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https://api.github.com/repos/huggingface/datasets/issues/2175 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2175/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2175/comments | https://api.github.com/repos/huggingface/datasets/issues/2175/events | https://github.com/huggingface/datasets/issues/2175 | 851,836,096 | MDU6SXNzdWU4NTE4MzYwOTY= | 2,175 | dataset.search_batch() function outputs all -1 indices sometime. | {
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"Actually, I found the answer [here](https://github.com/facebookresearch/faiss/wiki/FAQ#what-does-it-mean-when-a-search-returns--1-ids). \r\n\r\nSo we have to do some modifications to the code for instances where the index doesn't retrieve any IDs.",
"@lhoestq @patrickvonplaten \r\n\r\nI also found another short... | 2021-04-06T21:50:49Z | 2021-04-16T12:21:16Z | 2021-04-16T12:21:15Z | NONE | null | null | null | I am working with RAG and playing around with different faiss indexes. At the moment I use **index = faiss.index_factory(768, "IVF65536_HNSW32,Flat")**.
During the retrieval phase exactly in [this line of retrieval_rag.py](https://github.com/huggingface/transformers/blob/master/src/transformers/models/rag/retrieval_rag.py#L231) an error issue when all retrieved indices are -1. Please refer to the screenshot of a PID worker.
Here, my retrieve batch size is 2 and n_docs is 5. I can solve this by working around np. stack, but I want to ask, why we get an output index of -1. Do you have any idea :) ?
Is this a problem of the index, where the faiss can't find any similar vector?
Is there documentation on the output index being -1?
@lhoestq
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https://api.github.com/repos/huggingface/datasets/issues/4301 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4301/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4301/comments | https://api.github.com/repos/huggingface/datasets/issues/4301/events | https://github.com/huggingface/datasets/pull/4301 | 1,230,401,256 | PR_kwDODunzps43idlE | 4,301 | Add ImageNet-Sketch dataset | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"I think you can go ahead with uploading the data, and also ping the author in parallel. I think the images may subject to copyright anyway (scrapped from google image) so the dataset author is not allowed to set a license to the data... | 2022-05-09T23:38:45Z | 2022-05-23T18:14:14Z | 2022-05-23T18:05:29Z | CONTRIBUTOR | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/1539 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1539/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1539/comments | https://api.github.com/repos/huggingface/datasets/issues/1539/events | https://github.com/huggingface/datasets/pull/1539 | 765,338,910 | MDExOlB1bGxSZXF1ZXN0NTM4OTQyMTU4 | 1,539 | Added Wiki Asp dataset | {
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"> Awesome thank you !\r\n> \r\n> I just left one comment.\r\n> \r\n> Also it looks like the dummy_data.zip files are quite big (around 500KB each)\r\n> Can you try to reduce their sizes please ? Ideally they should be <20KB each\r\n> \r\n> To do so feel free to take a look inside them and in the jsonl files only k... | 2020-12-13T12:18:34Z | 2020-12-22T10:16:01Z | 2020-12-22T10:16:01Z | CONTRIBUTOR | null | 0 | {
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I have added Wiki Asp dataset. Please review the PR. | {
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https://api.github.com/repos/huggingface/datasets/issues/1455 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1455/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1455/comments | https://api.github.com/repos/huggingface/datasets/issues/1455/events | https://github.com/huggingface/datasets/pull/1455 | 761,205,073 | MDExOlB1bGxSZXF1ZXN0NTM1OTA1OTQy | 1,455 | Add HEAD-QA: A Healthcare Dataset for Complex Reasoning | {
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"Thank you for your review @lhoestq, I've changed the types of `qid` and `ra` and now they are integers as `aid`.\r\n\r\nReady for another review!"
] | 2020-12-10T12:36:56Z | 2020-12-17T17:03:32Z | 2020-12-17T16:58:11Z | CONTRIBUTOR | null | 0 | {
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} | HEAD-QA is a multi-choice HEAlthcare Dataset, the questions come from exams to access a specialized position in the
Spanish healthcare system. | {
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https://api.github.com/repos/huggingface/datasets/issues/6252 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6252/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6252/comments | https://api.github.com/repos/huggingface/datasets/issues/6252/events | https://github.com/huggingface/datasets/issues/6252 | 1,906,375,378 | I_kwDODunzps5xoPrS | 6,252 | exif_transpose not done to Image (PIL problem) | {
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"Indeed, it makes sense to do this by default. \r\n\r\nIn the meantime, you can use `.with_transform` to transpose the images when accessing them:\r\n\r\n```python\r\nimport PIL.ImageOps\r\n\r\ndef exif_transpose_transform(batch):\r\n batch[\"image\"] = [PIL.ImageOps.exif_transpose(image) for image in batch[\"imag... | 2023-09-21T08:11:46Z | 2023-09-22T14:07:52Z | null | NONE | null | null | null | ### Feature request
I noticed that some of my images loaded using PIL have some metadata related to exif that can rotate them when loading.
Since the dataset.features.Image uses PIL for loading, the loaded image may be rotated (width and height will be inverted) thus for tasks as object detection and layoutLM this can create some inconsistencies (between input bboxes and input images).
For now there is no option in datasets.features.Image to specify that. We need to do the following when preparing examples (when preparing images for training, test or inference):
```
from PIL import Image, ImageOps
pil = ImageOps.exif_transpose(pil)
```
reference: https://stackoverflow.com/a/63950647/5720150
Is it possible to add this by default to the datasets.feature.Image ? or to add the option to do the ImageOps.exif_transpose?
Thank you
### Motivation
Prevent having inverted data related to exif metadata that may affect object detection tasks
### Your contribution
Changing in datasets.featrues.Image I can help with that. | {
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https://api.github.com/repos/huggingface/datasets/issues/4010 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4010/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4010/comments | https://api.github.com/repos/huggingface/datasets/issues/4010/events | https://github.com/huggingface/datasets/pull/4010 | 1,179,848,036 | PR_kwDODunzps409_QV | 4,010 | Fix None issue with Sequence of dict | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Merging since I'd like do do a patch release soon for this one"
] | 2022-03-24T17:58:59Z | 2022-03-28T10:13:53Z | 2022-03-28T10:08:40Z | MEMBER | null | 0 | {
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} | `Features.encode_example` currently fails if it contains a sequence if dict like `Sequence({"subcolumn": Value("int32")})` and if `None` is passed instead of the dict.
```python
File "/Users/quentinlhoest/Desktop/hf/datasets/src/datasets/features/features.py", line 1310, in encode_example
return encode_nested_example(self, example)
File "/Users/quentinlhoest/Desktop/hf/datasets/src/datasets/features/features.py", line 973, in encode_nested_example
return {k: encode_nested_example(sub_schema, sub_obj) for k, (sub_schema, sub_obj) in zip_dict(schema, obj)}
File "/Users/quentinlhoest/Desktop/hf/datasets/src/datasets/features/features.py", line 973, in <dictcomp>
return {k: encode_nested_example(sub_schema, sub_obj) for k, (sub_schema, sub_obj) in zip_dict(schema, obj)}
File "/Users/quentinlhoest/Desktop/hf/datasets/src/datasets/features/features.py", line 998, in encode_nested_example
for k, (sub_schema, sub_objs) in zip_dict(schema.feature, obj):
File "/Users/quentinlhoest/Desktop/hf/datasets/src/datasets/utils/py_utils.py", line 207, in zip_dict
yield key, tuple(d[key] for d in dicts)
File "/Users/quentinlhoest/Desktop/hf/datasets/src/datasets/utils/py_utils.py", line 207, in <genexpr>
yield key, tuple(d[key] for d in dicts)
TypeError: 'NoneType' object is not subscriptable
```
I fixed this issue and updated the tests (this case was missing in the tests) | {
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https://api.github.com/repos/huggingface/datasets/issues/2198 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2198/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2198/comments | https://api.github.com/repos/huggingface/datasets/issues/2198/events | https://github.com/huggingface/datasets/pull/2198 | 854,357,481 | MDExOlB1bGxSZXF1ZXN0NjEyMzE0MTIz | 2,198 | added file_permission in load_dataset | {
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"From offline discussions: we want to make the permissions handling consistent with `transformers`. However from discussion in https://github.com/huggingface/transformers/pull/11119 it looks like it might not be a good solution to provide this argument. Users should use umask for now, and we'll see how things evol... | 2021-04-09T09:39:06Z | 2021-04-16T14:11:46Z | 2021-04-16T14:11:46Z | CONTRIBUTOR | null | 0 | {
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} | As discussed in #2065 I've added `file_permission` argument in `load_dataset`.
Added mainly 2 things here:
1) Permission of downloaded datasets when converted to .arrow files can be changed with argument `file_permission` argument in `load_dataset` (default is 0o644 only)
2) Incase the user uses `map` later on to generate another cache file of dataset, it ensures the permissions of newly generated file are similar to that of` *-train.arrow` file inside cache_dir for that dataset. | {
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https://api.github.com/repos/huggingface/datasets/issues/4148 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4148/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4148/comments | https://api.github.com/repos/huggingface/datasets/issues/4148/events | https://github.com/huggingface/datasets/issues/4148 | 1,201,169,242 | I_kwDODunzps5HmGNa | 4,148 | fix confusing bleu metric example | {
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] | closed | false | null | [] | null | [] | 2022-04-12T06:18:26Z | 2022-04-13T14:16:34Z | 2022-04-13T14:16:34Z | NONE | null | null | null | **Is your feature request related to a problem? Please describe.**
I would like to see the example in "Metric Card for BLEU" changed.
The 0th element in the predictions list is not closed in square brackets, and the 1st list is missing a comma.
The BLEU score are calculated correctly, but it is difficult to understand, so it would be helpful if you could correct this.
```
>> predictions = [
... ["hello", "there", "general", "kenobi", # <- no closing square bracket.
... ["foo", "bar" "foobar"] # <- no comma between "bar" and "foobar"
... ]
>>> references = [
... [["hello", "there", "general", "kenobi"]],
... [["foo", "bar", "foobar"]]
... ]
>>> bleu = datasets.load_metric("bleu")
>>> results = bleu.compute(predictions=predictions, references=references)
>>> print(results)
{'bleu': 0.6370964381207871, ...
```
**Describe the solution you'd like**
```
>> predictions = [
... ["hello", "there", "general", "kenobi", # <- no closing square bracket.
... ["foo", "bar" "foobar"] # <- no comma between "bar" and "foobar"
... ]
# and
>>> print(results)
{'bleu':1.0, ...
```
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https://api.github.com/repos/huggingface/datasets/issues/3551 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3551/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3551/comments | https://api.github.com/repos/huggingface/datasets/issues/3551/events | https://github.com/huggingface/datasets/pull/3551 | 1,096,561,111 | PR_kwDODunzps4wq_AO | 3,551 | Add more compression types for `to_json` | {
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"@lhoestq, I looked into how to compress with `zipfile` for which few methods exist, let me know which one looks good:\r\n1. create the file in normal `wb` mode and then zip it separately\r\n2. use `ZipFile.write_str` to write file into the archive. For this we'll need to change how we're writing files from `_write... | 2022-01-07T18:25:02Z | 2022-07-10T14:36:55Z | 2022-02-21T15:58:15Z | CONTRIBUTOR | null | 0 | {
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} | This PR adds `bz2`, `xz`, and `zip` (WIP) for `to_json`. I also plan to add `infer` like how `pandas` does it | {
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"> Also I was wondering this is really needed to have `utils.metadata` as a submodule of `datasets` ? This is only used by the CI so I'm not sure we should have this in the actual `datasets` package.\r\n\r\nI'm unclear on the suggestion, would you rather have a root-level `./metadata.py` file? I think it's well whe... | 2021-03-24T08:52:41Z | 2021-04-26T08:27:14Z | 2021-04-26T08:27:13Z | CONTRIBUTOR | null | 0 | {
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} | - `pydantic` metadata schema with dedicated validators against our taxonomy
- ci script to validate new changes against this schema and start a vertuous loop
- soft validation on tasks ids since we expect the taxonomy to undergo some changes in the near future
for reference with the current validation we have ~365~ 378 datasets with invalid metadata! full error report [_here_.](https://gist.github.com/theo-m/61b3c0c47fc6121d08d3174bd4c2a26b) | {
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https://api.github.com/repos/huggingface/datasets/issues/1385 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1385/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1385/comments | https://api.github.com/repos/huggingface/datasets/issues/1385/events | https://github.com/huggingface/datasets/pull/1385 | 760,351,405 | MDExOlB1bGxSZXF1ZXN0NTM1MTk3Nzk5 | 1,385 | add best2009 | {
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} | `best2009` is a Thai word-tokenization dataset from encyclopedia, novels, news and articles by [NECTEC](https://www.nectec.or.th/) (148,995/2,252 lines of train/test). It was created for [BEST 2010: Word Tokenization Competition](https://thailang.nectec.or.th/archive/indexa290.html?q=node/10). The test set answers are not provided publicly. | {
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https://api.github.com/repos/huggingface/datasets/issues/5484 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5484/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5484/comments | https://api.github.com/repos/huggingface/datasets/issues/5484/events | https://github.com/huggingface/datasets/pull/5484 | 1,562,877,070 | PR_kwDODunzps5I1oaq | 5,484 | Update docs for `nyu_depth_v2` dataset | {
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"I think I need to create another PR on https://huggingface.co/datasets/huggingface/documentation-images/tree/main/datasets for hosting the images there?",
"_The documentation is not available anymore as the PR was closed or merged._",
"Thanks for the update @awsaf49 !",
"> Thanks a lot for the updates!\r\n> ... | 2023-01-30T17:37:08Z | 2023-09-29T06:43:11Z | 2023-02-05T14:15:04Z | CONTRIBUTOR | null | 0 | {
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} | This PR will fix the issue mentioned in #5461. Here is brief overview,
## Bug:
Discrepancy between depth map of `nyu_depth_v2` dataset [here](https://huggingface.co/docs/datasets/main/en/depth_estimation) and actual depth map. Depth values somehow got **discretized/clipped** resulting in depth maps that are different from actual ones. Here is a side-by-side comparison,
## Fix:
When I first loaded the datasets from HF I noticed it was 30GB but in DenseDepth data is only 4GB with dtype=uint8. This means data from fast-depth (before loading to HF) must have high precision. So when I tried to dig deeper by directly loading depth_map from `h5py`, I found depth_map from `h5py` came with `float32`. But when the data is processed in HF with `datasets.Image()` it was directly converted to `uint8` from `float32` hence the **discretized** depth map.
https://github.com/huggingface/datasets/blob/c78559cacbb0ca6e0bc8bfc313cc0359f8c23ead/src/datasets/features/image.py#L91-L93
cc: @sayakpaul @lhoestq
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https://api.github.com/repos/huggingface/datasets/issues/5393 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5393/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5393/comments | https://api.github.com/repos/huggingface/datasets/issues/5393/events | https://github.com/huggingface/datasets/pull/5393 | 1,512,908,613 | PR_kwDODunzps5GTg0a | 5,393 | Finish deprecating the fs argument | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"> Thanks for the deprecation. Some minor suggested fixes below...\r\n> \r\n> Also note that the corresponding tests should be updated as well.\r\n\r\nThanks for the suggestions/typo fixes. I updated the failing test - passing locall... | 2022-12-28T15:33:17Z | 2023-01-18T12:42:33Z | 2023-01-18T12:35:32Z | CONTRIBUTOR | null | 0 | {
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} | See #5385 for some discussion on this
The `fs=` arg was depcrecated from `Dataset.save_to_disk` and `Dataset.load_from_disk` in `2.8.0` (to be removed in `3.0.0`). There are a few other places where the `fs=` arg was still used (functions/methods in `datasets.info` and `datasets.load`). This PR adds a similar behavior, warnings and the `storage_options=` arg to these functions and methods.
One question: should the "deprecated" / "added" versions be `2.8.1` for the docs/warnings on these? Right now I'm going with "fs was deprecated in 2.8.0" but "storage_options= was added in 2.8.1" where appropriate.
@mariosasko | {
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https://api.github.com/repos/huggingface/datasets/issues/1372 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1372/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1372/comments | https://api.github.com/repos/huggingface/datasets/issues/1372/events | https://github.com/huggingface/datasets/pull/1372 | 760,274,046 | MDExOlB1bGxSZXF1ZXN0NTM1MTMzMzQ4 | 1,372 | Add OPUS Books Dataset | {
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"@lhoestq done"
] | 2020-12-09T12:08:49Z | 2020-12-14T09:56:28Z | 2020-12-14T09:56:27Z | MEMBER | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/2325 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2325/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2325/comments | https://api.github.com/repos/huggingface/datasets/issues/2325/events | https://github.com/huggingface/datasets/pull/2325 | 876,653,121 | MDExOlB1bGxSZXF1ZXN0NjMwNzU1MzIx | 2,325 | Added the HLGD dataset | {
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"Is there anything else needed from my end?",
"Thanks Bhavitvya and Quentin, this was very streamlined!"
] | 2021-05-05T16:53:29Z | 2021-05-12T14:55:13Z | 2021-05-12T14:16:38Z | CONTRIBUTOR | null | 0 | {
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} | Added the Headline Grouping Dataset (HLGD), from the NAACL2021 paper: News Headline Grouping as a Challenging NLU Task
Dataset Link: https://github.com/tingofurro/headline_grouping
Paper link: https://people.eecs.berkeley.edu/~phillab/pdfs/NAACL2021_HLG.pdf | {
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https://api.github.com/repos/huggingface/datasets/issues/4113 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4113/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4113/comments | https://api.github.com/repos/huggingface/datasets/issues/4113/events | https://github.com/huggingface/datasets/issues/4113 | 1,194,843,532 | I_kwDODunzps5HN92M | 4,113 | Multiprocessing with FileLock fails in python 3.9 | {
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"Closing this one because it must be used this way actually:\r\n```python\r\ndef main():\r\n with FileLock(\"tmp.lock\"):\r\n with Pool(2) as pool:\r\n pool.map(run, range(2))\r\n\r\nif __name__ == \"__main__\":\r\n main()\r\n```"
] | 2022-04-06T16:27:09Z | 2022-11-28T11:49:14Z | 2022-11-28T11:49:14Z | MEMBER | null | null | null | On python 3.9, this code hangs:
```python
from multiprocessing import Pool
from filelock import FileLock
def run(i):
print(f"got the lock in multi process [{i}]")
with FileLock("tmp.lock"):
with Pool(2) as pool:
pool.map(run, range(2))
```
This is because the subprocesses try to acquire the lock from the main process for some reason. This is not the case in older versions of python.
This can cause many issues in python 3.9. In particular, we use multiprocessing to fetch data files when you load a dataset (as long as there are >16 data files). Therefore `imagefolder` hangs, and I expect any dataset that needs to download >16 files to hang as well.
Let's see if we can fix this and have a CI that runs on 3.9.
cc @mariosasko @julien-c | {
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https://api.github.com/repos/huggingface/datasets/issues/1659 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1659/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1659/comments | https://api.github.com/repos/huggingface/datasets/issues/1659/events | https://github.com/huggingface/datasets/pull/1659 | 775,831,288 | MDExOlB1bGxSZXF1ZXN0NTQ2NDM1OTcy | 1,659 | update dataset info | {
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https://api.github.com/repos/huggingface/datasets/issues/5740 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5740/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5740/comments | https://api.github.com/repos/huggingface/datasets/issues/5740/events | https://github.com/huggingface/datasets/pull/5740 | 1,664,132,130 | PR_kwDODunzps5OHI08 | 5,740 | Fix CI mock filesystem fixtures | {
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"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_a... | 2023-04-12T08:52:35Z | 2023-04-13T11:01:24Z | 2023-04-13T10:54:13Z | MEMBER | null | 0 | {
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} | This PR fixes the fixtures of our CI mock filesystems.
Before, we had to pass `clobber=True` to `fsspec.register_implementation` to overwrite the still present previously added "mock" filesystem. That meant that the mock filesystem fixture was not working properly, because the previously added "mock" filesystem, should have been deleted by the fixture.
This PR fixes the mock filesystem fixtures, so that the "mock" filesystem is properly deleted from the inner `fsspec` registry.
Tests were added to check the correct behavior of the mock filesystem fixtures.
Related to:
- #5733 | {
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https://api.github.com/repos/huggingface/datasets/issues/1756 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1756/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1756/comments | https://api.github.com/repos/huggingface/datasets/issues/1756/events | https://github.com/huggingface/datasets/issues/1756 | 790,380,028 | MDU6SXNzdWU3OTAzODAwMjg= | 1,756 | Ccaligned multilingual translation dataset | {
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] | closed | false | null | [] | null | [] | 2021-01-20T22:18:44Z | 2021-03-01T10:36:21Z | 2021-03-01T10:36:21Z | CONTRIBUTOR | null | null | null | ## Adding a Dataset
- **Name:** *name of the dataset*
- **Description:** *short description of the dataset (or link to social media or blog post)*
- CCAligned consists of parallel or comparable web-document pairs in 137 languages aligned with English. These web-document pairs were constructed by performing language identification on raw web-documents, and ensuring corresponding language codes were corresponding in the URLs of web documents. This pattern matching approach yielded more than 100 million aligned documents paired with English. Recognizing that each English document was often aligned to mulitple documents in different target language, we can join on English documents to obtain aligned documents that directly pair two non-English documents (e.g., Arabic-French).
- **Paper:** *link to the dataset paper if available*
- https://www.aclweb.org/anthology/2020.emnlp-main.480.pdf
- **Data:** *link to the Github repository or current dataset location*
- http://www.statmt.org/cc-aligned/
- **Motivation:** *what are some good reasons to have this dataset*
- The authors says it's an high quality dataset.
- it's pretty large and includes many language pairs. It could be interesting training mt5 on this task.
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
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https://api.github.com/repos/huggingface/datasets/issues/5416 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5416/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5416/comments | https://api.github.com/repos/huggingface/datasets/issues/5416/events | https://github.com/huggingface/datasets/pull/5416 | 1,526,988,113 | PR_kwDODunzps5HDLmR | 5,416 | Fix RuntimeError: Sharding is ambiguous for this dataset | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"By the way, do we know how many datasets are impacted by this issue?\r\n\r\nMaybe we should do a patch release with this fix.",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==6.0.0\n\n<details>\n<summary>Show updated be... | 2023-01-10T08:43:19Z | 2023-01-18T17:12:17Z | 2023-01-18T14:09:02Z | MEMBER | null | 0 | {
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} | This PR fixes the RuntimeError: Sharding is ambiguous for this dataset.
The error for ambiguous sharding will be raised only if num_proc > 1.
Fix #5415, fix #5414.
Fix https://huggingface.co/datasets/ami/discussions/3. | {
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"Hi @lhoestq \r\n\r\nThanks for approving. Request you to close PR #1435 as well."
] | 2021-02-03T16:57:49Z | 2021-02-04T19:47:51Z | 2021-02-04T16:21:48Z | CONTRIBUTOR | null | 0 | {
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Requesting @lhoestq to review. | {
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https://api.github.com/repos/huggingface/datasets/issues/1661 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1661/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1661/comments | https://api.github.com/repos/huggingface/datasets/issues/1661/events | https://github.com/huggingface/datasets/pull/1661 | 775,840,801 | MDExOlB1bGxSZXF1ZXN0NTQ2NDQzNjYx | 1,661 | updated dataset cards | {
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https://api.github.com/repos/huggingface/datasets/issues/1977 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1977/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1977/comments | https://api.github.com/repos/huggingface/datasets/issues/1977/events | https://github.com/huggingface/datasets/issues/1977 | 820,312,022 | MDU6SXNzdWU4MjAzMTIwMjI= | 1,977 | ModuleNotFoundError: No module named 'apache_beam' for wikipedia datasets | {
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"I sometimes also get this error with other languages of the same dataset:\r\n\r\n File \"/dara/libs/anaconda3/envs/code/lib/python3.7/site-packages/datasets-1.3.0-py3.7.egg/datasets/arrow_reader.py\", line 322, in read_table\r\n stream = stream_from(filename)\r\n File \"pyarrow/io.pxi\", line 782, in pyarrow.... | 2021-03-02T19:21:28Z | 2021-03-03T10:17:40Z | null | NONE | null | null | null | Hi
I am trying to run run_mlm.py code [1] of huggingface with following "wikipedia"/ "20200501.aa" dataset:
`python run_mlm.py --model_name_or_path bert-base-multilingual-cased --dataset_name wikipedia --dataset_config_name 20200501.aa --do_train --do_eval --output_dir /tmp/test-mlm --max_seq_length 256
`
I am getting this error, but as per documentation, huggingface dataset provide processed version of this dataset and users can load it without requiring setup extra settings for apache-beam. could you help me please to load this dataset?
Do you think I can run run_ml.py with this dataset? or anyway I could subsample and train the model? I greatly appreciate providing the processed version of all languages for this dataset, which allow the user to use them without setting up apache-beam,. thanks
I really appreciate your help.
@lhoestq
thanks.
[1] https://github.com/huggingface/transformers/blob/master/examples/language-modeling/run_mlm.py
error I get:
```
>>> import datasets
>>> datasets.load_dataset("wikipedia", "20200501.aa")
Downloading and preparing dataset wikipedia/20200501.aa (download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size) to /dara/temp/cache_home_2/datasets/wikipedia/20200501.aa/1.0.0/4021357e28509391eab2f8300d9b689e7e8f3a877ebb3d354b01577d497ebc63...
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/dara/temp/libs/anaconda3/envs/codes/lib/python3.7/site-packages/datasets-1.3.0-py3.7.egg/datasets/load.py", line 746, in load_dataset
use_auth_token=use_auth_token,
File "/dara/temp/libs/anaconda3/envs/codes/lib/python3.7/site-packages/datasets-1.3.0-py3.7.egg/datasets/builder.py", line 573, in download_and_prepare
dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
File "/dara/temp/libs/anaconda3/envs/codes/lib/python3.7/site-packages/datasets-1.3.0-py3.7.egg/datasets/builder.py", line 1099, in _download_and_prepare
import apache_beam as beam
ModuleNotFoundError: No module named 'apache_beam'
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/5052 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5052/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5052/comments | https://api.github.com/repos/huggingface/datasets/issues/5052/events | https://github.com/huggingface/datasets/pull/5052 | 1,393,076,765 | PR_kwDODunzps4_-PZw | 5,052 | added from_generator method to IterableDataset class. | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"I added a test and moved the `streaming` param from `read` to `__init_`. Then, I also decided to update the `read` method of the rest of the packaged modules to account for this param. \r\n\r\n@hamid-vakilzadeh Are you OK with these ... | 2022-09-30T22:14:05Z | 2022-10-05T12:51:48Z | 2022-10-05T12:10:48Z | CONTRIBUTOR | null | 0 | {
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} | Hello,
This resolves issues #4988.
I added a method `from_generator` to class `IterableDataset`.
I modified the `read` method of input stream generator to also return Iterable_dataset.
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https://api.github.com/repos/huggingface/datasets/issues/3270 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3270/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3270/comments | https://api.github.com/repos/huggingface/datasets/issues/3270/events | https://github.com/huggingface/datasets/pull/3270 | 1,053,465,662 | PR_kwDODunzps4uhcxm | 3,270 | Add os.listdir for streaming | {
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https://api.github.com/repos/huggingface/datasets/issues/2868 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2868/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2868/comments | https://api.github.com/repos/huggingface/datasets/issues/2868/events | https://github.com/huggingface/datasets/issues/2868 | 987,139,146 | MDU6SXNzdWU5ODcxMzkxNDY= | 2,868 | Add Common Objects in 3D (CO3D) | {
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"color": "bfdadc",... | open | false | null | [] | null | [] | 2021-09-02T20:36:12Z | 2021-12-08T12:02:10Z | null | CONTRIBUTOR | null | null | null | ## Adding a Dataset
- **Name:** *Common Objects in 3D (CO3D)*
- **Description:** *See blog post [here](https://ai.facebook.com/blog/common-objects-in-3d-dataset-for-3d-reconstruction)*
- **Paper:** *[link to paper](https://arxiv.org/abs/2109.00512)*
- **Data:** *[link to data](https://ai.facebook.com/datasets/co3d-downloads/)*
- **Motivation:** *excerpt from above blog post:*
> As the first data set of its kind, CO3D will aptly enable reconstruction of real-life 3D objects. Indeed, CO3D already provides training data to enable our NeRFormer to tackle the new-view synthesis (NVS) task. Here, photorealistic NVS is a major step on the path to fully immersive AR/VR effects, where objects can be virtually transported across different environments, which will allow connecting users by sharing or recollecting their experiences.
>
> Besides practical applications in AR/VR, we hope that the data set will become a standard testbed for the recent proliferation of methods (including NeRFormer, Implicit Differentiable Renderer, NeRF, and others) that reconstruct 3D scenes by means of an implicit shape model.
>
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
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- **Name:** *name of the dataset*
- **Description:** *short description of the dataset (or link to social media or blog post)*
- **Paper:** *link to the dataset paper if available*
- **Data:** *link to the Github repository or current dataset location*
- **Motivation:** *what are some good reasons to have this dataset*
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md). | {
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https://api.github.com/repos/huggingface/datasets/issues/2874 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2874/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2874/comments | https://api.github.com/repos/huggingface/datasets/issues/2874/events | https://github.com/huggingface/datasets/pull/2874 | 989,685,328 | MDExOlB1bGxSZXF1ZXN0NzI4Mzg2Mjg4 | 2,874 | Support streaming datasets that use pathlib | {
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"I've tried https://github.com/huggingface/datasets/issues/2866 again, and I get the same error.\r\n\r\n```python\r\nimport datasets as ds\r\nds.load_dataset('counter', split=\"train\", streaming=False)\r\n```",
"@severo Issue #2866 is not fully fixed yet: multiple patches need to be implemented for `pathlib`, as... | 2021-09-07T07:35:49Z | 2021-09-07T18:25:22Z | 2021-09-07T11:41:15Z | MEMBER | null | 0 | {
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} | This PR extends the support in streaming mode for datasets that use `pathlib.Path`.
Related to: #2866.
CC: @severo | {
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https://api.github.com/repos/huggingface/datasets/issues/5669 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5669/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5669/comments | https://api.github.com/repos/huggingface/datasets/issues/5669/events | https://github.com/huggingface/datasets/issues/5669 | 1,638,070,046 | I_kwDODunzps5hovce | 5,669 | Almost identical datasets, huge performance difference | {
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"Do I miss something here?",
"Hi! \r\n\r\nThe first dataset stores images as bytes (the \"image\" column type is `datasets.Image()`) and decodes them as `PIL.Image` objects and the second dataset stores them as variable-length lists (the \"image\" column type is `datasets.Sequence(...)`)), so I guess going from `... | 2023-03-23T18:20:20Z | 2023-04-09T18:56:23Z | null | CONTRIBUTOR | null | null | null | ### Describe the bug
I am struggling to understand (huge) performance difference between two datasets that are almost identical.
### Steps to reproduce the bug
# Fast (normal) dataset speed:
```python
import cv2
from datasets import load_dataset
from torch.utils.data import DataLoader
dataset = load_dataset("beans", split="train")
for x in DataLoader(dataset.with_format("torch"), batch_size=16, shuffle=True, num_workers=8):
pass
```
The above pass over the dataset takes about 1.5 seconds on my computer.
However, if I re-create (almost) the same dataset, the sweep takes HUGE amount of time: 15 minutes. Steps to reproduce:
```python
def transform(example):
example["image2"] = cv2.imread(example["image_file_path"])
return example
dataset2 = dataset.map(transform, remove_columns=["image"])
for x in DataLoader(dataset2.with_format("torch"), batch_size=16, shuffle=True, num_workers=8):
pass
```
### Expected behavior
Same timings
### Environment info
python==3.10.9
datasets==2.10.1 | {
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https://api.github.com/repos/huggingface/datasets/issues/1367 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1367/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1367/comments | https://api.github.com/repos/huggingface/datasets/issues/1367/events | https://github.com/huggingface/datasets/pull/1367 | 760,208,191 | MDExOlB1bGxSZXF1ZXN0NTM1MDc4MTAx | 1,367 | adding covid-tweets-japanese | {
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"I think it's because the file you download uncompresses into a file and not a folder so `--autogenerate` couldn't create dummy data for you. See in your dummy_data.zip if there is a file there. If not, manually create your dummy data and compress them to dummy_data.zip.",
"@cstorm125 Thank you for the comment! \... | 2020-12-09T10:34:01Z | 2020-12-09T17:25:14Z | 2020-12-09T17:25:14Z | CONTRIBUTOR | null | 0 | {
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} | Adding COVID-19 Japanese Tweets Dataset as part of the sprint.
Testing with dummy data is not working (the file is said to not exist). Sorry for the incomplete PR. | {
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https://api.github.com/repos/huggingface/datasets/issues/1286 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1286/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1286/comments | https://api.github.com/repos/huggingface/datasets/issues/1286/events | https://github.com/huggingface/datasets/issues/1286 | 759,291,509 | MDU6SXNzdWU3NTkyOTE1MDk= | 1,286 | [libprotobuf FATAL /sentencepiece/src/../third_party/protobuf-lite/google/protobuf/repeated_field.h:1505] CHECK failed: (index) >= (0): terminate called after throwing an instance of 'google::protobuf::FatalException' what(): CHECK failed: (index) >= (0): Aborted | {
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"I remember also getting the same issue for several other translation datasets like all the iwslt2017 group, this is blokcing me and I really need to fix it and I was wondering if you have an idea on this. @lhoestq thanks,. ",
"maybe there is an empty line or something inside these datasets? could you tell me wh... | 2020-12-08T09:44:15Z | 2020-12-12T19:36:22Z | 2020-12-12T16:22:36Z | CONTRIBUTOR | null | null | null | Hi
I am getting this error when evaluating on wmt16-ro-en using finetune_trainer.py of huggingface repo. thank for your help
{'epoch': 20.0}
100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 20/20 [00:16<00:00, 1.22it/s]
12/08/2020 10:41:19 - INFO - seq2seq.trainers.trainer - Saving model checkpoint to outputs/experiment/joint/finetune/lr-2e-5
12/08/2020 10:41:24 - INFO - __main__ - {'wmt16-en-ro': Dataset(features: {'src_texts': Value(dtype='string', id=None), 'task': Value(dtype='string', id=None), 'tgt_texts': Value(dtype='string', id=None)}, num_rows: 1998), 'qnli': Dataset(features: {'src_texts': Value(dtype='string', id=None), 'task': Value(dtype='string', id=None), 'tgt_texts': Value(dtype='string', id=None)}, num_rows: 5462), 'scitail': Dataset(features: {'src_texts': Value(dtype='string', id=None), 'task': Value(dtype='string', id=None), 'tgt_texts': Value(dtype='string', id=None)}, num_rows: 1303)}
12/08/2020 10:41:24 - INFO - __main__ - *** Evaluate ***
12/08/2020 10:41:24 - INFO - seq2seq.utils.utils - using task specific params for wmt16-en-ro: {'max_length': 300, 'num_beams': 4}
12/08/2020 10:41:24 - INFO - seq2seq.trainers.trainer - ***** Running Evaluation *****
12/08/2020 10:41:24 - INFO - seq2seq.trainers.trainer - Num examples = 1998
12/08/2020 10:41:24 - INFO - seq2seq.trainers.trainer - Batch size = 64
100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 32/32 [00:37<00:00, 1.19s/it][libprotobuf FATAL /sentencepiece/src/../third_party/protobuf-lite/google/protobuf/repeated_field.h:1505] CHECK failed: (index) >= (0):
terminate called after throwing an instance of 'google::protobuf::FatalException'
what(): CHECK failed: (index) >= (0):
Aborted
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https://api.github.com/repos/huggingface/datasets/issues/2517 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2517/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2517/comments | https://api.github.com/repos/huggingface/datasets/issues/2517/events | https://github.com/huggingface/datasets/pull/2517 | 924,643,345 | MDExOlB1bGxSZXF1ZXN0NjczMjUwODk1 | 2,517 | Fix typo in MatthewsCorrelation class name | {
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https://api.github.com/repos/huggingface/datasets/issues/3012 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3012/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3012/comments | https://api.github.com/repos/huggingface/datasets/issues/3012/events | https://github.com/huggingface/datasets/pull/3012 | 1,014,958,931 | PR_kwDODunzps4soRTu | 3,012 | Replace item with float in metrics | {
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} | As pointed out by @mariosasko in #3001, calling `float()` instad of `.item()` is faster.
Moreover, it might avoid potential issues if any of the third-party functions eventually returns a `float` instead of an `np.float64`.
Related to #3001. | {
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https://api.github.com/repos/huggingface/datasets/issues/2789 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2789/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2789/comments | https://api.github.com/repos/huggingface/datasets/issues/2789/events | https://github.com/huggingface/datasets/pull/2789 | 967,361,934 | MDExOlB1bGxSZXF1ZXN0NzA5NTQwMzY5 | 2,789 | Updated dataset description of DaNE | {
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"Thanks for finishing it @albertvillanova "
] | 2021-08-11T19:58:48Z | 2021-08-12T16:10:59Z | 2021-08-12T16:06:01Z | CONTRIBUTOR | null | 0 | {
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"@SBrandeis thanks for the review, I applied your suggested changes, but CI is failing now not sure about the error.",
"Many thanks @Nilanshrajput !\r\nThe failing tests on CI are not related to your changes, merging master on your branch should fix them :)\r\nIf you're interested in what causes the CI to fail,... | 2020-12-12T13:46:48Z | 2020-12-17T15:34:50Z | 2020-12-17T15:34:50Z | CONTRIBUTOR | null | 0 | {
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} | Added nq_open Open-domain question answering dataset.
The NQ-Open task is currently being used to evaluate submissions to the EfficientQA competition, which is part of the NeurIPS 2020 competition track. | {
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https://api.github.com/repos/huggingface/datasets/issues/1636 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1636/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1636/comments | https://api.github.com/repos/huggingface/datasets/issues/1636/events | https://github.com/huggingface/datasets/issues/1636 | 774,574,378 | MDU6SXNzdWU3NzQ1NzQzNzg= | 1,636 | winogrande cannot be dowloaded | {
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"I have same issue for other datasets (`myanmar_news` in my case).\r\n\r\nA version of `datasets` runs correctly on my local machine (**without GPU**) which looking for the dataset at \r\n```\r\nhttps://raw.githubusercontent.com/huggingface/datasets/master/datasets/myanmar_news/myanmar_news.py\r\n```\r\n\r\nMeanwhi... | 2020-12-24T22:28:22Z | 2022-10-05T12:35:44Z | 2022-10-05T12:35:44Z | NONE | null | null | null | Hi,
I am getting this error when trying to run the codes on the cloud. Thank you for any suggestion and help on this @lhoestq
```
File "./finetune_trainer.py", line 318, in <module>
main()
File "./finetune_trainer.py", line 148, in main
for task in data_args.tasks]
File "./finetune_trainer.py", line 148, in <listcomp>
for task in data_args.tasks]
File "/workdir/seq2seq/data/tasks.py", line 65, in get_dataset
dataset = self.load_dataset(split=split)
File "/workdir/seq2seq/data/tasks.py", line 466, in load_dataset
return datasets.load_dataset('winogrande', 'winogrande_l', split=split)
File "/usr/local/lib/python3.6/dist-packages/datasets/load.py", line 589, in load_dataset
path, script_version=script_version, download_config=download_config, download_mode=download_mode, dataset=True
File "/usr/local/lib/python3.6/dist-packages/datasets/load.py", line 267, in prepare_module
local_path = cached_path(file_path, download_config=download_config)
File "/usr/local/lib/python3.6/dist-packages/datasets/utils/file_utils.py", line 308, in cached_path
use_etag=download_config.use_etag,
File "/usr/local/lib/python3.6/dist-packages/datasets/utils/file_utils.py", line 487, in get_from_cache
raise ConnectionError("Couldn't reach {}".format(url))
ConnectionError: Couldn't reach https://raw.githubusercontent.com/huggingface/datasets/1.1.3/datasets/winogrande/winogrande.py
yo/0 I1224 14:17:46.419031 31226 main shadow.py:122 > Traceback (most recent call last):
File "/usr/lib/python3.6/runpy.py", line 193, in _run_module_as_main
"__main__", mod_spec)
File "/usr/lib/python3.6/runpy.py", line 85, in _run_code
exec(code, run_globals)
File "/usr/local/lib/python3.6/dist-packages/torch/distributed/launch.py", line 260, in <module>
main()
File "/usr/local/lib/python3.6/dist-packages/torch/distributed/launch.py", line 256, in main
cmd=cmd)
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/2670 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2670/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2670/comments | https://api.github.com/repos/huggingface/datasets/issues/2670/events | https://github.com/huggingface/datasets/issues/2670 | 947,120,709 | MDU6SXNzdWU5NDcxMjA3MDk= | 2,670 | Using sharding to parallelize indexing | {
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] | open | false | null | [] | null | [] | 2021-07-18T21:26:26Z | 2021-10-07T13:33:25Z | null | CONTRIBUTOR | null | null | null | **Is your feature request related to a problem? Please describe.**
Creating an elasticsearch index on large dataset could be quite long and cannot be parallelized on shard (the index creation is colliding)
**Describe the solution you'd like**
When working on dataset shards, if an index already exists, its mapping should be checked and if compatible, the indexing process should continue with the shard data.
Additionally, at the end of the process, the `_indexes` dict should be send back to the original dataset object (from which the shards have been created) to allow to use the index for later filtering on the whole dataset.
**Describe alternatives you've considered**
Each dataset shard could created independent partial indices. then on the whole dataset level, indices should be all referred in `_indexes` dict and be used in querying through `get_nearest_examples()`. The drawback is that the scores will be computed independently on the partial indices leading to inconsistent values for most scoring based on corpus level statistics (tf/idf, BM25).
**Additional context**
The objectives is to parallelize the index creation to speed-up the process (ie surcharging the ES server which is fine to handle large load) while later enabling search on the whole dataset. | {
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https://api.github.com/repos/huggingface/datasets/issues/4269 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4269/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4269/comments | https://api.github.com/repos/huggingface/datasets/issues/4269/events | https://github.com/huggingface/datasets/pull/4269 | 1,223,865,145 | PR_kwDODunzps43Nzwh | 4,269 | Add license and point of contact to big_patent dataset | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-05-03T09:24:07Z | 2022-05-06T08:38:09Z | 2022-05-03T11:16:19Z | MEMBER | null | 0 | {
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- license
- point of contact | {
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https://api.github.com/repos/huggingface/datasets/issues/4053 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4053/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4053/comments | https://api.github.com/repos/huggingface/datasets/issues/4053/events | https://github.com/huggingface/datasets/issues/4053 | 1,184,500,378 | I_kwDODunzps5Gmgqa | 4,053 | Modify datatype from `int32` to `float` for pearsonr, spearmanr. | {
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"@Woodywarhol9 good catch, thanks for reporting.\r\n\r\nWe are fixing this."
] | 2022-03-29T08:27:41Z | 2022-03-29T14:02:20Z | 2022-03-29T14:02:20Z | NONE | null | null | null | **Is your feature request related to a problem? Please describe.**
- Now [Pearsonr](https://github.com/huggingface/datasets/blob/master/metrics/pearsonr/pearsonr.py) and [Spearmanr](https://github.com/huggingface/datasets/blob/master/metrics/spearmanr/spearmanr.py) both get input data as 'int32'.
**Describe the solution you'd like**
- Considering that those metrics are widely used for the STS task(labels are in 'float' data type),
it would be better to modify datatype from 'int32' to 'float' for getting exact values of similarity. | {
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https://api.github.com/repos/huggingface/datasets/issues/5587 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5587/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5587/comments | https://api.github.com/repos/huggingface/datasets/issues/5587/events | https://github.com/huggingface/datasets/pull/5587 | 1,603,139,420 | PR_kwDODunzps5K70pp | 5,587 | Fix `sort` with indices mapping | {
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"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==6.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_a... | 2023-02-28T14:05:08Z | 2023-02-28T17:28:57Z | 2023-02-28T17:21:58Z | CONTRIBUTOR | null | 0 | {
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} | Fixes the `key` range in the `query_table` call in `sort` to account for an indices mapping
Fix #5586 | {
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https://api.github.com/repos/huggingface/datasets/issues/5671 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5671/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5671/comments | https://api.github.com/repos/huggingface/datasets/issues/5671/events | https://github.com/huggingface/datasets/issues/5671 | 1,640,840,012 | I_kwDODunzps5hzTtM | 5,671 | How to use `load_dataset('glue', 'cola')` | {
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"Sounds like an issue with incompatible `transformers` dependencies versions.\r\n\r\nCan you try to update `transformers` ?\r\n\r\nEDIT: I checked the `transformers` dependencies and it seems like you need `tokenizers>=0.10.1,<0.11` with `transformers==4.5.1`\r\n\r\nEDIT2: this old version of `datasets` seems to im... | 2023-03-26T09:40:34Z | 2023-03-28T07:43:44Z | 2023-03-28T07:43:43Z | NONE | null | null | null | ### Describe the bug
I'm new to use HuggingFace datasets but I cannot use `load_dataset('glue', 'cola')`.
- I was stacked by the following problem:
```python
from datasets import load_dataset
cola_dataset = load_dataset('glue', 'cola')
---------------------------------------------------------------------------
InvalidVersion Traceback (most recent call last)
File <timed exec>:1
(Omit because of long error message)
File /usr/local/lib/python3.8/site-packages/packaging/version.py:197, in Version.__init__(self, version)
195 match = self._regex.search(version)
196 if not match:
--> 197 raise InvalidVersion(f"Invalid version: '{version}'")
199 # Store the parsed out pieces of the version
200 self._version = _Version(
201 epoch=int(match.group("epoch")) if match.group("epoch") else 0,
202 release=tuple(int(i) for i in match.group("release").split(".")),
(...)
208 local=_parse_local_version(match.group("local")),
209 )
InvalidVersion: Invalid version: '0.10.1,<0.11'
```
- You can check this full error message in my repository: [MLOps-Basics/week_0_project_setup/experimental_notebooks/data_exploration.ipynb](https://github.com/makinzm/MLOps-Basics/blob/eabab4b837880607d9968d3fa687c70177b2affd/week_0_project_setup/experimental_notebooks/data_exploration.ipynb)
### Steps to reproduce the bug
- This is my repository to reproduce: [MLOps-Basics/week_0_project_setup](https://github.com/makinzm/MLOps-Basics/tree/eabab4b837880607d9968d3fa687c70177b2affd/week_0_project_setup)
1. cd `/DockerImage` and command `docker build . -t week0`
2. cd `/` and command `docker-compose up`
3. Run `experimental_notebooks/data_exploration.ipynb`
----
Just to be sure, I wrote down Dockerfile and requirements.txt
- Dockerfile
```Dockerfile
FROM python:3.8
WORKDIR /root/working
RUN apt-get update && \
apt-get install -y python3-dev python3-pip python3-venv && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
COPY requirements.txt .
RUN pip3 install --no-cache-dir jupyter notebook && pip install --no-cache-dir -r requirements.txt
CMD ["bash"]
```
- requirements.txt
```txt
pytorch-lightning==1.2.10
datasets==1.6.2
transformers==4.5.1
scikit-learn==0.24.2
```
### Expected behavior
There is no bug to implement `load_dataset('glue', 'cola')`
### Environment info
I already wrote it. | {
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https://api.github.com/repos/huggingface/datasets/issues/4900 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4900/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4900/comments | https://api.github.com/repos/huggingface/datasets/issues/4900/events | https://github.com/huggingface/datasets/issues/4900 | 1,352,405,855 | I_kwDODunzps5QnBNf | 4,900 | Dataset Viewer issue for asaxena1990/Dummy_dataset | {
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"Seems to be linked to the use of the undocumented `_resolve_features` method in the dataset viewer backend:\r\n\r\n```\r\n>>> from datasets import load_dataset\r\n>>> dataset = load_dataset(\"asaxena1990/Dummy_dataset\", name=\"asaxena1990--Dummy_dataset\", split=\"train\", streaming=True)\r\nUsing custom data con... | 2022-08-26T15:15:44Z | 2023-07-24T15:42:09Z | 2023-07-24T15:42:09Z | NONE | null | null | null | ### Link
_No response_
### Description
_No response_
### Owner
_No response_ | {
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https://api.github.com/repos/huggingface/datasets/issues/6105 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6105/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6105/comments | https://api.github.com/repos/huggingface/datasets/issues/6105/events | https://github.com/huggingface/datasets/pull/6105 | 1,829,008,430 | PR_kwDODunzps5WyiJD | 6,105 | Fix error when loading from GCP bucket | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2023-07-31T11:44:46Z | 2023-08-01T10:48:52Z | 2023-08-01T10:38:54Z | MEMBER | null | 0 | {
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} | Fix `resolve_pattern` for filesystems with tuple protocol.
Fix #6100.
The bug code lines were introduced by:
- #6028 | {
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https://api.github.com/repos/huggingface/datasets/issues/3543 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3543/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3543/comments | https://api.github.com/repos/huggingface/datasets/issues/3543/events | https://github.com/huggingface/datasets/issues/3543 | 1,095,226,438 | I_kwDODunzps5BR9RG | 3,543 | Allow loading community metrics from the hub, just like datasets | {
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"Hi ! Thanks for your message :) This is a great idea indeed. We haven't started working on this yet though. For now I guess you can host your metric on the Hub (either with your model or your dataset) and use `hf_hub_download` to download it (docs [here](https://github.com/huggingface/huggingface_hub/blob/main/doc... | 2022-01-06T11:26:26Z | 2022-05-31T20:59:14Z | 2022-05-31T20:53:37Z | CONTRIBUTOR | null | null | null | **Is your feature request related to a problem? Please describe.**
Currently, I can load a metric implemented by me by providing the local path to the file in `load_metric`.
However, there is no option to do it with the metric uploaded to the hub.
This means that if I want to allow other users to use it, they must download it first which makes the usage less smooth.
**Describe the solution you'd like**
Load metrics from the hub just like datasets are loaded.
In order to not break stuff, the convention can be to put the metric file in a "metrics" folder in the hub.
| {
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https://api.github.com/repos/huggingface/datasets/issues/2495 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2495/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2495/comments | https://api.github.com/repos/huggingface/datasets/issues/2495/events | https://github.com/huggingface/datasets/issues/2495 | 920,170,030 | MDU6SXNzdWU5MjAxNzAwMzA= | 2,495 | JAX formatting | {
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"gists... | null | [] | 2021-06-14T08:32:07Z | 2021-06-21T16:15:49Z | 2021-06-21T16:15:49Z | MEMBER | null | null | null | We already support pytorch, tensorflow, numpy, pandas and arrow dataset formatting. Let's add jax as well | {
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https://api.github.com/repos/huggingface/datasets/issues/4612 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4612/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4612/comments | https://api.github.com/repos/huggingface/datasets/issues/4612/events | https://github.com/huggingface/datasets/issues/4612 | 1,290,984,660 | I_kwDODunzps5M8tzU | 4,612 | Release 2.3.0 broke custom iterable datasets | {
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"Apparently, `fsspec` does not allow access to attribute-based modules anymore, such as `fsspec.async`.\r\n\r\nHowever, this is a fairly simple fix:\r\n- Change the import to: `from fsspec import asyn`;\r\n- Change line 18 to: `asyn.iothread[0] = None`;\r\n- Change line 19 to `asyn.loop[0] = None`.",
"Hi! I think... | 2022-07-01T06:46:07Z | 2022-07-05T15:08:21Z | 2022-07-05T15:08:21Z | NONE | null | null | null | ## Describe the bug
Trying to iterate examples from custom iterable dataset fails to bug introduced in `torch_iterable_dataset.py` since the release of 2.3.0.
## Steps to reproduce the bug
```python
next(iter(custom_iterable_dataset))
```
## Expected results
`next(iter(custom_iterable_dataset))` should return examples from the dataset
## Actual results
```
/usr/local/lib/python3.7/dist-packages/datasets/formatting/dataset_wrappers/torch_iterable_dataset.py in _set_fsspec_for_multiprocess()
16 See https://github.com/fsspec/gcsfs/issues/379
17 """
---> 18 fsspec.asyn.iothread[0] = None
19 fsspec.asyn.loop[0] = None
20
AttributeError: module 'fsspec' has no attribute 'asyn'
```
## Environment info
- `datasets` version: 2.3.0
- Platform: Linux-5.4.188+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.13
- PyArrow version: 8.0.0
- Pandas version: 1.3.5
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https://api.github.com/repos/huggingface/datasets/issues/1681 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1681/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1681/comments | https://api.github.com/repos/huggingface/datasets/issues/1681/events | https://github.com/huggingface/datasets/issues/1681 | 777,644,163 | MDU6SXNzdWU3Nzc2NDQxNjM= | 1,681 | Dataset "dane" missing | {
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"Hi @KennethEnevoldsen ,\r\nI think the issue might be that this dataset was added during the community sprint and has not been released yet. It will be available with the v2 of datasets.\r\nFor now, you should be able to load the datasets after installing the latest (master) version of datasets using pip:\r\npip i... | 2021-01-03T14:03:03Z | 2021-01-05T08:35:35Z | 2021-01-05T08:35:13Z | CONTRIBUTOR | null | null | null | the `dane` dataset appear to be missing in the latest version (1.1.3).
```python
>>> import datasets
>>> datasets.__version__
'1.1.3'
>>> "dane" in datasets.list_datasets()
True
```
As we can see it should be present, but doesn't seem to be findable when using `load_dataset`.
```python
>>> datasets.load_dataset("dane")
Traceback (most recent call last):
File "/home/kenneth/.Envs/EDP/lib/python3.8/site-packages/datasets/load.py", line 267, in prepare_module
local_path = cached_path(file_path, download_config=download_config)
File "/home/kenneth/.Envs/EDP/lib/python3.8/site-packages/datasets/utils/file_utils.py", line 300, in cached_path
output_path = get_from_cache(
File "/home/kenneth/.Envs/EDP/lib/python3.8/site-packages/datasets/utils/file_utils.py", line 486, in get_from_cache
raise FileNotFoundError("Couldn't find file at {}".format(url))
FileNotFoundError: Couldn't find file at https://raw.githubusercontent.com/huggingface/datasets/1.1.3/datasets/dane/dane.py
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/home/kenneth/.Envs/EDP/lib/python3.8/site-packages/datasets/load.py", line 278, in prepare_module
local_path = cached_path(file_path, download_config=download_config)
File "/home/kenneth/.Envs/EDP/lib/python3.8/site-packages/datasets/utils/file_utils.py", line 300, in cached_path
output_path = get_from_cache(
File "/home/kenneth/.Envs/EDP/lib/python3.8/site-packages/datasets/utils/file_utils.py", line 486, in get_from_cache
raise FileNotFoundError("Couldn't find file at {}".format(url))
FileNotFoundError: Couldn't find file at https://s3.amazonaws.com/datasets.huggingface.co/datasets/datasets/dane/dane.py
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/kenneth/.Envs/EDP/lib/python3.8/site-packages/datasets/load.py", line 588, in load_dataset
module_path, hash = prepare_module(
File "/home/kenneth/.Envs/EDP/lib/python3.8/site-packages/datasets/load.py", line 280, in prepare_module
raise FileNotFoundError(
FileNotFoundError: Couldn't find file locally at dane/dane.py, or remotely at https://raw.githubusercontent.com/huggingface/datasets/1.1.3/datasets/dane/dane.py or https://s3.amazonaws.com/datasets.huggingface.co/datasets/datasets/dane/dane.py
```
This issue might be relevant to @ophelielacroix from the Alexandra Institut whom created the data. | {
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https://api.github.com/repos/huggingface/datasets/issues/5071 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5071/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5071/comments | https://api.github.com/repos/huggingface/datasets/issues/5071/events | https://github.com/huggingface/datasets/pull/5071 | 1,397,301,270 | PR_kwDODunzps5AMG3g | 5,071 | Support DEFAULT_CONFIG_NAME when no BUILDER_CONFIGS | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Super, thanks a lot for adding this support, Albert!"
] | 2022-10-05T06:28:39Z | 2022-10-06T14:43:12Z | 2022-10-06T14:40:26Z | MEMBER | null | 0 | {
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} | This PR supports defining a default config name, even if no predefined allowed config names are set.
Fix #5070.
CC: @stas00 | {
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https://api.github.com/repos/huggingface/datasets/issues/6175 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6175/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6175/comments | https://api.github.com/repos/huggingface/datasets/issues/6175/events | https://github.com/huggingface/datasets/pull/6175 | 1,863,592,678 | PR_kwDODunzps5YnKlx | 6,175 | PyArrow 13 CI fixes | {
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"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_a... | 2023-08-23T15:45:53Z | 2023-08-25T13:15:59Z | 2023-08-25T13:06:52Z | CONTRIBUTOR | null | 0 | {
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} | Fixes:
* bumps the PyArrow version check in the `cast_array_to_feature` to avoid the offset bug (still not fixed)
* aligns the Pandas formatting tests with the Numpy ones (the current test fails due to https://github.com/apache/arrow/pull/35656, which requires `.to_pandas(coerce_temporal_nanoseconds=True)` to always return `datetime [ns]` objects)
Fix #6173
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https://api.github.com/repos/huggingface/datasets/issues/1251 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1251/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1251/comments | https://api.github.com/repos/huggingface/datasets/issues/1251/events | https://github.com/huggingface/datasets/pull/1251 | 758,503,689 | MDExOlB1bGxSZXF1ZXN0NTMzNjY2NTg2 | 1,251 | Add Wiki Atomic Edits Dataset (43M edits) | {
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"@lhoestq fixed :)"
] | 2020-12-07T13:23:08Z | 2020-12-14T10:05:01Z | 2020-12-14T10:05:00Z | MEMBER | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/4508 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4508/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4508/comments | https://api.github.com/repos/huggingface/datasets/issues/4508/events | https://github.com/huggingface/datasets/issues/4508 | 1,272,718,921 | I_kwDODunzps5L3CZJ | 4,508 | cast_storage method from datasets.features | {
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"Hi! We've recently added a check to the `ClassLabel` type to ensure the values are in the valid label range `-1, 0, ..., num_classes-1` (-1 is used for missing values). The error in your case happens only if the `labels` column is of type `Sequence(ClassLabel(...))` before the `map` call and can be avoided by call... | 2022-06-15T20:47:22Z | 2022-06-16T13:54:07Z | 2022-06-16T13:54:07Z | NONE | null | null | null | ## Describe the bug
A bug occurs when mapping a function to a dataset object. I ran the same code with the same data yesterday and it worked just fine. It works when i run locally on an old version of datasets.
## Steps to reproduce the bug
Steps are:
- load whatever datset
- write a preprocessing function such as "tokenize_and_align_labels" written in https://huggingface.co/docs/transformers/tasks/token_classification
- map the function on dataset and get "ValueError: Class label -100 less than -1" from cast_storage method from datasets.features
# Sample code to reproduce the bug
def tokenize_and_align_labels(examples):
tokenized_inputs = tokenizer(examples["tokens"], truncation=True, is_split_into_words=True, max_length=38,padding="max_length")
labels = []
for i, label in enumerate(examples[f"labels"]):
word_ids = tokenized_inputs.word_ids(batch_index=i) # Map tokens to their respective word.
previous_word_idx = None
label_ids = []
for word_idx in word_ids: # Set the special tokens to -100.
if word_idx is None:
label_ids.append(-100)
elif word_idx != previous_word_idx: # Only label the first token of a given word.
label_ids.append(label[word_idx])
else:
label_ids.append(-100)
previous_word_idx = word_idx
labels.append(label_ids)
tokenized_inputs["labels"] = labels
return tokenized_inputs
tokenizer = AutoTokenizer.from_pretrained("distilbert-base-uncased")
dt = dataset.map(tokenize_and_align_labels, batched=True)
## Expected results
New dataset objects should load and do on older versions.
## Actual results
"ValueError: Class label -100 less than -1" from cast_storage method from datasets.features
## Environment info
everything works fine on older installations of datasets/transformers
Issue arises when installing datasets on google collab under python3.7
I can't manage to find the exact output you're requirering but version printed is datasets-2.3.2
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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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} | 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/5210 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5210/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5210/comments | https://api.github.com/repos/huggingface/datasets/issues/5210/events | https://github.com/huggingface/datasets/pull/5210 | 1,438,492,507 | PR_kwDODunzps5CVUzx | 5,210 | Tweak readme | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Nit: We should also update the `Disclaimers` section to let the dataset owners know they should use Hub discussions rather than GH issues for removal requests/updates",
"Updated the disclaimers section, thanks !\r\n\r\nDoes it soun... | 2022-11-07T14:51:23Z | 2022-11-24T11:35:07Z | 2022-11-24T11:26:16Z | MEMBER | null | 0 | {
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} | Tweaked some paragraphs mentioning the modalities we support + added a paragraph on security | {
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https://api.github.com/repos/huggingface/datasets/issues/3000 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3000/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3000/comments | https://api.github.com/repos/huggingface/datasets/issues/3000/events | https://github.com/huggingface/datasets/pull/3000 | 1,013,613,219 | PR_kwDODunzps4skusL | 3,000 | Fix json loader when conversion not implemented | {
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"And we're already at PR number 3,000 ! ^^",
"Thank you so much for fixing this @lhoestq 😍 ! I just tested the branch out and it works like a charm!"
] | 2021-10-01T17:47:22Z | 2021-10-01T18:05:00Z | 2021-10-01T17:54:23Z | MEMBER | null | 0 | {
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} | Sometimes the arrow json parser fails if the `block_size` is too small and returns an `ArrowNotImplementedError: JSON conversion to struct...` error.
By increasing the block size it makes it work again.
Hopefully it should help with https://github.com/huggingface/datasets/issues/2799
I tried with the file mentioned in the issue and it worked for me
cc @lewtun can you try again from this branch ? | {
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https://api.github.com/repos/huggingface/datasets/issues/3105 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3105/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3105/comments | https://api.github.com/repos/huggingface/datasets/issues/3105/events | https://github.com/huggingface/datasets/issues/3105 | 1,029,098,843 | I_kwDODunzps49Vs1b | 3,105 | download_mode=`force_redownload` does not work on removed datasets | {
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"descrip... | open | false | null | [] | null | [] | 2021-10-18T13:12:38Z | 2021-10-22T09:36:10Z | null | CONTRIBUTOR | null | null | null | ## Describe the bug
If a cached dataset is removed from the library, I don't see how to delete it programmatically. I thought that using `force_redownload` would try to refresh the cache, then raise an exception, but it reuses the cache instead.
## Steps to reproduce the bug
_requires to already have `wit` in the cache_: see https://github.com/huggingface/datasets/pull/2981
```python
import datasets as ds
dataset = ds.load_dataset("wit", split="train", download_mode='force_redownload')
```
## Expected results
It should raise an exception, since the dataset does not exist anymore.
## Actual results
It uses the cached result
```
Using the latest cached version of the module from /home/slesage/.cache/huggingface/modules/datasets_modules/datasets/wit/107afbffd48e058b19101bddc47fbee25fa68eb6d50a733e262875f1285a5171 (last modified on Wed Sep 29 08:21:10 2021) since it couldn't be found locally at wit, or remotely on the Hugging Face Hub.
```
## Environment info
- `datasets` version: 1.13.4.dev0
- Platform: Linux-5.11.0-1019-aws-x86_64-with-glibc2.31
- Python version: 3.9.6
- PyArrow version: 4.0.1 | {
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https://api.github.com/repos/huggingface/datasets/issues/4215 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4215/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4215/comments | https://api.github.com/repos/huggingface/datasets/issues/4215/events | https://github.com/huggingface/datasets/pull/4215 | 1,214,579,162 | PR_kwDODunzps42uuhY | 4,215 | Add `drop_last_batch` to `IterableDataset.map` | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-04-25T14:15:19Z | 2022-05-03T15:56:07Z | 2022-05-03T15:48:54Z | CONTRIBUTOR | null | 0 | {
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"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_a... | 2023-09-15T14:23:33Z | 2023-09-19T18:02:21Z | 2023-09-19T17:53:17Z | CONTRIBUTOR | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/3628 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3628/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3628/comments | https://api.github.com/repos/huggingface/datasets/issues/3628/events | https://github.com/huggingface/datasets/issues/3628 | 1,113,930,644 | I_kwDODunzps5CZTuU | 3,628 | Dataset Card Creator drops information for "Additional Information" Section | {
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] | open | false | null | [] | null | [] | 2022-01-25T14:06:17Z | 2022-01-25T14:09:01Z | null | NONE | null | null | null | First of all, the card creator is a great addition and really helpful for streamlining dataset cards!
## Describe the bug
I encountered an inconvenient bug when entering "Additional Information" in the react app, which drops already entered text when switching to a previous section, and then back again to "Additional Information". I was able to reproduce the issue in both Firefox and Chrome, so I suspect a problem with the React logic that doesn't expect users to switch back in the final section.
Edit: I'm also not sure whether this is the right place to open the bug report on, since it's not clear to me which particular project it belongs to, or where I could find associated source code.
## Steps to reproduce the bug
1. Navigate to the Section "Additional Information" in the [dataset card creator](https://huggingface.co/datasets/card-creator/)
2. Enter text in an arbitrary field, e.g., "Dataset Curators".
3. Switch back to a previous section, like "Dataset Creation".
4. When switching back again to "Additional Information", the text has been deleted.
Notably, this behavior can be reproduced again and again, it's not just problematic for the first "switch-back" from Additional Information.
## Expected results
For step 4, the previously entered information should still be present in the boxes, similar to the behavior to all other sections (switching back there works as expected)
## Actual results
The text boxes are empty again, and previously entered text got deleted.
## Environment info
- `datasets` version: N/A
- Platform: Firefox 96.0 / Chrome 97.0
- Python version: N/A
- PyArrow version: N/A
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} | This dataset consists of 3048 similar and dissimilar medical question pairs hand-generated and labeled by Curai's doctors.
Dataset : https://github.com/curai/medical-question-pair-dataset
Paper : https://drive.google.com/file/d/1CHPGBXkvZuZc8hpr46HeHU6U6jnVze-s/view | {
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https://api.github.com/repos/huggingface/datasets/issues/3697 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3697/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3697/comments | https://api.github.com/repos/huggingface/datasets/issues/3697/events | https://github.com/huggingface/datasets/pull/3697 | 1,129,795,724 | PR_kwDODunzps4yXeXo | 3,697 | Add code-fill datasets for pretraining/finetuning/evaluating | {
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"Hi ! Thanks for adding this dataset :)\r\n\r\nIt looks like your PR contains many changes in files that are unrelated to your changes, I think it might come from running `make style` with an outdated version of `black`. Could you try opening a new PR that only contains your additions ? (or force push to this PR)"
... | 2022-02-10T10:31:48Z | 2022-07-06T15:19:58Z | 2022-07-06T15:19:58Z | NONE | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/1982 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1982/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1982/comments | https://api.github.com/repos/huggingface/datasets/issues/1982/events | https://github.com/huggingface/datasets/pull/1982 | 821,448,791 | MDExOlB1bGxSZXF1ZXN0NTg0MjM2NzQ0 | 1,982 | Fix NestedDataStructure.data for empty dict | {
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"I validated that this fixed the problem, thank you, @albertvillanova!\r\n",
"still facing the same issue or similar:\r\nfrom datasets import load_dataset\r\nwtm14_test = load_dataset('wmt14',\"de-en\",cache_dir='./datasets')\r\n\r\n~\\.cache\\huggingface\\modules\\datasets_modules\\datasets\\wmt14\\43e717d978d22... | 2021-03-03T20:16:51Z | 2021-03-04T16:46:04Z | 2021-03-03T22:48:36Z | MEMBER | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/3721 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3721/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3721/comments | https://api.github.com/repos/huggingface/datasets/issues/3721/events | https://github.com/huggingface/datasets/pull/3721 | 1,137,617,108 | PR_kwDODunzps4yzXCd | 3,721 | Multi-GPU support for `FaissIndex` | {
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"Any love?",
"Hi, any update?",
"@albertvillanova Sorry for bothering you again, quick follow up: is there anything else you want me to add / modify?",
"Hi @rentruewang , we updated the documentation on `master`, could you merge `master` into your branch please ?",
"@lhoestq I've merge `huggingface/datasets... | 2022-02-14T17:26:51Z | 2022-03-07T16:28:57Z | 2022-03-07T16:28:56Z | CONTRIBUTOR | null | 0 | {
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} | 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/4034 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4034/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4034/comments | https://api.github.com/repos/huggingface/datasets/issues/4034/events | https://github.com/huggingface/datasets/pull/4034 | 1,183,033,285 | PR_kwDODunzps41IpN1 | 4,034 | Fix null checksum in xcopa dataset | {
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https://api.github.com/repos/huggingface/datasets/issues/4548 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4548/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4548/comments | https://api.github.com/repos/huggingface/datasets/issues/4548/events | https://github.com/huggingface/datasets/issues/4548 | 1,282,218,096 | I_kwDODunzps5MbRhw | 4,548 | Metadata.jsonl for Imagefolder is ignored if it's in a parent directory to the splits directories/do not have "{split}_" prefix | {
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"I agree it would be nice to support this. It doesn't fit really well in the current data_files.py, where files of each splits are separated in different folder though, maybe we have to modify a bit the logic here. \r\n\r\nOne idea would be to extend `get_patterns_in_dataset_repository` and `get_patterns_locally` t... | 2022-06-23T10:58:57Z | 2022-06-30T10:15:32Z | 2022-06-30T10:15:32Z | CONTRIBUTOR | null | null | null | If data contains a single `metadata.jsonl` file for several splits, it won't be included in a dataset's `data_files` and therefore ignored.
This happens when a directory is structured like as follows:
```
train/
file_1.jpg
file_2.jpg
test/
file_3.jpg
file_4.jpg
metadata.jsonl
```
or like as follows:
```
train_file_1.jpg
train_file_2.jpg
test_file_3.jpg
test_file_4.jpg
metadata.jsonl
```
The same for HF repos.
because it's ignored by the patterns [here](https://github.com/huggingface/datasets/blob/master/src/datasets/data_files.py#L29)
@lhoestq @mariosasko Do you think it's better to add this functionality in `data_files.py` or just specifically in imagefolder/audiofolder code? In `data_files.py` would me more general but I don't know if there are any other cases when that might be needed.
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https://api.github.com/repos/huggingface/datasets/issues/4503 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4503/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4503/comments | https://api.github.com/repos/huggingface/datasets/issues/4503/events | https://github.com/huggingface/datasets/pull/4503 | 1,272,367,055 | PR_kwDODunzps45twLR | 4,503 | Refactor and add metadata to fever dataset | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"But this is somehow fever v3 dataset (see this link https://fever.ai/ under the dropdown menu called Datasets). Our fever dataset already contains v1 and v2 configs. Then, I added this as if v3 config (but named feverous instead of v... | 2022-06-15T14:59:47Z | 2022-07-06T11:54:15Z | 2022-07-06T11:41:30Z | MEMBER | null | 0 | {
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} | Related to: #4452 and #3792. | {
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https://api.github.com/repos/huggingface/datasets/issues/4129 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4129/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4129/comments | https://api.github.com/repos/huggingface/datasets/issues/4129/events | https://github.com/huggingface/datasets/issues/4129 | 1,197,376,796 | I_kwDODunzps5HXoUc | 4,129 | dataset metadata for reproducibility | {
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"+1 on this idea. This could be powerful for helping better track datasets used for model training and help with automatic model card creation. \r\n\r\nOne possible way of doing this would be to store some/most/all the arguments passed to `load_dataset` if a hub id is passed. i.e. store the Hub ID, configuration, e... | 2022-04-08T14:17:28Z | 2023-09-29T09:23:56Z | null | NONE | null | null | null | When pulling a dataset from the hub, it would be useful to have some metadata about the specific dataset and version that is used. The metadata could then be passed to the `Trainer` which could then be saved to a model card. This is useful for people who run many experiments on different versions (commits/branches) of the same dataset.
The dataset could have a list of “source datasets” metadata and ignore what happens to them before arriving in the Trainer (i.e. ignore mapping, filtering, etc.).
Here is a basic representation (made by @lhoestq )
```python
>>> from datasets import load_dataset
>>>
>>> my_dataset = load_dataset(...)["train"]
>>> my_dataset = my_dataset.map(...)
>>>
>>> my_dataset.sources
[HFHubDataset(repo_id=..., revision=..., arguments={...})]
``` | {
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"Hi @cbarond there's already an open issue at https://github.com/dair-ai/emotion_dataset/issues/5, as the data seems to be missing now, so check that issue instead 👍🏻 ",
"Thanks @cbarond for reporting and @alvarobartt for pointing to the issue we opened in the author's repo.\r\n\r\nIndeed, this issue was first ... | 2022-12-08T19:07:09Z | 2023-02-23T19:13:19Z | 2022-12-09T10:46:11Z | NONE | null | null | null | ### Describe the bug
The emotion dataset gives a FileNotFoundError. The full error is: `FileNotFoundError: Couldn't find file at https://www.dropbox.com/s/1pzkadrvffbqw6o/train.txt?dl=1`.
It was working yesterday (December 7, 2022), but stopped working today (December 8, 2022).
### Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset("emotion")
```
### Expected behavior
The dataset should load properly.
### Environment info
- `datasets` version: 2.7.1
- Platform: Windows-10-10.0.19045-SP0
- Python version: 3.9.13
- PyArrow version: 10.0.1
- Pandas version: 1.5.1 | {
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https://api.github.com/repos/huggingface/datasets/issues/6219 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6219/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6219/comments | https://api.github.com/repos/huggingface/datasets/issues/6219/events | https://github.com/huggingface/datasets/pull/6219 | 1,884,244,334 | PR_kwDODunzps5ZsgPK | 6,219 | Release: 2.14.5 | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6219). All of your documentation changes will be reflected on that endpoint.",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchma... | 2023-09-06T15:17:10Z | 2023-09-06T15:46:20Z | 2023-09-06T15:18:51Z | MEMBER | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/4322 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4322/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4322/comments | https://api.github.com/repos/huggingface/datasets/issues/4322/events | https://github.com/huggingface/datasets/pull/4322 | 1,233,596,947 | PR_kwDODunzps43s1wy | 4,322 | Added stratify option to train_test_split function. | {
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"> Nice thank you ! This will be super useful :)\r\n> \r\n> Could you also add some tests in test_arrow_dataset.py and add an example of usage in the `Example:` section of the `train_test_split` docstring ?\r\n\r\nI will try to do it, is there any documentation for adding test cases? I have never done it before.",
... | 2022-05-12T08:00:31Z | 2022-11-22T14:53:55Z | 2022-05-25T20:43:51Z | CONTRIBUTOR | null | 0 | {
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} | This PR adds `stratify` option to `train_test_split` method. I took reference from scikit-learn's `StratifiedShuffleSplit` class for implementing stratified split and integrated the changes as were suggested by @lhoestq.
It fixes #3452.
@lhoestq Please review and let me know, if any changes are required.
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"@lhoestq maybe we could also use (if available) the ETag of the remote file in `create_config_id`?",
"> @lhoestq maybe we could also use (if available) the ETag of the remote file in `create_config_id`?\r\n\r\nSure ! We can get the ETag with\r\n```python\r\nheaders = get_authentication_headers_for_url(url, use_a... | 2021-07-09T14:07:38Z | 2021-07-09T16:13:41Z | 2021-07-09T16:13:41Z | MEMBER | null | 0 | {
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} | Add support for (streaming) remote data files:
```python
data_files = f"https://huggingface.co/datasets/{repo_id}/resolve/main/{relative_file_path}"
ds = load_dataset("json", split="train", data_files=data_files, streaming=True)
```
cc: @thomwolf | {
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https://api.github.com/repos/huggingface/datasets/issues/4912 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4912/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4912/comments | https://api.github.com/repos/huggingface/datasets/issues/4912/events | https://github.com/huggingface/datasets/issues/4912 | 1,355,078,864 | I_kwDODunzps5QxNzQ | 4,912 | datasets map() handles all data at a stroke and takes long time | {
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"Hi ! Interesting question ;)\r\n\r\n> Which is better? Process in map() or in data-collator\r\n\r\nAs you said, both can be used in practice: map() if you want to preprocess before training, or a data-collator (or the equivalent `dataset.set_transform`) if you want to preprocess on-the-fly during training. Both op... | 2022-08-30T02:25:56Z | 2023-04-06T09:43:58Z | 2022-09-06T09:23:35Z | NONE | null | null | null | **1. Background**
Huggingface datasets package advises using `map()` to process data in batches. In the example code on pretraining masked language model, they use `map()` to tokenize all data at a stroke before the train loop.
The corresponding code:
```
with accelerator.main_process_first():
tokenized_datasets = raw_datasets.map(
tokenize_function,
batched=True,
num_proc=args.preprocessing_num_workers,
remove_columns=column_names,
load_from_cache_file=not args.overwrite_cache,
desc="Running tokenizer on every text in dataset"
)
```
**2. The problem**
Thus, when I try the same pertaining code with a much larger corpus, it takes quite a long time to tokenize.
Also, we can choose to tokenize data in `data-collator`. In this way, the program only tokenizes one batch in the next training step and avoids getting stuck in tokenization.
**3. My question**
As described above, my questions are:
* **Which is better? Process in `map()` or in `data-collator`**
* **Why huggingface advises `map()` function?** There should be some advantages to using `map()`
Thanks for your answers! | {
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https://api.github.com/repos/huggingface/datasets/issues/3064 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3064/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3064/comments | https://api.github.com/repos/huggingface/datasets/issues/3064/events | https://github.com/huggingface/datasets/issues/3064 | 1,023,900,075 | I_kwDODunzps49B3mr | 3,064 | Make `interleave_datasets` more robust | {
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"Hi @lhoestq Any response on this issue?",
"Hi ! Sorry for the late response\r\n\r\nI agree `interleave_datasets` would benefit a lot from having more flexibility. If I understand correctly it would be nice to be able to define stopping strategies like `stop=\"first_exhausted\"` (default) or `stop=\"all_exhauste... | 2021-10-12T14:34:53Z | 2022-07-30T08:47:26Z | null | NONE | null | null | null | **Is your feature request related to a problem? Please describe.**
Right now there are few hiccups using `interleave_datasets`. Interleaved dataset iterates until the smallest dataset completes it's iterator. In this way larger datasets may not complete full epoch of iteration.
It creates new problems in calculation of epoch since there are no way to track which dataset from `interleave_datasets` completes how many epoch.
**Describe the solution you'd like**
For `interleave_datasets` module,
- [ ] Add a boolean argument `--stop-iter` in `interleave_datasets` that enables dataset to either iterate infinite amount of time or not. That means it should not return `StopIterator` exception in case `--stop-iter=False`.
- [ ] Internal list variable `iter_cnt` that explains how many times (in steps/epochs) each dataset iterates at a given point.
- [ ] Add an argument `--max-iter` (list type) that explain maximum amount of time each of the dataset can iterate. After complete `--max-iter` of one dataset, other dataset should continue sampling and when all the dataset finish their respective `--max-iter`, only then return `StopIterator`
Note: I'm new to `datasets` api. May be these features are already there in the datasets.
Since multitask training is the latest trends, I believe this feature would make the `datasets` api more popular.
@lhoestq | {
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https://api.github.com/repos/huggingface/datasets/issues/1415 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1415/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1415/comments | https://api.github.com/repos/huggingface/datasets/issues/1415/events | https://github.com/huggingface/datasets/pull/1415 | 760,642,786 | MDExOlB1bGxSZXF1ZXN0NTM1NDQxMTQx | 1,415 | Add Hate Speech and Offensive Language Detection dataset | {
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"@lhoestq done! The failing testes don't seem to be related, it seems to be a connection issue, if I understand it correctly.",
"@lhoestq done!",
"merging since the CI is fixed on master"
] | 2020-12-09T20:22:12Z | 2020-12-14T18:06:44Z | 2020-12-14T16:25:31Z | CONTRIBUTOR | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/4137 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4137/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4137/comments | https://api.github.com/repos/huggingface/datasets/issues/4137/events | https://github.com/huggingface/datasets/pull/4137 | 1,199,000,453 | PR_kwDODunzps419D6A | 4,137 | Add single dataset citations for TweetEval | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"The `test_dataset_cards` method is failing with the error:\r\n\r\n```\r\nif error_messages:\r\n> raise ValueError(\"\\n\".join(error_messages))\r\nE ValueError: The following issues have been found in the dataset ... | 2022-04-10T11:51:54Z | 2022-04-12T07:57:22Z | 2022-04-12T07:51:15Z | CONTRIBUTOR | null | 0 | {
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} | This PR adds single data citations as per request of the original creators of the TweetEval dataset.
This is a recent email from the creator:
> Could I ask you a favor? Would you be able to add at the end of the README the citations of the single datasets as well? You can just copy our readme maybe? https://github.com/cardiffnlp/tweeteval#citing-tweeteval
(just to be sure that the creator of the single datasets also get credits when tweeteval is used)
Please let me know if this looks okay or if any changes are needed.
Thanks,
Gunjan
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3840). All of your documentation changes will be reflected on that endpoint."
] | 2022-03-07T10:06:53Z | 2022-03-07T10:12:36Z | 2022-03-07T10:07:24Z | MEMBER | null | 0 | {
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} | Temporarily fix CI for Windows by pinning `responses`.
See: https://app.circleci.com/pipelines/github/huggingface/datasets/10292/workflows/83de4a55-bff7-43ec-96f7-0c335af5c050/jobs/63355
Fix: #3839 | {
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https://api.github.com/repos/huggingface/datasets/issues/2699 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2699/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2699/comments | https://api.github.com/repos/huggingface/datasets/issues/2699/events | https://github.com/huggingface/datasets/issues/2699 | 950,221,226 | MDU6SXNzdWU5NTAyMjEyMjY= | 2,699 | cannot combine splits merging and streaming? | {
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"Hi ! That's missing indeed. We'll try to implement this for the next version :)\r\n\r\nI guess we just need to implement #2564 first, and then we should be able to add support for splits combinations"
] | 2021-07-22T01:13:25Z | 2021-07-22T08:27:47Z | null | NONE | null | null | null | this does not work:
`dataset = datasets.load_dataset('mc4','iw',split='train+validation',streaming=True)`
with error:
`ValueError: Bad split: train+validation. Available splits: ['train', 'validation']`
these work:
`dataset = datasets.load_dataset('mc4','iw',split='train+validation')`
`dataset = datasets.load_dataset('mc4','iw',split='train',streaming=True)`
`dataset = datasets.load_dataset('mc4','iw',split='validation',streaming=True)`
i could not find a reference to this in the documentation and the error message is confusing. also would be nice to allow streaming for the merged splits | {
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https://api.github.com/repos/huggingface/datasets/issues/3366 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3366/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3366/comments | https://api.github.com/repos/huggingface/datasets/issues/3366/events | https://github.com/huggingface/datasets/issues/3366 | 1,069,214,022 | I_kwDODunzps4_uulG | 3,366 | Add multimodal datasets | {
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- [ ] #2526
- [x] #1842
- [ ] #1810
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
@VictorSanh feel free to add and sort by priority any interesting dataset. I have added the multimodal dataset requests which were already present as issues. | {
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"This should be fixed now!\r\n\r\ncc @srush "
] | 2021-04-20T14:19:51Z | 2021-04-20T15:02:45Z | 2021-04-20T15:02:45Z | NONE | null | null | null | Link to datasets viwer (https://huggingface.co/datasets/viewer/) on Quick Tour page (https://huggingface.co/docs/datasets/quicktour.html) returns "502 Bad Gateway"
The same error with https://huggingface.co/datasets/viewer/?dataset=glue&config=mrpc | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2023-04-20T13:21:32Z | 2023-04-20T13:34:26Z | 2023-04-20T13:24:28Z | MEMBER | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/4867 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4867/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4867/comments | https://api.github.com/repos/huggingface/datasets/issues/4867/events | https://github.com/huggingface/datasets/pull/4867 | 1,344,982,646 | PR_kwDODunzps49fZle | 4,867 | Complete tags of superglue dataset card | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-08-19T23:44:39Z | 2022-08-22T09:14:03Z | 2022-08-22T08:58:31Z | CONTRIBUTOR | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/5399 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5399/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5399/comments | https://api.github.com/repos/huggingface/datasets/issues/5399/events | https://github.com/huggingface/datasets/issues/5399 | 1,515,548,427 | I_kwDODunzps5aVW8L | 5,399 | Got disconnected from remote data host. Retrying in 5sec [2/20] | {
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While trying to upload my image dataset of a CSV file type to huggingface by running the below code. The dataset consists of a little over 100k of image-caption pairs
### Steps to reproduce the bug
```
df = pd.read_csv('x.csv', encoding='utf-8-sig')
features = Features({
'link': Image(decode=True),
'caption': Value(dtype='string'),
})
#make sure u r logged in to HF
ds = Dataset.from_pandas(df, features=features)
ds.features
ds.push_to_hub("x/x")
```
I got the below error and It always stops at the same progress
```
100%|██████████| 4/4 [23:53<00:00, 358.48s/ba]
100%|██████████| 4/4 [24:37<00:00, 369.47s/ba]%|▍ | 1/22 [00:06<02:09, 6.16s/it]
100%|██████████| 4/4 [25:00<00:00, 375.15s/ba]%|▉ | 2/22 [25:54<2:36:15, 468.80s/it]
100%|██████████| 4/4 [24:53<00:00, 373.29s/ba]%|█▎ | 3/22 [51:01<4:07:07, 780.39s/it]
100%|██████████| 4/4 [24:01<00:00, 360.34s/ba]%|█▊ | 4/22 [1:17:00<5:04:07, 1013.74s/it]
100%|██████████| 4/4 [23:59<00:00, 359.91s/ba]%|██▎ | 5/22 [1:41:07<5:24:06, 1143.90s/it]
100%|██████████| 4/4 [24:16<00:00, 364.06s/ba]%|██▋ | 6/22 [2:05:14<5:29:15, 1234.74s/it]
100%|██████████| 4/4 [25:24<00:00, 381.10s/ba]%|███▏ | 7/22 [2:29:38<5:25:52, 1303.52s/it]
100%|██████████| 4/4 [25:24<00:00, 381.24s/ba]%|███▋ | 8/22 [2:56:02<5:23:46, 1387.58s/it]
100%|██████████| 4/4 [25:08<00:00, 377.23s/ba]%|████ | 9/22 [3:22:24<5:13:17, 1445.97s/it]
100%|██████████| 4/4 [24:11<00:00, 362.87s/ba]%|████▌ | 10/22 [3:48:24<4:56:02, 1480.19s/it]
100%|██████████| 4/4 [24:44<00:00, 371.11s/ba]%|█████ | 11/22 [4:12:42<4:30:10, 1473.66s/it]
100%|██████████| 4/4 [24:35<00:00, 368.81s/ba]%|█████▍ | 12/22 [4:37:34<4:06:29, 1478.98s/it]
100%|██████████| 4/4 [24:02<00:00, 360.67s/ba]%|█████▉ | 13/22 [5:03:24<3:45:04, 1500.45s/it]
100%|██████████| 4/4 [24:07<00:00, 361.78s/ba]%|██████▎ | 14/22 [5:27:33<3:17:59, 1484.97s/it]
100%|██████████| 4/4 [23:39<00:00, 354.85s/ba]%|██████▊ | 15/22 [5:51:48<2:52:10, 1475.82s/it]
Pushing dataset shards to the dataset hub: 73%|███████▎ | 16/22 [6:16:58<2:28:37, 1486.31s/it]Got disconnected from remote data host. Retrying in 5sec [1/20]
Got disconnected from remote data host. Retrying in 5sec [2/20]
Got disconnected from remote data host. Retrying in 5sec [3/20]
Got disconnected from remote data host. Retrying in 5sec [4/20]
Got disconnected from remote data host. Retrying in 5sec [5/20]
Got disconnected from remote data host. Retrying in 5sec [6/20]
Got disconnected from remote data host. Retrying in 5sec [7/20]
Got disconnected from remote data host. Retrying in 5sec [8/20]
Got disconnected from remote data host. Retrying in 5sec [9/20]
...
Got disconnected from remote data host. Retrying in 5sec [19/20]
Got disconnected from remote data host. Retrying in 5sec [20/20]
75%|███████▌ | 3/4 [24:47<08:15, 495.86s/ba]
Pushing dataset shards to the dataset hub: 73%|███████▎ | 16/22 [6:41:46<2:30:39, 1506.65s/it]
Output exceeds the size limit. Open the full output data in a text editor
---------------------------------------------------------------------------
ConnectionError Traceback (most recent call last)
<ipython-input-1-dbf8530779e9> in <module>
16 ds.features
```
### Expected behavior
I was trying to upload an image dataset and expected it to be fully uploaded
### Environment info
- `datasets` version: 2.8.0
- Platform: Windows-10-10.0.19041-SP0
- Python version: 3.7.9
- PyArrow version: 10.0.1
- Pandas version: 1.3.5 | {
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https://api.github.com/repos/huggingface/datasets/issues/1204 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1204/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1204/comments | https://api.github.com/repos/huggingface/datasets/issues/1204/events | https://github.com/huggingface/datasets/pull/1204 | 757,939,475 | MDExOlB1bGxSZXF1ZXN0NTMzMjA2MzE3 | 1,204 | adding meta_woz dataset | {
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https://api.github.com/repos/huggingface/datasets/issues/2221 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2221/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2221/comments | https://api.github.com/repos/huggingface/datasets/issues/2221/events | https://github.com/huggingface/datasets/pull/2221 | 857,833,770 | MDExOlB1bGxSZXF1ZXN0NjE1MTg4MTE5 | 2,221 | Add SLR70 - SLR80 and SLR86 to OpenSLR dataset | {
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} | I would like to add SLR70, SLR71, SLR72, SLR73, SLR74, SLR75, SLR76, SLR77, SLR78, SLR79, SLR80 and SLR86 to OpenSLR dataset. The languages are:
Nigerian English, Chilean Spanish, Columbian Spanish, Peruvian Spanish, Puerto Rico Spanish, Venezuelan Spanish, Basque, Galician, Gujarati and Kannada. | {
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See: https://github.com/huggingface/datasets/actions/runs/6322990957/job/17169678812?pr=6262
```
FAILED tests/test_py_utils.py::TempSeedTest::test_tensorflow - ImportError: cannot import name 'context' from 'tensorflow.python' (/opt/hostedtoolcache/Python/3.10.13/x64/lib/python3.10/site-packages/tensorflow/python/__init__.py)
```
```
_________________________ TempSeedTest.test_tensorflow _________________________
[gw1] linux -- Python 3.10.13 /opt/hostedtoolcache/Python/3.10.13/x64/bin/python
self = <tests.test_py_utils.TempSeedTest testMethod=test_tensorflow>
@require_tf
def test_tensorflow(self):
import tensorflow as tf
from tensorflow.keras import layers
model = layers.Dense(2)
def gen_random_output():
x = tf.random.uniform((1, 3))
return model(x).numpy()
> with temp_seed(42, set_tensorflow=True):
tests/test_py_utils.py:155:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
/opt/hostedtoolcache/Python/3.10.13/x64/lib/python3.10/contextlib.py:135: in __enter__
return next(self.gen)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
seed = 42, set_pytorch = False, set_tensorflow = True
@contextmanager
def temp_seed(seed: int, set_pytorch=False, set_tensorflow=False):
"""Temporarily set the random seed. This works for python numpy, pytorch and tensorflow."""
np_state = np.random.get_state()
np.random.seed(seed)
if set_pytorch and config.TORCH_AVAILABLE:
import torch
torch_state = torch.random.get_rng_state()
torch.random.manual_seed(seed)
if torch.cuda.is_available():
torch_cuda_states = torch.cuda.get_rng_state_all()
torch.cuda.manual_seed_all(seed)
if set_tensorflow and config.TF_AVAILABLE:
import tensorflow as tf
> from tensorflow.python import context as tfpycontext
E ImportError: cannot import name 'context' from 'tensorflow.python' (/opt/hostedtoolcache/Python/3.10.13/x64/lib/python3.10/site-packages/tensorflow/python/__init__.py)
/opt/hostedtoolcache/Python/3.10.13/x64/lib/python3.10/site-packages/datasets/utils/py_utils.py:257: ImportError
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/1767 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1767/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1767/comments | https://api.github.com/repos/huggingface/datasets/issues/1767/events | https://github.com/huggingface/datasets/pull/1767 | 792,068,497 | MDExOlB1bGxSZXF1ZXN0NTYwMDE2MzE2 | 1,767 | Add Librispeech ASR | {
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"> Awesome thank you !\r\n> \r\n> The dummy data are quite big but it was expected given that the raw files are flac files.\r\n> Given that the script doesn't even read the flac files I think we can remove them. Or maybe use empty flac files (see [here](https://hydrogenaud.io/index.php?topic=118685.0) for example).... | 2021-01-22T14:54:37Z | 2021-01-25T20:38:07Z | 2021-01-25T20:37:42Z | MEMBER | null | 0 | {
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} | This PR adds the librispeech asr dataset: https://www.tensorflow.org/datasets/catalog/librispeech
There are 2 configs: "clean" and "other" whereas there are two "train" datasets for "clean", hence the name "train.100" and "train.360".
As suggested by @lhoestq, due to the enormous size of the dataset in `.arrow` format, the speech files are not directly prepared to a float32-array, but instead just the path to the array file is stored. | {
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https://api.github.com/repos/huggingface/datasets/issues/5477 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5477/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5477/comments | https://api.github.com/repos/huggingface/datasets/issues/5477/events | https://github.com/huggingface/datasets/issues/5477 | 1,559,909,892 | I_kwDODunzps5c-lYE | 5,477 | Unpin sqlalchemy once issue is fixed | {
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"@albertvillanova It looks like that issue has been fixed so I made a PR to unpin sqlalchemy! ",
"The source issue:\r\n- https://github.com/pandas-dev/pandas/issues/40686\r\n\r\nhas been fixed:\r\n- https://github.com/pandas-dev/pandas/pull/48576\r\n\r\nThe fix was released yesterday (2023-04-03) only in `pandas-... | 2023-01-27T15:01:55Z | 2023-04-04T08:06:43Z | null | MEMBER | null | null | null | Once the source issue is fixed:
- pandas-dev/pandas#51015
we should revert the pin introduced in:
- #5476 | {
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"Hi ! Have you tried other values for `preprocessing_num_workers` ? Is it always process 0 that is slower ?\r\nThere are no difference between process 0 and the others except that it processes the first shard of the dataset.",
"Hi, I have found the reason of it. Before using the map function to tokenize the data,... | 2021-04-30T08:00:33Z | 2021-05-04T11:00:11Z | null | NONE | null | null | null | Hi, _datasets_ is really amazing! I am following [run_mlm_no_trainer.py](url) to pre-train BERT, and it uses `tokenized_datasets = raw_datasets.map(
tokenize_function,
batched=True,
num_proc=args.preprocessing_num_workers,
remove_columns=column_names,
load_from_cache_file=not args.overwrite_cache,
)` to tokenize by multiprocessing. However, I have found that when `num_proc`>1，the process _#0_ is much slower than others.
It looks like this:
It takes more than 12 hours for #0, while others just about half an hour. Could anyone tell me it is normal or not, and is there any methods to speed up it?
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https://api.github.com/repos/huggingface/datasets/issues/3657 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3657/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3657/comments | https://api.github.com/repos/huggingface/datasets/issues/3657/events | https://github.com/huggingface/datasets/pull/3657 | 1,120,602,620 | PR_kwDODunzps4x5f1I | 3,657 | Extend dataset builder for streaming in `get_dataset_split_names` | {
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"I'm impatient to see if it has an impact on the number of valid datasets for the dataset viewer. For the record, today:\r\n\r\n<img width=\"660\" alt=\"Capture d’écran 2022-02-01 à 14 32 19\" src=\"https://user-images.githubusercontent.com/1676121/151977579-b5a239d9-6662-4aeb-bfd1-eef6b8249991.png\">\r\n",
"Th... | 2022-02-01T12:21:24Z | 2022-02-03T22:49:06Z | 2022-02-02T11:22:01Z | CONTRIBUTOR | null | 0 | {
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} | Currently, `get_dataset_split_names` doesn't extend a builder module to support streaming, even though it uses `StreamingDownloadManager` to download data. This PR fixes that.
To test the change, run the following:
```bash
pip install git+https://github.com/huggingface/datasets.git@fix-get_dataset_split_names-streaming
python -c "from datasets import get_dataset_split_names; print(get_dataset_split_names('facebook/multilingual_librispeech', 'german', download_mode='force_redownload', revision='137923f945552c6afdd8b60e4a7b43e3088972c1'))"
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/3283 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3283/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3283/comments | https://api.github.com/repos/huggingface/datasets/issues/3283/events | https://github.com/huggingface/datasets/issues/3283 | 1,055,495,874 | I_kwDODunzps4-6ZbC | 3,283 | Add Speech Commands dataset | {
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"#self-assign"
] | 2021-11-16T22:39:56Z | 2021-12-10T10:30:15Z | 2021-12-10T10:30:15Z | MEMBER | null | null | null | ## Adding a Dataset
- **Name:** Speech commands
- **Description:** A Dataset for Limited-Vocabulary Speech Recognition
- **Paper:** https://arxiv.org/abs/1804.03209
- **Data:** https://www.tensorflow.org/datasets/catalog/speech_commands, Available:
http://download.tensorflow.org/data/speech_commands_v0.02.tar.gz
- **Motivation:** Nice dataset for audio classification training
cc @anton-l
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-04-22T14:56:21Z | 2022-05-03T15:28:42Z | 2022-05-03T15:21:48Z | CONTRIBUTOR | null | 0 | {
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"It can be solved temporarily by remove `resolve` in \r\nhttps://github.com/huggingface/datasets/blob/bef23be3d9543b1ca2da87ab2f05070201044ddc/src/datasets/data_files.py#L278",
"Hi, thanks for reporting and suggesting a fix! We still need to account for `.`/`..` in the file path, so a more robust fix would be `P... | 2022-10-11T06:10:58Z | 2022-11-14T14:40:20Z | 2022-11-14T14:40:20Z | NONE | null | null | null | **Is your feature request related to a problem? Please describe.**
Like this: #4015
When there are **symbolic links** to pictures in the data folder, the parent folder name of the **real file** will be used as the class name instead of the parent folder of the symbolic link itself. Can you give an option to decide whether to enable symbolic link tracking?
This is inconsistent with the `torchvision.datasets.ImageFolder` behavior.
For example:
It use `others` in green circle as class label but not `abnormal`, I wish `load_dataset` not use the real file parent as label.
**Describe the solution you'd like**
A clear and concise description of what you want to happen.
**Describe alternatives you've considered**
A clear and concise description of any alternative solutions or features you've considered.
**Additional context**
Add any other context about the feature request here.
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"_The documentation is not available anymore as the PR was closed or merged._",
"Thanks @osanseviero. Am I good to merge? ",
"I would wait for a second approval just in case :) ",
"Sure :) ",
"Merging since the images have been pushed as LFS files ([PR](https://huggingface.co/datasets/huggingface/documentat... | 2022-11-02T04:34:36Z | 2022-11-04T18:25:57Z | 2022-11-04T18:23:34Z | MEMBER | null | 0 | {
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} | Closes #5181
I have opened a PR on Hub (https://huggingface.co/datasets/huggingface/documentation-images/discussions/5) to include the images in our central Hub repository. Once the PR is merged I will edit the image links.
I have also prepared a [Colab Notebook](https://colab.research.google.com/drive/1BMDCfOTBnyshoME5RSxn5iQy-TWeFbOA?usp=sharing) in case anyone wants to play.
- [x] Replace the image links | {
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"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_a... | 2023-09-27T07:40:18Z | 2023-09-28T15:39:16Z | 2023-09-28T15:30:40Z | MEMBER | null | 0 | {
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} | Currently our CI usually raises 404 errors when trying to delete temporary repositories. See, e.g.: https://github.com/huggingface/datasets/actions/runs/6314980985/job/17146507884
```
FAILED tests/test_upstream_hub.py::TestPushToHub::test_push_dataset_dict_to_hub_multiple_files_with_max_shard_size - huggingface_hub.utils._errors.RepositoryNotFoundError: 404 Client Error. (Request ID: Root=1-6512fb99-4a52c561752ece3d77eb6d57;2b61cae4-613d-4a73-bbb1-2faf9e32b02d)
Repository Not Found for url: https://hub-ci.huggingface.co/api/repos/delete.
Please make sure you specified the correct `repo_id` and `repo_type`.
If you are trying to access a private or gated repo, make sure you are authenticated.
FAILED tests/test_upstream_hub.py::TestPushToHub::test_push_dataset_to_hub_custom_features_audio - huggingface_hub.utils._errors.RepositoryNotFoundError: 404 Client Error. (Request ID: Root=1-6512fbb2-0333dd666d42f0e173c2bb68;dfdc4271-b49b-4008-8c49-f05cf7c1d53d)
Repository Not Found for url: https://hub-ci.huggingface.co/api/repos/delete.
Please make sure you specified the correct `repo_id` and `repo_type`.
If you are trying to access a private or gated repo, make sure you are authenticated.
FAILED tests/test_upstream_hub.py::TestPushToHub::test_push_dataset_dict_to_hub_custom_splits - huggingface_hub.utils._errors.RepositoryNotFoundError: 404 Client Error. (Request ID: Root=1-6512fbca-167690694f39770a5b3a444e;baeaa905-0a57-4585-ac97-9aaae12dd47d)
Repository Not Found for url: https://hub-ci.huggingface.co/api/repos/delete.
Please make sure you specified the correct `repo_id` and `repo_type`.
If you are trying to access a private or gated repo, make sure you are authenticated.
```
I think this can be caused by collisions in temporary repository IDs because we create them in multiprocessing:
```python
with temporary_repo(f"{CI_HUB_USER}/test-{int(time.time() * 10e3)}") as ds_name:
```
This can also be caused when there is another issue that does not allow the creation of the repository, thus making it impossible to delete it.
This PR tries to fix this issue by increasing the precision of the number on the repository ID: `10e6` instead of `10e3`.
Additionally, this PR catches RepositoryNotFoundError.
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} | [] | 2021-07-06T17:06:28Z | 2021-07-12T14:10:35Z | 2021-07-07T12:50:31Z | CONTRIBUTOR | null | 0 | {
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} | Fixes #2600
Also I moved the check for `num_proc` larger than dataset size added in #2566 up so that multiprocessing is not used with one process. | {
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"_The documentation is not available anymore as the PR was closed or merged._",
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https://api.github.com/repos/huggingface/datasets/issues/2089 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2089/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2089/comments | https://api.github.com/repos/huggingface/datasets/issues/2089/events | https://github.com/huggingface/datasets/issues/2089 | 836,788,019 | MDU6SXNzdWU4MzY3ODgwMTk= | 2,089 | Add documentaton for dataset README.md files | {
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"Hi ! We are using the [datasets-tagging app](https://github.com/huggingface/datasets-tagging) to select the tags to add.\r\n\r\nWe are also adding the full list of tags in #2107 \r\nThis covers multilinguality, language_creators, licenses, size_categories and task_categories.\r\n\r\nIn general if you want to add a... | 2021-03-20T11:44:38Z | 2023-07-25T16:45:38Z | 2023-07-25T16:45:37Z | CONTRIBUTOR | null | null | null | Hi,
the dataset README files have special headers.
Somehow a documenation of the allowed values and tags is missing.
Could you add that?
Just to give some concrete questions that should be answered imo:
- which values can be passted to multilinguality?
- what should be passed to language_creators?
- which values should licenses have? What do I say when it is a custom license? Should I add a link?
- how should I choose size_categories ? What are valid ranges?
- what are valid task_categories?
Thanks
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"Hi @lhoestq \r\n\r\nI have added the readme file as well, please if you could check it once \r\n\r\nThank you "
] | 2020-12-12T16:23:49Z | 2020-12-14T20:45:24Z | 2020-12-14T20:45:24Z | CONTRIBUTOR | null | 0 | {
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