Datasets:

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[ "@lhoestq - if you could take a final review here this would be great (if you have 5min :-) ) ", "Don't think the failures are related but not 100% sure", "Yes the CI fail is unrelated - you can ignore it" ]

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[ "same issue. downgrade it to a lower version.", "Thanks for reporting, I'll take a look tomorrow :)" ]

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[ "It seems like the doc can't be compiled right now because of the following:\r\n\r\n```\r\nTraceback (most recent call last):\r\n File \"/usr/local/bin/doc-builder\", line 33, in <module>\r\n sys.exit(load_entry_point('doc-builder', 'console_scripts', 'doc-builder')())\r\n File \"/__w/datasets/datasets/doc-builder/src/doc_builder/commands/doc_builder_cli.py\", line 39, in main\r\n args.func(args)\r\n File \"/__w/datasets/datasets/doc-builder/src/doc_builder/commands/build.py\", line 95, in build_command\r\n build_doc(\r\n File \"/__w/datasets/datasets/doc-builder/src/doc_builder/build_doc.py\", line 361, in build_doc\r\n anchors_mapping = build_mdx_files(package, doc_folder, output_dir, page_info)\r\n File \"/__w/datasets/datasets/doc-builder/src/doc_builder/build_doc.py\", line 200, in build_mdx_files\r\n raise type(e)(f\"There was an error when converting {file} to the MDX format.\\n\" + e.args[0]) from e\r\nTypeError: There was an error when converting datasets/docs/source/package_reference/table_classes.mdx to the MDX format.\r\nexpected string or bytes-like object\r\n```", "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3793). All of your documentation changes will be reflected on that endpoint.", "This is due to the injection of docstrings from PyArrow. I think I can fix that by moving all the docstrings and fix them manually.", "> It seems like the doc can't be compiled right now because of the following:\r\n\r\nit is expected since there is something I need to change on doc-builder side.\r\n\r\n> This is due to the injection of docstrings from PyArrow. I think I can fix that by moving all the docstrings and fix them manually.\r\n\r\n@lhoestq I will let you know if we need to change it manually.\r\n\r\n@LysandreJik thanks a lot for this PR! I only had one question [here](https://github.com/huggingface/datasets/pull/3793#discussion_r816100194)", "> @lhoestq I will let you know if we need to change it manually.\r\n\r\nIt would be simpler to change it manually anyway - I don't want our documentation to break if PyArrow has documentation issues", "For some reason it fails when `Installing node dependencies` when running `npm ci` from the `kit` directory, any idea why @mishig25 ?", "Checking it rn", "It's very likely linked to an OOM error: https://github.com/huggingface/transformers/pull/15710#issuecomment-1051737337" ]

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[ "Same issue with `dataset = load_dataset(\"dbpedia_14\")`\r\n```\r\nNonMatchingChecksumError: Checksums didn't match for dataset source files:\r\n['https://drive.google.com/uc?export=download&id=0Bz8a_Dbh9QhbQ2Vic1kxMmZZQ1k']", "I think this is a side-effect of #3787. The checksums won't match because the URLs have changed. @rafikg @Y0mingZhang, while this is fixed, maybe you can load the datasets as such:\r\n\r\n`data = datasets.load_dataset(\"wiki_lingua\", name=language, split=\"train[:2000]\", ignore_verifications=True)`\r\n`dataset = load_dataset(\"dbpedia_14\", ignore_verifications=True)`\r\n\r\nThis will, most probably, skip the verifications and integrity checks listed [here](https://huggingface.co/docs/datasets/loading_datasets.html#integrity-verifications)", "Hi! Installing the `datasets` package from master (`pip install git+https://github.com/huggingface/datasets.git`) and then redownloading the datasets with `download_mode` set to `force_redownload` (e.g. `dataset = load_dataset(\"dbpedia_14\", download_mode=\"force_redownload\")`) should fix the issue.", "Hi @rafikg and @Y0mingZhang, thanks for reporting.\r\n\r\nIndeed it seems that Google Drive changed their way to access their data files. We have recently handled that change:\r\n- #3787\r\n\r\nbut it will be accessible to users only in our next release of the `datasets` version.\r\n- Note that our latest release (version 1.18.3) was made before this fix: https://github.com/huggingface/datasets/releases/tag/1.18.3\r\n\r\nIn the meantime, as @mariosasko explained, you can incorporate this \"fix\" by installing our library from the GitHub master branch:\r\n```shell\r\npip install git+https://github.com/huggingface/datasets#egg=datasets\r\n```\r\nThen, you should force the redownload of the data (before the fix, you are just downloading/caching the virus scan warning page, instead of the data file):\r\n```shell\r\ndata = datasets.load_dataset(\"wiki_lingua\", name=language, split=\"train[:2000]\", download_mode=\"force_redownload\")", "@albertvillanova by running:\r\n```\r\npip install git+https://github.com/huggingface/datasets#egg=datasets\r\ndata = datasets.load_dataset(\"wiki_lingua\", name=language, split=\"train[:2000]\", download_mode=\"force_redownload\", ignore_verifications=True)\r\n```\r\n\r\nI had a pickle error **UnpicklingError: invalid load key, '<'** in this part of code both `locally and on google colab`:\r\n\r\n```\r\n\"\"\"Yields examples.\"\"\"\r\nwith open(filepath, \"rb\") as f:\r\n data = pickle.load(f)\r\nfor id_, row in enumerate(data.items()):\r\n yield id_, {\"url\": row[0], \"article\": self._process_article(row[1])}\r\n```\r\n", "This issue impacts many more datasets than the ones mention in this thread. Can we post # of downloads for each dataset by day (by successes and failures)? If so, it should be obvious which ones are failing.", "I can see this problem too in xcopa, unfortunately installing the latest master (1.18.4.dev0) doesn't work, @albertvillanova .\r\n\r\n```\r\nfrom datasets import load_dataset\r\ndataset = load_dataset(\"xcopa\", \"it\")\r\n```\r\n\r\nThrows\r\n\r\n```\r\nin verify_checksums(expected_checksums, recorded_checksums, verification_name)\r\n 38 if len(bad_urls) > 0:\r\n 39 error_msg = \"Checksums didn't match\" + for_verification_name + \":\\n\"\r\n---> 40 raise NonMatchingChecksumError(error_msg + str(bad_urls))\r\n 41 logger.info(\"All the checksums matched successfully\" + for_verification_name)\r\n 42 \r\n\r\nNonMatchingChecksumError: Checksums didn't match for dataset source files:\r\n['https://github.com/cambridgeltl/xcopa/archive/master.zip']\r\n```", "Hi @rafikg, I think that is another different issue. Let me check it... \r\n\r\nI guess maybe you are using a different Python version that the one the dataset owner used to create the pickle file...", "@kwchurch the datasets impacted for this specific issue are the ones which are hosted at Google Drive.", "@afcruzs-ms I think your issue is a different one, because that dataset is not hosted at Google Drive. Would you mind open another issue for that other problem, please? Thanks! :)", "@albertvillanova just to let you know that I tried it locally and on colab and it is the same error", "There are many many datasets on HugggingFace that are receiving this checksum error. Some of these datasets are very popular. There must be a way to track these errors, or to do regression testing. We don't want to catch each of these errors on each dataset, one at a time.", "@rafikg I am sorry, but I can't reproduce your issue. For me it works OK for all languages. See: https://colab.research.google.com/drive/1yIcLw1it118-TYE3ZlFmV7gJcsF6UCsH?usp=sharing", "@kwchurch the PR #3787 fixes this issue (generated by a change in Google Drive service) for ALL datasets with this issue. Once we make our next library release (in a couple of days), the fix will be accessible to all users that update our library from PyPI.", "By the way, @rafikg, I discovered the URL for Spanish was wrong. I've created a PR to fix it:\r\n- #3806 ", "I have the same problem with \"wider_face\" dataset. It seems that \"load_dataset\" function can not download the dataset from google drive.\r\n", "still getting this issue with datasets==2.2.2 for \r\ndataset_fever_original_dev = load_dataset('fever', \"v1.0\", split=\"labelled_dev\")\r\n(this one seems to be hosted by aws though)\r\n\r\nupdate: also tried to install from source to get the latest 2.2.3.dev0, but still get the error below (and also force-redownloaded)\r\n\r\nupdate2: Seems like this issues is linked to a change in the links in the specific fever datasets: https://fever.ai/\r\n\"28/04/2022\r\nDataset download URLs have changed\r\nDownload URLs for shared task data for FEVER, FEVER2.0 and FEVEROUS have been updated. New URLS begin with https://fever.ai/download/[task name]/[filename]. All resource pages have been updated with the new URLs. Previous dataset URLs may not work and should be updated if you require these in your scripts. \"\r\n\r\n=> I don't know how to update the links for HF datasets - would be great if someone could update them :) \r\n\r\n```\r\n\r\nDownloading and preparing dataset fever/v1.0 (download: 42.78 MiB, generated: 38.39 MiB, post-processed: Unknown size, total: 81.17 MiB) to /root/.cache/huggingface/datasets/fever/v1.0/1.0.0/956b0a9c4b05e126fd956be73e09da5710992b5c85c30f0e5e1c500bc6051d0a...\r\n\r\nDownloading data files: 100%\r\n6/6 [00:07<00:00, 1.21s/it]\r\nDownloading data:\r\n278/? [00:00<00:00, 2.34kB/s]\r\nDownloading data:\r\n278/? [00:00<00:00, 1.53kB/s]\r\nDownloading data:\r\n278/? [00:00<00:00, 7.43kB/s]\r\nDownloading data:\r\n278/? [00:00<00:00, 5.54kB/s]\r\nDownloading data:\r\n278/? [00:00<00:00, 6.19kB/s]\r\nDownloading data:\r\n278/? [00:00<00:00, 7.51kB/s]\r\nExtracting data files: 100%\r\n6/6 [00:00<00:00, 108.05it/s]\r\n\r\n---------------------------------------------------------------------------\r\n\r\nNonMatchingChecksumError Traceback (most recent call last)\r\n\r\n[<ipython-input-20-92ec5c728ecf>](https://localhost:8080/#) in <module>()\r\n 27 # get labels for fever-nli-dev from original fever - only works for dev\r\n 28 # \"(The labels for both dev and test are hidden but you can retrieve the label for dev using the cid and the original FEVER data.)\"\" https://github.com/easonnie/combine-FEVER-NSMN/blob/master/other_resources/nli_fever.md\r\n---> 29 dataset_fever_original_dev = load_dataset('fever', \"v1.0\", split=\"labelled_dev\")\r\n 30 df_fever_original_dev = pd.DataFrame(data={\"id\": dataset_fever_original_dev[\"id\"], \"label\": dataset_fever_original_dev[\"label\"], \"claim\": dataset_fever_original_dev[\"claim\"], \"evidence_id\": dataset_fever_original_dev[\"evidence_id\"]})\r\n 31 df_fever_dev = pd.merge(df_fever_dev, df_fever_original_dev, how=\"left\", left_on=\"cid\", right_on=\"id\")\r\n\r\n4 frames\r\n\r\n[/usr/local/lib/python3.7/dist-packages/datasets/utils/info_utils.py](https://localhost:8080/#) in verify_checksums(expected_checksums, recorded_checksums, verification_name)\r\n 38 if len(bad_urls) > 0:\r\n 39 error_msg = \"Checksums didn't match\" + for_verification_name + \":\\n\"\r\n---> 40 raise NonMatchingChecksumError(error_msg + str(bad_urls))\r\n 41 logger.info(\"All the checksums matched successfully\" + for_verification_name)\r\n 42 \r\n\r\nNonMatchingChecksumError: Checksums didn't match for dataset source files:\r\n['https://s3-eu-west-1.amazonaws.com/fever.public/train.jsonl', 'https://s3-eu-west-1.amazonaws.com/fever.public/shared_task_dev.jsonl', 'https://s3-eu-west-1.amazonaws.com/fever.public/shared_task_dev_public.jsonl', 'https://s3-eu-west-1.amazonaws.com/fever.public/shared_task_test.jsonl', 'https://s3-eu-west-1.amazonaws.com/fever.public/paper_dev.jsonl', 'https://s3-eu-west-1.amazonaws.com/fever.public/paper_test.jsonl']\r\n```\r\n", "I think this has to be fixed on the google drive side, but you also have to delete the bad stuff from your local cache. This is not a great design, but it is what it is.", "We have fixed the issues with the datasets:\r\n- wider_face: by hosting their data files on the HuggingFace Hub (CC: @HosseynGT)\r\n- fever: by updating to their new data URLs (CC: @MoritzLaurer)", "The yelp_review_full datasets has this problem as well and can't be fixed with the suggestion.", "This is a super-common failure mode. We really need to find a better workaround. My solution was to wait until the owner of the dataset in question did the right thing, and then I had to delete my cached versions of the datasets with the bad checksums. I don't understand why this happens. Would it be possible to maintain a copy of the most recent version that was known to work, and roll back to that automatically if the checksums fail? And if the checksums fail, couldn't the system automatically flush the cached versions with the bad checksums? It feels like we are blaming the provider of the dataset, when in fact, there are things that the system could do to ease the pain. Let's take these error messages seriously. There are too many of them involving too many different datasets.", "the [exams](https://huggingface.co/datasets/exams) dataset also has this issue and the provided fix above doesn't work", "Same for [DART dataset](https://huggingface.co/datasets/dart):\r\n```\r\nNonMatchingChecksumError: Checksums didn't match for dataset source files:\r\n['https://raw.githubusercontent.com/Yale-LILY/dart/master/data/v1.1.1/dart-v1.1.1-full-train.json', 'https://raw.githubusercontent.com/Yale-LILY/dart/master/data/v1.1.1/dart-v1.1.1-full-dev.json', 'https://raw.githubusercontent.com/Yale-LILY/dart/master/data/v1.1.1/dart-v1.1.1-full-test.json']\r\n```", "same for multi_news dataset", "- @thesofakillers the issue with `exams` was fixed on 16 Aug by this PR:\r\n - #4853\r\n- @Aktsvigun the issue with `dart` has been transferred to the Hub: https://huggingface.co/datasets/dart/discussions/1\r\n - and fixed by PR: https://huggingface.co/datasets/dart/discussions/2\r\n- @Carol-gutianle the issue with `multi_news` have been transferred to the Hub as well: https://huggingface.co/datasets/multi_news/discussions/1\r\n - not reproducible: maybe you should try to update `datasets`\r\n\r\nFor information to everybody, we are removing the checksum verifications (that were creating a bad user experience). This will be in place in the following weeks." ]

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[ "I think we're only missing the hosted runner to be configured for this repository and we should be good", "Regarding the self-hosted runner, I actually encourage using the approach defined here: https://github.com/huggingface/transformers/pull/15710, which doesn't leverage a self-hosted runner. This prevents queuing jobs, which is important when we expect several concurrent jobs.", "Opened a PR for that on your branch here: https://github.com/huggingface/datasets/pull/3793" ]

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[ "Do you think we have a dedicated branch for all the changes we want to do to wikipedia ? Then once everything looks good + we have preprocessed the main languages, we can merge it on the `master` branch", "Yes, @lhoestq, I agree with you.\r\n\r\nI have just created the dedicated branch [`update-wikipedia`](https://github.com/huggingface/datasets/tree/update-wikipedia). We can merge every PR (once validated) to that branch; once all changes are merged to that branch, we could create the preprocessed datasets and then merge the branch to master. ", "@lhoestq I guess you approve this PR?" ]

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[ "I see two options:\r\n1. drop the \"dev\" keyword since it can be considered too generic\r\n2. improve the pattern to something more reasonable, e.g. asking for a separator before and after \"dev\"\r\n```python\r\n[\"*[ ._-]dev[ ._-]*\", \"dev[ ._-]*\"]\r\n```\r\n\r\nI think 2. is nice. If we agree on this one we can even decide to require the separation for the other split keywords \"train\", \"test\" etc.", "Yes, I had something like that on mind: \"dev\" not being part of a word.\r\n```\r\n\"[^a-zA-Z]dev[^a-zA-Z]\"", "Is there a reason why we want that regex? It feels like something that'll still be an issue for some weird case. \"my_dataset_dev\" doesn't match your regex, \"my_dataset_validation\" doesn't either ... Why not always \"train\" unless specified?", "The regex is needed as part of our effort to make datasets configurable without code. In particular we define some generic dataset repository structures that users can follow\r\n\r\n> ```\r\n> \"[^a-zA-Z]*dev[^a-zA-Z]*\"\r\n> ```\r\n\r\nunfortunately our glob doesn't support \"^\": \r\n\r\nhttps://github.com/fsspec/filesystem_spec/blob/3e739db7e53f5b408319dcc9d11e92bc1f938902/fsspec/spec.py#L465-L479", "> \"my_dataset_dev\" doesn't match your regex, \"my_dataset_validation\" doesn't either ... Why not always \"train\" unless specified?\r\n\r\nAnd `my_dataset_dev.foo` would match the pattern, and we also have the same pattern but for the \"validation\" keyword so `my_dataset_validation.foo` would work too", "> The regex is needed as part of our effort to make datasets configurable without code\r\n\r\nThis feels like coding with the filename ^^'", "This is still much easier than having to write a full dataset script right ? :p" ]

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[ "Thanks for this @albertvillanova!", "Once this PR merged into master and until our next `datasets` library release, you can get this fix by installing our library from the GitHub master branch:\r\n```shell\r\npip install git+https://github.com/huggingface/datasets#egg=datasets\r\n```\r\nThen, if you had previously tried to load the data and got the checksum error, you should force the redownload of the data (before the fix, you just downloaded and cached the virus scan warning page, instead of the data file):\r\n```shell\r\nload_dataset(\"...\", download_mode=\"force_redownload\")\r\n```", "Thanks, that solved a bunch of problems we had downstream!\r\ncf. https://github.com/ElementAI/picard/issues/61" ]

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[ "Once the PR merged into master and until our next `datasets` library release, you can get this fix by installing our library from the GitHub master branch:\r\n```shell\r\npip install git+https://github.com/huggingface/datasets#egg=datasets\r\n```\r\nThen, if you had previously tried to load the data and got the checksum error, you should force the redownload of the data (before the fix, you just downloaded and cached the virus scan warning page, instead of the data file):\r\n```shell\r\nload_dataset(\"...\", download_mode=\"force_redownload\")\r\n```" ]

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[ "Thank you, @albertvillanova!", "Got it. Thanks for explaining this, @albertvillanova!\r\n\r\n> On the other hand, the tests are not passing because the dummy data should also be fixed. Once done, this PR will be able to be merged into master.\r\n\r\nWill do this 👍", "Hi ! I think we need to fix the issue for every dataset. This can be done simply by fixing how we handle Google Drive links, see my comment https://github.com/huggingface/datasets/pull/3775#issuecomment-1050970157", "Hi @lhoestq! I think @albertvillanova has already fixed this in #3787", "Cool ! I missed this one :) thanks", "No problem!", "Hi, @AngadSethi, I think that once:\r\n- #3787 \r\n\r\nwas merged, issue:\r\n- #3784 \r\n\r\nwas also fixed.\r\n\r\nTherefore, I think this PR is no longer necessary. I'm closing it. Let me know if you agree.", "Yes, absolutely @albertvillanova! I agree :)" ]

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[ "#self-assign", "@AngadSethi thanks for reporting and thanks for your PR!", "Glad to help @albertvillanova! Just fine-tuning the PR, will comment once I am able to get it up and running 😀", "Fixed by:\r\n- #3787" ]

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[ "@mariosasko it was indeed while reading that PR, that I remembered this change I wanted to do long ago... 😉" ]

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[ "Hi ! Thanks for reporting, indeed `disable_nullable` doesn't seem to be supported in this case. Maybe at one point we can have `disable_nullable` as a parameter of certain feature types" ]

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[ "Hello! I added the tags and created a PR. Just to note, regarding the paperswithcode_id tag, that currently has the value \"reddit\"; the dataset described as reddit in paperswithcode is https://paperswithcode.com/dataset/reddit and it isn't the Webis-tldr-17. I could not find Webis-tldr-17 in paperswithcode neither in the Summarization category nor using the keywords reddit, webis, & tldr. I didn't change this tag." ]

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[ "I also filled some missing sections in the dataset card" ]

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[ "Hi @Darshan2104, thanks for reporting.\r\n\r\nPlease note that at Hugging Face we do not host the data of this dataset, but just a loading script pointing to the host of the data owners.\r\n\r\nApparently the data owners changed their data host server. After googling it, I found their new website at: https://lil.nlp.cornell.edu/newsroom/index.html\r\n- Download page: https://lil.nlp.cornell.edu/newsroom/download/index.html\r\n\r\nI'm fixing the link in our Datasets library.", "@albertvillanova Thanks for the solution and link you made my day!" ]

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[ "I'm not sure if the documentation explains why the dataset identifiers might have a namespace or not (the user/org): 'glue' vs 'severo/glue'. Do you think we should explain it, and relate it to the GitHub/Hub distinction?", "> I'm not sure if the documentation explains why the dataset identifiers might have a namespace or not (the user/org): 'glue' vs 'severo/glue'. Do you think we should explain it, and relate it to the GitHub/Hub distinction?\r\n\r\nI added an explanation, let me know if it sounds good to you:\r\n\r\n```\r\nDatasets used to be hosted on our GitHub repository, but all datasets have now been migrated to the Hugging Face Hub.\r\nThe legacy GitHub datasets were added originally on our GitHub repository and therefore don't have a namespace: \"squad\", \"glue\", etc. unlike the other datasets that are named \"username/dataset_name\" or \"org/dataset_name\".\r\n```\r\n", "Thanks for the feedbacks ! Merging this now - if you have some comments I can take care of them in a subsequent PR\r\n\r\nI'll also take care of resolving the conflicts with https://github.com/huggingface/datasets/pull/3690" ]

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[ "Hi @jvanz, thank you for your proposal.\r\n\r\nIn fact, we are aware that it is very common the problem you mention. Because of that, we are currently working in implementing a new version of wikipedia on the Hub, with all data preprocessed (no need to use Apache Beam), from where you will be able to use `data_files` to load only a specific subset of the data files.\r\n\r\nSee:\r\n- #3401 " ]

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[ "I think it actually comes from an issue here:\r\n\r\nhttps://github.com/huggingface/datasets/blob/810b12f763f5cf02f2e43565b8890d278b7398cd/src/datasets/utils/file_utils.py#L575-L579\r\n\r\nand \r\n\r\nhttps://github.com/huggingface/datasets/blob/810b12f763f5cf02f2e43565b8890d278b7398cd/src/datasets/utils/streaming_download_manager.py#L386-L389\r\n\r\nThis code doesn't seem to work anymore. This can probably be fixed with\r\n\r\n```python\r\nif url.startswith(\"https://drive.google.com/\"): \r\n url += \"&confirm=t\"\r\n cookies = response.cookies \r\n```\r\n\r\nbecause Google Drive doesn't return the `download_warning` cookie anymore.", "Actually it seems that is has been fixed already in https://github.com/huggingface/datasets/pull/3787 :)\r\n\r\nI think it should have fixed the gigaword dataset loading", "@lhoestq The linked PR indeed fixes the issue. This PR is still worth merging IMO to update `gigaword`'s card." ]

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[ "Thanks for reporting, @anna-kay. We are fixing it.", "@albertvillanova Thank you for the fast response! However I am still getting the same error:\r\n\r\nDownloading: 2.23kB [00:00, ?B/s]\r\nTraceback (most recent call last):\r\n File \"C:\\Users\\Anna\\PycharmProjects\\summarization\\main.py\", line 17, in <module>\r\n dataset = load_dataset('reddit_tifu', 'long')\r\n File \"C:\\Users\\Anna\\Desktop\\summarization\\summarization_env\\lib\\site-packages\\datasets\\load.py\", line 1702, in load_dataset\r\n builder_instance.download_and_prepare(\r\n File \"C:\\Users\\Anna\\Desktop\\summarization\\summarization_env\\lib\\site-packages\\datasets\\builder.py\", line 594, in download_and_prepare\r\n self._download_and_prepare(\r\n File \"C:\\Users\\Anna\\Desktop\\summarization\\summarization_env\\lib\\site-packages\\datasets\\builder.py\", line 665, in _download_and_prepare\r\n verify_checksums(\r\n File \"C:\\Users\\Anna\\Desktop\\summarization\\summarization_env\\lib\\site-packages\\datasets\\utils\\info_utils.py\", line 40, in verify_checksums\r\n raise NonMatchingChecksumError(error_msg + str(bad_urls))\r\ndatasets.utils.info_utils.NonMatchingChecksumError: Checksums didn't match for dataset source files:\r\n['https://drive.google.com/uc?export=download&id=1ffWfITKFMJeqjT8loC8aiCLRNJpc_XnF']\r\n\r\nI have cleaned the cache/huggingface/datasets & cache/huggingface/modules files and also tried on another machine with a fresh installation of trasnformers & datasets. \r\nThe reddit_tifu.py that gets downloaded still has the previous url on line 51, _URL = \"https://drive.google.com/uc?export=download&id=1ffWfITKFMJeqjT8loC8aiCLRNJpc_XnF\" ", "Hi @anna-kay, I'm sorry I didn't clearly explain the details to you:\r\n- the error has been fixed in our `master` branch on GitHub: https://github.com/huggingface/datasets/commit/8ae21bf6a77175dc803ce2f1b93d18b8fbf45586\r\n- the fix will not be accessible to users in PyPI until our next release of the `datasets` library\r\n - our latest release (version 1.18.3) was made 23 days ago: https://github.com/huggingface/datasets/releases/tag/1.18.3\r\n- in the meantime, you can get the fix if you install datasets from our GitHub `master` branch:\r\n ```\r\n pip install git+https://github.com/huggingface/datasets#egg=datasets\r\n ```", "@albertvillanova Ok great, makes sence. Thank you very much for the explanation!" ]

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[ "Thanks for reporting, @kolk.\r\n\r\nWe are fixing it. " ]

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[ "Hi ! Indeed `map` is dropping the index right now, because one can create a dataset with more or fewer rows using `map` (and therefore the index might not be relevant anymore)\r\n\r\nI guess we could check the resulting dataset length, and if the user hasn't changed the dataset size we could keep the index, what do you think ?", "doing `.add_column(\"x\",x_data)` also removes the index. the new column might be irrelevant to the index so I don't think it should drop. \r\n\r\nMinimal example\r\n\r\n```python\r\nfrom datasets import load_dataset\r\nimport numpy as np\r\n\r\ndata=load_dataset(\"ceyda/cats_vs_dogs_sample\") #just a test dataset\r\ndata=data[\"train\"]\r\nembd_data=data.map(lambda x: {\"emb\":np.random.uniform(-1,0,50).astype(np.float32)})\r\nembd_data.add_faiss_index(column=\"emb\")\r\nprint(embd_data.list_indexes())\r\nembd_data=embd_data.add_column(\"x\",[0]*data.num_rows)\r\nprint(embd_data.list_indexes())\r\n```", "I agree `add_column` shouldn't drop the index indeed ! Is it something you'd like to contribute ? I think it's just a matter of copying the `self._indexes` dictionary to the output dataset" ]

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[ "Oh, this URL shouldn't be updated to the tagging app as it's actually used for creating the README - closing this." ]

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[ "Hi @jvanz, thanks for reporting.\r\n\r\nPlease note that Wikimedia website does not longer host Wikipedia dumps for so old dates.\r\n\r\nFor a list of accessible dump dates of `pt` Wikipedia, please see: https://dumps.wikimedia.org/ptwiki/\r\n\r\nYou can load for example `20220220` `pt` Wikipedia:\r\n```python\r\ndataset = load_dataset(\"wikipedia\", language=\"pt\", date=\"20220220\", beam_runner=\"DirectRunner\")\r\n```", "> ```python\r\n> dataset = load_dataset(\"wikipedia\", language=\"pt\", date=\"20220220\", beam_runner=\"DirectRunner\")\r\n> ```\r\n\r\nThank you! I did not know that I can do this. I was following the example in the error message when I do not define which language dataset I'm trying to download.\r\n\r\nI've tried something similar changing the date in the `load_dataset` call that I've shared in the bug description. Obviously, it did not work. I need to read the docs more carefully next time. My bad!\r\n\r\nThanks again and sorry for the noise.\r\n\r\n" ]

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[ "Hi @Dref360, thanks a lot for your proposal.\r\n\r\nIt totally makes sense to have more flexibility when class encoding, I agree.\r\n\r\nYou could even further customize the class encoding by passing an instance of `ClassLabel` itself (instead of replicating `ClassLabel` instantiation arguments as `Dataset.class_encode_column` arguments).\r\n\r\nAnd the latter made me think of `Dataset.cast_column`...\r\n\r\nMaybe better to have some others' opinions @lhoestq @mariosasko ", "Hi @Dref360! You can use [`Dataset.align_labels_with_mapping`](https://huggingface.co/docs/datasets/master/package_reference/main_classes.html#datasets.Dataset.align_labels_with_mapping) after `Dataset.class_encode_column` to assign a different mapping of labels to ids.\r\n\r\n@albertvillanova I'd like to avoid adding more complexity to the API where it's not (absolutely) needed, so I don't think introducing a new param in `Dataset.class_encode_column` is a good idea.\r\n\r\n", "I wasn't aware that it existed thank you for the link.\n\nClosing then! " ]

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[ "Hi @Muhtasham you should take a look at https://huggingface.co/blog/data-measurements-tool and accompanying demo app at https://huggingface.co/spaces/huggingface/data-measurements-tool\r\n\r\nWe would be interested in your feedback. cc @meg-huggingface @sashavor @yjernite " ]

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[ "Hi @kingabzpro.\r\n\r\nI think you need to create a loading script that creates the dataset from the CSV file and the image paths.\r\n\r\nAs example, you could have a look at the Food-101 dataset: https://huggingface.co/datasets/food101\r\n- Loading script: https://huggingface.co/datasets/food101/blob/main/food101.py\r\n\r\nOnce the loading script is created, the viewer will show a previsualization of your dataset. ", "@albertvillanova I don't think this is the issue. I have created another dataset with similar files and format and it works. https://huggingface.co/datasets/kingabzpro/savtadepth-flags-V2", "Yes, you are right, that was not the issue.\r\n\r\nJust take into account that sometimes the viewer can take some time until it shows the preview of the dataset.\r\nAfter some time, yours is finally properly shown: https://huggingface.co/datasets/kingabzpro/savtadepth-flags", "The problem was resolved by deleted the dataset and creating new one with similar name and then clicking on flag button.", "I think if you make manual changes to dataset the whole system breaks. " ]

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[ "Thanks! Used here: https://github.com/huggingface/datasets-preview-backend/blob/main/src/datasets_preview_backend/models/dataset.py#L26 :) " ]

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[ "We usually find issues with files hosted at Google Drive...\r\n\r\nIn this case we download the Google Drive Virus scan warning instead of the data file.", "Fixed: https://huggingface.co/datasets/head_qa/viewer/en/train. Thanks\r\n\r\n<img width=\"1551\" alt=\"Capture d’écran 2022-02-28 à 15 29 04\" src=\"https://user-images.githubusercontent.com/1676121/156000224-fd3f62c6-8b54-4df1-8911-bdcb0bac3f1a.png\">\r\n" ]

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[ "Awesome thank you ! The implementation of the parent `Metric` class was assuming that all metrics were supposed to have references/predictions pairs - I just changed that so you don't have to override `compute()`. I took the liberty of doing the changes directly inside this PR to make sure it works as expected with perplexity.\r\n\r\nOther than that it looks in pretty good shape :) I just did minor changes like remove a remaining `print` as well as fixing the `Features` defined in `_info()`. I also renamed `input_text` to `input_texts` since it makes it more obvious that it's a list of strings - let me know if it sounds good to you.\r\n\r\nLet me know if you'd like to make other changes or if it's all good for you !", "The test with the full test set seems to take too much time in the CI - maybe we can just select `split=\"test[:few_examples]\"` (around 10 maybe ?)" ]

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[ "Hi! If I'm not mistaken, this behavior is intentional, but I agree it could be more intuitive.\r\n\r\n@albertvillanova Do you remember why you decided not to decode columns in the `Audio` feature PR when `input_columns` is not `None`? IMO we should decode those columns, and we don't even have to use lazy structures here because the user explicitly requires them in the map transform. \r\n\r\ncc @lhoestq for visibility", "I think I excluded to decorate the function when `input_columns` were passed as a quick fix for some non-passing tests: \r\n- https://github.com/huggingface/datasets/pull/2324/commits/9d7c3e8fa53e23ec636859b4407eeec904b1b3f9\r\n\r\nThat PR was quite complex and I decided to focus on the main feature requests, leaving refinements for subsequent PRs.\r\n\r\nNote that when `input_columns` are passed, the signature of the function is effectively changed, while the decorated function expects an item (whether an example or a batch) as first arg (which is not the case when passing `input_columns`.\r\n\r\nI agree we should consider supporting the case when `input_columns` are passed." ]

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[ "Thanks for reporting. The dataset viewer depends on some backend treatments, and for now, they might take some hours to get processed. We're working on improving it.", "It has finally been processed. Thanks for the patience.", "Thanks for the info @severo !" ]

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[ "Fixed on master (see https://github.com/huggingface/datasets/pull/3719).", "Awesome, I did not find that one! Thanks." ]

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[ "Related to: https://github.com/huggingface/datasets/issues/3444", "Cool ! `filter` will be very useful. There can be a filter that you can apply on a streaming dataset:\r\n```python\r\nload_dataset(..., streaming=True).filter(lambda x: x[\"lang\"] == \"sw\")\r\n```\r\n\r\nOtherwise if you want to apply a filter on the source files that are going to be used for streaming, the logic has to be impIemented directly in the dataset script, or if there's no dataset script this can be done with pattern matching\r\n```python\r\nload_dataset(..., lang=\"sw\") # if the dataset script supports this parameter\r\nload_dataset(..., data_files=\"data/lang=sw/*\") # if there's no dataset script, but only data files\r\n```\r\n\r\n--------------\r\n\r\nHere are also some additional ideas of API to convert from iterable to map-style dataset:\r\n```python\r\non_disk_dataset = streaming_dataset.to_disk()\r\non_disk_dataset = streaming_dataset.to_disk(path=\"path/to/my/dataset/dir\")\r\n\r\nin_memory_dataset = streaming_dataset.take(100).to_memory() # to experiment without having to write files\r\n```\r\n--------------\r\n\r\nFinally regarding `push_to_hub`, we can replace `batch_size` by `shard_size` (same API as for on-disk datasets). The default is 500MB per file\r\n\r\nLet me know what you think !", "Regarding conversion, I'd also ask for some kind of equivalent to `save_to_disk` for an `IterableDataset`.\r\n\r\nSimilarly to the streaming to hub idea, my use case would be to define a sequence of dataset transforms via `.map()`, using an `IterableDataset` as the input (so processing could start without doing whole download up-front), but streaming the resultant processed dataset just to disk.", "That makes sense @athewsey , thanks for the suggestion :)\r\n\r\nMaybe instead of the `to_disk` we could simply have `save_to_disk` instead:\r\n```python\r\nstreaming_dataset.save_to_disk(\"path/to/my/dataset/dir\")\r\non_disk_dataset = load_from_disk(\"path/to/my/dataset/dir\")\r\n\r\nin_memory_dataset = Dataset.from_list(list(streaming_dataset.take(100))) # to experiment without having to write files\r\n```" ]

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[ "Thnaks for reporting @jaketae. We are fixing it. " ]

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[ "Hi ! Thanks this will be very useful :)\r\n\r\nIt looks like there are some changes in the github diff that are not related to your contribution, can you try fixing this by merging `master` into your PR, or create a new PR from an updated version of `master` ?", "I have already solved the conflict on this latest version. This is my first time sending PR, if there's anything I need to adjust just let me know~", "Thanks, most changes are gone :)\r\nIt still seems to include changes though - do you mind try creating a new branch from upstream/master and create a new PR please ?", "Yeah sure, I'll try to send a new PR today!", "Please forward to [#3850](https://github.com/huggingface/datasets/pull/3850)", "Thanks ! Closing this one in favor of https://github.com/huggingface/datasets/pull/3850/files" ]

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[ "Hmm the doctest failed again - maybe the full result needs to be on one single line", "cc @lhoestq for the final review", "Cool ! Feel free to merge if it's all good for you" ]

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[ "_The documentation is not available anymore as the PR was closed or merged._", "The CI fails are unrelated to this PR, merging !", "thanks 🙇🏽 " ]