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https://api.github.com/repos/huggingface/datasets/issues/3800 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3800/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3800/comments | https://api.github.com/repos/huggingface/datasets/issues/3800/events | https://github.com/huggingface/datasets/pull/3800 | 1,155,620,761 | PR_kwDODunzps4zvkjA | 3,800 | Added computer vision tasks | {
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} | [] | closed | false | null | [] | null | [] | "2022-03-01T17:37:46" | "2022-03-04T07:15:55" | "2022-03-04T07:15:55" | CONTRIBUTOR | null | Previous PR was in my fork so thought it'd be easier if I do it from a branch. Added computer vision task datasets according to HF tasks. | {
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https://api.github.com/repos/huggingface/datasets/issues/3799 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3799/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3799/comments | https://api.github.com/repos/huggingface/datasets/issues/3799/events | https://github.com/huggingface/datasets/pull/3799 | 1,155,356,102 | PR_kwDODunzps4zus9R | 3,799 | Xtreme-S Metrics | {
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} | [] | closed | false | null | [] | null | [] | "2022-03-01T13:42:28" | "2022-03-16T14:40:29" | "2022-03-16T14:40:26" | MEMBER | null | **Added datasets (TODO)**:
- [x] MLS
- [x] Covost2
- [x] Minds-14
- [x] Voxpopuli
- [x] FLoRes (need data)
**Metrics**: Done | {
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https://api.github.com/repos/huggingface/datasets/issues/3798 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3798/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3798/comments | https://api.github.com/repos/huggingface/datasets/issues/3798/events | https://github.com/huggingface/datasets/pull/3798 | 1,154,411,066 | PR_kwDODunzps4zrl5Y | 3,798 | Fix error message in CSV loader for newer Pandas versions | {
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} | [] | closed | false | null | [] | null | [] | "2022-02-28T18:24:10" | "2022-02-28T18:51:39" | "2022-02-28T18:51:38" | CONTRIBUTOR | null | Fix the error message in the CSV loader for `Pandas >= 1.4`. To fix this, I directly print the current file name in the for-loop. An alternative would be to use a check similar to this:
```python
csv_file_reader.handle.handle if datasets.config.PANDAS_VERSION >= version.parse("1.4") else csv_file_reader.f
```
CC: @SBrandeis | {
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https://api.github.com/repos/huggingface/datasets/issues/3797 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3797/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3797/comments | https://api.github.com/repos/huggingface/datasets/issues/3797/events | https://github.com/huggingface/datasets/pull/3797 | 1,154,383,063 | PR_kwDODunzps4zrgAD | 3,797 | Reddit dataset card contribution | {
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} | [] | closed | false | null | [] | null | [] | "2022-02-28T17:53:18" | "2023-03-09T22:08:58" | "2022-03-01T12:58:57" | CONTRIBUTOR | null | Description tags for webis-tldr-17 added. | {
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https://api.github.com/repos/huggingface/datasets/issues/3796 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3796/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3796/comments | https://api.github.com/repos/huggingface/datasets/issues/3796/events | https://github.com/huggingface/datasets/pull/3796 | 1,154,298,629 | PR_kwDODunzps4zrOQ4 | 3,796 | Skip checksum computation if `ignore_verifications` is `True` | {
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} | [] | closed | false | null | [] | null | [] | "2022-02-28T16:28:45" | "2022-02-28T17:03:46" | "2022-02-28T17:03:46" | CONTRIBUTOR | null | This will speed up the loading of the datasets where the number of data files is large (can easily happen with `imagefoler`, for instance) | {
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https://api.github.com/repos/huggingface/datasets/issues/3795 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3795/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3795/comments | https://api.github.com/repos/huggingface/datasets/issues/3795/events | https://github.com/huggingface/datasets/issues/3795 | 1,153,261,281 | I_kwDODunzps5EvV7h | 3,795 | can not flatten natural_questions dataset | {
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"same issue. downgrade it to a lower version.",
"Thanks for reporting, I'll take a look tomorrow :)"
] | "2022-02-27T13:57:40" | "2022-03-21T14:36:12" | "2022-03-21T14:36:12" | NONE | null | ## Describe the bug
after downloading the natural_questions dataset, can not flatten the dataset considering there are `long answer` and `short answer` in `annotations`.
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset('natural_questions',cache_dir = 'data/dataset_cache_dir')
dataset['train'].flatten()
```
## Expected results
a dataset with `long_answer` as features
## Actual results
Traceback (most recent call last):
File "temp.py", line 5, in <module>
dataset['train'].flatten()
File "/Users/hannibal046/anaconda3/lib/python3.8/site-packages/datasets/fingerprint.py", line 413, in wrapper
out = func(self, *args, **kwargs)
File "/Users/hannibal046/anaconda3/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 1296, in flatten
dataset._data = update_metadata_with_features(dataset._data, dataset.features)
File "/Users/hannibal046/anaconda3/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 536, in update_metadata_with_features
features = Features({col_name: features[col_name] for col_name in table.column_names})
File "/Users/hannibal046/anaconda3/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 536, in <dictcomp>
features = Features({col_name: features[col_name] for col_name in table.column_names})
KeyError: 'annotations.long_answer'
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.8.13
- Platform: MBP
- Python version: 3.8
- PyArrow version: 6.0.1
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https://api.github.com/repos/huggingface/datasets/issues/3794 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3794/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3794/comments | https://api.github.com/repos/huggingface/datasets/issues/3794/events | https://github.com/huggingface/datasets/pull/3794 | 1,153,185,343 | PR_kwDODunzps4zniT4 | 3,794 | Add Mahalanobis distance metric | {
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} | [] | closed | false | null | [] | null | [] | "2022-02-27T10:56:31" | "2022-03-02T14:46:15" | "2022-03-02T14:46:15" | CONTRIBUTOR | null | Mahalanobis distance is a very useful metric to measure the distance from one datapoint X to a distribution P.
In this PR I implement the metric in a simple way with the help of numpy only.
Similar to the [MAUVE implementation](https://github.com/huggingface/datasets/blob/master/metrics/mauve/mauve.py), we can make this metric accept texts as input and encode them with a featurize model, if that is desirable. | {
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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."
] | "2022-02-25T19:55:09" | "2022-10-12T13:33:26" | "2022-02-28T08:44:18" | NONE | null | ## Dataset viewer issue for 'wiki_lingua*'
**Link:** *link to the dataset viewer page*
`data = datasets.load_dataset("wiki_lingua", name=language, split="train[:2000]")
`
*short description of the issue*
```
[NonMatchingChecksumError: Checksums didn't match for dataset source files:
['https://drive.google.com/uc?export=download&id=11wMGqNVSwwk6zUnDaJEgm3qT71kAHeff']]()
```
Am I the one who added this dataset ? No
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} | [] | closed | false | null | [] | null | [] | "2022-02-25T18:26:35" | "2022-03-01T13:10:43" | "2022-03-01T13:10:42" | CONTRIBUTOR | null | As discussed in https://github.com/huggingface/datasets/pull/2830#issuecomment-1048989764, this PR adds a QOL improvement to easily reference the files inside a directory in `load_dataset` using the `data_dir` param (very handy for ImageFolder because it avoids globbing, but also useful for the other loaders). Additionally, it fixes the issue with `HfFileSystem.isdir`, which would previously always return `False`, and aligns the path-handling logic in `HfFileSystem` with `fsspec.GitHubFileSystem`. | {
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} | [] | closed | false | null | [] | null | [] | "2022-02-25T16:38:47" | "2022-03-01T15:55:42" | "2022-03-01T15:55:41" | MEMBER | null | I added the three scripts:
- build_dev_documentation.yml
- build_documentation.yml
- delete_dev_documentation.yml
I got them from `transformers` and did a few changes:
- I removed the `transformers`-specific dependencies
- I changed all the paths to be "datasets" instead of "transformers"
- I passed the `--library_name datasets` arg to the `doc-builder build` command (according to https://github.com/huggingface/doc-builder/pull/94/files#diff-bcc33cf7c223511e498776684a9a433810b527a0a38f483b1487e8a42b6575d3R26)
cc @LysandreJik @mishig25 | {
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https://api.github.com/repos/huggingface/datasets/issues/3789 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3789/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3789/comments | https://api.github.com/repos/huggingface/datasets/issues/3789/events | https://github.com/huggingface/datasets/pull/3789 | 1,150,587,404 | PR_kwDODunzps4zeQpx | 3,789 | Add URL and ID fields to Wikipedia dataset | {
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} | [] | closed | false | null | [] | null | [] | "2022-02-25T15:34:37" | "2022-03-04T08:24:24" | "2022-03-04T08:24:23" | MEMBER | null | This PR adds the URL field, so that we conform to proper attribution, required by their license: provide credit to the authors by including a hyperlink (where possible) or URL to the page or pages you are re-using.
About the conversion from title to URL, I found that apart from replacing blanks with underscores, some other special character must also be percent-encoded (e.g. `"` to `%22`): https://meta.wikimedia.org/wiki/Help:URL
Therefore, I have finally used `urllib.parse.quote` function. This additionally percent-encodes non-ASCII characters, but Wikimedia docs say these are equivalent:
> For the other characters either the code or the character can be used in internal and external links, they are equivalent. The system does a conversion when needed.
> [[%C3%80_propos_de_M%C3%A9ta]]
> is rendered as [À_propos_de_Méta](https://meta.wikimedia.org/wiki/%C3%80_propos_de_M%C3%A9ta), almost like [À propos de Méta](https://meta.wikimedia.org/wiki/%C3%80_propos_de_M%C3%A9ta), which leads to this page on Meta with in the address bar the URL
> [http://meta.wikipedia.org/wiki/%C3%80_propos_de_M%C3%A9ta](https://meta.wikipedia.org/wiki/%C3%80_propos_de_M%C3%A9ta)
> while [http://meta.wikipedia.org/wiki/À_propos_de_Méta](https://meta.wikipedia.org/wiki/%C3%80_propos_de_M%C3%A9ta) leads to the same.
Fix #3398.
CC: @geohci | {
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Fix #3786, fix #3784. | {
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https://api.github.com/repos/huggingface/datasets/issues/3786 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3786/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3786/comments | https://api.github.com/repos/huggingface/datasets/issues/3786/events | https://github.com/huggingface/datasets/issues/3786 | 1,150,233,067 | I_kwDODunzps5Ejynr | 3,786 | Bug downloading Virus scan warning page from Google Drive URLs | {
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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```"
] | "2022-02-25T09:32:23" | "2022-03-03T09:25:59" | "2022-02-25T11:56:35" | MEMBER | null | ## Describe the bug
Recently, some issues were reported with URLs from Google Drive, where we were downloading the Virus scan warning page instead of the data file itself.
See:
- #3758
- #3773
- #3784
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https://api.github.com/repos/huggingface/datasets/issues/3785 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3785/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3785/comments | https://api.github.com/repos/huggingface/datasets/issues/3785/events | https://github.com/huggingface/datasets/pull/3785 | 1,150,069,801 | PR_kwDODunzps4zciES | 3,785 | Fix: Bypass Virus Checks in Google Drive Links (CNN-DM dataset) | {
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} | [] | closed | false | null | [] | null | [] | "2022-02-25T05:48:57" | "2022-03-03T16:43:47" | "2022-03-03T14:03:37" | NONE | null | This commit fixes the issue described in #3784. By adding an extra parameter to the end of Google Drive links, we are able to bypass the virus check and download the datasets.
So, if the original link looked like https://drive.google.com/uc?export=download&id=0BwmD_VLjROrfTHk4NFg2SndKcjQ
The new link now looks like https://drive.google.com/uc?export=download&id=0BwmD_VLjROrfTHk4NFg2SndKcjQ&confirm=t
Fixes #3784 | {
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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"
] | "2022-02-25T05:24:47" | "2022-03-03T14:05:17" | "2022-03-03T14:05:17" | NONE | null | ## Describe the bug
I am unable to download the CNN-Dailymail dataset. Upon closer investigation, I realised why this was happening:
- The dataset sits in Google Drive, and both the CNN and DM datasets are large.
- Google is unable to scan the folder for viruses, **so the link which would originally download the dataset, now downloads the source code of this web page:**
![image](https://user-images.githubusercontent.com/58678541/155658435-c2f497d7-7601-4332-94b1-18a62dd96422.png)
- **This leads to the following error**:
```python
NotADirectoryError: [Errno 20] Not a directory: '/root/.cache/huggingface/datasets/downloads/1bc05d24fa6dda2468e83a73cf6dc207226e01e3c48a507ea716dc0421da583b/cnn/stories'
```
## Steps to reproduce the bug
```python
import datasets
dataset = datasets.load_dataset("cnn_dailymail", "3.0.0", split="train")
```
## Expected results
That the dataset is downloaded and processed just like other datasets.
## Actual results
Hit with this error:
```python
NotADirectoryError: [Errno 20] Not a directory: '/root/.cache/huggingface/datasets/downloads/1bc05d24fa6dda2468e83a73cf6dc207226e01e3c48a507ea716dc0421da583b/cnn/stories'
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.18.3
- Platform: Linux-5.4.144+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.12
- PyArrow version: 6.0.1
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https://api.github.com/repos/huggingface/datasets/issues/3783 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3783/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3783/comments | https://api.github.com/repos/huggingface/datasets/issues/3783/events | https://github.com/huggingface/datasets/pull/3783 | 1,149,256,744 | PR_kwDODunzps4zZ1jR | 3,783 | Support passing str to iter_files | {
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https://api.github.com/repos/huggingface/datasets/issues/3782 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3782/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3782/comments | https://api.github.com/repos/huggingface/datasets/issues/3782/events | https://github.com/huggingface/datasets/pull/3782 | 1,148,994,022 | PR_kwDODunzps4zY-Xb | 3,782 | Error of writing with different schema, due to nonpreservation of nullability | {
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```
dataset.map(
batched=True,
disable_nullable=True,
)
```
will get the following error at here https://github.com/huggingface/datasets/blob/c9967f55626931f8059dc416526c791444cdfdf7/src/datasets/arrow_writer.py#L516
`pyarrow.lib.ArrowInvalid: Tried to write record batch with different schema`
## 2. Debugging
### 2.1 tracing
During `_map_single`, the following are called
https://github.com/huggingface/datasets/blob/c9967f55626931f8059dc416526c791444cdfdf7/src/datasets/arrow_dataset.py#L2523
https://github.com/huggingface/datasets/blob/c9967f55626931f8059dc416526c791444cdfdf7/src/datasets/arrow_writer.py#L511
### 2.2. Observation
The problem is, even after `table_cast`, `pa_table.schema != self._schema`
`pa_table.schema` (before/after `table_cast`)
```
input_ids: list<item: int32>
child 0, item: int32
```
`self._schema`
```
input_ids: list<item: int32> not null
child 0, item: int32
```
### 2.3. Reason
https://github.com/huggingface/datasets/blob/c9967f55626931f8059dc416526c791444cdfdf7/src/datasets/table.py#L1121
Here we lose nullability stored in `schema` because it seems that `Features` is always nullable and don't store nullability.
https://github.com/huggingface/datasets/blob/c9967f55626931f8059dc416526c791444cdfdf7/src/datasets/table.py#L1103
So, casting to schema from such `Features` loses nullability, and eventually causes error of writing with different schema
## 3. Solution
1. Let `Features` stores nullability.
2. Directly cast table with original schema but not schema from converted `Features`. (this PR)
3. Don't `cast_table` when `write_table` | {
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https://api.github.com/repos/huggingface/datasets/issues/3781 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3781/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3781/comments | https://api.github.com/repos/huggingface/datasets/issues/3781/events | https://github.com/huggingface/datasets/pull/3781 | 1,148,599,680 | PR_kwDODunzps4zXr_O | 3,781 | Reddit dataset card additions | {
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} | [] | closed | false | null | [] | null | [] | "2022-02-23T21:29:16" | "2022-02-28T18:00:40" | "2022-02-28T11:21:14" | CONTRIBUTOR | null | The changes proposed are based on the "TL;DR: Mining Reddit to Learn Automatic Summarization" paper & https://zenodo.org/record/1043504#.YhaKHpbQC38
It is a Reddit dataset indeed, but the name given to the dataset by the authors is Webis-TLDR-17 (corpus), so perhaps it should be modified as well.
The task at which the dataset is aimed is abstractive summarization.
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https://api.github.com/repos/huggingface/datasets/issues/3778 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3778/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3778/comments | https://api.github.com/repos/huggingface/datasets/issues/3778/events | https://github.com/huggingface/datasets/issues/3778 | 1,147,898,946 | I_kwDODunzps5Ea4xC | 3,778 | Not be able to download dataset - "Newsroom" | {
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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!"
] | "2022-02-23T10:15:50" | "2022-02-23T17:05:04" | "2022-02-23T13:26:40" | NONE | null | Hello,
I tried to download the **newsroom** dataset but it didn't work out for me. it said me to **download it manually**!
For manually, Link is also didn't work! It is sawing some ad or something!
If anybody has solved this issue please help me out or if somebody has this dataset please share your google drive link, it would be a great help!
Thanks
Darshan Tank | {
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https://api.github.com/repos/huggingface/datasets/issues/3777 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3777/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3777/comments | https://api.github.com/repos/huggingface/datasets/issues/3777/events | https://github.com/huggingface/datasets/pull/3777 | 1,147,232,875 | PR_kwDODunzps4zTVrz | 3,777 | Start removing canonical datasets logic | {
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} | [] | closed | false | null | [] | null | [] | "2022-02-22T18:23:30" | "2022-02-24T15:04:37" | "2022-02-24T15:04:36" | MEMBER | null | I updated the source code and the documentation to start removing the "canonical datasets" logic.
Indeed this makes the documentation confusing and we don't want this distinction anymore in the future. Ideally users should share their datasets on the Hub directly.
### Changes
- the documentation about dataset loading mentions the datasets on the Hub (no difference between canonical and community, since they all have their own repository now)
- the documentation about adding a dataset doesn't explain the technical differences between canonical and community anymore, and only presents how to add a community dataset. There is still a small section at the bottom that mentions the datasets that are still on GitHub and redirects to the `ADD_NEW_DATASET.md` guide on GitHub about how to contribute a dataset to the `datasets` library
- the code source doesn't mention "canonical" anymore anywhere. There is still a `GitHubDatasetModuleFactory` class that is left, but I updated the docstring to say that it will be eventually removed in favor of the `HubDatasetModuleFactory` classes that already exist
Would love to have your feedbacks on this !
cc @julien-c @thomwolf @SBrandeis | {
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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!"
] | "2022-02-22T10:57:07" | "2022-02-25T19:27:49" | "2022-02-22T12:38:44" | CONTRIBUTOR | null | ## Describe the bug
A checksum occurs when downloading the reddit_tifu data (both long & short).
## Steps to reproduce the bug
reddit_tifu_dataset = load_dataset('reddit_tifu', 'long')
## Expected results
The expected result is for the dataset to be downloaded and cached locally.
## Actual results
File "/.../lib/python3.9/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=1ffWfITKFMJeqjT8loC8aiCLRNJpc_XnF']
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.18.3
- Platform: Linux-5.13.0-30-generic-x86_64-with-glibc2.31
- Python version: 3.9.7
- PyArrow version: 7.0.0
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"Thanks for reporting, @kolk.\r\n\r\nWe are fixing it. "
] | "2022-02-22T00:43:33" | "2022-02-22T08:12:39" | "2022-02-22T08:12:39" | NONE | null | ### Describe the bug
Failure to generate dataset msr_sqa because of duplicate keys.
### Steps to reproduce the bug
```
from datasets import load_dataset
load_dataset("msr_sqa")
```
### Expected results
The examples keys should be unique.
**Actual results**
```
>>> load_dataset("msr_sqa")
Downloading:
6.72k/? [00:00<00:00, 148kB/s]
Downloading:
2.93k/? [00:00<00:00, 53.8kB/s]
Using custom data configuration default
Downloading and preparing dataset msr_sqa/default (download: 4.57 MiB, generated: 26.25 MiB, post-processed: Unknown size, total: 30.83 MiB) to /root/.cache/huggingface/datasets/msr_sqa/default/0.0.0/70b2a497bd3cc8fc960a3557d2bad1eac5edde824505e15c9c8ebe4c260fd4d1...
Downloading: 100%
4.80M/4.80M [00:00<00:00, 7.49MB/s]
---------------------------------------------------------------------------
DuplicatedKeysError Traceback (most recent call last)
[/usr/local/lib/python3.7/dist-packages/datasets/builder.py](https://localhost:8080/#) in _prepare_split(self, split_generator)
1080 example = self.info.features.encode_example(record)
-> 1081 writer.write(example, key)
1082 finally:
8 frames
DuplicatedKeysError: FAILURE TO GENERATE DATASET !
Found duplicate Key: nt-639
Keys should be unique and deterministic in nature
During handling of the above exception, another exception occurred:
DuplicatedKeysError Traceback (most recent call last)
[/usr/local/lib/python3.7/dist-packages/datasets/arrow_writer.py](https://localhost:8080/#) in check_duplicate_keys(self)
449 for hash, key in self.hkey_record:
450 if hash in tmp_record:
--> 451 raise DuplicatedKeysError(key)
452 else:
453 tmp_record.add(hash)
DuplicatedKeysError: FAILURE TO GENERATE DATASET !
Found duplicate Key: nt-639
Keys should be unique and deterministic in nature
```
### Environment info
datasets version: 1.18.3
Platform: Google colab notebook
Python version: 3.7
PyArrow version: 6.0.1
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} | [] | closed | false | null | [] | null | [] | "2022-02-21T16:57:47" | "2022-02-22T08:35:03" | "2022-02-22T08:35:02" | CONTRIBUTOR | null | A fix + expose a new method, following https://github.com/huggingface/datasets/pull/3670 | {
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https://api.github.com/repos/huggingface/datasets/issues/3765 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3765/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3765/comments | https://api.github.com/repos/huggingface/datasets/issues/3765/events | https://github.com/huggingface/datasets/pull/3765 | 1,145,126,881 | PR_kwDODunzps4zMdIL | 3,765 | Update URL for tagging app | {
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} | [] | closed | false | null | [] | null | [] | "2022-02-20T20:34:31" | "2022-02-20T20:36:10" | "2022-02-20T20:36:06" | MEMBER | null | This PR updates the URL for the tagging app to be the one on Spaces. | {
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{
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"url": "https://api.github.com/repos/huggingface/datasets/labels/dataset-viewer",
"name": "dataset-viewer",
"color": "E5583E",
"default": false,
"description": "Related to the dataset viewer on huggingface.co"
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] | closed | false | null | [] | null | [] | "2022-02-20T19:05:43" | "2022-02-21T08:55:58" | "2022-02-21T08:55:58" | NONE | null | ## Dataset viewer issue for '*name of the dataset*'
**Link:** *link to the dataset viewer page*
*short description of the issue*
Am I the one who added this dataset ? Yes-No
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https://api.github.com/repos/huggingface/datasets/issues/3763 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3763/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3763/comments | https://api.github.com/repos/huggingface/datasets/issues/3763/events | https://github.com/huggingface/datasets/issues/3763 | 1,145,099,878 | I_kwDODunzps5EQNZm | 3,763 | It's not possible download `20200501.pt` dataset | {
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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"
] | "2022-02-20T18:34:58" | "2022-02-21T12:06:12" | "2022-02-21T09:25:06" | NONE | null | ## Describe the bug
The dataset `20200501.pt` is broken.
The available datasets: https://dumps.wikimedia.org/ptwiki/
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset("wikipedia", "20200501.pt", beam_runner='DirectRunner')
```
## Expected results
I expect to download the dataset locally.
## Actual results
```
>>> from datasets import load_dataset
>>> dataset = load_dataset("wikipedia", "20200501.pt", beam_runner='DirectRunner')
Downloading and preparing dataset wikipedia/20200501.pt to /home/jvanz/.cache/huggingface/datasets/wikipedia/20200501.pt/1.0.0/009f923d9b6dd00c00c8cdc7f408f2b47f45dd4f5fb7982a21f9448f4afbe475...
/home/jvanz/anaconda3/envs/tf-gpu/lib/python3.9/site-packages/apache_beam/__init__.py:79: UserWarning: This version of Apache Beam has not been sufficiently tested on Python 3.9. You may encounter bugs or missing features.
warnings.warn(
0%| | 0/1 [00:00<?, ?it/s]
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/jvanz/anaconda3/envs/tf-gpu/lib/python3.9/site-packages/datasets/load.py", line 1702, in load_dataset
builder_instance.download_and_prepare(
File "/home/jvanz/anaconda3/envs/tf-gpu/lib/python3.9/site-packages/datasets/builder.py", line 594, in download_and_prepare
self._download_and_prepare(
File "/home/jvanz/anaconda3/envs/tf-gpu/lib/python3.9/site-packages/datasets/builder.py", line 1245, in _download_and_prepare
super()._download_and_prepare(
File "/home/jvanz/anaconda3/envs/tf-gpu/lib/python3.9/site-packages/datasets/builder.py", line 661, in _download_and_prepare
split_generators = self._split_generators(dl_manager, **split_generators_kwargs)
File "/home/jvanz/.cache/huggingface/modules/datasets_modules/datasets/wikipedia/009f923d9b6dd00c00c8cdc7f408f2b47f45dd4f5fb7982a21f9448f4afbe475/wikipedia.py", line 420, in _split_generators
downloaded_files = dl_manager.download_and_extract({"info": info_url})
File "/home/jvanz/anaconda3/envs/tf-gpu/lib/python3.9/site-packages/datasets/utils/download_manager.py", line 307, in download_and_extract
return self.extract(self.download(url_or_urls))
File "/home/jvanz/anaconda3/envs/tf-gpu/lib/python3.9/site-packages/datasets/utils/download_manager.py", line 195, in download
downloaded_path_or_paths = map_nested(
File "/home/jvanz/anaconda3/envs/tf-gpu/lib/python3.9/site-packages/datasets/utils/py_utils.py", line 260, in map_nested
mapped = [
File "/home/jvanz/anaconda3/envs/tf-gpu/lib/python3.9/site-packages/datasets/utils/py_utils.py", line 261, in <listcomp>
_single_map_nested((function, obj, types, None, True))
File "/home/jvanz/anaconda3/envs/tf-gpu/lib/python3.9/site-packages/datasets/utils/py_utils.py", line 196, in _single_map_nested
return function(data_struct)
File "/home/jvanz/anaconda3/envs/tf-gpu/lib/python3.9/site-packages/datasets/utils/download_manager.py", line 216, in _download
return cached_path(url_or_filename, download_config=download_config)
File "/home/jvanz/anaconda3/envs/tf-gpu/lib/python3.9/site-packages/datasets/utils/file_utils.py", line 298, in cached_path
output_path = get_from_cache(
File "/home/jvanz/anaconda3/envs/tf-gpu/lib/python3.9/site-packages/datasets/utils/file_utils.py", line 612, in get_from_cache
raise FileNotFoundError(f"Couldn't find file at {url}")
FileNotFoundError: Couldn't find file at https://dumps.wikimedia.org/ptwiki/20200501/dumpstatus.json
```
## Environment info
```
- `datasets` version: 1.18.3
- Platform: Linux-5.3.18-150300.59.49-default-x86_64-with-glibc2.31
- Python version: 3.9.7
- PyArrow version: 6.0.1
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/3762 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3762/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3762/comments | https://api.github.com/repos/huggingface/datasets/issues/3762/events | https://github.com/huggingface/datasets/issues/3762 | 1,144,849,557 | I_kwDODunzps5EPQSV | 3,762 | `Dataset.class_encode` should support custom class names | {
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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! "
] | "2022-02-19T21:21:45" | "2022-02-21T12:16:35" | "2022-02-21T12:16:35" | CONTRIBUTOR | null | I can make a PR, just wanted approval before starting.
**Is your feature request related to a problem? Please describe.**
It is often the case that classes are not ordered in alphabetical order. Current `class_encode_column` sort the classes before indexing.
https://github.com/huggingface/datasets/blob/master/src/datasets/arrow_dataset.py#L1235
**Describe the solution you'd like**
I would like to add a **optional** parameter `class_names` to `class_encode_column` that would be used for the mapping instead of sorting the unique values.
**Describe alternatives you've considered**
One can use map instead. I find it harder to read.
```python
CLASS_NAMES = ['apple', 'orange', 'potato']
ds = ds.map(lambda item: CLASS_NAMES.index(item[label_column]))
# Proposition
ds = ds.class_encode_column(label_column, CLASS_NAMES)
```
**Additional context**
I can make the PR if this feature is accepted.
| {
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https://api.github.com/repos/huggingface/datasets/issues/3761 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3761/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3761/comments | https://api.github.com/repos/huggingface/datasets/issues/3761/events | https://github.com/huggingface/datasets/issues/3761 | 1,144,830,702 | I_kwDODunzps5EPLru | 3,761 | Know your data for HF hub | {
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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 "
] | "2022-02-19T19:48:47" | "2022-02-21T14:15:23" | "2022-02-21T14:15:23" | NONE | null | **Is your feature request related to a problem? Please describe.**
Would be great to see be able to understand datasets with the goal of improving data quality, and helping mitigate fairness and bias issues.
**Describe the solution you'd like**
Something like https://knowyourdata.withgoogle.com/ for HF hub | {
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https://api.github.com/repos/huggingface/datasets/issues/3760 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3760/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3760/comments | https://api.github.com/repos/huggingface/datasets/issues/3760/events | https://github.com/huggingface/datasets/issues/3760 | 1,144,804,558 | I_kwDODunzps5EPFTO | 3,760 | Unable to view the Gradio flagged call back dataset | {
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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. "
] | "2022-02-19T17:45:08" | "2022-03-22T07:12:11" | "2022-03-22T07:12:11" | NONE | null | ## Dataset viewer issue for '*savtadepth-flags*'
**Link:** *[savtadepth-flags](https://huggingface.co/datasets/kingabzpro/savtadepth-flags)*
*with the Gradio 2.8.1 the dataset viers stopped working. I tried to add values manually but its not working. The dataset is also not showing the link with the app https://huggingface.co/spaces/kingabzpro/savtadepth.*
Am I the one who added this dataset ? Yes
| {
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https://api.github.com/repos/huggingface/datasets/issues/3759 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3759/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3759/comments | https://api.github.com/repos/huggingface/datasets/issues/3759/events | https://github.com/huggingface/datasets/pull/3759 | 1,143,400,770 | PR_kwDODunzps4zGhQu | 3,759 | Rename GenerateMode to DownloadMode | {
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- Renames `GenerateMode` to `DownloadMode`
- Implements `DeprecatedEnum`
- Deprecates `GenerateMode`
Close #769. | {
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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"
] | "2022-02-18T16:32:43" | "2022-02-28T14:29:18" | "2022-02-21T14:39:19" | CONTRIBUTOR | null | ## Describe the bug
A file for the `head_qa` dataset is missing (https://drive.google.com/u/0/uc?export=download&id=1a_95N5zQQoUCq8IBNVZgziHbeM-QxG2t/HEAD_EN/train_HEAD_EN.json)
## Steps to reproduce the bug
```python
>>> from datasets import load_dataset
>>> load_dataset("head_qa", name="en")
```
## Expected results
The dataset should be loaded
## Actual results
```
Downloading and preparing dataset head_qa/en (download: 75.69 MiB, generated: 2.69 MiB, post-processed: Unknown size, total: 78.38 MiB) to /home/slesage/.cache/huggingface/datasets/head_qa/en/1.1.0/583ab408e8baf54aab378c93715fadc4d8aa51b393e27c3484a877e2ac0278e9...
Downloading data: 2.21kB [00:00, 2.05MB/s]
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/datasets/load.py", line 1729, in load_dataset
builder_instance.download_and_prepare(
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/datasets/builder.py", line 594, in download_and_prepare
self._download_and_prepare(
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/datasets/builder.py", line 665, in _download_and_prepare
verify_checksums(
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/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/u/0/uc?export=download&id=1a_95N5zQQoUCq8IBNVZgziHbeM-QxG2t']
```
## Environment info
- `datasets` version: 1.18.4.dev0
- Platform: Linux-5.11.0-1028-aws-x86_64-with-glibc2.31
- Python version: 3.9.6
- PyArrow version: 6.0.1
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https://api.github.com/repos/huggingface/datasets/issues/3757 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3757/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3757/comments | https://api.github.com/repos/huggingface/datasets/issues/3757/events | https://github.com/huggingface/datasets/pull/3757 | 1,143,300,880 | PR_kwDODunzps4zGK7p | 3,757 | Add perplexity to metrics | {
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This code differs from the code in [this](https://huggingface.co/docs/transformers/perplexity) HF blog post because the blogpost code fails in at least the following circumstances:
- returns nans whenever the stride = 1
- hits a runtime error when the stride is significantly larger than the max model length (e.g. if max_model_length = 512 and stride = 1024)
Note that:
- As it is, it only works for causal models. Pseudoperplexity can be added later as another metric to work with masked language models.
- It takes in a list of strings so that it can be dataset independent. This does mean that it doesn't currently batch inputs, and is therefore relatively slow.
- It overwrites the metrics compute() function for a specific perplexity compute() function. This is because the current general metrics compute() function requires model-generated predictions, which doesn't make sense in the context of perplexity | {
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https://api.github.com/repos/huggingface/datasets/issues/3756 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3756/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3756/comments | https://api.github.com/repos/huggingface/datasets/issues/3756/events | https://github.com/huggingface/datasets/issues/3756 | 1,143,273,825 | I_kwDODunzps5EJPlh | 3,756 | Images get decoded when using `map()` with `input_columns` argument on a dataset | {
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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."
] | "2022-02-18T15:35:38" | "2022-12-13T16:59:06" | "2022-12-13T16:59:06" | NONE | null | ## Describe the bug
The `datasets.features.Image` feature class decodes image data by default. Expectedly, when indexing a dataset or using the `map()` method, images are returned as PIL Image instances.
However, when calling `map()` and setting a specific data column with the `input_columns` argument, the image data is passed as raw byte representation to the mapping function.
## Steps to reproduce the bug
```python
from datasets import load_dataset
from torchvision import transforms
from PIL.Image import Image
dataset = load_dataset('mnist', split='train')
def transform_all_columns(example):
# example['image'] is encoded as PIL Image
assert isinstance(example['image'], Image)
return example
def transform_image_column(image):
# image is decoded here and represented as raw bytes
assert isinstance(image, Image)
return image
# single-sample dataset for debugging purposes
dev = dataset.select([0])
dev.map(transform_all_columns)
dev.map(transform_image_column, input_columns='image')
```
## Expected results
Image data should be passed in decoded form, i.e. as PIL Image objects to the mapping function unless the `decode` attribute on the image feature is set to `False`.
## Actual results
The mapping function receives images as raw byte data.
## Environment info
- `datasets` version: 1.18.3
- Platform: Linux-5.11.0-49-generic-x86_64-with-glibc2.32
- Python version: 3.8.0b4
- PyArrow version: 7.0.0
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https://api.github.com/repos/huggingface/datasets/issues/3755 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3755/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3755/comments | https://api.github.com/repos/huggingface/datasets/issues/3755/events | https://github.com/huggingface/datasets/issues/3755 | 1,143,032,961 | I_kwDODunzps5EIUyB | 3,755 | Cannot preview dataset | {
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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 !"
] | "2022-02-18T13:06:45" | "2022-02-19T14:30:28" | "2022-02-18T15:41:33" | NONE | null | ## Dataset viewer issue for '*rubrix/news*'
**Link:https://huggingface.co/datasets/rubrix/news** *link to the dataset viewer page*
Cannot see the dataset preview:
```
Status code: 400
Exception: Status400Error
Message: Not found. Cache is waiting to be refreshed.
```
Am I the one who added this dataset ? No
| {
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https://api.github.com/repos/huggingface/datasets/issues/3754 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3754/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3754/comments | https://api.github.com/repos/huggingface/datasets/issues/3754/events | https://github.com/huggingface/datasets/issues/3754 | 1,142,886,536 | I_kwDODunzps5EHxCI | 3,754 | Overflowing indices in `select` | {
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"Fixed on master (see https://github.com/huggingface/datasets/pull/3719).",
"Awesome, I did not find that one! Thanks."
] | "2022-02-18T11:30:52" | "2022-02-18T11:38:23" | "2022-02-18T11:38:23" | MEMBER | null | ## Describe the bug
The `Dataset.select` function seems to accept indices that are larger than the dataset size and seems to effectively use `index %len(ds)`.
## Steps to reproduce the bug
```python
from datasets import Dataset
ds = Dataset.from_dict({"test": [1,2,3]})
ds = ds.select(range(5))
print(ds)
print()
print(ds["test"])
```
Result:
```python
Dataset({
features: ['test'],
num_rows: 5
})
[1, 2, 3, 1, 2]
```
This behaviour is not documented and can lead to unexpected behaviour when for example taking a sample larger than the dataset and thus creating a lot of duplicates.
## Expected results
It think this should throw an error or at least a very big warning:
```python
IndexError: Invalid key: 5 is out of bounds for size 3
```
## Environment info
- `datasets` version: 1.18.3
- Platform: macOS-12.0.1-x86_64-i386-64bit
- Python version: 3.9.10
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https://api.github.com/repos/huggingface/datasets/issues/3752 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3752/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3752/comments | https://api.github.com/repos/huggingface/datasets/issues/3752/events | https://github.com/huggingface/datasets/pull/3752 | 1,142,627,889 | PR_kwDODunzps4zD1D9 | 3,752 | Update metadata JSON for cats_vs_dogs dataset | {
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Fix #3750. | {
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https://api.github.com/repos/huggingface/datasets/issues/3751 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3751/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3751/comments | https://api.github.com/repos/huggingface/datasets/issues/3751/events | https://github.com/huggingface/datasets/pull/3751 | 1,142,609,327 | PR_kwDODunzps4zDw9_ | 3,751 | Fix typo in train split name | {
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} | [] | closed | false | null | [] | null | [] | "2022-02-18T08:18:04" | "2022-02-18T14:28:52" | "2022-02-18T14:28:52" | MEMBER | null | In the README guide (and consequently in many datasets) there was a typo in the train split name:
```
| Tain | Valid | Test |
```
This PR:
- fixes the typo in the train split name
- fixes the column alignment of the split tables
in the README guide and in all datasets. | {
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"Thnaks for reporting @jaketae. We are fixing it. "
] | "2022-02-18T05:46:39" | "2022-02-18T14:56:11" | "2022-02-18T14:56:11" | CONTRIBUTOR | null | ## Describe the bug
Cannot download cats_vs_dogs dataset due to `NonMatchingSplitsSizesError`.
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset("cats_vs_dogs")
```
## Expected results
Loading is successful.
## Actual results
```
NonMatchingSplitsSizesError: [{'expected': SplitInfo(name='train', num_bytes=7503250, num_examples=23422, dataset_name='cats_vs_dogs'), 'recorded': SplitInfo(name='train', num_bytes=7262410, num_examples=23410, dataset_name='cats_vs_dogs')}]
```
## Environment info
Reproduced on a fresh [Colab notebook](https://colab.research.google.com/drive/13GTvrSJbBGvL2ybDdXCBZwATd6FOkMub?usp=sharing).
## Additional Context
Originally reported in https://github.com/huggingface/transformers/issues/15698.
cc @mariosasko | {
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1. It is able to show the progress bar by adding the length of the iterator.
2. Pass in tqdm_kwargs so that can enable more feasibility for the control of tqdm library. | {
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```python
gen_kwargs = {
"files": [os.path.join(data_dir, filename) for filename in all_files],
"metadata_files": [all_metadata[filename] for filename in all_files],
}
```
IMO this is important to avoid big but silent issues.
Fix https://github.com/huggingface/datasets/issues/3744 | {
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It is entirely based on mmseg's [implementation](https://github.com/open-mmlab/mmsegmentation/blob/master/mmseg/core/evaluation/metrics.py).
I've removed any PyTorch dependency, and rely on Numpy only. | {
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] | closed | false | null | [] | null | [] | "2022-02-17T15:07:21" | "2022-02-23T15:00:58" | "2022-02-23T15:00:58" | MEMBER | null | Sometimes a dataset script has a `_split_generators` that returns several files as well as the corresponding metadata of each file. It often happens that they end up in two separate lists in the `gen_kwargs`:
```python
gen_kwargs = {
"files": [os.path.join(data_dir, filename) for filename in all_files],
"metadata_files": [all_metadata[filename] for filename in all_files],
}
```
It happened for Multilingual Spoken Words for example in #3666
However currently **the two lists are shuffled independently** when shuffling the shards in streaming mode. This leads to `_generate_examples` not having the right metadata for each file.
To prevent this issue I suggest that we always shuffle lists of the same length the exact same way to avoid such a big but silent issue.
cc @polinaeterna | {
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https://api.github.com/repos/huggingface/datasets/issues/3742 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3742/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3742/comments | https://api.github.com/repos/huggingface/datasets/issues/3742/events | https://github.com/huggingface/datasets/pull/3742 | 1,141,174,549 | PR_kwDODunzps4y-1v5 | 3,742 | Fix ValueError message formatting in int2str | {
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} | [] | closed | false | null | [] | null | [] | "2022-02-17T10:50:08" | "2022-02-17T15:32:02" | "2022-02-17T15:32:02" | CONTRIBUTOR | null | Hi!
I bumped into this particular `ValueError` during my work (because an instance of `np.int64` was passed instead of regular Python `int`), and so I had to `print(type(values))` myself. Apparently, it's just the missing `f` to make message an f-string.
It ain't much for a contribution, but it's honest work. Hope it spares someone else a few seconds in the future 😃 | {
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https://api.github.com/repos/huggingface/datasets/issues/3741 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3741/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3741/comments | https://api.github.com/repos/huggingface/datasets/issues/3741/events | https://github.com/huggingface/datasets/pull/3741 | 1,141,132,649 | PR_kwDODunzps4y-syt | 3,741 | Rm sphinx doc | {
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} | [] | closed | false | null | [] | null | [] | "2022-02-17T10:11:37" | "2022-02-17T10:15:17" | "2022-02-17T10:15:12" | CONTRIBUTOR | null | Checklist
- [x] Update circle ci yaml
- [x] Delete sphinx static & python files in docs dir
- [x] Update readme in docs dir
- [ ] Update docs config in setup.py | {
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https://api.github.com/repos/huggingface/datasets/issues/3740 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3740/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3740/comments | https://api.github.com/repos/huggingface/datasets/issues/3740/events | https://github.com/huggingface/datasets/pull/3740 | 1,140,720,739 | PR_kwDODunzps4y9XAP | 3,740 | Support streaming for pubmed | {
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} | [] | closed | false | null | [] | null | [] | "2022-02-17T00:18:22" | "2022-02-18T14:42:13" | "2022-02-18T14:42:13" | CONTRIBUTOR | null | This PR makes some minor changes to the `pubmed` dataset to allow for `streaming=True`. Fixes #3739.
Basically, I followed the C4 dataset which works in streaming mode as an example, and made the following changes:
* Change URL prefix from `ftp://` to `https://`
* Explicilty `open` the filename and pass the XML contents to `etree.fromstring(xml_str)`
The Github diff tool makes it look like the changes are larger than they are, sorry about that.
I tested locally and the `pubmed` dataset now works in both normal and streaming modes. There is some overhead at the start of each shard in streaming mode as building the XML tree online is quite slow (each pubmed .xml.gz file is ~20MB), but the overhead gets amortized over all the samples in the shard. On my laptop with a single CPU worker I am able to stream at about ~600 samples/s. | {
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https://api.github.com/repos/huggingface/datasets/issues/3739 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3739/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3739/comments | https://api.github.com/repos/huggingface/datasets/issues/3739/events | https://github.com/huggingface/datasets/issues/3739 | 1,140,329,189 | I_kwDODunzps5D-Arl | 3,739 | Pubmed dataset does not work in streaming mode | {
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"Thanks for reporting, @abhi-mosaic (related to #3655).\r\n\r\nPlease note that `xml.etree.ElementTree.parse` already supports streaming:\r\n- #3476\r\n\r\nNo need to refactor to use `open`/`xopen`. Is is enough with importing the package `as ET` (instead of `as etree`)."
] | "2022-02-16T17:13:37" | "2022-02-18T14:42:13" | "2022-02-18T14:42:13" | CONTRIBUTOR | null | ## Describe the bug
Trying to use the `pubmed` dataset with `streaming=True` fails.
## Steps to reproduce the bug
```python
import datasets
pubmed_train = datasets.load_dataset('pubmed', split='train', streaming=True)
print (next(iter(pubmed_train)))
```
## Expected results
I would expect to see the first training sample from the pubmed dataset.
## Actual results
```
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/Users/abhinav/Documents/mosaicml/mosaicml_venv/lib/python3.8/site-packages/datasets/iterable_dataset.py", line 367, in __iter__
for key, example in self._iter():
File "/Users/abhinav/Documents/mosaicml/mosaicml_venv/lib/python3.8/site-packages/datasets/iterable_dataset.py", line 364, in _iter
yield from ex_iterable
File "/Users/abhinav/Documents/mosaicml/mosaicml_venv/lib/python3.8/site-packages/datasets/iterable_dataset.py", line 79, in __iter__
for key, example in self.generate_examples_fn(**self.kwargs):
File "/Users/abhinav/.cache/huggingface/modules/datasets_modules/datasets/pubmed/9715addf10c42a7877a2149ae0c5f2fddabefc775cd1bd9b03ac3f012b86ce46/pubmed.py", line 373, in _generate_examples
tree = etree.parse(filename)
File "/Library/Developer/CommandLineTools/Library/Frameworks/Python3.framework/Versions/3.8/lib/python3.8/xml/etree/ElementTree.py", line 1202, in parse
tree.parse(source, parser)
File "/Library/Developer/CommandLineTools/Library/Frameworks/Python3.framework/Versions/3.8/lib/python3.8/xml/etree/ElementTree.py", line 584, in parse
source = open(source, "rb")
FileNotFoundError: [Errno 2] No such file or directory: 'gzip://pubmed21n0001.xml::ftp://ftp.ncbi.nlm.nih.gov/pubmed/baseline/pubmed21n0001.xml.gz'
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.18.2
- Platform: macOS-11.4-x86_64-i386-64bit
- Python version: 3.8.2
- PyArrow version: 6.0.0
## Comments
The error looks like an issue with `open` vs. `xopen` inside the `xml` package. It looks like it's trying to open the remote source URL, which has been edited with prefix `gzip://...`.
Maybe there can be an explicit `xopen` before passing the raw data to `etree`, something like:
```python
# Before
tree = etree.parse(filename)
root = tree.getroot()
# After
with xopen(filename) as f:
data_str = f.read()
root = etree.fromstring(data_str)
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/3737 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3737/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3737/comments | https://api.github.com/repos/huggingface/datasets/issues/3737/events | https://github.com/huggingface/datasets/pull/3737 | 1,140,148,050 | PR_kwDODunzps4y7uFf | 3,737 | Make RedCaps streamable | {
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} | [] | closed | false | null | [] | null | [] | "2022-02-16T15:12:23" | "2022-02-16T15:28:38" | "2022-02-16T15:28:37" | CONTRIBUTOR | null | Make RedCaps streamable.
@lhoestq Using `data/redcaps_v1.0_annotations.zip` as a download URL gives an error locally when running `datasets-cli test` (will investigate this another time) | {
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https://api.github.com/repos/huggingface/datasets/issues/3736 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3736/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3736/comments | https://api.github.com/repos/huggingface/datasets/issues/3736/events | https://github.com/huggingface/datasets/pull/3736 | 1,140,134,483 | PR_kwDODunzps4y7rMR | 3,736 | Local paths in common voice | {
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} | [] | closed | false | null | [] | null | [] | "2022-02-16T15:01:29" | "2022-09-21T14:58:38" | "2022-02-22T09:13:43" | MEMBER | null | Continuation of https://github.com/huggingface/datasets/pull/3664:
- pass the `streaming` parameter to _split_generator
- update @anton-l's code to use this parameter for `common_voice`
- add a comment to explain why we use `download_and_extract` in non-streaming and `iter_archive` in streaming
Now the `common_voice` dataset has a local path back in `ds["path"]`, and this field is `None` in streaming mode.
cc @patrickvonplaten @anton-l @albertvillanova
Fix #3663. | {
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https://api.github.com/repos/huggingface/datasets/issues/3734 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3734/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3734/comments | https://api.github.com/repos/huggingface/datasets/issues/3734/events | https://github.com/huggingface/datasets/pull/3734 | 1,140,050,336 | PR_kwDODunzps4y7ZU2 | 3,734 | Fix bugs in NewsQA dataset | {
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} | [] | closed | false | null | [] | null | [] | "2022-02-16T13:51:28" | "2022-02-17T07:54:26" | "2022-02-17T07:54:25" | MEMBER | null | Fix #3733. | {
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NewsQA dataset has the following bugs:
- the field `validated_answers` is an exact copy of the field `answers` but with the addition of `'count': [0]` to each dict
- the field `badQuestion` does not appear in `answers` nor `validated_answers`
## Steps to reproduce the bug
By inspecting the dataset script we can see that:
- the parsing of `validated_answers` is a copy-paste of the one for `answers`
- the `badQuestion` field is ignored in the parsing of both `answers` and `validated_answers`
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"Thanks for reporting @byw2.\r\nWe are fixing it.\r\nIn the meantime, you can load the dataset by passing `ignore_verifications=True`:\r\n ```python\r\ndataset = load_dataset(\"multi_news\", ignore_verifications=True)"
] | "2022-02-16T05:11:08" | "2022-02-16T20:05:06" | "2022-02-16T08:48:46" | NONE | null | ## Describe the bug
When using the load_dataset function from datasets module to load the Multi-News dataset, does not load the dataset but throws Checksum Error instead.
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset("multi_news")
```
## Expected results
Should download and load Multi-News dataset.
## Actual results
Throws the following error and cannot load data successfully:
```
NonMatchingChecksumError: Checksums didn't match for dataset source files:
['https://drive.google.com/uc?export=download&id=1vRY2wM6rlOZrf9exGTm5pXj5ExlVwJ0C']
```
Could this issue please be looked at? Thanks! | {
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"Hi @kg-nlp, thanks for reporting.\r\n\r\nThat is weird... I guess we would need some sample data file where this behavior appears to reproduce the bug for further investigation... ",
"ok, I found the reason why that two results are not same.\r\nthere is /u2029 in the text, the datasets will split sentence according to the /u2029,but when I use open function will not do that .\r\nso I want to know which function shell do that\r\nthanks"
] | "2022-02-16T01:13:31" | "2022-03-15T16:16:09" | "2022-03-15T16:16:09" | NONE | null | ## Describe the bug
when I use load_dataset to read a txt file I find that the number of the samples is incorrect
## Steps to reproduce the bug
```
fr = open('train.txt','r',encoding='utf-8').readlines()
print(len(fr)) # 1199637
datasets = load_dataset('text', data_files={'train': ['train.txt']}, streaming=False)
print(len(datasets['train'])) # 1199649
```
I also use command line operation to verify it
```
$ wc -l train.txt
1199637 train.txt
```
## Expected results
please fix that issue
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.8.3
- Platform:windows&linux
- Python version:3.7
- PyArrow version:6.0.1
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"duplicate of https://github.com/huggingface/datasets/issues/2300"
] | "2022-02-15T23:04:55" | "2022-02-16T18:49:12" | "2022-02-16T18:49:12" | MEMBER | null | ## Adding a Dataset
- **Name:** VoxPopuli
- **Description:** A Large-Scale Multilingual Speech Corpus
- **Paper:** https://arxiv.org/pdf/2101.00390.pdf
- **Data:** https://github.com/facebookresearch/voxpopuli
- **Motivation:** one of the largest (if not the largest) multilingual speech corpus: 400K hours of multilingual unlabeled speech + 17k hours of labeled speech
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
👀 @kahne @Molugan
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https://api.github.com/repos/huggingface/datasets/issues/3727 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3727/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3727/comments | https://api.github.com/repos/huggingface/datasets/issues/3727/events | https://github.com/huggingface/datasets/pull/3727 | 1,138,979,732 | PR_kwDODunzps4y34JN | 3,727 | Patch all module attributes in its namespace | {
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However those are only a subset of all the module attributes in its namespace (`__dict__` variable).
This PR fixes the problem of modules that have non-None `__all__` variable, but try to access an attribute present in `__dict__` (and not in `__all__`).
For example, `pandas` has attribute `__version__` only present in `__dict__`.
- Before version 1.4, pandas `__all__` was None, thus all attributes in `__dict__` were patched
- From version 1.4, pandas `__all__` is not None, thus attributes in `__dict__` not present in `__all__` are ignored
Fix #3724.
CC: @severo @lvwerra | {
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https://api.github.com/repos/huggingface/datasets/issues/3726 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3726/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3726/comments | https://api.github.com/repos/huggingface/datasets/issues/3726/events | https://github.com/huggingface/datasets/pull/3726 | 1,138,870,362 | PR_kwDODunzps4y3iSv | 3,726 | Use config pandas version in CSV dataset builder | {
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Related to #3724. | {
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] | null | [] | "2022-02-15T15:16:19" | "2022-02-15T16:55:44" | "2022-02-15T16:55:44" | MEMBER | null | ## Describe the bug
If we upgrade to pandas `1.4`, the patching of the pandas module is no longer working
```
AttributeError: '_PatchedModuleObj' object has no attribute '__version__'
```
## Steps to reproduce the bug
```
pip install pandas==1.4
```
```python
from datasets import load_dataset
ds = load_dataset("lvwerra/red-wine", split="train", streaming=True)
item = next(iter(ds))
item
```
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https://api.github.com/repos/huggingface/datasets/issues/3723 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3723/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3723/comments | https://api.github.com/repos/huggingface/datasets/issues/3723/events | https://github.com/huggingface/datasets/pull/3723 | 1,138,789,493 | PR_kwDODunzps4y3RuI | 3,723 | Fix flatten of complex feature types | {
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Inspired by `cast`/`table_cast`, I've introduced a `table_flatten` function to handle the Image/Audio types.
CC: @SBrandeis
Fix #3686.
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} | [] | closed | false | null | [] | null | [] | "2022-02-14T17:26:51" | "2022-03-07T16:28:57" | "2022-03-07T16:28:56" | CONTRIBUTOR | null | Per #3716 , current implementation does not take into consideration that `faiss` can run on multiple GPUs.
In this commit, I provided multi-GPU support for `FaissIndex` by modifying the device management in `IndexableMixin.add_faiss_index` and `FaissIndex.load`.
Now users are able to pass in
1. a positive integer (as usual) to use 1 GPU
2. a negative integer `-1` to use all GPUs
3. a list of integers e.g. `[0, 1]` to run only on those GPUs
4. Of course, passing in nothing still runs on CPU.
This closes: #3716 | {
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https://api.github.com/repos/huggingface/datasets/issues/3719 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3719/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3719/comments | https://api.github.com/repos/huggingface/datasets/issues/3719/events | https://github.com/huggingface/datasets/pull/3719 | 1,137,237,622 | PR_kwDODunzps4yyFv7 | 3,719 | Check if indices values in `Dataset.select` are within bounds | {
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} | [] | closed | false | null | [] | null | [] | "2022-02-14T12:31:41" | "2022-02-14T19:19:22" | "2022-02-14T19:19:22" | CONTRIBUTOR | null | Fix #3707
Instead of reusing `_check_valid_index_key` from `datasets.formatting`, I defined a new function to provide a more meaningful error message.
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https://api.github.com/repos/huggingface/datasets/issues/3718 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3718/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3718/comments | https://api.github.com/repos/huggingface/datasets/issues/3718/events | https://github.com/huggingface/datasets/pull/3718 | 1,137,196,388 | PR_kwDODunzps4yx8r2 | 3,718 | Fix Evidence Infer Treatment dataset | {
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} | [] | closed | false | null | [] | null | [] | "2022-02-14T11:58:07" | "2022-02-14T13:21:45" | "2022-02-14T13:21:44" | MEMBER | null | This PR:
- fixes a bug in the script, by removing an unnamed column with the row index: fix KeyError
- fix the metadata JSON, by adding both configurations (1.1 and 2.0): fix ExpectedMoreDownloadedFiles
- updates the dataset card
Fix #3515. | {
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https://api.github.com/repos/huggingface/datasets/issues/3717 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3717/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3717/comments | https://api.github.com/repos/huggingface/datasets/issues/3717/events | https://github.com/huggingface/datasets/issues/3717 | 1,137,183,015 | I_kwDODunzps5DyAkn | 3,717 | wrong condition in `Features ClassLabel encode_example` | {
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"Hi @Tudyx, \r\n\r\nPlease note that in Python, the boolean NOT operator (`not`) has lower precedence than comparison operators (`<=`, `<`), thus the expression you mention is equivalent to:\r\n```python\r\n not (-1 <= example_data < self.num_classes)\r\n```\r\n\r\nAlso note that as expected, the exception is raised if:\r\n- `example_data < -1`\r\n- or `example_data >= self.num_classes`\r\n\r\nThe raise of the exception is expected when `example_data` equals 4 and `self.num_classes` equals 4 too."
] | "2022-02-14T11:44:35" | "2022-02-14T15:09:36" | "2022-02-14T15:07:43" | NONE | null | ## Describe the bug
The `encode_example` function in *features.py* seems to have a wrong condition.
```python
if not -1 <= example_data < self.num_classes:
raise ValueError(f"Class label {example_data:d} greater than configured num_classes {self.num_classes}")
```
## Expected results
The `not - 1` condition change the result of the condition. For instance, if `example_data` equals 4 and ` self.num_classes` equals 4 too, `example_data < self.num_classes` will give `False` as expected . But if i add the `not - 1` condition, `not -1 <= example_data < self.num_classes` will give `True` and raise an exception.
## Environment info
- `datasets` version: 1.18.3
- Python version: 3.8.10
- PyArrow version: 7.00
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https://api.github.com/repos/huggingface/datasets/issues/3716 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3716/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3716/comments | https://api.github.com/repos/huggingface/datasets/issues/3716/events | https://github.com/huggingface/datasets/issues/3716 | 1,136,831,092 | I_kwDODunzps5Dwqp0 | 3,716 | `FaissIndex` to support multiple GPU and `custom_index` | {
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"Hi @rentruewang, thansk for reporting and for your PR!!! We should definitely support this. ",
"@albertvillanova Great! :)"
] | "2022-02-14T06:21:43" | "2022-03-07T16:28:56" | "2022-03-07T16:28:56" | CONTRIBUTOR | null | **Is your feature request related to a problem? Please describe.**
Currently, because `device` is of the type `int | None`, to leverage `faiss-gpu`'s multi-gpu support, you need to create a `custom_index`. However, if using a `custom_index` created by e.g. `faiss.index_cpu_to_all_gpus`, then `FaissIndex.save` does not work properly because it checks the device id (which is an int, so no multiple GPUs).
**Describe the solution you'd like**
I would like `FaissIndex` to support multiple GPUs, by passing in a list to `add_faiss_index`.
**Describe alternatives you've considered**
Alternatively, I would like it to at least provide a warning cause it wasn't the behavior that I expected.
**Additional context**
Relavent source code here:
https://github.com/huggingface/datasets/blob/6ed6ac9448311930557810383d2cfd4fe6aae269/src/datasets/search.py#L340-L349
Device management needs changing to support multiple GPUs, probably by `isinstance` calls.
I can provide a PR if you like :)
Thanks for reading!
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1) Errors in table load-in. Split by a single comma instead of using pandas is wrong.
2) id reduplicated in _generate_examples function.
3) Missing information of history questions which make it hard to use.
I fix it refer to https://github.com/HKUNLP/UnifiedSKG. And we test it to perform normally. | {
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https://api.github.com/repos/huggingface/datasets/issues/3714 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3714/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3714/comments | https://api.github.com/repos/huggingface/datasets/issues/3714/events | https://github.com/huggingface/datasets/issues/3714 | 1,136,105,530 | I_kwDODunzps5Dt5g6 | 3,714 | tatoeba_mt: File not found error and key error | {
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"Looks like I solved my problems ..."
] | "2022-02-13T16:35:45" | "2022-02-13T20:44:04" | "2022-02-13T20:44:04" | NONE | null | ## Dataset viewer issue for 'tatoeba_mt'
**Link:** https://huggingface.co/datasets/Helsinki-NLP/tatoeba_mt
My data loader script does not seem to work.
The files are part of the local repository but cannot be found. An example where it should work is the subset for "afr-eng".
Another problem is that I do not have validation data for all subsets and I don't know how to properly check whether validation exists in the configuration before I try to download it. An example is the subset for "afr-deu".
Am I the one who added this dataset ? Yes
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- [x] Update circle ci yaml
- [x] Delete sphinx static & python files in docs dir
- [x] Update readme in docs dir
- [ ] Update docs config in setup.py | {
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https://api.github.com/repos/huggingface/datasets/issues/3710 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3710/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3710/comments | https://api.github.com/repos/huggingface/datasets/issues/3710/events | https://github.com/huggingface/datasets/pull/3710 | 1,133,955,393 | PR_kwDODunzps4ymQMQ | 3,710 | Fix CI code quality issue | {
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cc @polinaeterna this will be useful if we have audio datasets that are canonical and for which you'd like to host data files | {
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https://api.github.com/repos/huggingface/datasets/issues/3707 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3707/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3707/comments | https://api.github.com/repos/huggingface/datasets/issues/3707/events | https://github.com/huggingface/datasets/issues/3707 | 1,132,741,903 | I_kwDODunzps5DhEUP | 3,707 | `.select`: unexpected behavior with `indices` | {
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"Hi! Currently, we compute the final index as `index % len(dset)`. I agree this behavior is somewhat unexpected and that it would be more appropriate to raise an error instead (this is what `df.iloc` in Pandas does, for instance).\r\n\r\n@albertvillanova @lhoestq wdyt?",
"I agree. I think `index % len(dset)` was used to support negative indices.\r\n\r\nI think this needs to be fixed in `datasets.formatting.formatting._check_valid_index_key` if I'm not mistaken"
] | "2022-02-11T15:20:01" | "2022-02-14T19:19:21" | "2022-02-14T19:19:21" | NONE | null | ## Describe the bug
The `.select` method will not throw when sending `indices` bigger than the dataset length; `indices` will be wrapped instead. This behavior is not documented anywhere, and is not intuitive.
## Steps to reproduce the bug
```python
from datasets import Dataset
ds = Dataset.from_dict({"text": ["d", "e", "f"], "label": [4, 5, 6]})
res1 = ds.select([1, 2, 3])['text']
res2 = ds.select([1000])['text']
```
## Expected results
Both results should throw an `Error`.
## Actual results
`res1` will give `['e', 'f', 'd']`
`res2` will give `['e']`
## Environment info
Bug found from this environment:
- `datasets` version: 1.16.1
- Platform: macOS-10.16-x86_64-i386-64bit
- Python version: 3.8.7
- PyArrow version: 6.0.1
It was also replicated on `master`.
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https://api.github.com/repos/huggingface/datasets/issues/3706 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3706/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3706/comments | https://api.github.com/repos/huggingface/datasets/issues/3706/events | https://github.com/huggingface/datasets/issues/3706 | 1,132,218,874 | I_kwDODunzps5DfEn6 | 3,706 | Unable to load dataset 'big_patent' | {
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"Hi @ankitk2109,\r\n\r\nHave you tried passing the split name with the keyword `split=`? See e.g. an example in our Quick Start docs: https://huggingface.co/docs/datasets/quickstart.html#load-the-dataset-and-model\r\n```python\r\n ds = load_dataset(\"big_patent\", \"d\", split=\"validation\")",
"Hi @albertvillanova,\r\n\r\nThanks for your response.\r\n\r\nYes, I tried the `split='validation'` as well. But getting the same issue. ",
"I'm sorry, but I can't reproduce your problem:\r\n```python\r\nIn [5]: ds = load_dataset(\"big_patent\", \"d\", split=\"validation\")\r\nDownloading and preparing dataset big_patent/d (download: 6.01 GiB, generated: 169.61 MiB, post-processed: Unknown size, total: 6.17 GiB) to .../.cache/big_patent/d/1.0.0/bdefa7c0b39fba8bba1c6331b70b738e30d63c8ad4567f983ce315a5fef6131c...\r\nDownloading data: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6.45G/6.45G [27:36<00:00, 3.89MB/s]\r\nExtracting data files: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 3/3 [03:18<00:00, 66.08s/it]\r\nDataset big_patent downloaded and prepared to .../.cache/big_patent/d/1.0.0/bdefa7c0b39fba8bba1c6331b70b738e30d63c8ad4567f983ce315a5fef6131c. Subsequent calls will reuse this data. \r\n\r\nIn [6]: ds\r\nOut[6]: \r\nDataset({\r\n features: ['description', 'abstract'],\r\n num_rows: 565\r\n})\r\n",
"Maybe you had a connection issue while downloading the file and this was corrupted?\r\nOur cache system uses the file you downloaded first time.\r\nIf so, you could try forcing redownload of the file with:\r\n```python\r\nds = load_dataset(\"big_patent\", \"d\", split=\"validation\", download_mode=\"force_redownload\")",
"I am able to download the dataset with ``` download_mode=\"force_redownload\"```. As you mentioned it was an issue with the cached version which was failed earlier due to a network issue. I am closing the issue now, once again thank you."
] | "2022-02-11T09:48:34" | "2022-02-14T15:26:03" | "2022-02-14T15:26:03" | NONE | null | ## Describe the bug
Unable to load the "big_patent" dataset
## Steps to reproduce the bug
```python
load_dataset('big_patent', 'd', 'validation')
```
## Expected results
Download big_patents' validation split from the 'd' subset
## Getting an error saying:
{FileNotFoundError}Local file ..\huggingface\datasets\downloads\6159313604f4f2c01e7d1cac52139343b6c07f73f6de348d09be6213478455c5\bigPatentData\train.tar.gz doesn't exist
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version:1.18.3
- Platform: Windows
- Python version:3.8
- PyArrow version:7.0.0
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https://api.github.com/repos/huggingface/datasets/issues/3705 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3705/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3705/comments | https://api.github.com/repos/huggingface/datasets/issues/3705/events | https://github.com/huggingface/datasets/pull/3705 | 1,132,053,226 | PR_kwDODunzps4yfhyj | 3,705 | Raise informative error when loading a save_to_disk dataset | {
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} | [] | closed | false | null | [] | null | [] | "2022-02-11T08:21:03" | "2022-02-11T22:56:40" | "2022-02-11T22:56:39" | MEMBER | null | People recurrently report error when trying to load a dataset (using `load_dataset`) that was previously saved using `save_to_disk`.
This PR raises an informative error message telling them they should use `load_from_disk` instead.
Close #3700. | {
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https://api.github.com/repos/huggingface/datasets/issues/3704 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3704/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3704/comments | https://api.github.com/repos/huggingface/datasets/issues/3704/events | https://github.com/huggingface/datasets/issues/3704 | 1,132,042,631 | I_kwDODunzps5DeZmH | 3,704 | OSCAR-2109 datasets are misaligned and truncated | {
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"Hi @adrianeboyd, thanks for reporting.\r\n\r\nThere is indeed a bug in that community dataset:\r\nLine:\r\n```python\r\nmetadata_and_text_files = list(zip(metadata_files, text_files))\r\n``` \r\nshould be replaced with\r\n```python\r\nmetadata_and_text_files = list(zip(sorted(metadata_files), sorted(text_files)))\r\n```\r\n\r\nI am going to contact their owners (https://huggingface.co/oscar-corpus) in order to inform them about the bug.\r\n\r\nI keep you informed.",
"That fix is part of it, but it's clearly not the only issue.\r\n\r\nI also already contacted the OSCAR creators, but I reported it here because it looked like huggingface members were the main authors in the git history. Is there a better place to have reported this?",
"Hello,\r\n\r\nWe've had an issue that could be linked to this one here: https://github.com/oscar-corpus/corpus/issues/15.\r\n\r\nI have been spot checking the source (`.txt`/`.jsonl`) files for a while, and have not found issues, especially in the start/end of corpora (but I conceed that more integration testing would be necessary on our side).\r\n\r\nThe text and metadata files are designed to be used in sync (with `lang_part_n.txt` and `lang_meta_part_n.jsonl` working together), while staying independent from part to part, so that anyone could randomly choose a part and work with it.\r\n\r\nThe fix @albertvillanova proposed should fix the problem, as the parts will be in sync again.\r\n\r\nLet me know if you need help or more details, I'd be glad to help!",
"I'm happy to move the discussion to the other repo!\r\n\r\nMerely sorting the files only **maybe** fixes the processing of the first part. If the first part contains non-unix newlines, it will still be misaligned/truncated, and all the following parts will be truncated with incorrect text offsets and metadata due the offset and newline bugs.",
"Fixed:\r\n- https://huggingface.co/datasets/oscar-corpus/OSCAR-2109/commit/3cd7e95aa1799b73c5ea8afc3989635f3e19b86b",
"Hi @Uinelj, This is a total noobs question but how can I integrate that bugfix into my code? I reinstalled the datasets library this time from source. Should that have fixed the issue? I am still facing the misalignment issue. Do I need to download the dataset from scratch?",
"Hi, I re-downloaded the dataset and still have the problem. See: https://github.com/oscar-corpus/corpus/issues/18",
"Sorry @norakassner for the late reply.\r\n\r\nThere are indeed several issues creating the misalignment, as @adrianeboyd cleverly pointed out:\r\n- https://huggingface.co/datasets/oscar-corpus/OSCAR-2109/commit/3cd7e95aa1799b73c5ea8afc3989635f3e19b86b fixed one of them\r\n- but there are still others to be fixed",
"Normally, the issues should be fixed now:\r\n- Fix offset initialization for each file: https://huggingface.co/datasets/oscar-corpus/OSCAR-2109/commit/1ad9b7bfe00798a9258a923b887bb1c8d732b833\r\n- Disable default universal newline support: https://huggingface.co/datasets/oscar-corpus/OSCAR-2109/commit/0c2f307d3167f03632f502af361ac6c3c393f510\r\n\r\nFeel free to reopen if you find additional misalignments/truncations.\r\n\r\nCC: @adrianeboyd @norakassner @Uinelj ",
"Thanks for the updates!\r\n\r\nThe purist in me would still like to have the rstrip not strip additional characters from the original text (unicode whitespace mainly in practice, I think), but the differences are extremely small in practice and it doesn't actually matter for my current task:\r\n\r\n```python\r\ntext = \"\".join([text_f.readline() for _ in range(meta[\"nb_sentences\"])]).rstrip(\"\\n\")\r\n```"
] | "2022-02-11T08:14:59" | "2022-03-17T18:01:04" | "2022-03-16T16:21:28" | NONE | null | ## Describe the bug
The `oscar-corpus/OSCAR-2109` data appears to be misaligned and truncated by the dataset builder for subsets that contain more than one part and for cases where the texts contain non-unix newlines.
## Steps to reproduce the bug
A few examples, although I'm not sure how deterministic the particular (mis)alignment is in various configurations:
```python
from datasets import load_dataset
dataset = load_dataset("oscar-corpus/OSCAR-2109", "deduplicated_fi", split="train", use_auth_token=True)
entry = dataset[0]
# entry["text"] is from fi_part_3.txt.gz
# entry["meta"] is from fi_meta_part_2.jsonl.gz
dataset = load_dataset("oscar-corpus/OSCAR-2109", "deduplicated_no", split="train", use_auth_token=True)
entry = dataset[900000]
# entry["text"] is from no_part_3.txt.gz and contains a blank line
# entry["meta"] is from no_meta_part_1.jsonl.gz
dataset = load_dataset("oscar-corpus/OSCAR-2109", "deduplicated_mk", split="train", streaming=True, use_auth_token=True)
# 9088 texts in the dataset are empty
```
For `deduplicated_fi`, all exported raw texts from the dataset are 17GB rather than 20GB as reported in the data splits overview table. The token count with `wc -w` for the raw texts is 2,067,556,874 rather than the expected 2,357,264,196 from the data splits table.
For `deduplicated_no` all exported raw texts contain 624,040,887 rather than the expected 776,354,517 tokens.
For `deduplicated_mk` it is 122,236,936 rather than 134,544,934 tokens.
I'm not expecting the `wc -w` counts to line up exactly with the data splits table, but for comparison the `wc -w` count for `deduplicated_mk` on the raw texts is 134,545,424.
## Issues
* The meta / text files are not paired correctly when loading, so the extracted texts do not have the right offsets, the metadata is not associated with the correct text, and the text files may not be processed to the end or may be processed beyond the end (empty texts).
* The line count offset is not reset per file so the texts aren't aligned to the right offsets in any parts beyond the first part, leading to truncation when in effect blank lines are not skipped.
* Non-unix newline characters are treated as newlines when reading the text files while the metadata only counts unix newlines for its line offsets, leading to further misalignments between the metadata and the extracted texts, and which also results in truncation.
## Expected results
All texts from the OSCAR release are extracted according to the metadata and aligned with the correct metadata.
## Fixes
Not necessarily the exact fixes/checks you may want to use (I didn't test all languages or do any cross-platform testing, I'm not sure all the details are compatible with streaming), however to highlight the issues:
```diff
diff --git a/OSCAR-2109.py b/OSCAR-2109.py
index bbac1076..5eee8de7 100644
--- a/OSCAR-2109.py
+++ b/OSCAR-2109.py
@@ -20,6 +20,7 @@
import collections
import gzip
import json
+import os
import datasets
@@ -387,9 +388,20 @@ class Oscar2109(datasets.GeneratorBasedBuilder):
with open(checksum_file, encoding="utf-8") as f:
data_filenames = [line.split()[1] for line in f if line]
data_urls = [self.config.base_data_path + data_filename for data_filename in data_filenames]
- text_files = dl_manager.download([url for url in data_urls if url.endswith(".txt.gz")])
- metadata_files = dl_manager.download([url for url in data_urls if url.endswith(".jsonl.gz")])
+ # sort filenames so corresponding parts are aligned
+ text_files = sorted(dl_manager.download([url for url in data_urls if url.endswith(".txt.gz")]))
+ metadata_files = sorted(dl_manager.download([url for url in data_urls if url.endswith(".jsonl.gz")]))
+ assert len(text_files) == len(metadata_files)
metadata_and_text_files = list(zip(metadata_files, text_files))
+ for meta_path, text_path in metadata_and_text_files:
+ # check that meta/text part numbers are the same
+ if "part" in os.path.basename(text_path):
+ assert (
+ os.path.basename(text_path).replace(".txt.gz", "").split("_")[-1]
+ == os.path.basename(meta_path).replace(".jsonl.gz", "").split("_")[-1]
+ )
+ else:
+ assert len(metadata_and_text_files) == 1
return [
datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"metadata_and_text_files": metadata_and_text_files}),
]
@@ -397,10 +409,14 @@ class Oscar2109(datasets.GeneratorBasedBuilder):
def _generate_examples(self, metadata_and_text_files):
"""This function returns the examples in the raw (text) form by iterating on all the files."""
id_ = 0
- offset = 0
for meta_path, text_path in metadata_and_text_files:
+ # line offsets are per text file
+ offset = 0
logger.info("generating examples from = %s", text_path)
- with gzip.open(open(text_path, "rb"), "rt", encoding="utf-8") as text_f:
+ # some texts contain non-Unix newlines that should not be
+ # interpreted as line breaks for the line counts in the metadata
+ # with readline()
+ with gzip.open(open(text_path, "rb"), "rt", encoding="utf-8", newline="\n") as text_f:
with gzip.open(open(meta_path, "rb"), "rt", encoding="utf-8") as meta_f:
for line in meta_f:
# read meta
@@ -411,7 +427,12 @@ class Oscar2109(datasets.GeneratorBasedBuilder):
offset += 1
text_f.readline()
# read text
- text = "".join([text_f.readline() for _ in range(meta["nb_sentences"])]).rstrip()
+ text_lines = [text_f.readline() for _ in range(meta["nb_sentences"])]
+ # all lines contain text (no blank lines or EOF)
+ assert all(text_lines)
+ assert "\n" not in text_lines
offset += meta["nb_sentences"]
+ # only strip the trailing newline
+ text = "".join(text_lines).rstrip("\n")
yield id_, {"id": id_, "text": text, "meta": meta}
id_ += 1
```
I've tested this with a number of smaller deduplicated languages with 1-20 parts and the resulting datasets looked correct in terms of word count and size when compared to the data splits table and raw texts, and the text/metadata alignments were correct in all my spot checks. However, there are many many languages I didn't test and I'm not sure that there aren't any texts containing blank lines in the corpus, for instance. For the cases I tested, the assertions related to blank lines and EOF made it easier to verify that the text and metadata were aligned as intended, since there would be little chance of spurious alignments of variable-length texts across so much data. | {
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https://api.github.com/repos/huggingface/datasets/issues/3702 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3702/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3702/comments | https://api.github.com/repos/huggingface/datasets/issues/3702/events | https://github.com/huggingface/datasets/pull/3702 | 1,130,666,707 | PR_kwDODunzps4yahKc | 3,702 | Update data URL of lm1b dataset | {
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https://api.github.com/repos/huggingface/datasets/issues/3701 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3701/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3701/comments | https://api.github.com/repos/huggingface/datasets/issues/3701/events | https://github.com/huggingface/datasets/pull/3701 | 1,130,498,738 | PR_kwDODunzps4yZ8Dw | 3,701 | Pin ElasticSearch | {
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} | [] | closed | false | null | [] | null | [] | "2022-02-10T17:15:26" | "2022-02-10T17:31:13" | "2022-02-10T17:31:12" | MEMBER | null | Until we manage to support ES 8.0, I'm setting the version to `<8.0.0`
Currently we're getting this error on 8.0:
```python
ValueError: Either 'hosts' or 'cloud_id' must be specified
```
When instantiating a `Elasticsearch()` object | {
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https://api.github.com/repos/huggingface/datasets/issues/3700 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3700/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3700/comments | https://api.github.com/repos/huggingface/datasets/issues/3700/events | https://github.com/huggingface/datasets/issues/3700 | 1,130,252,496 | I_kwDODunzps5DXkjQ | 3,700 | Unable to load a dataset | {
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"Hi! `load_dataset` is intended to be used to load a canonical dataset (`wikipedia`), a packaged dataset (`csv`, `json`, ...) or a dataset hosted on the Hub. For local datasets saved with `save_to_disk(\"path/to/dataset\")`, use `load_from_disk(\"path/to/dataset\")`.",
"Maybe we should raise an informative error message in this case..."
] | "2022-02-10T15:05:53" | "2022-02-11T22:56:39" | "2022-02-11T22:56:39" | NONE | null | ## Describe the bug
Unable to load a dataset from Huggingface that I have just saved.
## Steps to reproduce the bug
On Google colab
`! pip install datasets `
`from datasets import load_dataset`
`my_path = "wiki_dataset"`
`dataset = load_dataset('wikipedia', "20200501.fr")`
`dataset.save_to_disk(my_path)`
`dataset = load_dataset(my_path)`
## Expected results
Loading the dataset
## Actual results
ValueError: Couldn't cast
_data_files: list<item: struct<filename: string>>
child 0, item: struct<filename: string>
child 0, filename: string
_fingerprint: string
_format_columns: null
_format_kwargs: struct<>
_format_type: null
_indexes: struct<>
_output_all_columns: bool
_split: string
to
{'builder_name': Value(dtype='string', id=None), 'citation': Value(dtype='string', id=None), 'config_name': Value(dtype='string', id=None), 'dataset_size': Value(dtype='int64', id=None), 'description': Value(dtype='string', id=None), 'download_checksums': {}, 'download_size': Value(dtype='int64', id=None), 'features': {'title': {'dtype': Value(dtype='string', id=None), 'id': Value(dtype='null', id=None), '_type': Value(dtype='string', id=None)}, 'text': {'dtype': Value(dtype='string', id=None), 'id': Value(dtype='null', id=None), '_type': Value(dtype='string', id=None)}}, 'homepage': Value(dtype='string', id=None), 'license': Value(dtype='string', id=None), 'post_processed': Value(dtype='null', id=None), 'post_processing_size': Value(dtype='null', id=None), 'size_in_bytes': Value(dtype='int64', id=None), 'splits': {'train': {'name': Value(dtype='string', id=None), 'num_bytes': Value(dtype='int64', id=None), 'num_examples': Value(dtype='int64', id=None), 'dataset_name': Value(dtype='string', id=None)}}, 'supervised_keys': Value(dtype='null', id=None), 'task_templates': Value(dtype='null', id=None), 'version': {'version_str': Value(dtype='string', id=None), 'description': Value(dtype='string', id=None), 'major': Value(dtype='int64', id=None), 'minor': Value(dtype='int64', id=None), 'patch': Value(dtype='int64', id=None)}}
because column names don't match
## Environment info
- `datasets` version: 1.18.3
- Platform: Linux-5.4.144+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.12
- PyArrow version: 6.0.1
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Fix #413. | {
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Fix #3630. | {
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This PR, removes `names_file` as a field of the data class `ClassLabel`.
- it is only used at instantiation to generate the `labels` field
Fix #3631. | {
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} | [] | closed | false | null | [] | null | [] | "2022-02-08T18:45:19" | "2022-02-08T19:56:40" | "2022-02-08T19:56:39" | MEMBER | null | Upgrades the `datasets` library quality tool `black` to use the first stable release of `black`, version 22.0. | {
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https://api.github.com/repos/huggingface/datasets/issues/3690 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3690/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3690/comments | https://api.github.com/repos/huggingface/datasets/issues/3690/events | https://github.com/huggingface/datasets/pull/3690 | 1,127,493,538 | PR_kwDODunzps4yP2p5 | 3,690 | Update docs to new frontend/UI | {
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} | [] | closed | false | null | [] | null | [] | "2022-02-08T16:38:09" | "2022-03-03T20:04:21" | "2022-03-03T20:04:20" | CONTRIBUTOR | null | ### TLDR: Update `datasets` `docs` to the new syntax (markdown and mdx files) & frontend (as how it looks on [hf.co/transformers](https://huggingface.co/docs/transformers/index))
| Light mode | Dark mode |
|-----------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------|
| <img width="400" alt="Screenshot 2022-02-17 at 14 15 34" src="https://user-images.githubusercontent.com/11827707/154489358-e2fb3708-8d72-4fb6-93f0-51d4880321c0.png"> | <img width="400" alt="Screenshot 2022-02-17 at 14 16 27" src="https://user-images.githubusercontent.com/11827707/154489596-c5a1311b-181c-4341-adb3-d60a7d3abe85.png"> |
## Checklist
- [x] update datasets docs to new syntax (should call `doc-builder convert`) (this PR)
- [x] discuss `@property` methods frontend https://github.com/huggingface/doc-builder/pull/87
- [x] discuss `inject_arrow_table_documentation` (this PR) https://github.com/huggingface/datasets/pull/3690#discussion_r801847860
- [x] update datasets docs path on moon-landing https://github.com/huggingface/moon-landing/pull/2089
- [x] convert pyarrow docstring from Numpydoc style to groups style https://github.com/huggingface/doc-builder/pull/89(https://stackoverflow.com/a/24385103/6558628)
- [x] handle `Raises` section on frontend and doc-builder https://github.com/huggingface/doc-builder/pull/86
- [x] check imgs path (this PR) (nothing to update here)
- [x] doc exaples block has to follow format `Examples::` https://github.com/huggingface/datasets/pull/3693
- [x] fix [this docstring](https://github.com/huggingface/datasets/blob/6ed6ac9448311930557810383d2cfd4fe6aae269/src/datasets/arrow_dataset.py#L3339) (causing svelte compilation error)
- [x] Delete sphinx related files
- [x] Delete sphinx CI
- [x] Update docs config in setup.py
- [x] add `versions.yml` in doc-build https://github.com/huggingface/doc-build/pull/1
- [x] add `versions.yml` in doc-build-dev https://github.com/huggingface/doc-build-dev/pull/1
- [x] https://github.com/huggingface/moon-landing/pull/2089
- [x] format docstrings for example `datasets.DatasetBuilder.download_and_prepare` args format look wrong
- [x] create new github actions. (can probably be in a separate PR) (see the transformers equivalents below)
1. [build_dev_documentation.yml](https://github.com/huggingface/transformers/blob/master/.github/workflows/build_dev_documentation.yml)
2. [build_documentation.yml](https://github.com/huggingface/transformers/blob/master/.github/workflows/build_documentation.yml)
3. [delete_dev_documentation.yml](https://github.com/huggingface/transformers/blob/master/.github/workflows/delete_dev_documentation.yml)
## Note to reviewers
The number of changed files is a lot (100+) because I've converted all `.rst` files to `.mdx` files & they are compiling fine on the svelte side (also, moved all the imgs to to [doc-imgs repo](https://huggingface.co/datasets/huggingface/documentation-images/tree/main/datasets)). Moreover, you should just review them on preprod and see if the rendering look fine.
_Therefore, I'd suggest to focus on the changed_ **`.py`** and **CI files** (github workflows, etc. you can use [this filter here](https://github.com/huggingface/datasets/pull/3690/files?file-filters%5B%5D=.py&file-filters%5B%5D=.yml&show-deleted-files=true&show-viewed-files=true)) during the review & ignore `.mdx` files. (if there's a bug in `.mdx` files, we can always handle it in a separate PR afterwards). | {
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