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https://api.github.com/repos/huggingface/datasets/issues/3954
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1,172,141,664
I_kwDODunzps5F3XZg
3,954
The dataset preview is not available for tdklab/Hebrew_Squad_v1.1 dataset
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[ "Hi @MatanBenChorin, thanks for reporting.\r\n\r\nPlease, take into account that the preview may take some time until it properly renders (we are working to reduce this time).\r\n\r\nMaybe @severo can give more details on this.", "Hi, \r\nThank you", "Thanks for reporting. We are looking at it and will give upd...
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## Dataset viewer issue for 'tdklab/Hebrew_Squad_v1.1' **Link:** https://huggingface.co/api/datasets/tdklab/Hebrew_Squad_v1.1?full=true The dataset preview is not available for this dataset. Am I the one who added this dataset ? Yes
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1,172,123,736
I_kwDODunzps5F3TBY
3,953
Add ImageNet Sketch
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[ "Can you assign this task to me? @nreimers @mariosasko ", "Hi! Sure! Let us know if you need any pointers." ]
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## Adding a Dataset - **Name:** ImageNet Sketch - **Description:** ImageNet-Sketch is a dataset consisting of sketch-like images, that matches the ImageNet classification validation set in categories and scale. - **Paper:** [Learning Robust Global Representations by Penalizing Local Predictive Power](https://arxiv.org/abs/1905.13549) - **Data:** https://github.com/HaohanWang/ImageNet-Sketch - **Motivation:** Allows for evaluating the robustness of vision models. 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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Checksum error for glue sst2, stsb, rte etc datasets
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[ "Hi, @ravindra-ut.\r\n\r\nI'm sorry but I can't reproduce your problem:\r\n```python\r\nIn [1]: from datasets import load_dataset\r\n\r\nIn [2]: ds = load_dataset(\"glue\", \"sst2\")\r\nDownloading builder script: 28.8kB [00:00, 11.6MB/s] ...
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NONE
null
## Describe the bug Checksum error for glue sst2, stsb, rte etc datasets ## Steps to reproduce the bug ```python >>> nlp.load_dataset('glue', 'sst2') Downloading and preparing dataset glue/sst2 (download: 7.09 MiB, generated: 4.81 MiB, post-processed: Unknown sizetotal: 11.90 MiB) to Downloading: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 73.0/73.0 [00:00<00:00, 18.2kB/s] Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/Library/Python/3.8/lib/python/site-packages/nlp/load.py", line 548, in load_dataset builder_instance.download_and_prepare( File "/Library/Python/3.8/lib/python/site-packages/nlp/builder.py", line 462, in download_and_prepare self._download_and_prepare( File "/Library/Python/3.8/lib/python/site-packages/nlp/builder.py", line 521, in _download_and_prepare verify_checksums( File "/Library/Python/3.8/lib/python/site-packages/nlp/utils/info_utils.py", line 38, in verify_checksums raise NonMatchingChecksumError(error_msg + str(bad_urls)) nlp.utils.info_utils.NonMatchingChecksumError: Checksums didn't match for dataset source files: ['https://firebasestorage.googleapis.com/v0/b/mtl-sentence-representations.appspot.com/o/data%2FSST-2.zip?alt=media&token=aabc5f6b-e466-44a2-b9b4-cf6337f84ac8'] ``` ## Expected results dataset load should succeed without checksum error. ## Actual results ``` Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/Library/Python/3.8/lib/python/site-packages/nlp/load.py", line 548, in load_dataset builder_instance.download_and_prepare( File "/Library/Python/3.8/lib/python/site-packages/nlp/builder.py", line 462, in download_and_prepare self._download_and_prepare( File "/Library/Python/3.8/lib/python/site-packages/nlp/builder.py", line 521, in _download_and_prepare verify_checksums( File "/Library/Python/3.8/lib/python/site-packages/nlp/utils/info_utils.py", line 38, in verify_checksums raise NonMatchingChecksumError(error_msg + str(bad_urls)) nlp.utils.info_utils.NonMatchingChecksumError: Checksums didn't match for dataset source files: ['https://firebasestorage.googleapis.com/v0/b/mtl-sentence-representations.appspot.com/o/data%2FSST-2.zip?alt=media&token=aabc5f6b-e466-44a2-b9b4-cf6337f84ac8'] ``` ## Environment info - `datasets` version: '1.18.3' - Platform: Mac OS - Python version: Python 3.8.9 - PyArrow version: '7.0.0'
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Forked streaming datasets try to `open` data urls rather than use network
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[ "Thanks for reporting this second issue as well. We definitely want to make streaming datasets fully working in a distributed setup and with the best performance. Right now it only supports single process.\r\n\r\nIn this issue it seems that the streaming capabilities that we offer to dataset builders are not transf...
1,647,465,662,000
1,654,894,046,000
1,654,894,046,000
NONE
null
## Describe the bug Building on #3950, if you bypass the pickling problem you still can't use the dataset. Somehow something gets confused and the forked processes try to `open` urls rather than anything else. ## Steps to reproduce the bug ```python from multiprocessing import freeze_support import transformers from transformers import Trainer, AutoModelForCausalLM, TrainingArguments import datasets import torch.utils.data # work around #3950 class TorchIterableDataset(datasets.IterableDataset, torch.utils.data.IterableDataset): pass def _ensure_format(v: datasets.IterableDataset) -> datasets.IterableDataset: return TorchIterableDataset(v._ex_iterable, v.info, v.split, "torch", v._shuffling) if __name__ == '__main__': freeze_support() ds = datasets.load_dataset('oscar', "unshuffled_deduplicated_en", split='train', streaming=True) ds = _ensure_format(ds) model = AutoModelForCausalLM.from_pretrained("distilgpt2") Trainer(model, train_dataset=ds, args=TrainingArguments("out", max_steps=1000, dataloader_num_workers=4)).train() ``` ## Expected results I'd expect the dataset to load the url correctly and produce examples. ## Actual results ``` warnings.warn( ***** Running training ***** Num examples = 8000 Num Epochs = 9223372036854775807 Instantaneous batch size per device = 8 Total train batch size (w. parallel, distributed & accumulation) = 8 Gradient Accumulation steps = 1 Total optimization steps = 1000 0%| | 0/1000 [00:00<?, ?it/s]Traceback (most recent call last): File "/Users/dlwh/src/mistral/src/stream_fork_crash.py", line 22, in <module> Trainer(model, train_dataset=ds, args=TrainingArguments("out", max_steps=1000, dataloader_num_workers=4)).train() File "/Users/dlwh/.conda/envs/mistral/lib/python3.8/site-packages/transformers/trainer.py", line 1339, in train for step, inputs in enumerate(epoch_iterator): File "/Users/dlwh/.conda/envs/mistral/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 521, in __next__ data = self._next_data() File "/Users/dlwh/.conda/envs/mistral/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 1203, in _next_data return self._process_data(data) File "/Users/dlwh/.conda/envs/mistral/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 1229, in _process_data data.reraise() File "/Users/dlwh/.conda/envs/mistral/lib/python3.8/site-packages/torch/_utils.py", line 434, in reraise raise exception FileNotFoundError: Caught FileNotFoundError in DataLoader worker process 0. Original Traceback (most recent call last): File "/Users/dlwh/.conda/envs/mistral/lib/python3.8/site-packages/torch/utils/data/_utils/worker.py", line 287, in _worker_loop data = fetcher.fetch(index) File "/Users/dlwh/.conda/envs/mistral/lib/python3.8/site-packages/torch/utils/data/_utils/fetch.py", line 32, in fetch data.append(next(self.dataset_iter)) File "/Users/dlwh/.conda/envs/mistral/lib/python3.8/site-packages/datasets/iterable_dataset.py", line 497, in __iter__ for key, example in self._iter(): File "/Users/dlwh/.conda/envs/mistral/lib/python3.8/site-packages/datasets/iterable_dataset.py", line 494, in _iter yield from ex_iterable File "/Users/dlwh/.conda/envs/mistral/lib/python3.8/site-packages/datasets/iterable_dataset.py", line 87, in __iter__ yield from self.generate_examples_fn(**self.kwargs) File "/Users/dlwh/.cache/huggingface/modules/datasets_modules/datasets/oscar/84838bd49d2295f62008383b05620571535451d84545037bb94d6f3501651df2/oscar.py", line 358, in _generate_examples with gzip.open(open(filepath, "rb"), "rt", encoding="utf-8") as f: FileNotFoundError: [Errno 2] No such file or directory: 'https://s3.amazonaws.com/datasets.huggingface.co/oscar/1.0/unshuffled/deduplicated/en/en_part_1.txt.gz' Error in atexit._run_exitfuncs: Traceback (most recent call last): File "/Users/dlwh/.conda/envs/mistral/lib/python3.8/multiprocessing/popen_fork.py", line 27, in poll pid, sts = os.waitpid(self.pid, flag) File "/Users/dlwh/.conda/envs/mistral/lib/python3.8/site-packages/torch/utils/data/_utils/signal_handling.py", line 66, in handler _error_if_any_worker_fails() RuntimeError: DataLoader worker (pid 6932) is killed by signal: Terminated: 15. 0%| | 0/1000 [00:02<?, ?it/s] ``` ## Environment info <!-- You can run the command `datasets-cli env` and copy-and-paste its output below. --> - `datasets` version: 2.0.0 - Platform: macOS-12.2-arm64-arm-64bit - Python version: 3.8.12 - PyArrow version: 7.0.0 - Pandas version: 1.4.1
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Streaming Datasets don't work with Transformers Trainer when dataloader_num_workers>1
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[ "Hi, thanks for reporting. This could be related to https://github.com/huggingface/datasets/issues/3148 too\r\n\r\nWe should definitely make `TorchIterableDataset` picklable by moving it in the main code instead of inside a function. If you'd like to contribute, feel free to open a Pull Request :)\r\n\r\nI'm also t...
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## Describe the bug Streaming Datasets can't be pickled, so any interaction between them and multiprocessing results in a crash. ## Steps to reproduce the bug ```python import transformers from transformers import Trainer, AutoModelForCausalLM, TrainingArguments import datasets ds = datasets.load_dataset('oscar', "unshuffled_deduplicated_en", split='train', streaming=True).with_format("torch") model = AutoModelForCausalLM.from_pretrained("distilgpt2") Trainer(model, train_dataset=ds, args=TrainingArguments("out", max_steps=1000, dataloader_num_workers=4)).train() ``` ## Expected results For this code I'd expect a crash related to not having preprocessed the data, but instead we get a pickling error. ## Actual results ``` 0%| | 0/1000 [00:00<?, ?it/s]Traceback (most recent call last): File "/Users/dlwh/src/mistral/src/stream_fork_crash.py", line 7, in <module> Trainer(model, train_dataset=ds, args=TrainingArguments("out", max_steps=1000, dataloader_num_workers=4)).train() File "/Users/dlwh/.conda/envs/mistral/lib/python3.8/site-packages/transformers/trainer.py", line 1339, in train for step, inputs in enumerate(epoch_iterator): File "/Users/dlwh/.conda/envs/mistral/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 359, in __iter__ return self._get_iterator() File "/Users/dlwh/.conda/envs/mistral/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 305, in _get_iterator return _MultiProcessingDataLoaderIter(self) File "/Users/dlwh/.conda/envs/mistral/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 918, in __init__ w.start() File "/Users/dlwh/.conda/envs/mistral/lib/python3.8/multiprocessing/process.py", line 121, in start self._popen = self._Popen(self) File "/Users/dlwh/.conda/envs/mistral/lib/python3.8/multiprocessing/context.py", line 224, in _Popen return _default_context.get_context().Process._Popen(process_obj) File "/Users/dlwh/.conda/envs/mistral/lib/python3.8/multiprocessing/context.py", line 284, in _Popen return Popen(process_obj) File "/Users/dlwh/.conda/envs/mistral/lib/python3.8/multiprocessing/popen_spawn_posix.py", line 32, in __init__ super().__init__(process_obj) File "/Users/dlwh/.conda/envs/mistral/lib/python3.8/multiprocessing/popen_fork.py", line 19, in __init__ self._launch(process_obj) File "/Users/dlwh/.conda/envs/mistral/lib/python3.8/multiprocessing/popen_spawn_posix.py", line 47, in _launch reduction.dump(process_obj, fp) File "/Users/dlwh/.conda/envs/mistral/lib/python3.8/multiprocessing/reduction.py", line 60, in dump ForkingPickler(file, protocol).dump(obj) AttributeError: Can't pickle local object 'iterable_dataset.<locals>.TorchIterableDataset' 0%| | 0/1000 [00:00<?, ?it/s] ``` This immediate crash can be fixed by not using a local class to make the `TorchIterableDataset` (Note that you have to do with_format("torch") or you get an exception because the dataset has no len) However, any lambdas etc used as maps will also trigger this crash. A more permanent fix would be to move away from multiprocessing and instead use something like pathos or multiprocessing_on_dill (https://stackoverflow.com/questions/19984152/what-can-multiprocessing-and-dill-do-together) Note that if you bypass this crash you get another crash. (I'll file a separate bug). ## Environment info - `datasets` version: 2.0.0 - Platform: macOS-12.2-arm64-arm-64bit - Python version: 3.8.12 - PyArrow version: 7.0.0 - Pandas version: 1.4.1
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Remove GLEU metric
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[ "_The documentation is not available anymore as the PR was closed or merged._" ]
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Remove the GLEU metric as it is not actually implemented.
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Google BLEU Metric Card
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[ "A few things that aren't clear for me:\r\n- \"Because it performs better on individual sentence pairs as compared to BLEU, Google BLEU has also been used in RL experiments.\" -- why is this the case? why would that make it more usable for RL? (also, you should put \"Reinforcement Learning\" explicitly, not just th...
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Add metric card for Google BLEU (GLEU) metric One thing I noticed while writing this up is that, while this metric was made specifically to be better than BLEU at the sentence level instead of the corpus level, the current implementation only allows the calculation of the corpus-level statistic. I think changing this would be a good thing to put on the to do list for the future.
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[ "_The documentation is not available anymore as the PR was closed or merged._", "Some thoughts:\r\n- For values, e.g. \"Defaults to False\", I would put False in code: `False`. Same for : \"Defaults to `4`.\"\r\n- I would put the following remark in \"Limitations\": \r\n> \"BLEU's output is always a number betwee...
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Add BLEU metric card
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Add newline to text dataset builder for controlling universal newlines mode
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3946). All of your documentation changes will be reflected on that endpoint.", "The failing CI test has nothing to do with this PR." ]
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Fix #3804.
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Fix comet metric
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[ "_The documentation is not available anymore as the PR was closed or merged._", "Finally I'm done updating the dependencies ^^'\r\n\r\ncc @sashavor can you review my changes in the metric card please ?", "Looks good to me! Just fixed a tiny typo :wink: ", "Thanks !" ]
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The COMET metric has been broken for a while since big breaking changes happened. We did not catch them in the CI because the slow test mocks the download_model function that was changed. This PR fixes the metric, updates the download_model mock and updates the doctest.
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Create README.md
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Proposing COMET metric card
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[Doc] Don't use v for version tags on GitHub
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3943). All of your documentation changes will be reflected on that endpoint." ]
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This removes the `v` automatically used by `doc-builder` for versions.
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[ "Hi @XingxingZhang, \r\n\r\nWe have already fixed this. You should update `datasets` version to at least 1.18.4:\r\n```shell\r\npip install -U datasets\r\n```\r\nAnd then force the redownload:\r\n```python\r\nload_dataset(\"...\", download_mode=\"force_redownload\")\r\n```\r\n\r\nDuplicate of:\r\n- #3773", "thank...
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## Describe the bug When loading the reddit_tifu dataset, it throws the exception "Checksums didn't match for dataset source files" ## Steps to reproduce the bug ```python import datasets from datasets import load_dataset print(datasets.__version__) # load_dataset('billsum') load_dataset('reddit_tifu', 'short') ``` ## Environment info <!-- You can run the command `datasets-cli env` and copy-and-paste its output below. --> - `datasets` version: 1.17.0 - Platform: mac os - Python version: Python 3.7.6 - PyArrow version: 3.0.0
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billsum dataset: Checksums didn't match for dataset source files:
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[ "Hi @XingxingZhang, thanks for reporting.\r\n\r\nThis was due to a change in Google Drive service:\r\n- #3786 \r\n\r\nWe have already fixed it:\r\n- #3787\r\n\r\nYou should update `datasets` version to at least 1.18.4:\r\n```shell\r\npip install -U datasets\r\n```\r\nAnd then force the redownload:\r\n```python\r\nl...
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## Describe the bug When loading the `billsum` dataset, it throws the exception "Checksums didn't match for dataset source files" ``` File "virtualenv_projects/codex/lib/python3.7/site-packages/datasets/utils/info_utils.py", line 40, in verify_checksums raise NonMatchingChecksumError(error_msg + str(bad_urls)) datasets.utils.info_utils.NonMatchingChecksumError: Checksums didn't match for dataset source files: ['https://drive.google.com/uc?export=download&id=1g89WgFHMRbr4QrvA0ngh26PY081Nv3lx'] ``` ## Steps to reproduce the bug ```python import datasets from datasets import load_dataset print(datasets.__version__) load_dataset('billsum') ``` ## Environment info <!-- You can run the command `datasets-cli env` and copy-and-paste its output below. --> - `datasets` version: 1.17.0 - Platform: mac os - Python version: Python 3.7.6 - PyArrow version: 3.0.0
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[ "_The documentation is not available anymore as the PR was closed or merged._" ]
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Initial CoVAL metric card
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[ "Thanks for reporting @qqaatw.\r\n\r\n@mishig25 @sgugger do you think this can be tweaked in the new doc framework?\r\n- From: https://github.com/huggingface/datasets/blob/v2.0.0/\r\n- To: https://github.com/huggingface/datasets/blob/2.0.0/", "@qqaatw thanks a lot for notifying about this issue!\r\n\r\nin compari...
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## Describe the bug The source links of v2.0.0 docs are broken: For exmaple, clicking the source button of this [class](https://huggingface.co/docs/datasets/v2.0.0/en/package_reference/main_classes#datasets.ClassLabel) will direct users to `https://github.com/huggingface/datasets/blob/v2.0.0/src/datasets/features/features.py#L747` here, the `v2.0.0` should be `2.0.0`. ## Steps to reproduce the bug ```python # Sample code to reproduce the bug ``` ## Expected results Redirecting to this link: `https://github.com/huggingface/datasets/blob/2.0.0/src/datasets/features/features.py#L747` ## Actual results Described above. ## Environment info <!-- You can run the command `datasets-cli env` and copy-and-paste its output below. --> - `datasets` version: - Platform: - Python version: - PyArrow version:
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Avoid info log messages from transformers in FrugalScore metric
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3938). All of your documentation changes will be reflected on that endpoint." ]
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Fix #3928.
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Missing languages in lvwerra/github-code dataset
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[ "Thanks for contacting @Eytan-S.\r\n\r\nI think @lvwerra could better answer this. ", "That seems to be an oversight - I originally planned to include them in the dataset and for some reason they were in the list of languages but not in the query. Since there is an issue with the deduplication step I'll rerun the...
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Hi, I'm working with the github-code dataset. First of all, thank you for creating this amazing dataset! I've noticed that two languages are missing from the dataset: TypeScript and Scala. Looks like they're also omitted from the query you used to get the original code. Are there any plans to add them in the future? Thanks!
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Fix Wikipedia version and re-add tests
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3936). All of your documentation changes will be reflected on that endpoint." ]
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To keep backward compatibility when loading using "wikipedia" dataset ID (https://huggingface.co/datasets/wikipedia), we have created the pre-processed data for the same languages we were offering before, but with updated date "20220301": - de - en - fr - frr - it - simple These pre-processed data can be accessed, e.g.: ```python ds = load_dataset("wikipedia", "20220301.frr", split="train") ``` The next step will be to offer the pre-processed data for many other languages, but when loading using "wikimedia/wikipedia": https://huggingface.co/datasets/wikimedia/wikipedia
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Create MAUVE metric card
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Proposing a MAUVE metric card
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Update README.md
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Fixing missing triple quote
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Create SARI metric card
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SARI metric card! (do we have an expert in text simplification to validate?.. :sweat_smile: )
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Add align_labels_with_mapping docs
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This PR documents the `align_labels_with_mapping` function to ensure predicted labels are aligned with the dataset, or to assign a different mapping of labels to ids (requested by @mariosasko πŸŽ‰ ). For this specific code sample, the current dataset has a `mixed` label that the original [dataset](https://huggingface.co/datasets/poem_sentiment#data-fields) didn't. Is there a way to remove this label so it is completely aligned with the original dataset mappings? Otherwise, I'll just leave it as it is.
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Create README.md
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Creating a README for IndicGLUE cc @mcmillanmajora for fact checking in terms of languages (also, are there any limitations of the dataset or eval metric that I'm not aware of?)
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Load a local dataset twice
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[ "Hi @caush, thanks for reporting:\r\n\r\nIn order to load local CSV files, you can use our \"csv\" loading script: https://huggingface.co/docs/datasets/loading#csv\r\n```python\r\ndataset = load_dataset(\"csv\", data_files=[\"data/file1.csv\", \"data/file2.csv\"])\r\n```\r\nOR:\r\n```python\r\ndataset = load_datase...
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## Describe the bug Load a local "dataset" composed of two csv files twice. ## Steps to reproduce the bug Put the two joined files in a repository named "Data". Then in python: import datasets as ds ds.load_dataset('Data', data_files = {'file1.csv', 'file2.csv'}) ## Expected results Should give something like (because files have only one data row): Title, clicks Truc et astuce, 123 Machin, 12 ## Actual results Gives Title, clicks Truc et astuce, 123 Machin, 12 Truc et astuce, 123 Machin, 12 ## Environment info [file1.csv](https://github.com/huggingface/datasets/files/8256322/file1.csv) [file2.csv](https://github.com/huggingface/datasets/files/8256323/file2.csv) - `datasets` version: 2.0.0 - Platform: Linux-5.4.0-65-generic-x86_64-with-glibc2.10 - Python version: 3.8.12 - PyArrow version: 7.0.0 - Pandas version: 1.4.1
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Frugal score deprecations
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[ "Hi @Ierezell, thanks for reporting.\r\n\r\nI'm making a PR to suppress those logs from the terminal. " ]
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## Describe the bug The frugal score returns a really verbose output with warnings that can be easily changed. ## Steps to reproduce the bug ```python # Sample code to reproduce the bug from datasets.load import load_metric frugal = load_metric("frugalscore") frugal.compute(predictions=["Do you like spinachis"], references=["Do you like spinach"]) ``` ## Expected results A clear and concise description of the expected results. ``` {'scores': [0.9946]} ``` ## Actual results Specify the actual results or traceback. ``` PyTorch: setting up devices The default value for the training argument `--report_to` will change in v5 (from all installed integrations to none). In v5, you will need to use `--report_to all` to get the same behavior as now. You should start updating your code and make this info disappear :-). 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 1/1 [00:00<00:00, 864.09ba/s] Using amp half precision backend The following columns in the test set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: sentence2, sentence1. If sentence2, sentence1 are not expected by `BertForSequenceClassification.forward`, you can safely ignore this message. ***** Running Prediction ***** Num examples = 1 Batch size = 64 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 1/1 [00:00<00:00, 4644.85it/s] {'scores': [0.9946]} ``` ## Environment info <!-- You can run the command `datasets-cli env` and copy-and-paste its output below. --> - `datasets` version: 1.17.0 - Platform: Linux-5.13.0-30-generic-x86_64-with-glibc2.29 - Python version: 3.8.10 - PyArrow version: 7.0.0
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Update main readme
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[ "_The documentation is not available anymore as the PR was closed or merged._", "What do you think @albertvillanova ?" ]
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The main readme was still focused on text datasets - I extended it by mentioning that we also support image and audio datasets
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3926). All of your documentation changes will be reflected on that endpoint." ]
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This PR adds some minor maintenance to the docs. The main fix is properly linking to pages in the callouts because some of the links would just redirect to a non-existent section on the same page.
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Fix main_classes docs index
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[ "_The documentation is not available anymore as the PR was closed or merged._", "Hmm it's still not good \r\n![image](https://user-images.githubusercontent.com/42851186/158429361-e19ce25b-c259-4ded-8473-075deafdbb96.png)\r\n\r\nany idea what could cause this ?", "Ok fixed :)" ]
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Currently the `main_classes` documentation has a wrong index. I believe this comes from issues in the examples of the Translation feature types ![image](https://user-images.githubusercontent.com/42851186/158426345-2ee1ceef-ddf3-4a6f-a93e-d1a8f38a44f5.png)
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Document cases for github datasets
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3924). All of your documentation changes will be reflected on that endpoint.", "Yay!" ]
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In general we recommend adding the new dataset under a username or organization in the Hugging Face Hub at [hf.co/datasets](hf.co/datasets), but users can still add a dataset on github in some cases. I added a paragraph in the documentation to explain in which cases it can make more sense to open a PR on github: - when you need the dataset to be reviewed - when you need long-term maintenance from the HF team - when there’s no clear org name / namespace that you can put the dataset under
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Add methods to IterableDatasetDict
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3923). All of your documentation changes will be reflected on that endpoint.", "Is this feature stale or needs any help to it ? If so I can quickly send a PR. Thanks\r\n\r\nCC : @lhoestq, @albertvillanova ", "These features h...
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Following the new methods added in #3826 and https://github.com/huggingface/datasets/pull/3862 I added several methods to IterableDatasetDict: - map - filter - shuffle - with_format - cast - cast_column - remove_columns - rename_column - rename_columns
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Fix NonMatchingChecksumError in MultiWOZ 2.2 dataset
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3922). All of your documentation changes will be reflected on that endpoint.", "Unrelated CI test failure. This PR can be merged." ]
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Fix #2957
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Fix NonMatchingChecksumError in CRD3 dataset
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3921). All of your documentation changes will be reflected on that endpoint.", "Unrelated test failure. This PR can be merged." ]
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Fix #3051
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'datasets.features' is not a package
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[ "Hi @Arij-Aladel,\r\n\r\nYou are using a very old version of our library `datasets`: 1.8.0\r\nCurrent version is 2.0.0 (and the previous one was 1.18.4)\r\n\r\nPlease, try to update `datasets` library and check if the problem persists:\r\n```shell\r\n/env/bin/pip install -U datasets", "The problem I can no I have...
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@albertvillanova python 3.9 os: ubuntu 20.04 In conda environment torch installed by ```/env/bin/pip install torch==1.9.0+cu111 torchvision==0.10.0+cu111 torchaudio==0.9.0 -f https://download.pytorch.org/whl/torch_stable.html``` datasets package is installed by ``` /env/bin/pip install datasets==1.8.0 ``` During runing the code I have this error ``` [6]<stderr>: File "/home/arij/Memory-transformer-with-hierarchical-attention_MLM/env/lib/python3.9/site-packages/torch/serialization.py", line 875, in find_class [6]<stderr>: return super().find_class(mod_name, name) [6]<stderr>:ModuleNotFoundError: No module named 'datasets.features.features'; 'datasets.features' is not a package ``` precisely this error appears when torch.load('data_file.pt') ``` Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/home/arij/Memory-transformer-with-hierarchical-attention_MLM/env/lib/python3.9/site-packages/torch/serialization.py", line 607, in load return _load(opened_zipfile, map_location, pickle_module, **pickle_load_args) File "/home/arij/Memory-transformer-with-hierarchical-attention_MLM/env/lib/python3.9/site-packages/torch/serialization.py", line 882, in _load result = unpickler.load() File "/home/arij/Memory-transformer-with-hierarchical-attention_MLM/env/lib/python3.9/site-packages/torch/serialization.py", line 875, in find_class return super().find_class(mod_name, name) ModuleNotFoundError: No module named 'datasets.features.features'; 'datasets.features' is not a package ``` Why I am getting this error?
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AttributeError: 'DatasetDict' object has no attribute 'features'
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[ "You are likely trying to get the `features` from a `DatasetDict`, a dictionary containing `Datasets`. You probably first want to index into a particular split from your `DatasetDict` i.e. `dataset['train'].features`. \r\n\r\nFor example \r\n\r\n```python \r\nds = load_dataset('mnist')\r\nds.features\r\n```\r\nRetu...
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## Describe the bug Receiving the error when trying to check for Dataset features ## Steps to reproduce the bug from datasets import Dataset dataset = Dataset.from_pandas(df[['id', 'words', 'bboxes', 'ner_tags', 'image_path']]) dataset.features ## Expected results A clear and concise description of the expected results. ## Actual results Getting the following errror AttributeError: 'DatasetDict' object has no attribute 'features' ## Environment info Copy-and-paste the text below in your GitHub issue. - `datasets` version: 1.18.4 - Platform: Linux-4.14.252-131.483.amzn1.x86_64-x86_64-with-glibc2.9 - Python version: 3.6.13 - PyArrow version: 6.0.1
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datasets.utils.info_utils.NonMatchingChecksumError: Checksums didn't match for dataset source files
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[ "Hi @willowdong! These issues were fixed on master. We will have a new release of `datasets` later today. In the meantime, you can avoid these issues by installing `datasets` from master as follows:\r\n```bash\r\npip install git+https://github.com/huggingface/datasets.git\r\n```", "You should force redownload:\r\...
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## Describe the bug Can't load the dataset ## Steps to reproduce the bug ```python # Sample code to reproduce the bug ``` from datasets import load_dataset dataset = load_dataset('multi_news') dataset_2=load_dataset("reddit_tifu", "long") ## Actual results raise NonMatchingChecksumError(error_msg + str(bad_urls)) datasets.utils.info_utils.NonMatchingChecksumError: Checksums didn't match for dataset source files: ['https://drive.google.com/uc?export=download&id=1ffWfITKFMJeqjT8loC8aiCLRNJpc_XnF'] ## Environment info - `datasets` version: 1.18.4 - Platform: macOS-10.16-x86_64-i386-64bit - Python version: 3.8.0 - PyArrow version: 6.0.1
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Create README.md
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3917). All of your documentation changes will be reflected on that endpoint." ]
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This follows the same structure as the GLUE metric card, hope that works for everyone :)
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3916). All of your documentation changes will be reflected on that endpoint." ]
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I still have a hesitation regarding the format of inputs -- whether it's a list or a list of lists? -- hopefully @lhoestq will be able to clarify. Also tagging @yjernite for the Limitations section. Happy to hear your thoughts!
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Metric card template
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[ "_The documentation is not available anymore as the PR was closed or merged._", "Looks like a great start! I have a general comment and a few specific comments.\r\n\r\nMy general comment is I wonder if we need a post for this template and the data and model card templates (or a combined one?) explaining why this ...
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Adding a metric card template, based on ideas and edits from @sashavor and I, as well as from comments from @lhoestq and others (thank you!). All feedback is welcome, but am especially curious about feedback in terms of: - things that should be included but aren't - things that are included but should be changed or removed - the instructions I included, and whether they should be added to, clarified, or deleted altogether
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Use templates for doc-builidng jobs
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3914). All of your documentation changes will be reflected on that endpoint.", "You can ignore the CI failures btw, they're unrelated to this PR" ]
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This PR updates the jobs for all doc-building related things by using the templates introduced on `doc-builder`. By putting those once there, we make sure every repo gets the latest fixes on the doc-building github actions :-) Note: all libraries must share the same docker image for those doc-building jobs. For now, all the one used (`huggingface/transformers-doc-builder`) contains all extra steps of the datasets install for docbuling (mainly libsndfile) but if in the future some additional steps are necessary on top of `pip install -e .[dev]`, this docker image will need to be updated with the extra deps.
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PR_kwDODunzps40afYJ
3,913
Deterministic split order in DatasetDict.map
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3913). All of your documentation changes will be reflected on that endpoint.", "I'm surprised this is needed because the order of the `dict` keys is deterministic as of Python 3.6 (documented in 3.7). Is there a reproducer for ...
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The order in which the splits are processed by `map` is not deterministic in `DatasetDict.map`. This can cause caching issues when the processing function is stateful and sensible to the order in which examples are processed Close https://github.com/huggingface/datasets/issues/3847
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add draft of registering function for pandas
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3912). All of your documentation changes will be reflected on that endpoint.", "That's cool ! Though I would expect such an integration to only require `huggingface_hub`, not the full `datasets` library. \r\n Indeed if users wa...
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This PR adds a register function for `pandas`. It allows to directly push `DataFrame` objects to the hub and in return loading datasets on the hub from `DataFrame`. The motivation for this integration is to enable the vast number of `pandas` users to be able to easily push `DataFrames` to the hub. Here is an example: ```python import pandas as pd from datasets import register_pandas register_pandas() # push to hub df = pd.DataFrame.from_dict({"test": [1,2,3]}) df.push_to_hub("my_test") # load from hub df_retrieved = pd.DataFrame.load_from_hub("lvwerra/my_test") ``` It follows a similar philosophy as the `tqdm` [integration](https://github.com/tqdm/tqdm#pandas-integration). Also see [this issue](https://github.com/pandas-dev/pandas/issues/46000) on the `pandas` repository. This is just a rough draft of what such integration could look like but I would like appreciate some feedback on this: is this something you would like to add the library and is this the way to go? cc @lhoestq @albertvillanova @julien-c
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Create README.md for CER metric
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[ "_The documentation is not available anymore as the PR was closed or merged._" ]
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Initial proposal for a CER metric card cc @patrickvonplaten - wdyt this time around? :smile:
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Fix text loader to split only on universal newlines
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3910). All of your documentation changes will be reflected on that endpoint.", "Looks like the test needs to be updated for windows ^^'", "I don't think this is the same issue as in https://github.com/oscar-corpus/corpus/issu...
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Currently, `text` loader breaks on a superset of universal newlines, which also contains Unicode line boundaries. See: https://docs.python.org/3/library/stdtypes.html#str.splitlines However, the expected behavior is to get the lines splitted only on universal newlines: "\n", "\r\n" and "\r". See: oscar-corpus/corpus#18 Fix #3729.
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I_kwDODunzps5FpxYK
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Error loading file audio when downloading the Common Voice dataset directly from the Hub
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[ "Hi ! It could an issue with torchaudio, which version of torchaudio are you using ? Can you also try updating `datasets` to 2.0.0 and see if it works ?", "I _might_ have a similar issue. I'm trying to use the librispeech_asr dataset and read it with soundfile.\r\n\r\n```python\r\nfrom datasets import load_datase...
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## Describe the bug When loading the Common_Voice dataset, by downloading it directly from the Hugging Face hub, some files can not be opened. ## Steps to reproduce the bug ```python import torch import torchaudio from datasets import load_dataset, load_metric from transformers import Wav2Vec2ForCTC, Wav2Vec2Processor import re test_dataset = load_dataset("common_voice", "it", split="test") #test_dataset = load_dataset('csv', data_files = {'test': '/workspace/Dataset/Common_Voice/cv-corpus80/it/test.csv'}) wer = load_metric("wer") processor = Wav2Vec2Processor.from_pretrained("joorock12/wav2vec2-large-xlsr-italian") model = Wav2Vec2ForCTC.from_pretrained("joorock12/wav2vec2-large-xlsr-italian") model.to("cuda") chars_to_ignore_regex = '[\,\?\.\!\-\;\:\"\β€œ\'\οΏ½]' resampler = torchaudio.transforms.Resample(48_000, 16_000) ``` ## Expected results The common voice dataset downloaded and correctly loaded whit the use of the hugging face datasets library. ## Actual results The error is: ```python 0ex [00:00, ?ex/s] --------------------------------------------------------------------------- RuntimeError Traceback (most recent call last) <ipython-input-48-ef87f4129e6e> in <module> 7 return batch 8 ----> 9 test_dataset = test_dataset.map(speech_file_to_array_fn) /opt/conda/lib/python3.8/site-packages/datasets/arrow_dataset.py in map(self, function, with_indices, with_rank, input_columns, batched, batch_size, drop_last_batch, remove_columns, keep_in_memory, load_from_cache_file, cache_file_name, writer_batch_size, features, disable_nullable, fn_kwargs, num_proc, suffix_template, new_fingerprint, desc) 2107 2108 if num_proc is None or num_proc == 1: -> 2109 return self._map_single( 2110 function=function, 2111 with_indices=with_indices, /opt/conda/lib/python3.8/site-packages/datasets/arrow_dataset.py in wrapper(*args, **kwargs) 516 self: "Dataset" = kwargs.pop("self") 517 # apply actual function --> 518 out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs) 519 datasets: List["Dataset"] = list(out.values()) if isinstance(out, dict) else [out] 520 for dataset in datasets: /opt/conda/lib/python3.8/site-packages/datasets/arrow_dataset.py in wrapper(*args, **kwargs) 483 } 484 # apply actual function --> 485 out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs) 486 datasets: List["Dataset"] = list(out.values()) if isinstance(out, dict) else [out] 487 # re-apply format to the output /opt/conda/lib/python3.8/site-packages/datasets/fingerprint.py in wrapper(*args, **kwargs) 411 # Call actual function 412 --> 413 out = func(self, *args, **kwargs) 414 415 # Update fingerprint of in-place transforms + update in-place history of transforms /opt/conda/lib/python3.8/site-packages/datasets/arrow_dataset.py in _map_single(self, function, with_indices, with_rank, input_columns, batched, batch_size, drop_last_batch, remove_columns, keep_in_memory, load_from_cache_file, cache_file_name, writer_batch_size, features, disable_nullable, fn_kwargs, new_fingerprint, rank, offset, disable_tqdm, desc, cache_only) 2465 if not batched: 2466 for i, example in enumerate(pbar): -> 2467 example = apply_function_on_filtered_inputs(example, i, offset=offset) 2468 if update_data: 2469 if i == 0: /opt/conda/lib/python3.8/site-packages/datasets/arrow_dataset.py in apply_function_on_filtered_inputs(inputs, indices, check_same_num_examples, offset) 2372 if with_rank: 2373 additional_args += (rank,) -> 2374 processed_inputs = function(*fn_args, *additional_args, **fn_kwargs) 2375 if update_data is None: 2376 # Check if the function returns updated examples /opt/conda/lib/python3.8/site-packages/datasets/arrow_dataset.py in decorated(item, *args, **kwargs) 2067 ) 2068 # Use the LazyDict internally, while mapping the function -> 2069 result = f(decorated_item, *args, **kwargs) 2070 # Return a standard dict 2071 return result.data if isinstance(result, LazyDict) else result <ipython-input-48-ef87f4129e6e> in speech_file_to_array_fn(batch) 3 def speech_file_to_array_fn(batch): 4 batch["sentence"] = re.sub(chars_to_ignore_regex, '', batch["sentence"]).lower() ----> 5 speech_array, sampling_rate = torchaudio.load(batch["path"]) 6 batch["speech"] = resampler(speech_array).squeeze().numpy() 7 return batch /opt/conda/lib/python3.8/site-packages/torchaudio/backend/sox_io_backend.py in load(filepath, frame_offset, num_frames, normalize, channels_first, format) 150 filepath, frame_offset, num_frames, normalize, channels_first, format) 151 filepath = os.fspath(filepath) --> 152 return torch.ops.torchaudio.sox_io_load_audio_file( 153 filepath, frame_offset, num_frames, normalize, channels_first, format) 154 RuntimeError: Error loading audio file: failed to open file common_voice_it_17415776.mp3 ``` ## Environment info - `datasets` version: 1.18.4 - Platform: Linux-5.4.0-x86_64-with-glibc2.10 - Python version: 3.8.5 - PyArrow version: 7.0.0
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Update README.md for SQuAD v2 metric
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3908). All of your documentation changes will be reflected on that endpoint." ]
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Putting "Values from popular papers" as a subsection of "Output values"
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Update README.md for SQuAD metric
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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." ]
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Putting "Values from popular papers" as a subsection of "Output values"
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NonMatchingChecksumError on Spider dataset
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[ "Hi @kolk, thanks for reporting.\r\n\r\nIndeed, Google Drive service recently changed their service and we had to add a fix to our library to cope with that change:\r\n- #3787 \r\n\r\nWe just made patch release last week: 1.18.4 https://github.com/huggingface/datasets/releases/tag/1.18.4\r\n\r\nPlease, feel free to...
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## Describe the bug Failure to generate dataset ```spider``` because of checksums error for dataset source files. ## Steps to reproduce the bug ``` from datasets import load_dataset spider = load_dataset("spider") ``` ## Expected results Checksums should match for files from url ['https://drive.google.com/uc?export=download&id=1_AckYkinAnhqmRQtGsQgUKAnTHxxX5J0'] ## Actual results ``` >>> load_dataset("spider") load_dataset("spider") Downloading and preparing dataset spider/spider (download: 95.12 MiB, generated: 5.17 MiB, post-processed: Unknown size, total: 100.29 MiB) to /home/user/.cache/huggingface/datasets/spider/spider/1.0.0/79778ebea87c59b19411f1eb3eda317e9dd5f7788a556d837ef25c3ae6e5e8b7... Traceback (most recent call last): File "/home/user/py3_env/lib/python3.8/site-packages/IPython/core/interactiveshell.py", line 3441, in run_code exec(code_obj, self.user_global_ns, self.user_ns) File "<ipython-input-5-d4cb54197348>", line 1, in <module> load_dataset("spider") File "/home/user/py3_env/lib/python3.8/site-packages/datasets/load.py", line 1702, in load_dataset builder_instance.download_and_prepare( File "/home/user/py3_env/lib/python3.8/site-packages/datasets/builder.py", line 594, in download_and_prepare self._download_and_prepare( File "/home/user/py3_env/lib/python3.8/site-packages/datasets/builder.py", line 665, in _download_and_prepare verify_checksums( File "/home/user/py3_env/lib/python3.8/site-packages/datasets/utils/info_utils.py", line 40, in verify_checksums raise NonMatchingChecksumError(error_msg + str(bad_urls)) datasets.utils.info_utils.NonMatchingChecksumError: Checksums didn't match for dataset source files: ['https://drive.google.com/uc?export=download&id=1_AckYkinAnhqmRQtGsQgUKAnTHxxX5J0'] ``` ## Environment info datasets version: 1.18.3 Platform: Ubuntu 20 LTS Python version: 3.8.10 PyArrow version: 6.0.1
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Perplexity Metric Card
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3905). All of your documentation changes will be reflected on that endpoint.", "I'm wondering if we should add that perplexity can be used for analyzing datasets as well", "Otherwise, looks good! Good job, @emibaylor !" ]
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Add Perplexity metric card Note that it is currently still missing the citation, but I plan to add it later today.
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CONLL2003 Dataset not available
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[ "Thanks for reporting, @omarespejel.\r\n\r\nI'm sorry but I can't reproduce the issue: the loading of the dataset works perfecto for me and I can reach the data URL: https://data.deepai.org/conll2003.zip\r\n\r\nMight it be due to a temporary problem in the data owner site (https://data.deepai.org/) that is fixed no...
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## Describe the bug [CONLL2003](https://huggingface.co/datasets/conll2003) Dataset can no longer reach 'https://data.deepai.org/conll2003.zip' ![image](https://user-images.githubusercontent.com/4755430/158084483-ff83631c-5154-4823-892d-577bf1166db0.png) ## Steps to reproduce the bug ```python from datasets import load_dataset datasets = load_dataset("conll2003") ``` ## Expected results Download the conll2003 dataset. ## Actual results Error: `ConnectionError: Couldn't reach https://data.deepai.org/conll2003.zip (error 502)`
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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 ...
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CONTRIBUTOR
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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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Can't import datasets: partially initialized module 'fsspec' has no attribute 'utils'
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[ "Update: `\"python3 -c \"from from datasets import Dataset, DatasetDict\"` works, but not if I import without the `python3 -c`", "Hi @arunasank, thanks for reporting.\r\n\r\nIt seems that this can be caused because you are using an old version of `fsspec`: the reason why it works if you run `python3` seems to be ...
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## Describe the bug Unable to import datasets ## Steps to reproduce the bug ```python from datasets import Dataset, DatasetDict ``` ## Expected results The import works without errors ## Actual results ``` AttributeError Traceback (most recent call last) <ipython-input-37-c8cfcbe62127> in <module> 11 # from tqdm import tqdm 12 # import torch ---> 13 from datasets import Dataset 14 # from transformers import Trainer, TrainingArguments, AutoModel, AutoTokenizer, AutoModelForMaskedLM, DataCollatorForLanguageModeling 15 # from sentence_transformers import SentenceTransformer ~/.local/lib/python3.8/site-packages/datasets/__init__.py in <module> 31 ) 32 ---> 33 from .arrow_dataset import Dataset, concatenate_datasets 34 from .arrow_reader import ArrowReader, ReadInstruction 35 from .arrow_writer import ArrowWriter ~/.local/lib/python3.8/site-packages/datasets/arrow_dataset.py in <module> 46 ) 47 ---> 48 import fsspec 49 import numpy as np 50 import pandas as pd ~/.local/lib/python3.8/site-packages/fsspec/__init__.py in <module> 10 from . import _version, caching 11 from .callbacks import Callback ---> 12 from .core import get_fs_token_paths, open, open_files, open_local 13 from .exceptions import FSTimeoutError 14 from .mapping import FSMap, get_mapper ~/.local/lib/python3.8/site-packages/fsspec/core.py in <module> 16 caches, 17 ) ---> 18 from .compression import compr 19 from .registry import filesystem, get_filesystem_class 20 from .utils import ( ~/.local/lib/python3.8/site-packages/fsspec/compression.py in <module> 68 69 ---> 70 register_compression("zip", unzip, "zip") 71 register_compression("bz2", BZ2File, "bz2") 72 ~/.local/lib/python3.8/site-packages/fsspec/compression.py in register_compression(name, callback, extensions, force) 44 45 for ext in extensions: ---> 46 if ext in fsspec.utils.compressions and not force: 47 raise ValueError( 48 "Duplicate compression file extension: %s (%s)" % (ext, name) AttributeError: partially initialized module 'fsspec' has no attribute 'utils' (most likely due to a circular import) ``` ## Environment info <!-- You can run the command `datasets-cli env` and copy-and-paste its output below. --> - `datasets` version: 1.18.4 - Platform: Jupyter notebook - Python version: 3.8.10 - PyArrow version: 7.0.0
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Dataset viewer issue for IndicParaphrase- the preview doesn't show
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[ "It seems to have been fixed:\r\n\r\n<img width=\"1534\" alt=\"Capture d’écran 2022-04-12 aΜ€ 14 10 07\" src=\"https://user-images.githubusercontent.com/1676121/162959599-6b7fef7c-8411-4e03-8f00-90040a658079.png\">\r\n" ]
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## Dataset viewer issue for '*IndicParaphrase*' **Link:** *[IndicParaphrase](https://huggingface.co/datasets/ai4bharat/IndicParaphrase/viewer/hi/validation)* *The preview of the dataset doesn't come up. The error on the console is: Status code: 400 Exception: FileNotFoundError Message: [Errno 2] No such file or directory: '/home/hf/datasets-preview-backend/hi_IndicParaphrase_v1.0.tar'* Am I the one who added this dataset ? Yes
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Add MetaShift dataset
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[ "_The documentation is not available anymore as the PR was closed or merged._", "@lhoestq Please could you review this when you get time. Thank you.", "Thanks a lot for your inputs @mariosasko .\r\n> Maybe we can add the generated meta-graphs to the card as images (with attributions)?\r\n\r\nYes. We can do this...
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CONTRIBUTOR
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This PR adds the MetaShift dataset. Dataset Request : Add MetaShift dataset [#3813](https://github.com/huggingface/datasets/issues/3813) @lhoestq As discussed, - I have copied the preprocessing script and modified it as required to not create new directories and folders and instead yield the images. - I do the preprocessing in _split_generators to get the required data which is then passed to _generate_examples. - Beyond the generated MetaShift dataset, the original preprocess script also generates the meta-graphs for each class, I have currently not included this part. [ Ref : [Link](https://github.com/Weixin-Liang/MetaShift#generate-full-metashift) ] - There is a Bonus section, the authors share. I have currently not included this part. [ Ref : [Link](https://github.com/Weixin-Liang/MetaShift#bonus-generate-the-metashift-attributes-dataset-subsets-defined-by-subject-attributes) ] - I had a basic test script which downloaded the dataset and tested the basic functionality. Things seems fine. For real data, I performed the following test : ``` RUN_SLOW=1 pytest tests/test_dataset_common.py::LocalDatasetTest::test_load_real_dataset_metashift ============================================== test session starts =============================================== platform linux -- Python 3.7.11, pytest-7.0.1, pluggy-1.0.0 rootdir: ./datasets plugins: hydra-core-1.1.1, datadir-1.3.1, forked-1.4.0, xdist-2.5.0 collected 1 item tests/test_dataset_common.py . [100%] ========================================= 1 passed in 4821.25s (1:20:21) ========================================= ``` - I couldn't get the dummy dataset. Need some inputs here. Error as follows : ``` Using custom data configuration default Dataset metashift with config None seems to already open files in the method `_split_generators(...)`. You might consider to instead only open files in the method `_generate_examples(...)` instead. If this is not possible the dummy data has to be created with less guidance. Make sure you create the file dummy_data/full-candidate-subsets.pkl. for split in generator_splits: UnboundLocalError: local variable 'generator_splits' referenced before assignment ``` To-Do : - [x] Currently I am using the default _SELECTED_CLASSES. I need to use config option here as suggested - [x] Complete fields in the Dataset Card. - [x] Tagging the dataset using the Datasets Tagging app. Need your help and suggestions for improvement. Thank you
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Add exact match metric
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[ "_The documentation is not available anymore as the PR was closed or merged._" ]
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Adding the exact match metric and its metric card. Note: Some of the tests have failed, but I wanted to make a PR anyway so that the rest of the code can be reviewed if anyone has time. I'll look into + work on fixing the failed tests when I'm back online after the weekend
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Create README.md for WER metric
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3898). All of your documentation changes will be reflected on that endpoint.", "For ASR you can probably ping @patrickvonplaten ", "Ah only noticed now that ` # Values from popular papers` is from a template. @lhoestq @sashav...
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Proposing a draft WER metric card, @lhoestq I'm not very certain about "Values from popular papers" -- I don't know ASR very well, what do you think of the examples I found?
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Align tqdm control/cache control with Transformers
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3897). All of your documentation changes will be reflected on that endpoint." ]
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This PR: * aligns the `tqdm` logic with Transformers (follows https://github.com/huggingface/transformers/pull/15167) by moving the code to `utils/logging.py`, adding `enable_progres_bar`/`disable_progres_bar` and removing `set_progress_bar_enabled` (a note for @lhoestq: I'm not adding `logging.tqdm` to the public namespace in this PR to avoid the situation where `from datasets import *; tqdm` would overshadow the standard `tqdm` * aligns the cache control with the new `tqdm` logic by adding `enable_caching`/`disable_caching` to the public namespace and deprecating `set_caching_enabled` (not fully removing it because it's used more often than `set_progress_bar_enabled` and has a dedicated example in the old docs) Fix #3586
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Missing google file for `multi_news` dataset
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[ "reported by @abidlabs ", "related to https://github.com/huggingface/datasets/pull/3843?", "`datasets` 1.18.4 fixes the issue when you load the dataset with `load_dataset`.\r\n\r\nWhen loading in streaming mode, the fix is indeed on https://github.com/huggingface/datasets/pull/3843 which will be merged soon :)"...
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CONTRIBUTOR
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## Dataset viewer issue for '*multi_news*' **Link:** https://huggingface.co/datasets/multi_news ``` Server error Status code: 400 Exception: FileNotFoundError Message: https://drive.google.com/uc?export=download&id=1vRY2wM6rlOZrf9exGTm5pXj5ExlVwJ0C/multi-news-original/train.src ``` Am I the one who added this dataset ? No
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Fix code examples indentation
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3895). All of your documentation changes will be reflected on that endpoint.", "Still not rendered properly: https://moon-ci-docs.huggingface.co/docs/datasets/pr_3895/en/package_reference/main_classes#datasets.Dataset.align_lab...
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Some code examples are currently not rendered correctly. I think this is because they are over-indented cc @mariosasko
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[docs] make dummy data creation optional
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3894). All of your documentation changes will be reflected on that endpoint.", "The dev doc build rendering doesn't seem to be updated with my last commit for some reason", "Merging it anyway since I'd like to share this page...
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Related to #3507 : dummy data for datasets created on the Hugging Face Hub are optional. We can discuss later to make them optional for datasets in this repository as well
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Add default branch for doc building
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3893). All of your documentation changes will be reflected on that endpoint.", "Yes! And when we discovered on the Transformers side that this check fails on the GitHub actions, we added a config attribute to have a default. Se...
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Since other libraries use `main` as their default branch and it's now the standard default, you have to specify a different name in the doc config if you're using `master` like datasets (`doc-builder` tries to guess it, but in the job, we have weird checkout of merge commits so it doesn't always manage to get it right). This PR makes sure it will always use master for the dev doc (until you decide to switchto main)
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Fix CLI test checksums
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3892). All of your documentation changes will be reflected on that endpoint.", "Feel free to merge if it's good for you :)", "I've added a test @lhoestq. Once all green, I'll merge. ", "Last failing tests do not have nothin...
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Previous PR: - #3796 introduced a side effect: `datasets-cli test` generates `dataset_infos.json` with `None` checksum values. See: - #3805 This PR introduces a way for `datasets-cli test` to force to record infos, even if `verify_infos=False` Close #3848. CC: @craffel
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Fix race condition in doc build
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Following https://github.com/huggingface/datasets/runs/5499386744 it seems that race conditions that create issues when updating the doc. I took the same approach as in `transformers` to fix race conditions
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Update beans download urls
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3890). All of your documentation changes will be reflected on that endpoint.", "@albertvillanova Thanks for investigating and fixing that issue. I regenerated the `dataset_infos.json` file." ]
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Replace the old URLs with the Hub [URLs](https://huggingface.co/datasets/beans/tree/main/data). Also reported by @stevhliu. Fix #3889
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Cannot load beans dataset (Couldn't reach the dataset)
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[ "Hi ! A pull request is open to fix the dataset, we'll release a patch soon with a new release of `datasets` :)" ]
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## Describe the bug The beans dataset is unavailable to download. ## Steps to reproduce the bug ```python from datasets import load_dataset ds = load_dataset('beans') ``` ## Expected results The dataset would be downloaded with no issue. ## Actual results ``` ConnectionError: Couldn't reach https://storage.googleapis.com/ibeans/train.zip (error 403) ``` [It looks like the billing of this project has been disabled because it is associated with a delinquent account.](https://storage.googleapis.com/ibeans/train.zip ) ## Environment info Google Colab
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IterableDataset columns and feature types
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[ "#self-assign", "@alvarobartt I've assigned you the issue since I'm not actively working on it.", "Cool thanks @mariosasko I'll try to fix it in the upcoming days, thanks!", "@lhoestq so in order to address what’s not completed in this issue, do you think it makes sense to add a param `features` to `IterableD...
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Right now, an IterableDataset (e.g. when streaming a dataset) doesn't require to know the list of columns it contains, nor their types: `my_iterable_dataset.features` may be `None` However it's often interesting to know the column types and types. This helps knowing what's inside your dataset without having to manually check a few examples, and this is useful to prepare a processing pipeline or to train models. Here are a few cases that lead to `features` being `None`: 1. when loading a dataset with `load_dataset` on CSV, JSON Lines, etc. files: type inference is only done when iterating over the dataset 2. when calling `map`, because we don't know in advance what's the output of the user's function passed to `map` 3. when calling `rename_columns`, `remove_columns`, etc. because they rely on `map` Things we can consider, for each point above: 1.a infer the type automatically from the first samples on the dataset using prefetching, when the dataset builder doesn't provide the `features` 2.a allow the user to specify the `features` as an argument to `map` (this would be consistent with the non-streaming API) 2.b prefetch the first output value to infer the type 3.a don't rely on `map` directly and reuse the previous `features` and rename/remove the corresponding ones The thing is that prefetching can take a few seconds, while the operations above are instantaneous since no data are downloaded. Therefore I'm not sure whether this solution may be worth it. Maybe prefetching could also be done when explicitly asked by the user cc @mariosasko @albertvillanova
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ImageFolder improvements
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3887). All of your documentation changes will be reflected on that endpoint." ]
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This PR adds the following improvements to the `imagefolder` dataset: * skip the extract step for image files (as discussed in https://github.com/huggingface/datasets/pull/2830#discussion_r816817919) * option to drop labels by setting `drop_labels=True` (useful for image pretraining cc @NielsRogge). This is faster than loading a dataset and removing the `label` column because we don't need to iterate over the files to infer class labels.
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Retry HfApi call inside push_to_hub when 504 error
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3886). All of your documentation changes will be reflected on that endpoint.", "I made it more robust by increasing the wait time, and I also added some logs when a request is retried. Let me know if it's ok for you", "At the...
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Ass suggested by @lhoestq in #3872, this PR: - Implements a retry function - Retries HfApi call inside `push_to_hub` when 504 error. To be agreed: - max_retries = 2 (at 0.5 and 1 seconds) Fix #3872.
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Fix some shuffle docs
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Following #3842 some docs were still outdated (with `buffer_size` as the first argument)
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Fix bug in METEOR metric due to nltk version
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Fix #3883.
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The metric Meteor doesn't work for nltk ==3.6.4
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[ "Hi @zhaowei-wang98, thanks for reporting.\r\n\r\nWe are fixing it... " ]
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## Describe the bug Using the metric Meteor with nltk == 3.6.4 gives a TypeError: TypeError: descriptor 'lower' for 'str' objects doesn't apply to a 'list' object ## Steps to reproduce the bug ```python import datasets metric = datasets.load_metric("meteor") predictions = ["hello world"] references = ["hello world"] metric.compute(predictions=predictions, references=references) ``` ## Expected results TypeError: descriptor 'lower' for 'str' objects doesn't apply to a 'list' object I think this TypeError exists because input sentences are tokenized into lists of tokens and the str.lower() is applied to this list of tokens. ## Actual results No error but a meteor score ## Environment info <!-- You can run the command `datasets-cli env` and copy-and-paste its output below. --> - `datasets` version: 1.18.3 - Platform: linux - Python version: 3.8.12 - PyArrow version: 7.0.0
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Image process doc
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This PR is a first draft of how to process image data. It adds: - Load an image dataset with `image` and `path` (adds tip about `decode=False` param to access the path and bytes, thanks to @mariosasko). - Load an image using the `ImageFolder` builder. I know there is an [example](https://huggingface.co/docs/datasets/master/en/loading#image-folders) of this already, but I also wanted to add it here so users don't miss it. This doc seems important for centralizing all of the image-related things so far. Datasets has grown so quickly πŸš€ now that I think maybe splitting up the How-to guides by modality may be better since working with vision/audio data is slightly different from what users have seen up until now. This way we can continue to scale the docs to better accommodate vision/audio things. - Add a data augmentation with `set_transform`. There is only 1 example here so far, but we can certainly add more. Todo: - [x] Couldn't figure out why my augmentation function works with `set_transform` but not `map` πŸ₯². Working with @mariosasko on this!
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How to use Image folder
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[ "Even this from docs throw same error\r\n```\r\ndataset = load_dataset(\"imagefolder\", data_files=\"https://download.microsoft.com/download/3/E/1/3E1C3F21-ECDB-4869-8368-6DEBA77B919F/kagglecatsanddogs_3367a.zip\", split=\"train\")\r\n\r\n```", "Hi @INF800,\r\n\r\nPlease note that the `imagefolder` feature enhanc...
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Ran this code ``` load_dataset("imagefolder", data_dir="./my-dataset") ``` `https://raw.githubusercontent.com/huggingface/datasets/master/datasets/imagefolder/imagefolder.py` missing ``` --------------------------------------------------------------------------- FileNotFoundError Traceback (most recent call last) /tmp/ipykernel_33/1648737256.py in <module> ----> 1 load_dataset("imagefolder", data_dir="./my-dataset") /opt/conda/lib/python3.7/site-packages/datasets/load.py in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, ignore_verifications, keep_in_memory, save_infos, revision, use_auth_token, task, streaming, script_version, **config_kwargs) 1684 revision=revision, 1685 use_auth_token=use_auth_token, -> 1686 **config_kwargs, 1687 ) 1688 /opt/conda/lib/python3.7/site-packages/datasets/load.py in load_dataset_builder(path, name, data_dir, data_files, cache_dir, features, download_config, download_mode, revision, use_auth_token, script_version, **config_kwargs) 1511 download_config.use_auth_token = use_auth_token 1512 dataset_module = dataset_module_factory( -> 1513 path, revision=revision, download_config=download_config, download_mode=download_mode, data_files=data_files 1514 ) 1515 /opt/conda/lib/python3.7/site-packages/datasets/load.py in dataset_module_factory(path, revision, download_config, download_mode, force_local_path, dynamic_modules_path, data_files, **download_kwargs) 1200 f"Couldn't find a dataset script at {relative_to_absolute_path(combined_path)} or any data file in the same directory. " 1201 f"Couldn't find '{path}' on the Hugging Face Hub either: {type(e1).__name__}: {e1}" -> 1202 ) from None 1203 raise e1 from None 1204 else: FileNotFoundError: Couldn't find a dataset script at /kaggle/working/imagefolder/imagefolder.py or any data file in the same directory. Couldn't find 'imagefolder' on the Hugging Face Hub either: FileNotFoundError: Couldn't find file at https://raw.githubusercontent.com/huggingface/datasets/master/datasets/imagefolder/imagefolder.py ```
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Change the framework switches to the new syntax
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3880). All of your documentation changes will be reflected on that endpoint.", "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3880). All of your documentation changes will be reflected on...
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This PR updates the syntax of the framework-specific code samples. With this new syntax, you'll be able to: - have paragraphs of text be framework-specific instead of just code samples - have support for Flax code samples if you want. This should be merged after https://github.com/huggingface/doc-builder/pull/63 and https://github.com/huggingface/doc-builder/pull/130
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SQuAD v2 metric: create README.md
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Proposing SQuAD v2 metric card
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Update cats_vs_dogs size
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3878). All of your documentation changes will be reflected on that endpoint.", "Maybe `NonMatchingSplitsSizesError` errors should also tell the user to try using a more recent version of the dataset to get the fixes ?", "@lho...
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It seems like 12 new examples have been added to the `cats_vs_dogs`. This PR updates the size in the card and the info file to avoid a verification error (reported by @stevhliu).
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Align metadata to DCAT/DCAT-AP
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**Is your feature request related to a problem? Please describe.** Align to DCAT metadata to describe datasets **Describe the solution you'd like** Reuse terms and structure from DCAT in the metadata file, ideally generate a json-ld file dcat compliant **Describe alternatives you've considered** **Additional context** DCAT is a W3C standard extended in Europe with DCAT-AP, an example is data.europa.eu publishing datasets metadata in DCAT-AP
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Fix download_mode in dataset_module_factory
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Fix `download_mode` value set in `dataset_module_factory`. Before the fix, it was set to `bool` (default to `False`). Also set properly its default value in all public functions.
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Module namespace cleanup for v2.0
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[ "will it solve https://github.com/huggingface/datasets-preview-backend/blob/4c542a74244045929615640ccbba5a902c344c5a/pyproject.toml#L85-L89?", "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3875). All of your documentation changes will be reflected on that endpoint.", "@s...
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This is an attempt to make the user-facing `datasets`' submodule namespace cleaner: In particular, this PR does the following: * removes the unused `zip_nested` and `flatten_nest_dict` and their accompanying tests * removes `pyarrow` from the top-level namespace * properly uses `__all__` and the `from <module> import *` syntax to avoid importing the `<module>`'s submodules * cleans up the `utils` namespace * moves the `temp_seed` context manage from `datasets/utils/file_utils.py` to `datasets/utils/py_utils.py`
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add MSE and MAE metrics - V2
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[ "@mariosasko New PR here. I'm not sure how to add you as a co-author here. Also I see flake8 tests are failing, any inputs on how to resolve this ?\r\nAlso, let me know if any other changes are required. Thank you.", "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3874). Al...
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Created a new pull request to resolve unrelated changes in PR caused due to rebasing. Ref Older PR : [#3845](https://github.com/huggingface/datasets/pull/3845) Feature request here : Add support for continuous metrics (RMSE, MAE) [#3608](https://github.com/huggingface/datasets/issues/3608)
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Create SQuAD metric README.md
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3873). All of your documentation changes will be reflected on that endpoint.", "Oh one last thing I almost forgot, I think I would add a section \"Examples\" with examples of inputs and outputs and in particular: an example giv...
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Proposal for a metrics card structure (with an example based on the SQuAD metric). @thomwolf @lhoestq @douwekiela @lewtun -- feel free to comment on structure or content (it's an initial draft, so I realize there's stuff missing!).
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HTTP error 504 Server Error: Gateway Time-out
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[ "is pushing directly with git (and git-lfs) an option for you?", "I have installed git-lfs and doing this push with that\r\n", "yes but is there any way you could try pushing with `git` command line directly instead of `push_to_hub`?", "Okay. I didnt saved the dataset to my local machine. So, I processed the ...
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I am trying to push a large dataset(450000+) records with the help of `push_to_hub()` While pushing, it gives some error like this. ``` Traceback (most recent call last): File "data_split_speech.py", line 159, in <module> data_new_2.push_to_hub("user-name/dataset-name",private=True) File "/opt/conda/lib/python3.8/site-packages/datasets/dataset_dict.py", line 951, in push_to_hub repo_id, split, uploaded_size, dataset_nbytes = self[split]._push_parquet_shards_to_hub( File "/opt/conda/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 3556, in _push_parquet_shards_to_hub api.upload_file( File "/opt/conda/lib/python3.8/site-packages/huggingface_hub/hf_api.py", line 1017, in upload_file raise err File "/opt/conda/lib/python3.8/site-packages/huggingface_hub/hf_api.py", line 1008, in upload_file r.raise_for_status() File "/opt/conda/lib/python3.8/site-packages/requests/models.py", line 953, in raise_for_status raise HTTPError(http_error_msg, response=self) requests.exceptions.HTTPError: 504 Server Error: Gateway Time-out for url: https://huggingface.co/api/datasets/user-name/dataset-name/upload/main/data/train2-00041-of-00064.parquet ``` Can anyone help me to resolve this issue.
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add pandas to env command
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3871). All of your documentation changes will be reflected on that endpoint.", "Think failures are unrelated - feel free to merge whenever you want :-)" ]
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Pandas is a required packages and used quite a bit. I don't see any downside with adding its version to the `datasets-cli env` command.
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Add wikitablequestions dataset
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[ "@lhoestq Would you mind reviewing it when you're available? Thanks!\r\n", "> Awesome thanks for adding this dataset ! :) The dataset script and dataset cards look pretty good\r\n> \r\n> It looks like your `dummy_data.zip` files are quite big though (>1MB each), do you think we can reduce their sizes ? This way t...
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Making the Hub the place for datasets in Portuguese
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[ "Hi @omarespejel! I think the philosophy for `datasets` issues is to create concrete issues with proposals to add a specific, individual dataset rather than umbrella issues for things such as datasets for a language, since we could end up with hundreds of issues (one per language). I see NILC - USP has many dataset...
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Let's make Hugging Face Datasets the central hub for datasets in Portuguese :) **Motivation**. Datasets are currently quite scattered and an open-source central point such as the Hugging Face Hub would be ideal to support the growth of the Portuguese speaking community. What are some datasets in Portuguese worth integrating into the Hugging Face hub? Special thanks to @augusnunes for his collaboration on identifying the first ones: - [NILC - USP](http://www.nilc.icmc.usp.br/nilc/index.php/tools-and-resources). Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md). cc @osanseviero
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Ignore duplicate keys if `ignore_verifications=True`
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3868). All of your documentation changes will be reflected on that endpoint.", "Cool thanks ! Could you add a test please ?" ]
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Currently, it's impossible to generate a dataset if some keys from `_generate_examples` are duplicated. This PR allows skipping the check for duplicate keys if `ignore_verifications` is set to `True`.
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Update for the rename doc-builder -> hf-doc-utils
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[ "why utils? it's a builder no?", "~~@julien-c there was a vote πŸ™‚ https://huggingface.slack.com/archives/C021H1P1HKR/p1646405136644739~~\r\n\r\noh I see you already commeented in the thread as well", "Thanks ! It looks all good to me (provided `hf-doc-utils` is the name we keep in the end). I'm fine with this n...
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This PR adapts the job to the upcoming change of name of `doc-builder`.
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Bring back imgs so that forsk dont get broken
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3866). All of your documentation changes will be reflected on that endpoint.", "I think we just need to keep `datasets_logo_name.jpg` and `course_banner.png` because they appear in the README.md of the forks of `datasets`. The ...
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Add logo img
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3865). All of your documentation changes will be reflected on that endpoint.", "Superceded by https://github.com/huggingface/datasets/pull/3866" ]
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3,864
Update image dataset tags
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Align the existing image datasets' tags with new tags introduced in #3800.
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Update code blocks
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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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Manipulate columns on IterableDataset (rename columns, cast, etc.)
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3862). All of your documentation changes will be reflected on that endpoint.", "> IIUC we check if columns are present/not present directly in the yielded examples and not in info.features because info.features can be None (aft...
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I added: - add_column - cast - rename_column - rename_columns related to https://github.com/huggingface/datasets/issues/3444 TODO: - [x] docs - [x] tests
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big_patent cased version
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[ "To follow up on this: the cased and uncased versions actually contain different content, and the cased one is easier since it contains a Summary of the Invention in the input.\r\n\r\nSee the paper describing the issue here:\r\nhttps://aclanthology.org/2022.gem-1.34/", "Thanks for proposing the addition of the ca...
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Hi! I am interested in working with the big_patent dataset. In Tensorflow, there are a number of versions of the dataset: - 1.0.0 : lower cased tokenized words - 2.0.0 : Update to use cased raw strings - 2.1.2 (default): Fix update to cased raw strings. The version in the huggingface `datasets` library is the 1.0.0. I would be very interested in using the 2.1.2 cased version (used more, recently, for example in the Pegasus paper), but it does not seem to be supported (I tried using the `revision` parameter in `load_datasets`). Is there a way to already load it, or would it be possible to add that version?
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Small doc fixes
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3860). All of your documentation changes will be reflected on that endpoint.", "There are still some `.. code-block:: python` (e.g. see [this](https://huggingface.co/docs/datasets/master/en/package_reference/main_classes#datase...
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Unable to dowload big_patent (FileNotFoundError)
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[ "Hi @slvcsl, thanks for reporting.\r\n\r\nYesterday we just made a patch release of our `datasets` library that fixes this issue: version 1.18.4.\r\nhttps://pypi.org/project/datasets/#history\r\n\r\nPlease, feel free to update `datasets` library to the latest version: \r\n```shell\r\npip install -U datasets\r\n```\...
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## Describe the bug I am trying to download some splits of the big_patent dataset, using the following code: `ds = load_dataset("big_patent", "g", split="validation", download_mode="force_redownload") ` However, this leads to a FileNotFoundError. FileNotFoundError Traceback (most recent call last) [<ipython-input-3-8d8a745706a9>](https://localhost:8080/#) in <module>() 1 from datasets import load_dataset ----> 2 ds = load_dataset("big_patent", "g", split="validation", download_mode="force_redownload") 8 frames [/usr/local/lib/python3.7/dist-packages/datasets/load.py](https://localhost:8080/#) 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, script_version, **config_kwargs) 1705 ignore_verifications=ignore_verifications, 1706 try_from_hf_gcs=try_from_hf_gcs, -> 1707 use_auth_token=use_auth_token, 1708 ) 1709 [/usr/local/lib/python3.7/dist-packages/datasets/builder.py](https://localhost:8080/#) in download_and_prepare(self, download_config, download_mode, ignore_verifications, try_from_hf_gcs, dl_manager, base_path, use_auth_token, **download_and_prepare_kwargs) 593 if not downloaded_from_gcs: 594 self._download_and_prepare( --> 595 dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs 596 ) 597 # Sync info [/usr/local/lib/python3.7/dist-packages/datasets/builder.py](https://localhost:8080/#) in _download_and_prepare(self, dl_manager, verify_infos, **prepare_split_kwargs) 659 split_dict = SplitDict(dataset_name=self.name) 660 split_generators_kwargs = self._make_split_generators_kwargs(prepare_split_kwargs) --> 661 split_generators = self._split_generators(dl_manager, **split_generators_kwargs) 662 663 # Checksums verification [/root/.cache/huggingface/modules/datasets_modules/datasets/big_patent/bdefa7c0b39fba8bba1c6331b70b738e30d63c8ad4567f983ce315a5fef6131c/big_patent.py](https://localhost:8080/#) in _split_generators(self, dl_manager) 123 split_types = ["train", "val", "test"] 124 extract_paths = dl_manager.extract( --> 125 {k: os.path.join(dl_path, "bigPatentData", k + ".tar.gz") for k in split_types} 126 ) 127 extract_paths = {k: os.path.join(extract_paths[k], k) for k in split_types} [/usr/local/lib/python3.7/dist-packages/datasets/utils/download_manager.py](https://localhost:8080/#) in extract(self, path_or_paths, num_proc) 282 download_config.extract_compressed_file = True 283 extracted_paths = map_nested( --> 284 partial(cached_path, download_config=download_config), path_or_paths, num_proc=num_proc, disable_tqdm=False 285 ) 286 path_or_paths = NestedDataStructure(path_or_paths) [/usr/local/lib/python3.7/dist-packages/datasets/utils/py_utils.py](https://localhost:8080/#) in map_nested(function, data_struct, dict_only, map_list, map_tuple, map_numpy, num_proc, types, disable_tqdm) 260 mapped = [ 261 _single_map_nested((function, obj, types, None, True)) --> 262 for obj in utils.tqdm(iterable, disable=disable_tqdm) 263 ] 264 else: [/usr/local/lib/python3.7/dist-packages/datasets/utils/py_utils.py](https://localhost:8080/#) in <listcomp>(.0) 260 mapped = [ 261 _single_map_nested((function, obj, types, None, True)) --> 262 for obj in utils.tqdm(iterable, disable=disable_tqdm) 263 ] 264 else: [/usr/local/lib/python3.7/dist-packages/datasets/utils/py_utils.py](https://localhost:8080/#) in _single_map_nested(args) 194 # Singleton first to spare some computation 195 if not isinstance(data_struct, dict) and not isinstance(data_struct, types): --> 196 return function(data_struct) 197 198 # Reduce logging to keep things readable in multiprocessing with tqdm [/usr/local/lib/python3.7/dist-packages/datasets/utils/file_utils.py](https://localhost:8080/#) in cached_path(url_or_filename, download_config, **download_kwargs) 314 elif is_local_path(url_or_filename): 315 # File, but it doesn't exist. --> 316 raise FileNotFoundError(f"Local file {url_or_filename} doesn't exist") 317 else: 318 # Something unknown FileNotFoundError: Local file /root/.cache/huggingface/datasets/downloads/extracted/ad068abb3e11f9f2f5440b62e37eb2b03ee515df9de1637c55cd1793b68668b2/bigPatentData/train.tar.gz doesn't exist I have tried this in a number of machines, including on Colab, so I think this is not environment dependent. How do I load the bigPatent dataset?
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Udpate index.mdx margins
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3858). All of your documentation changes will be reflected on that endpoint." ]
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I_kwDODunzps5FSrqp
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Order of dataset changes due to glob.glob.
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[ "I agree using `glob.glob` alone is bad practice because it's not deterministic. Using `sorted` is a nice solution.\r\n\r\nNote that the `xglob` function you are referring to in the `streaming_download_manager.py` code just extends `glob.glob` for URLs - we don't change its behavior. That's why it has no `sorted()`...
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MEMBER
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## Describe the bug After discussion with @lhoestq, just want to mention here that `glob.glob(...)` should always be used in combination with `sorted(...)` to make sure the list of files returned by `glob.glob(...)` doesn't change depending on the OS system. There are currently multiple datasets that use `glob.glob()` without making use of `sorted(...)` even the streaming download manager (if I'm not mistaken): https://github.com/huggingface/datasets/blob/c14bfeb4af89da14f870de5ddaa584b08aa08eeb/src/datasets/utils/streaming_download_manager.py#L483
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PR_kwDODunzps40GUSf
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Fix push_to_hub with null images
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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3856). All of your documentation changes will be reflected on that endpoint." ]
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This code currently raises an error because of the null image: ```python import datasets dataset_dict = { 'name': ['image001.jpg', 'image002.jpg'], 'image': ['cat.jpg', None] } features = datasets.Features({ 'name': datasets.Value('string'), 'image': datasets.Image(), }) dataset = datasets.Dataset.from_dict(dataset_dict, features) dataset.push_to_hub("username/dataset") # this line produces an error: 'NoneType' object is not subscriptable ``` I fixed this in this PR TODO: - [x] add a test
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Bad error message when loading private dataset
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[ "We raise the error β€œ FileNotFoundError: can’t find the dataset” mainly to follow best practice in security (otherwise users could be able to guess what private repositories users/orgs may have)\r\n\r\nWe can indeed reformulate this and add the \"If this is a private repository,...\" part !", "Resolved via https:...
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MEMBER
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## Describe the bug A pretty common behavior of an interaction between the Hub and datasets is the following. An organization adds a dataset in private mode and wants to load it afterward. ```python from transformers import load_dataset ds = load_dataset("NewT5/dummy_data", "dummy") ``` This command then fails with: ```bash FileNotFoundError: Couldn't find a dataset script at /home/patrick/NewT5/dummy_data/dummy_data.py or any data file in the same directory. Couldn't find 'NewT5/dummy_data' on the Hugging Face Hub either: FileNotFoundError: Dataset 'NewT5/dummy_data' doesn't exist on the Hub ``` **even though** the user has access to the website `NewT5/dummy_data` since she/he is part of the org. We need to improve the error message here similar to how @sgugger, @LysandreJik and @julien-c have done it for transformers IMO. ## Steps to reproduce the bug E.g. execute the following code to see the different error messages between `transformes` and `datasets`. 1. Transformers ```python from transformers import BertModel BertModel.from_pretrained("NewT5/dummy_model") ``` The error message is clearer here - it gives: ``` OSError: patrickvonplaten/gpt2-xl is not a local folder and is not a valid model identifier listed on 'https://huggingface.co/models' If this is a private repository, make sure to pass a token having permission to this repo with `use_auth_token` or log in with `huggingface-cli login` and pass `use_auth_token=True`. ``` Let's maybe do the same for datasets? The PR was introduced to `transformers` here: https://github.com/huggingface/transformers/pull/15261 ## Expected results Better error message ## Actual results Specify the actual results or traceback. ## Environment info <!-- You can run the command `datasets-cli env` and copy-and-paste its output below. --> - `datasets` version: 1.18.4.dev0 - Platform: Linux-5.15.15-76051515-generic-x86_64-with-glibc2.34 - Python version: 3.9.7 - PyArrow version: 6.0.1
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3,854
load only England English dataset from common voice english dataset
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[ "Hi @amanjaiswal777,\r\n\r\nFirst note that the dataset you are trying to load is deprecated: it was the Common Voice dataset release as of Dec 2020.\r\n\r\nCurrently, Common Voice dataset releases are directly hosted on the Hub, under the Mozilla Foundation organization: https://huggingface.co/mozilla-foundation\r...
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training_data = load_dataset("common_voice", "en",split='train[:250]+validation[:250]') testing_data = load_dataset("common_voice", "en", split="test[:200]") I'm trying to load only 8% of the English common voice data with accent == "England English." Can somebody assist me with this? **Typical Voice Accent Proportions:** - 24% United States English - 8% England English - 5% India and South Asia (India, Pakistan, Sri Lanka) - 3% Australian English - 3% Canadian English - 2% Scottish English - 1% Irish English - 1% Southern African (South Africa, Zimbabwe, Namibia) - 1% New Zealand English Can we replicate this for Age as well? **Age proportions of the common voice:-** - 24% 19 - 29 - 14% 30 - 39 - 10% 40 - 49 - 6% < 19 - 4% 50 - 59 - 4% 60 - 69 - 1% 70 – 79
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