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[ "_The documentation is not available anymore as the PR was closed or merged._" ]

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[ "_The documentation is not available anymore as the PR was closed or merged._" ]

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[ "_The documentation is not available anymore as the PR was closed or merged._" ]

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[ "Thanks for reporting, @StevenTang1998.\r\n\r\nI'm looking into it. ", "Hi @StevenTang1998,\r\n\r\nWe have fixed the issue:\r\n- #4389\r\n\r\nThe fix will be available in our next `datasets` library release. In the meantime, you can incorporate that fix by installing `datasets` from our GitHub repo:\r\n```\r\npip install git+https://github.com/huggingface/datasets#egg=datasets\r\n```", "Thanks for your reply!!\r\nAnd the totto dataset has the same problem. The url should be change to [https://storage.googleapis.com/totto-public/totto_data.zip](https://storage.googleapis.com/totto-public/totto_data.zip).", "Hi again @StevenTang1998,\r\n\r\nI don't see any problem when loading `totto` dataset:\r\n```python\r\nIn [4]: import datasets\r\n ...: ds = datasets.load_dataset(\"totto\")\r\nDownloading builder script: 5.58kB [00:00, 5.33MB/s] \r\nDownloading metadata: 2.78kB [00:00, 2.96MB/s] \r\nUsing custom data configuration default\r\nDownloading and preparing dataset totto/default (download: 179.03 MiB, generated: 706.59 MiB, post-processed: Unknown size, total: 885.62 MiB) to .../.cache/huggingface/datasets/totto/default/1.0.0/263c85871e5451bc892c65ca0306c0629eb7beb161e0eb998f56231562335dd2...\r\nDownloading data: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 188M/188M [00:32<00:00, 5.77MB/s]\r\nDataset totto downloaded and prepared to .../.cache/huggingface/datasets/totto/default/1.0.0/263c85871e5451bc892c65ca0306c0629eb7beb161e0eb998f56231562335dd2. Subsequent calls will reuse this data.\r\n100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<00:00, 147.95it/s]\r\n\r\nIn [5]: ds\r\nOut[5]: \r\nDatasetDict({\r\n train: Dataset({\r\n features: ['id', 'table_page_title', 'table_webpage_url', 'table_section_title', 'table_section_text', 'table', 'highlighted_cells', 'example_id', 'sentence_annotations', 'overlap_subset'],\r\n num_rows: 120761\r\n })\r\n validation: Dataset({\r\n features: ['id', 'table_page_title', 'table_webpage_url', 'table_section_title', 'table_section_text', 'table', 'highlighted_cells', 'example_id', 'sentence_annotations', 'overlap_subset'],\r\n num_rows: 7700\r\n })\r\n test: Dataset({\r\n features: ['id', 'table_page_title', 'table_webpage_url', 'table_section_title', 'table_section_text', 'table', 'highlighted_cells', 'example_id', 'sentence_annotations', 'overlap_subset'],\r\n num_rows: 7700\r\n })\r\n})\r\n```", "Sorry, I didn't express it clearly. It's the totto dataset from gem.\r\ndatasets.load_dataset('gem', 'totto')\r\n", "@StevenTang1998 fixed in:\r\n- #4396", "Thanks!!" ]

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[ "_The documentation is not available anymore as the PR was closed or merged._", "I should point out that the hash will be the same if computed twice with the same code on the same version of dill (after adding huggingface's code that removes line numbers and file names, and sorts globals.) My changes in dill 0.3.5 and ones that I will make in 0.3.6 will result in different pickles than the ones dill 0.3.4 was making. This should still be fine for caching.", "Just some comments @lhoestq:\r\n\r\nThe best practice for testing is to have a `test_<filename>.py` for each `<filename>.py`. Therefore in order to have the filenames aligned, I would propose:\r\n- either renaming `fingerprint.py` to `caching.py`\r\n- or renaming `test_caching.py` to `test_fingerprint.py`\r\n\r\nOn the other hand, my idea when implementing this test was not to test all the functionalities of the `Hasher`, but just to have a regression test that fails if dill version is > 0.3.4 and the pin in our `setup.py` is not present. Just recall that we had no failing test in our CI when the issue with dill was found on `transformers`.\r\n\r\nThe objective of this PR is just to have a regression test for that case: I tested and I got `AttributeError: module 'dill._dill' has no attribute 'stack'`\r\n\r\nFor this regression test, I took into account this comment by @gugarosa: https://github.com/huggingface/datasets/issues/4379#issuecomment-1133131825\r\n\r\nThere is no equivalent test in `test_caching.py` because our CI did not fail before pinning dill.", "Ok I see, renaming it to `test_fingerprint.py` sounds like a good idea :)" ]

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[ "_The documentation is not available anymore as the PR was closed or merged._", "This looks like a breaking change no ?\r\nAlso could you explain why it would be better this way ?", "The might be only there to help type checkers, but I am not too familiar with the code base to know for sure. I think this might be useful:\n\nhttps://docs.python.org/3/library/typing.html#typing.TYPE_CHECKING", "> This looks like a breaking change no ?\r\n> Also could you explain why it would be better this way ?\r\n\r\nSorry, @lhoestq, I naively thought it was obvious. I have tried to give some arguments in the motivation of this PR (see above). I can give additional arguments if needed. " ]

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[ "Hi @NouamaneTazi, thanks for reporting.\r\n\r\nPlease note that both datasets are cached in the same directory because their loading builder classes have the same name: `class MTOP(datasets.GeneratorBasedBuilder)`.\r\n\r\nYou should name their builder classes differently, e.g.:\r\n- `MtopDomain`\r\n- `MtopIntent`", "Hi @NouamaneTazi, please note that after our fix:\r\n- #4388\r\n\r\nwe do not consider the class name anymore, but the name of the file where the loading builder class is implemented. " ]

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[ "_The documentation is not available anymore as the PR was closed or merged._" ]

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[ "Fixed by:\r\n- #4380 ", "Just an additional insight, the latest dill (either 0.3.5 or 0.3.5.1) also broke the hashing/fingerprinting of any mapping function.\r\n\r\nFor example:\r\n```\r\nfrom datasets import load_dataset\r\n\r\nd = load_dataset(\"rotten_tomatoes\")\r\nd.map(lambda x: x)\r\n```\r\n\r\nReturns the standard non-dillable error:\r\n```\r\nParameter 'function'=<function <lambda> at 0x7fe7d18c9560> of the transform datasets.arrow_dataset.Dataset._map_single couldn't be hashed properly....\r\n```", "@albertvillanova ExamplesTests.test_run_speech_recognition_seq2seq is in which file?", "Thanks a lot @gugarosa for the insight: we will incorporate it in our CI as regression testing for future dill releases.", "Hi @anivegesana, that test is in `transformers` library:\r\n- https://github.com/huggingface/transformers/blob/main/examples/pytorch/test_pytorch_examples.py#L449\r\n- https://github.com/huggingface/transformers/blob/main/examples/pytorch/speech-recognition/run_speech_recognition_seq2seq.py ", "@albertvillanova\n\nI did a deep dive into @gugarosa's problem and found the issue and it might be related to the one @sgugger discovered. In dill 0.3.5(.1), I created a new `save_function` that fixes a bug in dill that prevented the pickling of recursive inner functions. It was a more complete solution to the problem that `dill._dill.stack` tried to solve in the internal API of dill. Since `dill._dill.stack` was no longer needed, I removed it. Since datasets copies the `save_function` directly from the dill API, it stops working with the new dill version since `dill._dill.stack` is no longer present and the `save_function` has been updated with new code.\r\n\r\nhttps://github.com/huggingface/datasets/blob/95193ae61e92aa537d0c65d37a1fd9d2393aae89/src/datasets/utils/py_utils.py#L607-L678\r\n\r\n~If the dill version is below 0.3.5, you should keep this function. If it is after, you would need to update your copy of `save_function` to use the code I introduced, or manually add a `stack` variable to `dill._dill` if it doesn't exist. Fortunately, in any version of Python 3.7+, dictionaries are always in insertion order and dill no longer supports Python 3.6 or older. So, any globals dictionary saved by dill 0.3.5+ will be deterministic given that the version of dill is held constant and this save_function is unnecessary for newer versions of dill.~\r\n\r\nAh. I see what is happening. I guess a different copy of the function code is needed that sorts the global variables by name.\r\n\r\n```py\r\nif dill.__version__.split('.') < ['0', '3', '5']:\r\n # current save_function code inside here\r\nelse:\r\n # new save_function code inside here with the following line inserted after creating the globals\r\n globs = {k: globs[k] for k in sorted(globs.keys())} \r\n```\r\n\r\nWill look into the test case @sgugger pointed out after that and verify if this is causing the problem.\r\n\r\nI am actually looking into rewriting the global variables code in uqfoundation/dill#466 and will keep this in mind and will try to create an easy way to modify the global variables in dill 0.3.6 (for example, sort them by key like datasets does).", "Thanks a lot for your investigation @anivegesana.\r\n\r\nYes, we copied-pasted the old `save_function` function from `dill`, just adding a line to make deterministic the order of global variables `globs`. \r\n\r\nHowever, this function has changed a lot from version 0.3.5, after your PR (thank you for the fix in recursiveness, indeed):\r\n- uqfoundation/dill#443\r\n\r\nWe have to address this change.\r\n\r\nIf finally your PR to sort global variables is merged into dill 0.3.6, that will make our life easier, as the tweak will no longer be necessary. ;)\r\n\r\nI have included a regression test so that we are sure future releases of dill do not break `datasets`:\r\n- #4385 ", "I should note that because Python 3.6 and older are now deprecated and Python 3.7 has insertion order dictionaries, the globals in dill will have a deterministic order, just not sorted. I would still keep it sorted like you have it to help with stability (for example, if someone reorders variables in a file, then sorting the globals would not invalidate the cache.)\n\nIt seems that the order is not quite deterministic in IPython. Huggingface datasets seems to do well in Jupyter regardless, so it is not a good idea to remove the sorting. uqfoundation/dill#19" ]

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[ "_The documentation is not available anymore as the PR was closed or merged._", "& thank you!" ]

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[ "_The documentation is not available anymore as the PR was closed or merged._" ]

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[ "DUPLICATED comment from https://github.com/huggingface/datasets/issues/3807:\r\n\r\nmy code:\r\n```\r\nfrom datasets import load_dataset\r\n\r\ndataset = load_dataset(\"irc_disentangle\", download_mode=\"force_redownload\")\r\n```\r\nhowever, it produces the same error\r\n```\r\n[38](file:///Library/Frameworks/Python.framework/Versions/3.8/lib/python3.8/site-packages/datasets/utils/info_utils.py?line=37) if len(bad_urls) > 0:\r\n [39](file:///Library/Frameworks/Python.framework/Versions/3.8/lib/python3.8/site-packages/datasets/utils/info_utils.py?line=38) error_msg = \"Checksums didn't match\" + for_verification_name + \":\\n\"\r\n---> [40](file:///Library/Frameworks/Python.framework/Versions/3.8/lib/python3.8/site-packages/datasets/utils/info_utils.py?line=39) raise NonMatchingChecksumError(error_msg + str(bad_urls))\r\n [41](file:///Library/Frameworks/Python.framework/Versions/3.8/lib/python3.8/site-packages/datasets/utils/info_utils.py?line=40) logger.info(\"All the checksums matched successfully\" + for_verification_name)\r\n\r\nNonMatchingChecksumError: Checksums didn't match for dataset source files:\r\n['https://github.com/jkkummerfeld/irc-disentanglement/tarball/master']\r\n```\r\nI attempted to use the `ignore_verifications' as such:\r\n\r\n```\r\nds = datasets.load_dataset('irc_disentangle', download_mode=\"force_redownload\", ignore_verifications=True)\r\n\r\nDownloading builder script: 12.0kB [00:00, 5.92MB/s] \r\nDownloading metadata: 7.58kB [00:00, 3.48MB/s] \r\nNo config specified, defaulting to: irc_disentangle/ubuntu\r\nDownloading and preparing dataset irc_disentangle/ubuntu (download: 112.98 MiB, generated: 60.05 MiB, post-processed: Unknown size, total: 173.03 MiB) to /Users/laylabouzoubaa/.cache/huggingface/datasets/irc_disentangle/ubuntu/1.0.0/0f24ab262a21d8c1d989fa53ed20caa928f5880be26c162bfbc02445dbade7e5...\r\nDownloading data: 118MB [00:09, 12.1MB/s] \r\n \r\nDataset irc_disentangle downloaded and prepared to /Users/laylabouzoubaa/.cache/huggingface/datasets/irc_disentangle/ubuntu/1.0.0/0f24ab262a21d8c1d989fa53ed20caa928f5880be26c162bfbc02445dbade7e5. Subsequent calls will reuse this data.\r\n100%|██████████| 3/3 [00:00<00:00, 675.38it/s]\r\n```\r\nbut, this returns an empty set?\r\n```\r\nDatasetDict({\r\n train: Dataset({\r\n features: ['id', 'raw', 'ascii', 'tokenized', 'date', 'connections'],\r\n num_rows: 0\r\n })\r\n test: Dataset({\r\n features: ['id', 'raw', 'ascii', 'tokenized', 'date', 'connections'],\r\n num_rows: 0\r\n })\r\n validation: Dataset({\r\n features: ['id', 'raw', 'ascii', 'tokenized', 'date', 'connections'],\r\n num_rows: 0\r\n })\r\n})\r\n```\r\nnot sure what else to try at this point?\r\nThanks in advanced🤗", "Thanks for reporting, @labouz. I'm addressing it. ", "The issue with checksum and empty dataset has been fixed by:\r\n- #4377\r\n\r\nTo load the dataset, you should force the re-generation of the dataset from the downloaded file by passing `download_mode=\"reuse_cache_if_exists\"` to `load_dataset`.\r\n\r\nIn relation with the issue with the dataset viewer, first the dataset should be refactored to support streaming.", "parfait!\r\nit works now, thank you 🙏 ", "Hi there, \r\nI see this issue is closed, but I am wondering if there is any chance the source files have been moved since this fix? I am stumbling into the same NonMatchingChecksumError noted by lebouz's second post once 118MB of data has been downloaded, and have tried the solutions noted in the various fix checksum posts linked here and in other posts regarding passing in \"reuse_cache_if_exists\" to download_mode. Any suggestions? Thank you!\r\n\r\n" ]

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[ "_The documentation is not available anymore as the PR was closed or merged._", "Alright this is finally ready for review ! It's quite long I'm sorry, but it's not easy to disentangle everything ^^'\r\n\r\nThe main additions are in\r\n- src/datasets/formatting/dataset_wrappers/torch_iterable_dataset.py\r\n- src/datasets/iterable_dataset.py\r\n- src/datasets/utils/patching.py", "Added some comments and an error when lists have different lengths for sharding :)", "Let's resolve the merge conflict and the CI error (if it's related to the changes), and I can review the PR again.", "Feel free to review again :) The CI fail is unrelated to this PR and will be fixed by https://github.com/huggingface/datasets/pull/4472 (the hub now returns 401 instead of 404 for unauthenticated requests to non-existing repos)", "CI failures are unrelated to this PR - merging :)\r\n\r\n(CI fails are a mix of pip install fails and Hub fails)", "@lhoestq you're our hero :)" ]

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[ "Hi !\r\n\r\nMy guess is that some examples in your dataset are bigger than your RAM, and therefore loading them in RAM to pass them to `remove_non_indic_sentences` takes forever because it might use SWAP memory.\r\n\r\nMaybe several examples in your dataset are grouped together, can you check `len(lang_dataset[\"train\"])` and `lang_dataset[\"train\"].data.nbytes` of both datasets please ? It can also be helpful to check the distribution of lengths of each examples in your dataset.", "Closing due to inactivity" ]

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[ "_The documentation is not available anymore as the PR was closed or merged._" ]

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[ "_The documentation is not available anymore as the PR was closed or merged._" ]

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[ "_The documentation is not available anymore as the PR was closed or merged._" ]

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[ "_The documentation is not available anymore as the PR was closed or merged._" ]

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[ "_The documentation is not available anymore as the PR was closed or merged._", "Once we have added `long_answer_candidates` maybe it would be worth to also add the missing `candidate_index` (inside `long_answer`). What do you think, @seirasto ?", "Also note the \"Data Fields\" section in the README is missing the `long_answer` field.\r\n\r\nMoreover, there is no instance example in \"Data Instances\" section.", "We could either make these fixes in this PR or in a subsequent PR.", "@albertvillanova I've added the missing fields and updated the README to include a data instance and some other things. ", "Great! I've made the updates to align the README. Please let me know if I missed anything.", "As there were many minor little fixes, I thought it would be easier to fix them directly.", "I think the loading script is OK now. If it is also validated by another datasets maintainer, I could run the generation of the pre-processed data and then merge this PR into master (once all the tests are green).\r\n\r\nCC: @lhoestq ", "It looks good to me, thanks @seirasto !", "I have merged the master branch, so that we include all the fixes on Apache Beam + Google Dataflow.", "Pre-processing is running!\r\n\r\nAlready finished for \"dev\" config:\r\n```python\r\nIn [2]: ds = load_dataset(\"datasets/natural_questions\", \"dev\")\r\n\r\nIn [3]: ds\r\nOut[3]: \r\nDatasetDict({\r\n validation: Dataset({\r\n features: ['id', 'document', 'question', 'long_answer_candidates', 'annotations'],\r\n num_rows: 7830\r\n })\r\n})\r\n```", "There is an issue while running the preprocessing for the \"default\" (train+dev) config. Train data files are larger than than dev ones and workers run out of memory.\r\n\r\nI'm opening a separate issue to handle this problem: #4525", "@seirasto is proposing uploading their preprocessed data files to our Datasets bucket.\r\n\r\nI think @lhoestq can give a more informed answer about authentication requirements.", "Now that the data fiels are uploaded, can you merge the `main` branch into yours to re-trigger the CI @seirasto please ? :) Then I think we can merge if it's good for you @albertvillanova ", "Merge is done! I think someone needs to approve the CI to run :) ", "Can you run `make style` to fix the code formatting required by the CI please ?", "Thanks @albertvillanova! I've committed all your suggestions.", "The CI is green. I'm merging this PR." ]

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[ "I included the change from https://github.com/huggingface/datasets/pull/4302 directly in this PR, this way the datasets will be updated right away in the CI (the CI is only triggered when a dataset card is changed)", "_The documentation is not available anymore as the PR was closed or merged._", "Alright it's ready now :)\r\n\r\nHere is an example for the `ade_corpus_v2` dataset card. Notice the new `configs` key:\r\n\r\nhttps://github.com/huggingface/datasets/blob/76d9a141740a03f6836feb251f6059894b8d8046/datasets/ade_corpus_v2/README.md#L1-L78\r\n\r\nCI failures are only related to dataset cards missing some content." ]

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[ "Duplicate of:\r\n- #3956\r\n\r\nI think you should report that issue to `elasticsearch` library: https://github.com/elastic/elasticsearch-py" ]

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[ "_The documentation is not available anymore as the PR was closed or merged._", "Closing in favor of https://github.com/huggingface/datasets/pull/4367" ]

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[ "_The documentation is not available anymore as the PR was closed or merged._" ]

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[ "Hi! A dataset has to be streamable to work with the viewer. I did a quick test, and yours is, so this might be a bug in the viewer. cc @severo \r\n", "Looking at it. The message is now:\r\n\r\n```\r\nMessage: cannot cache function '__shear_dense': no locator available for file '/src/services/worker/.venv/lib/python3.9/site-packages/librosa/util/utils.py'\r\n```\r\n\r\nso possibly it's related to the libraries versions?\r\n", "Maybe this SO thread can help: https://stackoverflow.com/questions/59290386/runtimeerror-at-cannot-cache-function-shear-dense-no-locator-available-fo", "Same error for https://huggingface.co/datasets/LIUM/tedlium/viewer/release1/test. cc @sanchit-gandhi . I'm on it", "Fixed in the datasets viewer, by setting the `NUMBA_CACHE_DIR` env var to a writable directory.", "https://huggingface.co/datasets/Roh/ryanspeech/viewer/male/train\r\n\r\n<img width=\"1538\" alt=\"Capture d’écran 2022-06-08 à 11 30 08\" src=\"https://user-images.githubusercontent.com/1676121/172583285-4cd49a0f-5715-423b-95dd-5f6ace3b2416.png\">\r\n", "https://huggingface.co/datasets/LIUM/tedlium/viewer/\r\n\r\n<img width=\"1538\" alt=\"Capture d’écran 2022-06-08 à 14 31 52\" src=\"https://user-images.githubusercontent.com/1676121/172616897-fbcb7df7-0308-4d09-a17d-48826bc91374.png\">\r\n" ]

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[ "_The documentation is not available anymore as the PR was closed or merged._", "Thanks for contributing @leondz.\r\n\r\nThe checksums of the files have changed because more languages have been added:\r\n- the new language codes need to be added to the dataset card (README file)\r\n- I think the dataset version number should also be increased, so that users who had previously cached it, get a new dataset download (with the additional languages)", "Yep! All done (also fixed the language tags in the README which were iso639-3 instead of the expected bcp47)", "I guess the language code CI failure is due to languages.json being a subset of bcp47 (see issue #4304), happy to contribute a solution here, e.g. autogeneration of the lang list from the relevant isos and the ietf bcp47 subtag register or full code for validation", "> Thanks again for your contribution, @leondz.\r\n> \r\n> Yes, I think it is OK to set version 1.0.0 (as previous was 0.0.0).\r\n> \r\n> One of the CI failures is related to dummy data: once you have updated the dataset version, the dummy_data ZIP file should be moved from \"dummy/0.0.0/dummy_data.zip\" to \"dummy/1.0.0/dummy_data.zip\".\r\n\r\nOh, thanks, I missed that one\r\n\r\n\r\n> Other CI failure is related to missing languages in our resources file. This has been addressed in this PR:\r\n> \r\n> * #4371\r\n> \r\n> You should merge master branch into your feature branch to incorporate that fix.\r\n\r\nYeah, I saw this :) I already have the merge, thanks. I'm talking about the longer-term picture: every time another language code comes up (e.g. da-bornholm or es-VE), the json will need updating, because the current approach is non-exhaustive manual whitelisting instead of relying on the established bcp standard." ]

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[ "CI seems to fail due to languages incorrectly being flagged as invalid, I guess that's related to the currently-broken bcp47 validation (see #4304)", "_The documentation is not available anymore as the PR was closed or merged._" ]

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[ "_The documentation is not available anymore as the PR was closed or merged._" ]

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[ "@lhoestq I can take this issue. Please can you point out to me where I can find the other positional arguments?", "Hi @RohitRathore1 :)\r\n\r\nYou can find all the YAML tags in the tagging app here: https://hf.co/spaces/huggingface/datasets-tagging). They're all passed as arguments to a DatasetMetadata object used to validate the tags." ]

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[ "_The documentation is not available anymore as the PR was closed or merged._" ]

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[ "_The documentation is not available anymore as the PR was closed or merged._", "This PR requires one of these other PRs being merged first:\r\n- #4359 \r\n- huggingface/doc-builder#211" ]

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[ "_The documentation is not available anymore as the PR was closed or merged._" ]

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[ "Hi! Yes, the docs are outdated. Expect this to be fixed soon. \r\n\r\nIn the meantime, you can try to fix the issue yourself.\r\n\r\nThese are the configs/language pairs supported by `wmt15` from which you can choose:\r\n* `cs-en` (Czech - English)\r\n* `de-en` (German - English)\r\n* `fi-en` (Finnish- English)\r\n* `fr-en` (French - English)\r\n* `ru-en` (Russian - English)\r\n\r\nAnd the current implementation always uses all the subsets available for a language, so to define custom subsets, you'll have to clone the repo from the Hub and replace the line https://huggingface.co/datasets/wmt15/blob/main/wmt_utils.py#L688 with:\r\n`for split, ss_names in (self._subsets if self.config.subsets is None else self.config.subsets).items()`\r\n\r\nThen, you can load the dataset as follows:\r\n```python\r\nfrom datasets import load_dataset\r\ndset = load_dataset(\"path/to/local/wmt15_folder\", \"<one of 5 available configs>\", subsets=...)", "@mariosasko thanks a lot for the suggested fix! ", "Hi @mariosasko \r\n\r\nAre the docs updated? If not, I would like to get on it. I am new around here, would we helpful, if you can guide.\r\n\r\nThanks", "Hi @khushmeeet! The docs haven't been updated, so feel free to work on this issue. This is a tricky issue, so I'll give the steps you can follow to fix this:\r\n\r\nFirst, this code:\r\nhttps://github.com/huggingface/datasets/blob/7cff5b9726a223509dbd6224de3f5f452c8d924f/src/datasets/load.py#L113-L118\r\n\r\nneeds to be replaced with (makes the dataset builder search more robust and allows us to remove the ABC stuff from `wmt_utils.py`):\r\n```python\r\n for name, obj in module.__dict__.items():\r\n if inspect.isclass(obj) and issubclass(obj, main_cls_type):\r\n if inspect.isabstract(obj):\r\n continue\r\n module_main_cls = obj\r\n obj_module = inspect.getmodule(obj)\r\n if obj_module is not None and module == obj_module:\r\n break\r\n```\r\n\r\nThen, all the `wmt_utils.py` scripts need to be updated as follows (these are the diffs with the requiered changes):\r\n````diff\r\n import os\r\n import re\r\n import xml.etree.cElementTree as ElementTree\r\n-from abc import ABC, abstractmethod\r\n\r\n import datasets\r\n````\r\n\r\n````diff\r\nlogger = datasets.logging.get_logger(__name__)\r\n\r\n\r\n _DESCRIPTION = \"\"\"\\\r\n-Translate dataset based on the data from statmt.org.\r\n+Translation dataset based on the data from statmt.org.\r\n\r\n-Versions exists for the different years using a combination of multiple data\r\n-sources. The base `wmt_translate` allows you to create your own config to choose\r\n-your own data/language pair by creating a custom `datasets.translate.wmt.WmtConfig`.\r\n+Versions exist for different years using a combination of data\r\n+sources. The base `wmt` allows you to create a custom dataset by choosing\r\n+your own data/language pair. This can be done as follows:\r\n\r\n ```\r\n-config = datasets.wmt.WmtConfig(\r\n- version=\"0.0.1\",\r\n+from datasets import inspect_dataset, load_dataset_builder\r\n+\r\n+inspect_dataset(\"<insert the dataset name\", \"path/to/scripts\")\r\n+builder = load_dataset_builder(\r\n+ \"path/to/scripts/wmt_utils.py\",\r\n language_pair=(\"fr\", \"de\"),\r\n subsets={\r\n datasets.Split.TRAIN: [\"commoncrawl_frde\"],\r\n datasets.Split.VALIDATION: [\"euelections_dev2019\"],\r\n },\r\n )\r\n-builder = datasets.builder(\"wmt_translate\", config=config)\r\n-```\r\n\r\n+# Standard version\r\n+builder.download_and_prepare()\r\n+ds = builder.as_dataset()\r\n+\r\n+# Streamable version\r\n+ds = builder.as_streaming_dataset()\r\n+```\r\n \"\"\"\r\n````\r\n\r\n````diff\r\n+class Wmt(datasets.GeneratorBasedBuilder):\r\n \"\"\"WMT translation dataset.\"\"\"\r\n+\r\n+ BUILDER_CONFIG_CLASS = WmtConfig\r\n\r\n def __init__(self, *args, **kwargs):\r\n- if type(self) == Wmt and \"config\" not in kwargs: # pylint: disable=unidiomatic-typecheck\r\n- raise ValueError(\r\n- \"The raw `wmt_translate` can only be instantiated with the config \"\r\n- \"kwargs. You may want to use one of the `wmtYY_translate` \"\r\n- \"implementation instead to get the WMT dataset for a specific year.\"\r\n- )\r\n super(Wmt, self).__init__(*args, **kwargs)\r\n\r\n @property\r\n- @abstractmethod\r\n def _subsets(self):\r\n \"\"\"Subsets that make up each split of the dataset.\"\"\"\r\n````\r\n```diff\r\n \"\"\"Subsets that make up each split of the dataset for the language pair.\"\"\"\r\n source, target = self.config.language_pair\r\n filtered_subsets = {}\r\n- for split, ss_names in self._subsets.items():\r\n+ subsets = self._subsets if self.config.subsets is None else self.config.subsets\r\n+ for split, ss_names in subsets.items():\r\n filtered_subsets[split] = []\r\n for ss_name in ss_names:\r\n dataset = DATASET_MAP[ss_name]\r\n```\r\n\r\n`wmt14`, `wmt15`, `wmt16`, `wmt17`, `wmt18`, `wmt19` and `wmt_t2t` have this script, so all of them need to be updated. Also, the dataset summaries from the READMEs of these datasets need to be updated to match the new `_DESCRIPTION` string. And that's it! Let me know if you need additional help.", "Hi @mariosasko ,\r\n\r\nI have made the changes as suggested by you and have opened a PR #4537.\r\n\r\nThanks", "Resolved via #4554 " ]

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[ "_The documentation is not available anymore as the PR was closed or merged._" ]

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[ "Hi ! Thanks for reporting :) `datasets` usually returns a `pa.lib.ArrowInvalid` error if the feature types don't match.\r\n\r\nIt would be awesome if we had a way to reproduce the `OverflowError` in this case, to better understand what happened and be able to provide the best error message" ]

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[ "Hi! I like this idea. For consistency with `load_dataset`, we can use `fsspec`'s `TqdmCallback` in `.load_from_disk` to monitor the number of bytes downloaded, and in `.save_to_disk`, we can track the number of saved shards for consistency with `push_to_hub` (after we implement https://github.com/huggingface/datasets/issues/4196)." ]

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[ "Thanks for your contribution, @YEdenZ.\r\n\r\nPlease note that our old `metrics` module is in the process of being incorporated to a separate library called `evaluate`: https://github.com/huggingface/evaluate\r\n\r\nTherefore, I would ask you to transfer your PR to that repository. Thank you." ]

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[ "Note that this same issue occurs even if i preprocess with the more default way of tokenizing that uses LayoutLMv2Processor's internal OCR:\r\n\r\n```python\r\n feature_extractor = LayoutLMv2FeatureExtractor()\r\n tokenizer = LayoutLMv2Tokenizer.from_pretrained(\"microsoft/layoutlmv2-base-uncased\")\r\n processor = LayoutLMv2Processor(feature_extractor, tokenizer)\r\n encoded_inputs = processor(images, padding=\"max_length\", truncation=True)\r\n encoded_inputs[\"image\"] = np.array(encoded_inputs[\"image\"])\r\n encoded_inputs[\"label\"] = examples['label_id']\r\n```", "Wanted to make sure anyone that finds this also finds my other report: https://github.com/huggingface/datasets/issues/4352", "Did you close it because you found that it was due to the incorrect Feature types ?", "Yeah-- my analysis of the issue was wrong in this one so I just closed it while linking to the new issue", "I met with the same problem when doing some experiments about layoutlm. I tried to set the writer_batch_size to 1, and the error still exists. Is there any solutions to this problem?", "The problem lies in how your Features are defined. It's erroring out when it actually goes to write them to disk" ]

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[ "Hi, thanks for reporting! `git bisect` points to #2986 as the PR that introduced the bug. Since then, there have been some additional changes to the loading logic, and in the current state, `force_local_path` (set via `local_path`) forbids pulling a script from the internet instead of downloading it: https://github.com/huggingface/datasets/blob/cfae0545b2ba05452e16136cacc7d370b4b186a1/src/datasets/inspect.py#L89-L91\r\n\r\ncc @lhoestq: `force_local_path` is only used in `inspect_dataset` and `inspect_metric`. Is it OK if we revert the behavior to match the old one?", "Good catch ! Yea I think it's fine :)" ]

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[ "_The documentation is not available anymore as the PR was closed or merged._", "@lhoestq thanks for your review.\r\n\r\nPlease note that `xjoin` cannot be used in this context, as it always returns a POSIX path string and this is not suitable on Windows machines.", "<s>`xjoin` returns windows paths (not posix) on windows, since it just extends`os.path.join` </s>\r\n\r\nActually you are right.\r\n\r\nhttps://github.com/huggingface/datasets/blob/08ec04ccb59630a3029b2ecd8a14d327bddd0c4a/src/datasets/utils/streaming_download_manager.py#L104-L105\r\n\r\nThough this is not an issue because posix paths (as returned by Path().as_posix()) work on windows. That's why we can replace `os.path.join` with `xjoin` in streaming mode. They look like `c:/Program Files/` or something (can't confirm right now, I don't have a windows with me)", "Until now, we have always replaced \"/\" in paths with `os.path.join` (`os.sep`,...) in order to support Windows paths (that contain r\"\\\\\").\r\n\r\nNow, you suggest ignoring this and work with POSIX strings (with \"/\").\r\n\r\nAs an example, when passing `cache_dir=r\"C:\\Users\\Username\\.mycache\"`:\r\n- Until now, it results in `self._cache_downloaded_dir = r\"C:\\Users\\Username\\.mycache\\downloads\"`\r\n- If we use `xjoin`, it will give `self._cache_downloaded_dir = \"C:/Users/Username/.mycache/downloads\"`\r\n\r\nYou say this is OK and we don't care if we work with POSIX strings on Windows machines.\r\n\r\nI'm incorporating your suggested changes then...", "Also note that using `xjoin`, if we pass `cache_dir=\"C:\\\\Users\\\\Username\\\\.mycache\"`, we get:\r\n- `self._cache_dir_root = \"C:\\\\Users\\\\Username\\\\.mycache\"`\r\n- `self._cache_downloaded_dir = \"C:/Users/Username/.mycache/downloads\"`", "It looks like it broke the CI on windows :/ maybe this was not a good idea, sorry" ]

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[ "_The documentation is not available anymore as the PR was closed or merged._" ]

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[ "Hey @fxmarty :) Yes we are working on showing the docs of all the metrics on the Hugging face website. If you want to follow the advancements you can check the [evaluate](https://github.com/huggingface/evaluate) repository cc @lvwerra @sashavor " ]

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[ "Thanks ! This has been fixed in https://github.com/huggingface/datasets/pull/4377, we can close this PR" ]

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[ "I think the underlying issue is in https://github.com/huggingface/datasets/blob/c0ed6fdc29675b3565b01b77fde5ab5d9d8b60ec/src/datasets/commands/dummy_data.py#L124 - where `CSV`s are considered to be in the same class of file as text, jsonl, and tsv.\r\n\r\nI think this is an error because CSVs can have newlines within the rows of a file. I'm happy to make a PR to change how this handling works, or make the change within this PR. \r\n\r\nWe should figure out:\r\n1. Does this dummy data need to be generated more than once? (It looks like no)\r\n2. Should this be fixed generally? (needs a HF person to weigh in here)\r\n3. What is the right way for such a fix to exist permanently here; the [Contributing document](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md) doesn't provide guidance on any tests. Writing a test is several times more effort than fixing the underlying issue. (again needs a HF person)", "Would someone from HF mind taking a look at this PR? (@lhoestq)", "Hi ! Sorry for the delay in responding :)\r\n\r\nI don't think there's a big need to fix this in the general case for now, feel free to just generate the dummy data for this specific dataset :)\r\n\r\nThe `datasets-cli dummy_data datasets/mslr2022` command should tell you what dummy files to generate. In each dummy file you just need to include enough data to generate 4 or 5 examples", "_The documentation is not available anymore as the PR was closed or merged._", "Awesome! Generated the dummy data and the tests now pass. @jayded thanks for your help! If you and @lucylw are happy with this I think it's ready to be merged. @lhoestq this is ready for another look :)", "Hi @lhoestq, is there anything blocking this from being merged that I can address?", "Hi @JohnGiorgi ! Thanks for the changes, it looks all good now :)\r\n\r\nI think this dataset can be under the AllenAI page here: https://huggingface.co/allenai What do you think ?\r\nFeel free to create a new dataset repository on huggingface.co and upload your files (dataset script, readme, etc.)\r\n\r\nOnce the dataset is under the AllenAI org, we can close this PR\r\n", "> Hi @JohnGiorgi ! Thanks for the changes, it looks all good now :)\r\n> \r\n> I think this dataset can be under the AllenAI page here: https://huggingface.co/allenai What do you think ? Feel free to create a new dataset repository on huggingface.co and upload your files (dataset script, readme, etc.)\r\n> \r\n> Once the dataset is under the AllenAI org, we can close this PR\r\n\r\nSweet! It is uploaded here: https://huggingface.co/datasets/allenai/mslr2022", "Nice ! Thanks :)\r\n\r\nI think we can close this PR then.\r\n\r\nI noticed that the dataset preview is not available on this dataset, this is because we require datasets to work in streaming mode to show a preview. However TAR archives don't work well in streaming mode (you can't know in advance what files are inside a TAR archive without reading it completely). This can be fixed by using a ZIP archive instead.\r\n\r\nLet me know if you have questions or if I can help." ]

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[ "Summary of CircleCI errors:\r\n\r\n- **XSum**: missing 6 required positional arguments: 'annotations_creators', 'language_creators', 'licenses', 'multilinguality', 'size_categories', and 'source_datasets'\r\n- **Yelp_polarity**: missing 8 required positional arguments: 'annotations_creators', 'language_creators', 'licenses', 'multilinguality', 'size_categories', 'source_datasets', 'task_categories', and 'task_ids'", "_The documentation is not available anymore as the PR was closed or merged._" ]

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[ "Summary of CircleCI errors:\r\n\r\n- **sem_eval_2010_task_8**: missing 8 required positional arguments: 'annotations_creators', 'language_creators', 'licenses', 'multilinguality', 'size_categories', 'source_datasets', 'task_categories', and 'task_ids'\r\n- **sms_spam**: `Data Instances` and`Data Splits` are empty.\r\n- **Quora** : Expected some content in section `Citation Information` but it is empty, missing 8 required positional arguments: 'annotations_creators', 'language_creators', 'licenses', 'multilinguality', 'size_categories', 'source_datasets', 'task_categories', and 'task_ids'\r\n- **sentiment140**: missing 8 required positional arguments: 'annotations_creators', 'language_creators', 'licenses', 'multilinguality', 'size_categories', 'source_datasets', 'task_categories', and 'task_ids'\r\n\r\nThere are also some timeout errors, I don't really understand the source though :confused: ", "_The documentation is not available anymore as the PR was closed or merged._" ]

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[ "Summary of CircleCI errors:\r\n- **Jjigsaw_toxicity_pred**: `Citation Information` but it is empty.\r\n- **LIAR** : `Data Instances`,`Data Fields`, `Data Splits`, `Citation Information` are empty.\r\n- **MSRA NER** : Dataset Summary`, `Data Instances`, `Data Fields`, `Data Splits`, `Citation Information` are empty.\r\n", "The CI errors about missing content in the dataset cards can be ignored in this PR btw", "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_4336). All of your documentation changes will be reflected on that endpoint." ]

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[ "Summary of CircleCI errors:\r\n- **BoolQ**: missing 8 required positional arguments: 'annotations_creators', 'language_creators', 'licenses', 'multilinguality', 'size_categories', 'source_datasets', 'task_categories', and 'task_ids'\r\n- **Conllpp**: expected some content in section `Citation Information` but it is empty.\r\n- **GLUE**: 'annotations_creators', 'language_creators', 'source_datasets' :['unknown'] are not registered tags\r\n- **ConLL2003**: field 'task_ids': ['part-of-speech-tagging'] are not registered tags for 'task_ids'\r\n- **Hate_speech18:** Expected some content in section `Data Instances` but it is empty, Expected some content in section `Data Splits` but it is empty", "And yes we can ignore all the CI errors related to missing content in the dataset cards, these issues can be fixed in other PRs", "_The documentation is not available anymore as the PR was closed or merged._" ]

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[ "@lhoestq , Circle CI is giving me an error, saying that ['extended'] is a key that shouldn't be in the dataset metadata, but it was there before my modification (so I don't want to remove it)" ]

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[ "_The documentation is not available anymore as the PR was closed or merged._" ]

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[ "Hi @vpj, thanks for reporting.\r\n\r\nI'm sorry, but I can't reproduce your bug: I load \"20220301.simple\"in 9 seconds:\r\n```shell\r\ntime python -c \"from datasets import load_dataset; load_dataset('wikipedia', '20220301.simple')\"\r\n\r\nDownloading and preparing dataset wikipedia/20220301.simple (download: 228.58 MiB, generated: 224.18 MiB, post-processed: Unknown size, total: 452.76 MiB) to .../.cache/huggingface/datasets/wikipedia/20220301.simple/2.0.0/aa542ed919df55cc5d3347f42dd4521d05ca68751f50dbc32bae2a7f1e167559...\r\nDownloading: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1.66k/1.66k [00:00<00:00, 1.02MB/s]\r\nDownloading: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 235M/235M [00:02<00:00, 82.8MB/s]\r\nDataset wikipedia downloaded and prepared to .../.cache/huggingface/datasets/wikipedia/20220301.simple/2.0.0/aa542ed919df55cc5d3347f42dd4521d05ca68751f50dbc32bae2a7f1e167559. Subsequent calls will reuse this data.\r\n100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 290.75it/s]\r\n\r\nreal\t0m9.693s\r\nuser\t0m6.002s\r\nsys\t0m3.260s\r\n```\r\n\r\nCould you please check your environment info, as requested when opening this issue?\r\n```\r\n## Environment info\r\n<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->\r\n- `datasets` version:\r\n- Platform:\r\n- Python version:\r\n- PyArrow version:\r\n```\r\nMaybe you are using an old version of `datasets`...", "Downloading and processing `wikipedia simple` dataset completed in under 11sec on M1 Mac. Could you please check `dataset` version as mentioned by @albertvillanova? Also check system specs, if system is under load processing could take some time I guess." ]

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[ "_The documentation is not available anymore as the PR was closed or merged._" ]

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[ "Not sure if it's related... I was going to raise an issue for https://huggingface.co/datasets/domenicrosati/TruthfulQA which also has the same issue... https://huggingface.co/datasets/domenicrosati/TruthfulQA/viewer/domenicrosati--TruthfulQA/train \r\n\r\n", "Yes, it's related. The backend behind the dataset viewer is currently under too much load, and these datasets are still in the jobs queue. We're actively working on this issue, and we expect to fix the issue permanently soon. Thanks for your patience 🙏  ", "Thanks @severo and no worries! - a suggestion for a UI usability thing maybe is to indicate that the dataset processing is in the job queue (rather than no data?)", "Thanks, these are working great now (including @domenicrosati 's, afaics!)" ]

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[ "Hi @leondz, I agree it would be nice. We'll see what we can do ;)" ]

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[ "\r\n\r\nthat is reason my bytes`s empty\r\nbut i have some confused why path prior is higher than bytes?\r\n\r\nif you can make bytes in _generate_examples , you don`t have to make bytes to path?\r\nbecause we have path and bytes already", "> but i have some confused why path prior is higher than bytes?\r\n\r\nIf the audio file is already available locally, we don't need to store the bytes again.\r\n\r\nIf you don't specify a \"path\" to a local file, then the bytes are stored. You can set \"path\" to None for example.\r\n\r\n> if you can make bytes in _generate_examples , you don`t have to make bytes to path?\r\n> because we have path and bytes already\r\n\r\nIt's useful to pass both \"path\" and \"bytes\" in `_generate_examples`:\r\n- when the dataset has been downloaded, then the \"path\" to the audio files are stored and we can ignore \"bytes\" in order to save disk space.\r\n- when the dataset is loaded in streaming mode, the audio files are not available on your disk and therefore we use the \"bytes\" ", "@lhoestq \r\nFirst of all, thx for reply\r\n\r\nbut, if i put in \"bytes\" and \"path\"\r\nex) {\"bytes\":\"blah blah~\", \"path\":\"blah blah~\"}\r\n\r\nthat source working that my bytes to empty first,\r\nand then, re-calculate my bytes!\r\n\r\n\r\nif you have some pcm file, pcm is can read bytes.\r\nso, i put in bytes and paths.\r\nbut bytes is been None why encode_example func make None\r\nand then, on decode_example func, we no have bytes. so, calculate bytes to path.\r\npcm is not support librosa or soundfile, error occured!\r\n\r\nthe most important thing is not announced anywhere this situation can be reproduced\r\n\r\nis that truly right process flow?", "I don't think we support PCM files, feel free to convert your data to WAV for now.\r\n\r\nIt would be awesome to support PCM files though, let me know if you'd like to contribute this feature, I'd be happy to help", "@lhoestq oh, how can i contribute?", "You can clone the repository (see the guide on [how to contribute](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-create-a-pull-request)) and see how we can make the `Image.encode_example` method work with PCM data.\r\n\r\nThere might be other ways to approach this problem, but here is what I think is a reasonable one:\r\n\r\nI think `Image.encode_example` should be able to take PCM bytes as input and the sampling rate, and return the WAV bytes (built by combining the PCM bytes and the sampling rate info), so that `Image.decode_example` can read it.\r\n\r\nTo check if the input bytes are PCM data, you can just check if the extension of the `path` is \".pcm\".\r\n", "maybe i can start to contribute on this sunday!\r\n@lhoestq ", "@lhoestq plz check my pr #4409 \r\n\r\nam i wrong somting?", "Thanks, I reviewed your PR :)" ]

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[ "> Nice thank you ! This will be super useful :)\r\n> \r\n> Could you also add some tests in test_arrow_dataset.py and add an example of usage in the `Example:` section of the `train_test_split` docstring ?\r\n\r\nI will try to do it, is there any documentation for adding test cases? I have never done it before.", "Thanks for the changes !\r\n\r\n> I will try to do it, is there any documentation for adding test cases? I have never done it before.\r\n\r\nYou can just add a function `test_train_test_split_startify` in `test_arrow_dataset.py`.\r\n\r\nIn this function you can define a dataset and make sure that `train_test_split` with the `stratify` argument works as expected.\r\n\r\nYou can do `pytest tests/test_arrow_dataset.py::test_train_test_split_startify` to run your test.\r\n\r\nFeel free to get some inspiration from other tests like `test_interleave_datasets` for example", "I have added tests for stratified train_test_split in `test_arrow_dataset.py` file inside `test_train_test_split_startify` function. I have also added example usage with `stratify` arg in `Example:` section of the `train_test_split` docstring.\r\nResults of tests:\r\n```\r\n(data) nandwalritik@hp:~/datasets$ pytest tests/test_arrow_dataset.py::test_train_test_split_startify -W ignore\r\n============================================================================ test session starts ============================================================================\r\nplatform linux -- Python 3.9.5, pytest-7.1.2, pluggy-1.0.0\r\nrootdir: /home/nandwalritik/datasets\r\nplugins: datadir-1.3.1, forked-1.4.0, xdist-2.5.0\r\ncollected 1 item \r\n\r\ntests/test_arrow_dataset.py . [100%]\r\n\r\n============================================================================= 1 passed in 0.12s =============================================================================\r\n\r\n```", "Thanks a lot !\r\n\r\n`utils/stratify.py` sounds good yes :)\r\n\r\nAlso feel free to merge `master` into your branch to fix the CI ;)", "Added all the changes as were suggested and rebased with `main`.", "_The documentation is not available anymore as the PR was closed or merged._", "Hi, I encounter an error when I try to specify the stratify_by_column. However, I have a columns which specific the label of the row as a string. But an error showed when I try to do it. \"ValueError: Stratifying by column is only supported for ClassLabel column, and column code is Value.\".", "Hi @Damon03 , you can change the type of your column to ClassLabel using\r\n```python\r\nds = ds.class_encode_column(column_name)\r\n```\r\nthen you'll be free to use `stratify` :)", "Thank you so much. It worked." ]

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[ "@lhoestq Thank you for the great feedback! Looks like all tests are passing now :)", "_The documentation is not available anymore as the PR was closed or merged._" ]

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[ "Hi ! Thanks for reporting :)\r\n\r\nThis dataset was simply converted from [tensorflow datasets](https://github.com/tensorflow/datasets/blob/master/tensorflow_datasets/summarization/multi_news.py)\r\n\r\nI think we can just remove the `.strip(\"- \")` and keep this character", "Cool! I made a PR." ]

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[ "_The documentation is not available anymore as the PR was closed or merged._" ]

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