### Link https://huggingface.co/datasets/pn_summary/viewer/1.0.0/validation ### Description Getting an index error on the `validation` and `test` splits: ``` Server error Status code: 400 Exception: IndexError Message: list index out of range ``` ### Owner No
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Add Biwi Kinect Head Pose dataset.
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[ "_The documentation is not available anymore as the PR was closed or merged._", "Thanks for the detailed explanation of the structure!\r\n\r\n1. IMO it makes the most sense to yield one example for each person (so the total of 24 examples), so the features dict should be similar to this:\r\n \r\n ```python\r\n ...
2022-03-13T08:59:21Z
2022-05-31T17:02:19Z
2022-05-31T12:15:58Z
CONTRIBUTOR
null
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This PR adds the Biwi Kinect Head Pose dataset. Dataset Request : Add Biwi Kinect Head Pose Database [#3822](https://github.com/huggingface/datasets/issues/3822) The Biwi Kinect Head Pose Database is acquired with the Microsoft Kinect sensor, a structured IR light device.It contains 15K images of 20 people with 6 females and 14 males where 4 people were recorded twice. For each frame, there is : - a depth image, (.bin file) - a corresponding rgb image (both 640x480 pixels), - annotation ( present inside a .txt file) The ground truth is the 3D location of the head and its rotation. The dataset structure is as follows : ``` - 01.obj - 01 - frame_00003_depth.bin - frame_00003_pose.txt - frame_00003_rgb.png . . . - 02.obj - 02 - frame_00003_depth.bin - frame_00003_pose.txt - frame_00003_rgb.png . . . ``` Preview of frame_00003_pose.txt : ``` 0.988397 0.0731349 0.133128 -0.0441539 0.976945 -0.208876 -0.145334 0.200575 0.968838 126.665 40.4515 876.198 ``` I have used the following dataset features : ``` features=datasets.Features( { "person_id": datasets.Value("string"), "frame_number": datasets.Value("string"), "depth_image": datasets.Value("string"), "rgb_image": datasets.Image(), "3D_head_center": datasets.Array2D(shape=(3, 3), dtype="float"), "3D_head_rotation": datasets.Value("float"), } ``` I am giving the path to the depth_image here. I need some inputs for the following : 1. For each person, the dataset has the following additional information : ``` For each sequence, the corresponding .obj file represents a head template deformed to match the neutral face of that specific person. [*.obj file] In each folder, two .cal files contain calibration information for the depth and the color camera, e.g., the intrinsic camera matrix of the depth camera and the global rotation and translation to the rgb camera. ``` Wanted to know how we can represent these features ? 2. For _generate_examples , do I parse the directories and fetch the required information ? This would mean reading the .txt file to obtain the "3D_head_center" and "3D_head_rotation" details. We could precompute the features information and have a metadata file and use the metadata file to yield information in _generate_examples ? Wanted your thoughts for the best approach for this ?
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Transformer Class on dataset
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[ "Hi ! Do you have an example in mind that shows how this could be useful ?", "Example:\n\nMerge 2 datasets into one datasets\n\nLabel extraction from dataset\n\ndataset(text, label)\n —> dataset(text, newlabel)\n\nTextCleaning.\n\n\nFor image dataset, \nTransformation are easier (ie linear algebra).\n\n\n\n\n\n...
2021-07-06T07:27:15Z
2022-11-02T14:26:09Z
2022-11-02T14:26:09Z
NONE
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Just wondering if you have intenttion to create TransformerClass : dataset --> dataset and make determnistic transformation (ie not fit).
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new pr for Turkish NER
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[ "Can you run `make style` to fix the code format ?\r\n\r\nAlso it looks like the file `file_downloaded/TWNERTC_TC_Coarse Grained NER_DomainIndependent_NoiseReduction.zip/TWNERTC_TC_Coarse Grained NER_DomainIndependent_NoiseReduction.DUMP` is missing inside the dummy_data.zip\r\n\r\n\r\n(note that `TWNERTC_TC_Coarse...
2020-12-07T21:40:26Z
2020-12-09T13:45:05Z
2020-12-09T13:45:05Z
CONTRIBUTOR
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Add The Mexican Emotional Speech Database (MESD)
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2022-01-13T23:49:36Z
2022-01-27T14:14:38Z
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## Adding a Dataset - **Name:** *The Mexican Emotional Speech Database (MESD)* - **Description:** *Contains 864 voice recordings with six different prosodies: anger, disgust, fear, happiness, neutral, and sadness. Furthermore, three voice categories are included: female adult, male adult, and child. * - **Paper:** *[Paper](https://ieeexplore.ieee.org/abstract/document/9629934/authors#authors)* - **Data:** *[link to the Github repository or current dataset location](https://data.mendeley.com/datasets/cy34mh68j9/3)* - **Motivation:** *Would add Spanish speech data to the HF datasets :) * Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
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Consider adding `ipywidgets` as a dependency.
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[ "Hi! We use `tqdm` to display progress bars, so I suggest you open this issue in their repo.", "It depends on how you use `tqdm`, no? \r\n\r\nDoesn't this library import via; \r\n\r\n```\r\nfrom tqdm.notebook import tqdm\r\n```", "Hi! Sorry for the late reply. We import `tqdm` as `from tqdm.auto import tqdm`, w...
2022-01-24T14:27:11Z
2022-02-24T09:04:36Z
2022-02-24T09:04:36Z
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When I install `datasets` in a fresh virtualenv with jupyterlab I always see this error. ``` ImportError: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html ``` It's a bit of a nuisance, because I need to run shut down the jupyterlab server in order to install the required dependency. Might it be an option to just include it as a dependency here?
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Add MultiParaCrawl Dataset
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Document loading from relative path
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[ "_The documentation is not available anymore as the PR was closed or merged._", "Thanks for the feedback!\r\n\r\nI agree that adding it to `load_hub.mdx` is probably a bit too specific, especially for beginners reading the tutorials. Since this clarification is closely related to loading from the Hub (the only di...
2022-07-29T23:32:21Z
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This PR describes loading a dataset from the Hub by specifying a relative path in `data_dir` or `data_files` in `load_dataset` (see #4757).
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Fix flake8 style.
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Extend support for streaming datasets that use pathlib.Path.glob
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[ "I am thinking that ideally we should call `fs.glob()` instead...", "Thanks, @lhoestq: the idea of adding the mock filesystem is to avoid network calls and reduce testing time ;) \r\n\r\nI have added `rglob` as well and fixed some bugs." ]
2021-09-07T13:43:45Z
2021-09-10T09:50:49Z
2021-09-10T09:50:48Z
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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
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Dill 3.7 support
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[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea...
2023-07-24T12:33:58Z
2023-07-24T14:13:20Z
2023-07-24T14:04:36Z
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Adds support for dill 3.7.
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2020-12-13T19:33:10Z
2020-12-21T13:55:09Z
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Datasets need manual downloads. Have thus created dummy data as well. But pytest on real and dummy data are failing. I have completed the readme , tags and other required things. I need to create the metadata json once tests get successful. Opening a PR while working with Yacine Jernite to resolve my pytest issues.
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fixed download link for web_science
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2021-05-09T09:12:20Z
2021-05-10T13:35:53Z
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Fixes #2337. Should work with: `dataset = load_dataset("web_of_science", "WOS11967", ignore_verifications=True)`
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Fix loading how to guide (#5102)
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2022-10-12T10:34:42Z
2022-10-12T11:34:07Z
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Preserve encoding/decoding with features in `Iterable.map` call
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2022-01-10T13:32:20Z
2022-01-18T19:54:08Z
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As described in https://github.com/huggingface/datasets/issues/3505#issuecomment-1004755657, this PR uses a generator expression to encode/decode examples with `features` (which are set to None in `map`) before applying a map transform. Fix #3505
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3907). All of your documentation changes will be reflected on that endpoint." ]
2022-03-14T15:52:31Z
2022-03-15T17:04:20Z
2022-03-15T17:04:19Z
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Putting "Values from popular papers" as a subsection of "Output values"
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Update HellaSwag README.md
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2022-01-18T10:46:15Z
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Adding information from the git repo and paper that were missing
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REUSE_DATASET_IF_EXISTS don't work
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[ "Hi! Unfortunately, the current behavior is to delete the downloaded data when this error happens. So, I've opened a PR that removes the problematic import to avoid losing data due to `apache_beam` not being installed (we host the preprocessed version of `natual_questions` on the HF GCS, so requiring `apache_beam` ...
2023-09-26T03:02:16Z
2023-09-28T18:23:36Z
2023-09-28T18:23:36Z
NONE
null
null
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### Describe the bug I use the following code to download natural_question dataset. Even though I have completely download it, the next time I run this code, the new download procedure will start and cover the original /data/lxy/NQ config=datasets.DownloadConfig(resume_download=True,max_retries=100,cache_dir=r'/data/lxy/NQ',download_desc='NQ') data=datasets.load_dataset('natural_questions',cache_dir=r'/data/lxy/NQ',download_config=config,download_mode=DownloadMode.REUSE_DATASET_IF_EXISTS) --- Since I don't have apache_beam installed, it throw a exception. After I pip install apache_beam ,the download restart.. ![image](https://github.com/huggingface/datasets/assets/88258534/f28ce7fe-29ea-4348-b87f-e69182a8bd41) ### Steps to reproduce the bug run this two line code config=datasets.DownloadConfig(resume_download=True,max_retries=100,cache_dir=r'/data/lxy/NQ',download_desc='NQ') data=datasets.load_dataset('natural_questions',cache_dir=r'/data/lxy/NQ',download_config=config,download_mode=DownloadMode.REUSE_DATASET_IF_EXISTS) ### Expected behavior Download behavior can be correctly follow DownloadMode ### Environment info - `datasets` version: 2.14.4 - Platform: Linux-3.10.0-1160.88.1.el7.x86_64-x86_64-with-glibc2.17 - Python version: 3.9.17 - Huggingface_hub version: 0.16.4 - PyArrow version: 11.0.0 - Pandas version: 2.0.3
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4,828
Support PIL Image objects in `add_item`/`add_column`
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_4828). All of your documentation changes will be reflected on that endpoint.", "Hey @mariosasko could we please merge this? I'm still getting the original error at #4796 .", "Are you planning to continue working on this?" ]
2022-08-11T14:25:45Z
2023-09-24T10:15:33Z
null
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Fix #4796 PS: We should also improve the type inference in `OptimizedTypeSequence` to make it possible to also infer the complex types (only `Image` currently) in nested arrays (e.g. `[[pil_image], [pil_image, pil_image]]` or `[{"img": pil_image}`]), but I plan to address this in a separate PR.
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Add XSUM Hallucination Annotations Dataset
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[ "@lhoestq All necessary modifications have been done." ]
2020-12-06T16:40:19Z
2020-12-20T13:34:56Z
2020-12-16T16:57:11Z
CONTRIBUTOR
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Adding Google [XSum Hallucination Annotations](https://github.com/google-research-datasets/xsum_hallucination_annotations) dataset.
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Support streaming mlsum dataset
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[ "_The documentation is not available anymore as the PR was closed or merged._", "After unpinning `s3fs` and pinning `fsspec[http]>=2021.11.1`, the CI installs\r\n- `fsspec-2022.1.0`\r\n- `s3fs-0.5.1`\r\n\r\nand raises the following error:\r\n```\r\n ImportError while loading conftest '/home/runner/work/datasets/d...
2022-06-27T07:37:03Z
2022-07-21T13:37:30Z
2022-07-21T12:40:00Z
MEMBER
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Support streaming mlsum dataset. This PR: - pins `fsspec` min version with fixed BlockSizeError: `fsspec[http]>=2021.11.1` - https://github.com/fsspec/filesystem_spec/pull/830 - unpins `s3fs==2021.08.1` to align it with `fsspec` requirement: `s3fs>=2021.11.1` > s3fs 2021.8.1 requires fsspec==2021.08.1 - see discussion: https://github.com/huggingface/datasets/pull/2858/files#r700027326 - updates the following requirements to be compatible with the previous ones and one with each other: - `aiobotocore==1.4.2` to `aiobotocore>=2.0.1` (required by s3fs>=2021.11.1) - `boto3==1.17.106` to `boto3>=1.19.8` (to be compatible with aiobotocore>=2.0.1) - `botocore==1.20.106` to `botocore>=1.22.8` (to be compatible with aiobotocore and boto3) Fix #4572.
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1,410
Add penn treebank dataset
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[ "@yjernite I have updated the PR to be language modeling task specific. Please review!\r\n", "Yes a line corresponds to a sentence in this data." ]
2020-12-09T19:11:33Z
2020-12-16T09:38:23Z
2020-12-16T09:38:23Z
CONTRIBUTOR
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Update README.md
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[ "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_a...
2023-10-16T19:10:39Z
2023-10-17T15:13:37Z
2023-10-17T15:04:52Z
CONTRIBUTOR
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Fixed typos in ReadMe and added punctuation marks Tensorflow --> TensorFlow
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Add more information to the dataset card of mlqa dataset
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[ "#self-assign", "Fixed by:\r\n- #4809" ]
2022-08-09T07:35:42Z
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Fix DuplicatedKeysError in omp
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2021-07-07T07:38:32Z
2021-07-12T14:10:41Z
2021-07-07T12:56:35Z
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Close #2598.
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Adjust path to datasets tutorial in How-To
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[ "_The documentation is not available anymore as the PR was closed or merged._" ]
2022-04-12T01:20:34Z
2022-04-12T08:32:24Z
2022-04-12T08:26:02Z
CONTRIBUTOR
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The link in the How-To overview page to the Datasets tutorials is currently broken. This is just a small adjustment to make it match the format used in https://github.com/huggingface/datasets/blob/master/docs/source/tutorial.md. (Edit to add: The link in the PR deployment (https://moon-ci-docs.huggingface.co/docs/datasets/pr_4147/en/how_to) is also broken since it's actually hardcoded to `master` and not dynamic to the branch name, but other links seem to behave similarly.)
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1,771
Couldn't reach https://raw.githubusercontent.com/huggingface/datasets/1.2.1/datasets/csv/csv.py
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[ "I temporary manually download csv.py as custom dataset loading script", "Indeed in 1.2.1 the script to process csv file is downloaded. Starting from the next release though we include the csv processing directly in the library.\r\nSee PR #1726 \r\nWe'll do a new release soon :)", "Thanks." ]
2021-01-24T01:53:52Z
2021-01-24T23:06:29Z
2021-01-24T23:06:29Z
NONE
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Hi, When I load_dataset from local csv files, below error happened, looks raw.githubusercontent.com was blocked by the chinese government. But why it need to download csv.py? should it include when pip install the dataset? ``` Traceback (most recent call last): File "/home/tom/pyenv/pystory/lib/python3.6/site-packages/datasets/load.py", line 267, in prepare_module local_path = cached_path(file_path, download_config=download_config) File "/home/tom/pyenv/pystory/lib/python3.6/site-packages/datasets/utils/file_utils.py", line 343, in cached_path max_retries=download_config.max_retries, File "/home/tom/pyenv/pystory/lib/python3.6/site-packages/datasets/utils/file_utils.py", line 617, in get_from_cache raise ConnectionError("Couldn't reach {}".format(url)) ConnectionError: Couldn't reach https://raw.githubusercontent.com/huggingface/datasets/1.2.1/datasets/csv/csv.py ```
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5,551
Suggest scikit-learn instead of sklearn
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[ "good catch!", "_The documentation is not available anymore as the PR was closed or merged._", "The test fail is unrelated to this PR and fixed on `main` - merging :)", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==6.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: ...
2023-02-20T16:16:57Z
2023-02-21T13:27:57Z
2023-02-21T13:21:07Z
CONTRIBUTOR
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This is kinda unimportant fix but, the suggested `pip install sklearn` does not work. The current error message if sklearn is not installed: ``` ImportError: To be able to use [dataset name], you need to install the following dependency: sklearn. Please install it using 'pip install sklearn' for instance. ```
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5,935
Better row group size in push_to_hub
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[ "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_a...
2023-06-08T15:01:15Z
2023-06-09T17:47:37Z
2023-06-09T17:40:09Z
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This is a very simple change that improves `to_parquet` to use a more reasonable row group size for image and audio datasets. This is especially useful for `push_to_hub` and will provide a better experience with the dataset viewer on HF
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Clean up DatasetInfo and Dataset docstrings
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[ "_The documentation is not available anymore as the PR was closed or merged._" ]
2022-12-08T00:17:53Z
2022-12-08T19:33:14Z
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This PR cleans up the docstrings for `DatasetInfo` and about half of the methods in `Dataset`.
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Fix streaming for servers not supporting HTTP range requests
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[ "Does it mean that huge files might end up being downloaded? It would go against the purpose of streaming, I think. At least, this fallback should be an option that could be disabled", "Yes, it is against the purpose of streaming, but streaming is not possible if the server does not allow HTTP range requests.\n\n...
2022-02-08T15:41:05Z
2022-02-10T16:51:25Z
2022-02-10T16:51:25Z
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Some servers do not support HTTP range requests, whereas this is required to stream some file formats (like ZIP). ~~This PR implements a workaround for those cases, by download the files locally in a temporary directory (cleaned up by the OS once the process is finished).~~ This PR raises custom error explaining that streaming is not possible because data host server does not support HTTP range requests. Fix #3677.
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Bbaw egyptian
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[ "Hi @phiwi,\r\n\r\nThanks for contributing this nice dataset. If you have any blocking problem or question, do not hesitate to ask here. We are pleased to help you.\r\n\r\nCould you please first synchronize with our master branch? From your branch `bbaw_egyptian`, type:\r\n```\r\ngit fetch upstream master\r\ngit me...
2021-04-29T15:27:58Z
2021-05-06T17:25:25Z
2021-05-06T17:25:25Z
CONTRIBUTOR
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This is the "hieroglyph corpus" that I could unfortunately not contribute during the marathon. I re-extracted it again now, so that it is in the state as used in my paper (seee documentation). I hope it satiesfies your requirements and wish every scientist out their loads of fun deciphering a 5.000 years old language :-)
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Loading The flores data set for specific language
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[ "got that the syntax is like this\r\n\r\ndataset = load_dataset(\"facebook/flores\", \"ace_Arab\")" ]
2023-05-25T17:08:55Z
2023-05-25T17:21:38Z
2023-05-25T17:21:37Z
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### Describe the bug I am trying to load the Flores data set the code which is given is ``` from datasets import load_dataset dataset = load_dataset("facebook/flores") ``` This gives the error of config name ""ValueError: Config name is missing" Now if I add some config it gives me the some error "HFValidationError: Repo id must use alphanumeric chars or '-', '_', '.', '--' and '..' are forbidden, '-' and '.' cannot start or end the name, max length is 96: 'facebook/flores, 'ace_Arab''. " How I can load the data of the specific language ? Couldn't find any tutorial any one can help me out? ### Steps to reproduce the bug step one load the data set `from datasets import load_dataset dataset = load_dataset("facebook/flores")` it gives the error of config once config is given it gives the error of "HFValidationError: Repo id must use alphanumeric chars or '-', '_', '.', '--' and '..' are forbidden, '-' and '.' cannot start or end the name, max length is 96: 'facebook/flores, 'ace_Arab''. " ### Expected behavior Data set should be loaded but I am receiving error ### Environment info Datasets , python ,
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[ "welcome, awesome " ]
2020-12-16T16:28:14Z
2020-12-16T22:41:53Z
2020-12-16T17:20:28Z
CONTRIBUTOR
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description added, unnecessary comments removed from .py and readme.md reformated @lhoestq for #1584
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Docs for creating a loading script for image datasets
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[ "_The documentation is not available anymore as the PR was closed or merged._", "IMO it would make more sense to add a \"Create image dataset\" page with two main sections - a no-code approach with `imagefolder` + metadata (preferred way), and with a loading script (advanced). It should be clear when to choose wh...
2022-08-02T20:36:03Z
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This PR is a first draft of creating a loading script for image datasets. Feel free to let me know if there are any specificities I'm missing for this. 🙂 To do: - [x] Document how to create different configurations.
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set dev version
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5591). All of your documentation changes will be reflected on that endpoint.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==6.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchma...
2023-02-28T18:09:05Z
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OSCAR unshuffled_original_ko: NonMatchingSplitsSizesError
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[ "I tried `unshuffled_original_da` and it is also not working" ]
2021-09-18T10:39:13Z
2022-01-19T14:10:07Z
null
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## 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
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5,332
Passing numpy array to ClassLabel names causes ValueError
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[ "Should `datasets` allow `ClassLabel` input parameter to be an `np.array` even though internally we need to cast it to a Python list? @lhoestq @mariosasko ", "Hi! No, I don't think so. The `names` parameter is [annotated](https://github.com/huggingface/datasets/blob/582236640b9109988e5f7a16a8353696ffa09a16/src/d...
2022-12-05T12:59:03Z
2022-12-22T16:32:50Z
2022-12-22T16:32:50Z
CONTRIBUTOR
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### Describe the bug If a numpy array is passed to the names argument of ClassLabel, creating a dataset with those features causes an error. ### Steps to reproduce the bug https://colab.research.google.com/drive/1cV_es1PWZiEuus17n-2C-w0KEoEZ68IX TLDR: If I define my classes as: ``` my_classes = np.array(['one', 'two', 'three']) ``` Then this errors: ```py features = Features({'value': Value('string'), 'label': ClassLabel(names=my_classes)}) dataset = Dataset.from_list(my_data, features=features) ``` ``` ValueError Traceback (most recent call last) [<ipython-input-8-a8a9d53ec82f>](https://localhost:8080/#) in <module> ----> 1 dataset = Dataset.from_list(my_data, features=features) 11 frames [/usr/local/lib/python3.8/dist-packages/datasets/utils/py_utils.py](https://localhost:8080/#) in _asdict_inner(obj) 183 for f in fields(obj): 184 value = _asdict_inner(getattr(obj, f.name)) --> 185 if not f.init or value != f.default or f.metadata.get("include_in_asdict_even_if_is_default", False): 186 result[f.name] = value 187 return result ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all() ``` But this works: ``` features2 = Features({'value': Value('string'), 'label': ClassLabel(names=list(my_classes))}) dataset2 = Dataset.from_list(my_data, features=features2) ``` ### Expected behavior If I provide a numpy array of class names, I would expect either an error that the names list is the wrong type, or for it to be cast internally. ### Environment info - `datasets` version: 2.7.1 - Platform: Linux-5.15.0-56-generic-x86_64-with-glibc2.10 - Python version: 3.8.15 - PyArrow version: 10.0.1 - Pandas version: 1.5.2 Additionally: - Numpy version: 1.23.5
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Fix missing conda deps
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`aiohttp` was added as a dependency in #2662 but was missing for the conda build, which causes the 1.12.0 and 1.12.1 to fail. Fix #2932.
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Tensor operation not functioning in dataset mapping
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[ "Hi! The Torch ops in your snippet are not equivalent to the NumPy ones, hence the difference. You can get the same behavior by replacing the line `feature = torch.mean(feature, dim=1)` with `feature = feature.squeeze().mean(1)` .", "> Hi! The Torch ops in your snippet are not equivalent to the NumPy ones, hence ...
2022-10-18T17:53:35Z
2022-10-19T04:15:45Z
2022-10-19T04:15:44Z
NONE
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## Describe the bug I'm doing a torch.mean() operation in data preprocessing, and it's not working. ## Steps to reproduce the bug ``` from transformers import pipeline import torch import numpy as np from datasets import load_dataset device = 'cuda:0' raw_dataset = load_dataset("glue", "sst2") feature_extraction = pipeline('feature-extraction', 'bert-base-uncased', device=device) def extracted_data(examples): # feature = torch.tensor(feature_extraction(examples['sentence'], batch_size=16), device=device) # feature = torch.mean(feature, dim=1) feature = np.asarray(feature_extraction(examples['sentence'], batch_size=16)).squeeze().mean(1) print(feature.shape) return {'feature': feature} extracted_dataset = raw_dataset.map(extracted_data, batched=True, batch_size=16) ``` ## Results When running with torch.mean(), the shape printed out is [16, seq_len, 768], which is exactly the same before the operation. While numpy works just fine, which gives [16, 768]. ## Environment info - `datasets` version: 2.6.1 - Platform: Linux-4.4.0-142-generic-x86_64-with-glibc2.31 - Python version: 3.10.6 - PyArrow version: 9.0.0 - Pandas version: 1.5.0
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Fix bug in function validate_type for Python >= 3.9
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2022-08-09T10:32:42Z
2022-08-12T13:41:23Z
2022-08-12T13:27:04Z
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Fix `validate_type` function, so that it uses `get_origin` instead. This makes the function forward compatible. This fixes #4811 because: ```python In [4]: typing.Optional[str] Out[4]: typing.Optional[str] In [5]: get_origin(typing.Optional[str]) Out[5]: typing.Union ``` Fix #4811.
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Remove compression from xopen
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[ "After discussing with @lhoestq, a reasonable alternative:\r\n- `download_manager.extract(urlpath)` adds prefixes to `urlpath` in the same way as `fsspec` does for protocols, but we implement custom prefixes for all compression formats: \r\n `bz2::http://domain.org/filename.bz2`\r\n- `xopen` parses the `urlpath` a...
2021-08-18T09:35:59Z
2021-08-23T15:59:14Z
2021-08-23T15:59:14Z
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We implemented support for streaming with 2 requirements: - transparent use for the end user: just needs to pass the parameter `streaming=True` - no additional work for the contributors: previous loading scripts should also work in streaming mode with no (or minor) changes; and new loading scripts should not involve additional code to support streaming In order to fulfill these requirements, streaming implementation patched some Python functions: - the `open(urlpath)` function was patched with `fsspec.open(urlpath)` - the `os.path.join(urlpath, *others)` function was patched in order to add to `urlpath` hops (`::`) and extractor protocols (`zip://`), which are required by `fsspec.open` Recently, we implemented support for streaming all archive+compression formats: zip, tar, gz, bz2, lz4, xz, zst; tar.gz, tar.bz2,... Under the hood, the implementation: - passes an additional parameter `compression` to `fsspec.open`, so that it performs the decompression on the fly: `fsspec.open(urlpath, compression=...)` Some concerns have been raised about passing the parameter `compression` to `fsspec.open`: - https://github.com/huggingface/datasets/pull/2786#discussion_r689550254 - #2811 The main argument is that if `open` decompresses the file and afterwards we call `gzip.open` on it, that will raise an error in `oscar` dataset: ```python gzip.open(open(urlpath ``` While this is true: - it is not natural/usual to call `open` inside `gzip.open` (never seen this before) - indeed, this was recently (2 months ago) coded that way in `datasets` in order to allow streaming support (with previous implementation of streaming) In this particular case, there is a natural fix solution: #2811: - Revert the `open` inside the `gzip.open` (change done 2 months ago): `gzip.open(open(urlpath` => `gzip.open(urlpath` - Patch `gzip.open(urlpath` with `fsspec.open(urlpath, compression="gzip"` Are there other issues apart from this? Note that there is an issue just because the open inside of the gzip.open. There is no issue in the other cases where datasets loading scripts use just - `gzip.open` - `open` (after having called dl_manager.download_and_extract) TODO: - [ ] Is this really an issue? Please enumerate the `datasets` loading scripts where this is problematic. - For the moment, there are only 3 datasets where we have an `open` inside a `gzip.open`: - oscar (since 23 June), mc4 (since 2 July) and c4 (since 2 July) - In the 3 datasets, the only reason to put an open inside a gzip.open was indeed to force supporting streaming - [ ] If this is indeed an issue, which are the possible alternatives? Pros/cons?
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Support complex feature types as `features` in packaged loaders
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2022-05-17T17:53:23Z
2022-05-31T12:26:23Z
2022-05-31T12:16:32Z
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This PR adds `table_cast` to the packaged loaders to fix casting to the `Image`/`Audio`, `ArrayND` and `ClassLabel` types. If these types are not present in the `builder.config.features` dictionary, the built-in `pa.Table.cast` is used for better performance. Additionally, this PR adds `cast_storage` to `ClassLabel` to support the string to int conversion in `table_cast` and ensure that integer labels are in a valid range. Fix https://github.com/huggingface/datasets/issues/4210 This PR is also a solution for these (popular) discussions: https://discuss.huggingface.co/t/converting-string-label-to-int/2816 and https://discuss.huggingface.co/t/class-labels-for-custom-datasets/15130/2 TODO: * [x] tests
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Improve error message for missing pacakges from inside dataset script
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[ "_The documentation is not available anymore as the PR was closed or merged._", "I opened a PR before I noticed yours ^^' You can find it here: https://github.com/huggingface/datasets/pull/4484\r\n\r\nThe only comment I have regarding your message is that it possibly shows several `pip install` commands, whereas ...
2022-06-10T16:59:36Z
2022-10-06T13:46:26Z
2022-06-13T13:16:43Z
CONTRIBUTOR
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Improve the error message for missing packages from inside a dataset script: With this change, the error message for missing packages for `bigbench` looks as follows: ``` ImportError: To be able to use bigbench, you need to install the following dependencies: - 'bigbench' using 'pip install "bigbench @ https://storage.googleapis.com/public_research_data/bigbench/bigbench-0.0.1.tar.gz"' ``` And this is how it looked before: ``` ImportError: To be able to use bigbench, you need to install the following dependencies['bigbench', 'bigbench', 'bigbench', 'bigbench'] using 'pip install "bigbench @ https://storage.googleapis.com/public_research_data/bigbench/bigbench-0.0.1.tar.gz" bigbench bigbench bigbench' for instance' ```
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Checksum error when trying to load amazon_review dataset
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[ "It is solved now" ]
2022-01-20T21:20:32Z
2022-01-21T13:22:31Z
2022-01-21T13:22:31Z
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## Describe the bug A clear and concise description of what the bug is. ## Steps to reproduce the bug I am getting the issue when trying to load dataset using ``` dataset = load_dataset("amazon_polarity") ``` ## Expected results dataset loaded ## Actual results ``` --------------------------------------------------------------------------- NonMatchingChecksumError Traceback (most recent call last) <ipython-input-3-b4758ba980ae> in <module>() ----> 1 dataset = load_dataset("amazon_polarity") 2 dataset.set_format(type='pandas') 3 content_series = dataset['train']['content'] 4 label_series = dataset['train']['label'] 5 df = pd.concat([content_series, label_series], axis=1) 3 frames /usr/local/lib/python3.7/dist-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/u/0/uc?id=0Bz8a_Dbh9QhbaW12WVVZS2drcnM&export=download'] ``` ## Environment info <!-- You can run the command `datasets-cli env` and copy-and-paste its output below. --> - `datasets` version: 1.17.0 - Platform: Google colab - Python version: 3.7.12
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when i use datasets.load_dataset, i encounter the http connect error!
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[ "The `audiofolder` loader is not available in version `2.3.2`, hence the error. Please run the `pip install -U datasets` command to update the `datasets` installation to make `load_dataset(\"audiofolder\", ...)` work." ]
2023-07-18T10:16:34Z
2023-07-18T16:18:39Z
2023-07-18T16:18:39Z
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### Describe the bug `common_voice_test = load_dataset("audiofolder", data_dir="./dataset/",cache_dir="./cache",split=datasets.Split.TEST)` when i run the code above, i got the error as below: -------------------------------------------- ConnectionError: Couldn't reach https://raw.githubusercontent.com/huggingface/datasets/2.3.2/datasets/audiofolder/audiofolder.py (ConnectionError(MaxRetryError("HTTPSConnectionPool(host='raw.githubusercontent.com', port=443): Max retries exceeded with url: /huggingface/datasets/2.3.2/datasets/audiofolder/audiofolder.py (Caused by NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x7f299ed082e0>: Failed to establish a new connection: [Errno 101] Network is unreachable'))"))) -------------------------------------------------- My all data is on local machine, why does it need to connect the internet? how can i fix it, because my machine cannot connect the internet. ### Steps to reproduce the bug 1 ### Expected behavior no error when i use the load_dataset func ### Environment info python=3.8.15
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Wrong example in opus_gnome dataset card
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2022-08-09T03:21:27Z
2022-08-09T11:52:05Z
2022-08-09T11:52:05Z
CONTRIBUTOR
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## Describe the bug I found that [the example on opus_gone dataset ](https://github.com/huggingface/datasets/tree/main/datasets/opus_gnome#dataset-summary) doesn't work. ## Steps to reproduce the bug ```python load_dataset("gnome", lang1="it", lang2="pl") ``` `"gnome"` should be `"opus_gnome"` ## Expected results ```bash 100% 1/1 [00:00<00:00, 42.09it/s] DatasetDict({ train: Dataset({ features: ['id', 'translation'], num_rows: 8368 }) }) ``` ## Actual results ```bash Couldn't find 'gnome' on the Hugging Face Hub either: FileNotFoundError: Couldn't find file at https://raw.githubusercontent.com/huggingface/datasets/main/datasets/gnome/gnome.py ``` ## Environment info - `datasets` version: 2.4.0 - Platform: Linux-5.4.0-120-generic-x86_64-with-glibc2.27 - Python version: 3.9.13 - PyArrow version: 9.0.0 - Pandas version: 1.4.3
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4,293
Fix wrong map parameter name in cache docs
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[ "_The documentation is not available anymore as the PR was closed or merged._" ]
2022-05-08T07:27:46Z
2022-06-14T16:49:00Z
2022-06-14T16:07:00Z
CONTRIBUTOR
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The `load_from_cache` parameter of `map` should be `load_from_cache_file`.
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Update README.md
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2023-09-07T11:33:20Z
2023-09-13T22:32:31Z
2023-09-13T22:23:42Z
CONTRIBUTOR
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fixed a few typos
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remove int documentation from logging docs
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2022-05-23T09:24:55Z
2022-05-23T15:16:55Z
2022-05-23T15:08:32Z
MEMBER
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Removes the `int` documentation from the [logging section](https://huggingface.co/docs/datasets/package_reference/logging_methods#levels) of the docs.
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2022-05-21T02:15:18Z
2022-05-21T19:20:44Z
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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).
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Remove `HfFileSystem` and deprecate `S3FileSystem`
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2023-07-19T15:00:01Z
2023-07-19T17:39:11Z
2023-07-19T17:27:17Z
CONTRIBUTOR
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Remove the legacy `HfFileSystem` and deprecate `S3FileSystem` cc @philschmid for the SageMaker scripts/notebooks that still use `datasets`' `S3FileSystem`
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