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https://api.github.com/repos/huggingface/datasets/issues/7211 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7211/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7211/comments | https://api.github.com/repos/huggingface/datasets/issues/7211/events | https://github.com/huggingface/datasets/issues/7211 | 2,576,400,502 | I_kwDODunzps6ZkMB2 | 7,211 | Describe only selected fields in README | {
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] | open | false | null | [] | null | [] | 2024-10-09T16:25:47Z | 2024-10-09T16:25:47Z | null | NONE | null | null | {
"completed": 0,
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} | ### Feature request
Hi Datasets team!
Is it possible to add the ability to describe only selected fields of the dataset files in `README.md`? For example, I have this open dataset ([open-llm-leaderboard/results](https://huggingface.co/datasets/open-llm-leaderboard/results?row=0)) and I want to describe only some fields in order not to overcomplicate the Dataset Preview and filter out some fields
### Motivation
The `Results` dataset for the Open LLM Leaderboard contains json files with a complex nested structure. I would like to add `README.md` there to use the SQL console, for example. But if I describe the structure of this dataset completely, it will overcomplicate the use of Dataset Preview and the total number of columns will exceed 50
### Your contribution
I'm afraid I'm not familiar with the project structure, so I won't be able to open a PR, but I'll try to help with something else if possible | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7374 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7374/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7374/comments | https://api.github.com/repos/huggingface/datasets/issues/7374/events | https://github.com/huggingface/datasets/pull/7374 | 2,793,442,320 | PR_kwDODunzps6IC66n | 7,374 | Remove .h5 from imagefolder extensions | {
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} | [] | closed | false | null | [] | null | [] | 2025-01-16T18:17:24Z | 2025-01-16T18:26:40Z | 2025-01-16T18:26:38Z | MEMBER | null | null | null | the format is not relevant for imagefolder, and makes the viewer fail to process datasets on HF (so many that the viewer takes more time to process new datasets) | {
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https://api.github.com/repos/huggingface/datasets/issues/5221 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5221/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5221/comments | https://api.github.com/repos/huggingface/datasets/issues/5221/events | https://github.com/huggingface/datasets/issues/5221 | 1,442,309,094 | I_kwDODunzps5V9-Pm | 5,221 | Cannot push | {
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"Did you run `huggingface-cli lfs-enable-largefiles` before committing or before adding ? Maybe you can try before adding\r\n\r\nAnyway I'd encourage you to split your data into several TAR archives if possible, this way the dataset can loaded faster using multiprocessing (by giving each process a subset of shards ... | 2022-11-09T15:32:05Z | 2022-11-10T18:11:21Z | 2022-11-10T18:11:11Z | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
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} | ### Describe the bug
I am facing the issue when I try to push the tar.gz file around 11G to HUB.
```
(venv) ╭─laptop@laptop ~/PersonalProjects/data/ulaanbal_v0 ‹main●›
╰─$ du -sh *
4.0K README.md
13G data
516K test.jsonl
18M train.jsonl
4.0K ulaanbal_v0.py
11G ulaanbal_v0.tar.gz
452K validation.jsonl
(venv) ╭─laptop@laptop~/PersonalProjects/data/ulaanbal_v0 ‹main●›
╰─$ git add ulaanbal_v0.tar.gz && git commit -m 'large version'
(venv) ╭─laptop@laptop ~/PersonalProjects/data/ulaanbal_v0 ‹main●›
╰─$ git push
EOFoading LFS objects: 0% (0/1), 0 B | 0 B/s
Uploading LFS objects: 0% (0/1), 0 B | 0 B/s, done.
error: failed to push some refs to 'https://huggingface.co/datasets/bayartsogt/ulaanbal_v0'
```
I have already tried pushing a small version of this and it was working fine. So my guess it is probably because of the big file.
Following I run before the commit:
```
╰─$ git lfs install
╰─$ huggingface-cli lfs-enable-largefiles .
```
### Steps to reproduce the bug
Create a private dataset on huggingface and push 12G tar.gz file
### Expected behavior
To be pushed with no issue
### Environment info
- `datasets` version: 2.6.1
- Platform: Darwin-21.6.0-x86_64-i386-64bit
- Python version: 3.7.11
- PyArrow version: 10.0.0
- Pandas version: 1.3.5
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https://api.github.com/repos/huggingface/datasets/issues/6279 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6279/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6279/comments | https://api.github.com/repos/huggingface/datasets/issues/6279/events | https://github.com/huggingface/datasets/issues/6279 | 1,928,028,226 | I_kwDODunzps5y62BC | 6,279 | Batched IterableDataset | {
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"This is exactly what I was looking for. It would also be very useful for me :-)",
"This issue is really smashing the selling point of HF datasets... The only workaround I've found so far is to create a customized IterableDataloader which improves the loading speed to some extent.\r\n\r\nFor example I've a HF dat... | 2023-10-05T11:12:49Z | 2024-11-07T10:01:22Z | null | NONE | null | null | {
"completed": 0,
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} | ### Feature request
Hi,
could you add an implementation of a batched `IterableDataset`. It already support an option to do batch iteration via `.iter(batch_size=...)` but this cannot be used in combination with a torch `DataLoader` since it just returns an iterator.
### Motivation
The current implementation loads each element of a batch individually which can be very slow in cases of a big batch_size. I did some experiments [here](https://discuss.huggingface.co/t/slow-dataloader-with-big-batch-size/57224) and using a batched iteration would speed up data loading significantly.
### Your contribution
N/A | null | {
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https://api.github.com/repos/huggingface/datasets/issues/5825 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5825/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5825/comments | https://api.github.com/repos/huggingface/datasets/issues/5825/events | https://github.com/huggingface/datasets/issues/5825 | 1,697,327,483 | I_kwDODunzps5lKyl7 | 5,825 | FileNotFound even though exists | {
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"Hi! \r\n\r\nThis would only work if `bigscience/xP3` was a no-code dataset, but it isn't (it has a Python builder script).\r\n\r\nBut this should work: \r\n```python\r\nload_dataset(\"json\", data_files=\"https://huggingface.co/datasets/bigscience/xP3/resolve/main/ur/xp3_facebook_flores_spa_Latn-urd_Arab_devtest_a... | 2023-05-05T09:49:55Z | 2023-08-16T10:02:01Z | 2023-08-16T10:02:01Z | CONTRIBUTOR | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
I'm trying to download https://huggingface.co/datasets/bigscience/xP3/resolve/main/ur/xp3_facebook_flores_spa_Latn-urd_Arab_devtest_ab-spa_Latn-urd_Arab.jsonl which works fine in my webbrowser, but somehow not with datasets. Am I doing sth wrong?
```
Downloading builder script: 100%
2.82k/2.82k [00:00<00:00, 64.2kB/s]
Downloading readme: 100%
12.6k/12.6k [00:00<00:00, 585kB/s]
---------------------------------------------------------------------------
FileNotFoundError Traceback (most recent call last)
[<ipython-input-2-4b45446a91d5>](https://localhost:8080/#) in <cell line: 4>()
2 lang = "ur"
3 fname = "xp3_facebook_flores_spa_Latn-urd_Arab_devtest_ab-spa_Latn-urd_Arab.jsonl"
----> 4 dataset = load_dataset("bigscience/xP3", data_files=f"{lang}/{fname}")
6 frames
[/usr/local/lib/python3.10/dist-packages/datasets/data_files.py](https://localhost:8080/#) in _resolve_single_pattern_locally(base_path, pattern, allowed_extensions)
291 if allowed_extensions is not None:
292 error_msg += f" with any supported extension {list(allowed_extensions)}"
--> 293 raise FileNotFoundError(error_msg)
294 return sorted(out)
295
FileNotFoundError: Unable to find 'https://huggingface.co/datasets/bigscience/xP3/resolve/main/ur/xp3_facebook_flores_spa_Latn-urd_Arab_devtest_ab-spa_Latn-urd_Arab.jsonl' at /content/https:/huggingface.co/datasets/bigscience/xP3/resolve/main
```
### Steps to reproduce the bug
```
!pip install -q datasets
from datasets import load_dataset
lang = "ur"
fname = "xp3_facebook_flores_spa_Latn-urd_Arab_devtest_ab-spa_Latn-urd_Arab.jsonl"
dataset = load_dataset("bigscience/xP3", data_files=f"{lang}/{fname}")
```
### Expected behavior
Correctly downloads
### Environment info
latest versions | {
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https://api.github.com/repos/huggingface/datasets/issues/4929 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4929/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4929/comments | https://api.github.com/repos/huggingface/datasets/issues/4929/events | https://github.com/huggingface/datasets/pull/4929 | 1,361,508,366 | PR_kwDODunzps4-WK2w | 4,929 | Fixes a typo in loading documentation | {
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https://api.github.com/repos/huggingface/datasets/issues/4668 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4668/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4668/comments | https://api.github.com/repos/huggingface/datasets/issues/4668/events | https://github.com/huggingface/datasets/issues/4668 | 1,299,735,893 | I_kwDODunzps5NeGVV | 4,668 | Dataset Viewer issue for hungnm/multilingual-amazon-review-sentiment-processed | {
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"It seems like a private dataset. The viewer is currently not supported on the private datasets."
] | 2022-07-09T18:04:13Z | 2022-07-11T07:47:47Z | 2022-07-11T07:47:47Z | NONE | null | null | {
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} | ### Link
https://huggingface.co/hungnm/multilingual-amazon-review-sentiment
### Description
_No response_
### Owner
Yes | {
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https://api.github.com/repos/huggingface/datasets/issues/5298 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5298/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5298/comments | https://api.github.com/repos/huggingface/datasets/issues/5298/events | https://github.com/huggingface/datasets/issues/5298 | 1,464,681,871 | I_kwDODunzps5XTUWP | 5,298 | Bug in xopen with Windows pathnames | {
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From its implementation:
```python
def xopen(file: str, mode="r", *args, **kwargs):
file = _as_posix(PurePath(file))
main_hop, *rest_hops = file.split("::")
if is_local_path(main_hop):
return open(file, mode, *args, **kwargs)
```
On a Windows machine, if we pass the argument:
```python
xopen("C:\\Users\\USERNAME\\filename.txt")
```
it returns
```python
open("C:/Users/USERNAME/filename.txt")
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https://api.github.com/repos/huggingface/datasets/issues/4618 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4618/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4618/comments | https://api.github.com/repos/huggingface/datasets/issues/4618/events | https://github.com/huggingface/datasets/issues/4618 | 1,292,078,225 | I_kwDODunzps5NA4yR | 4,618 | contribute data loading for object detection datasets with yolo data format | {
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"Hi! The `imagefolder` script is already quite complex, so a standalone script sounds better. Also, I suggest we create an org on the Hub (e.g. `hf-loaders`) and store such scripts there for easier maintenance rather than having them as packaged modules (IMO only very generic loaders should be packaged). WDYT @lhoe... | 2022-07-02T15:21:59Z | 2022-07-21T14:10:44Z | null | NONE | null | null | {
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} | **Is your feature request related to a problem? Please describe.**
At the moment, HF datasets loads [image classification datasets](https://huggingface.co/docs/datasets/image_process) out-of-the-box. There could be a data loader for loading standard object detection datasets ([original discussion here](https://huggingface.co/datasets/jalFaizy/detect_chess_pieces/discussions/2))
**Describe the solution you'd like**
I wrote a [custom script](https://huggingface.co/datasets/jalFaizy/detect_chess_pieces/blob/main/detect_chess_pieces.py) to load dataset which has YOLO data format.
**Describe alternatives you've considered**
The script can either be a standalone dataset builder, or a modified version of `ImageFolder`
**Additional context**
I would be happy to contribute to this, but I would do it at a very slow pace (maybe a month or two) as I have my exams approaching 😄
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https://api.github.com/repos/huggingface/datasets/issues/5823 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5823/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5823/comments | https://api.github.com/repos/huggingface/datasets/issues/5823/events | https://github.com/huggingface/datasets/issues/5823 | 1,697,024,789 | I_kwDODunzps5lJosV | 5,823 | [2.12.0] DatasetDict.save_to_disk not saving to S3 | {
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"Hi ! Can you try adding the `s3://` prefix ?\r\n```python\r\nf\"s3://{s3_bucket}/{s3_dir}/{dataset_name}\"\r\n```",
"Ugh, yeah that was it. Thank you!",
"Hi @thejamesmarq, by any chance, did you use multiprocessing `num_proc > 1` when saving your dataset on the s3 bucket ? I'm struggling making it work in a mu... | 2023-05-05T05:22:59Z | 2024-05-30T16:11:31Z | 2023-05-05T15:01:17Z | NONE | null | null | {
"completed": 0,
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} | ### Describe the bug
When trying to save a `DatasetDict` to a private S3 bucket using `save_to_disk`, the artifacts are instead saved locally, and not in the S3 bucket.
I have tried using the deprecated `fs` as well as the `storage_options` arguments and I get the same results.
### Steps to reproduce the bug
1. Create a DatsetDict `dataset`
2. Create a S3FileSystem object
`s3 = datasets.filesystems.S3FileSystem(key=aws_access_key_id, secret=aws_secret_access_key)`
3. Save using `dataset_dict.save_to_disk(f"{s3_bucket}/{s3_dir}/{dataset_name}", storage_options=s3.storage_options)` or `dataset_dict.save_to_disk(f"{s3_bucket}/{s3_dir}/{dataset_name}", fs=s3)`
4. Check the corresponding S3 bucket and verify nothing has been uploaded
5. Check the path at f"{s3_bucket}/{s3_dir}/{dataset_name}" and verify that files have been saved there
### Expected behavior
Artifacts are uploaded at the f"{s3_bucket}/{s3_dir}/{dataset_name}" S3 location.
### Environment info
- `datasets` version: 2.12.0
- Platform: macOS-13.3.1-x86_64-i386-64bit
- Python version: 3.11.2
- Huggingface_hub version: 0.14.1
- PyArrow version: 12.0.0
- Pandas version: 2.0.1 | {
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https://api.github.com/repos/huggingface/datasets/issues/6360 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6360/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6360/comments | https://api.github.com/repos/huggingface/datasets/issues/6360/events | https://github.com/huggingface/datasets/issues/6360 | 1,965,672,950 | I_kwDODunzps51Kcn2 | 6,360 | Add support for `Sequence(Audio/Image)` feature in `push_to_hub` | {
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"This issue stems from https://github.com/huggingface/datasets/blob/6d2f2a5e0fea3827eccfd1717d8021c15fc4292a/src/datasets/table.py#L2203-L2205\r\n\r\nI'll address it as part of https://github.com/huggingface/datasets/pull/6283.\r\n\r\nIn the meantime, this should work\r\n\r\n```python\r\nimport pyarrow as pa\r\nfro... | 2023-10-27T14:39:57Z | 2024-02-06T19:24:20Z | 2024-02-06T19:24:20Z | CONTRIBUTOR | null | null | {
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} | ### Feature request
Allow for `Sequence` of `Image` (or `Audio`) to be embedded inside the shards.
### Motivation
Currently, thanks to #3685, when `embed_external_files` is set to True (which is the default) in `push_to_hub`, features of type `Image` and `Audio` are embedded inside the arrow/parquet shards, instead of only storing paths to the files.
I've noticed that this behavior does not extend to `Sequence` of `Image`, when working with a [dataset of timelapse images](https://huggingface.co/datasets/1aurent/Human-Embryo-Timelapse).
### Your contribution
I'll submit a PR if I find a way to add this feature | {
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https://api.github.com/repos/huggingface/datasets/issues/4814 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4814/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4814/comments | https://api.github.com/repos/huggingface/datasets/issues/4814/events | https://github.com/huggingface/datasets/issues/4814 | 1,333,356,230 | I_kwDODunzps5PeWbG | 4,814 | Support CSV as metadata file format in AudioFolder/ImageFolder | {
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} | Requested here: https://discuss.huggingface.co/t/how-to-structure-an-image-dataset-repo-using-the-image-folder-approach/21004. CSV is also used in AutoTrain for specifying metadata in image datasets. | {
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https://api.github.com/repos/huggingface/datasets/issues/6450 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6450/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6450/comments | https://api.github.com/repos/huggingface/datasets/issues/6450/events | https://github.com/huggingface/datasets/issues/6450 | 2,009,491,386 | I_kwDODunzps53xme6 | 6,450 | Support multiple image/audio columns in ImageFolder/AudioFolder | {
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"A duplicate of https://github.com/huggingface/datasets/issues/5760"
] | 2023-11-24T10:34:09Z | 2023-11-28T11:07:17Z | 2023-11-24T17:24:38Z | COLLABORATOR | null | null | {
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} | ### Feature request
Have a metadata.csv file with multiple columns that point to relative image or audio files.
### Motivation
Currently, ImageFolder allows one column, called `file_name`, pointing to relative image files. On the same model, AudioFolder allows one column, called `file_name`, pointing to relative audio files.
But it's not possible to have two image columns, or to have two audio column, or to have one audio column and one image column.
### Your contribution
no specific contribution | {
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https://api.github.com/repos/huggingface/datasets/issues/6163 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6163/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6163/comments | https://api.github.com/repos/huggingface/datasets/issues/6163/events | https://github.com/huggingface/datasets/issues/6163 | 1,857,682,241 | I_kwDODunzps5uuftB | 6,163 | Error type: ArrowInvalid Details: Failed to parse string: '[254,254]' as a scalar of type int32 | {
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"Answered on the forum [here](https://discuss.huggingface.co/t/error-type-arrowinvalid-details-failed-to-parse-string-254-254-as-a-scalar-of-type-int32/51323)."
] | 2023-08-19T11:34:40Z | 2023-08-21T13:28:16Z | null | NONE | null | null | {
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} | ### Describe the bug
I am getting the following error while I am trying to upload the CSV sheet to train a model. My CSV sheet content is exactly same as shown in the example CSV file in the Auto Train page. Attaching screenshot of error for reference. I have also tried converting the index of the answer that are integer into string by placing inverted commas and also without inverted commas.
Can anyone please help me out?
FYI : I am using Chrome browser.
Error type: ArrowInvalid
Details: Failed to parse string: '[254,254]' as a scalar of type int32
### Steps to reproduce the bug
Kindly let me know how to fix this?
### Expected behavior
Kindly let me know how to fix this?
### Environment info
Kindly let me know how to fix this? | null | {
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https://api.github.com/repos/huggingface/datasets/issues/5022 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5022/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5022/comments | https://api.github.com/repos/huggingface/datasets/issues/5022/events | https://github.com/huggingface/datasets/pull/5022 | 1,385,432,859 | PR_kwDODunzps4_kxYe | 5,022 | Fix languages of X-CSQA configs in xcsr dataset | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Thanks @lhoestq, I had missed that... ",
"thx for the super fast work @albertvillanova ! any estimate for when the relevant release will happen?\r\n\r\nThanks again ",
"@thesofakillers after a recent change in our library (see #4... | 2022-09-26T05:13:39Z | 2022-09-26T12:27:20Z | 2022-09-26T10:57:30Z | MEMBER | null | null | null | Fix #5017.
CC: @yangxqiao, @yuchenlin | {
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https://api.github.com/repos/huggingface/datasets/issues/7343 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7343/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7343/comments | https://api.github.com/repos/huggingface/datasets/issues/7343/events | https://github.com/huggingface/datasets/issues/7343 | 2,750,525,823 | I_kwDODunzps6j8bF_ | 7,343 | [Bug] Inconsistent behavior of data_files and data_dir in load_dataset method. | {
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"Hi ! `data_files` with a list is equivalent to `data_files={\"train\": data_files}` with a train test only.\r\n\r\nWhen no split are specified, they are inferred based on file names, and files with no apparent split are ignored",
"Thanks for your reply!\r\n`files with no apparent split are ignored`. Is there a o... | 2024-12-19T14:31:27Z | 2025-01-03T15:54:09Z | 2025-01-03T15:54:09Z | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
Inconsistent operation of data_files and data_dir in load_dataset method.
### Steps to reproduce the bug
# First
I have three files, named 'train.json', 'val.json', 'test.json'.
Each one has a simple dict `{text:'aaa'}`.
Their path are `/data/train.json`, `/data/val.json`, `/data/test.json`
I load dataset with `data_files` argument:
```py
files = [os.path.join('./data',file) for file in os.listdir('./data')]
ds = load_dataset(
path='json',
data_files=files,)
```
And I get:
```py
DatasetDict({
train: Dataset({
features: ['text'],
num_rows: 3
})
})
```
However, If I load dataset with `data_dir` argument:
```py
ds = load_dataset(
path='json',
data_dir='./data',)
```
And I get:
```py
DatasetDict({
train: Dataset({
features: ['text'],
num_rows: 1
})
validation: Dataset({
features: ['text'],
num_rows: 1
})
test: Dataset({
features: ['text'],
num_rows: 1
})
})
```
Two results are not the same. Their behaviors are not equal, even if the statement [here](https://github.com/huggingface/datasets/blob/d0c152a979d91cc34b605c0298aebc650ab7dd27/src/datasets/load.py#L1790) said that their behaviors are equal.
# Second
If some filename include 'test' while others do not, `load_dataset` only return `test` dataset and others files are **abandoned**.
Given two files named `test.json` and `1.json`
Each one has a simple dict `{text:'aaa'}`.
I load the dataset using:
```py
ds = load_dataset(
path='json',
data_dir='./data',)
```
Only `test` is returned, `1.json` is missing:
```py
DatasetDict({
test: Dataset({
features: ['text'],
num_rows: 1
})
})
```
Things do not change even I manually set `split='train'`
### Expected behavior
1. Fix the above bugs.
2. Although the document says that load_dataset method will `Find which file goes into which split (e.g. train/test) based on file and directory names or on the YAML configuration`, I hope I can manually decide whether to do so. Sometimes users may accidentally put a `test` string in the filename but they just want a single `train` dataset. If the number of files in `data_dir` is huge, it's not easy to find out what cause the second situation metioned above.
### Environment info
datasets==3.2.0
Ubuntu18.84 | {
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https://api.github.com/repos/huggingface/datasets/issues/6714 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6714/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6714/comments | https://api.github.com/repos/huggingface/datasets/issues/6714/events | https://github.com/huggingface/datasets/pull/6714 | 2,167,569,080 | PR_kwDODunzps5ooQd2 | 6,714 | Expand no-code dataset info with datasets-server info | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6714). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>... | 2024-03-04T19:18:10Z | 2024-03-04T20:28:30Z | 2024-03-04T20:22:15Z | COLLABORATOR | null | null | null | E.g., to have info about a dataset's number of examples for more informative TQDM bars. | {
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https://api.github.com/repos/huggingface/datasets/issues/7274 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7274/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7274/comments | https://api.github.com/repos/huggingface/datasets/issues/7274/events | https://github.com/huggingface/datasets/pull/7274 | 2,629,882,821 | PR_kwDODunzps6ArEt- | 7,274 | [MINOR:TYPO] Fix typo in exception text | {
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https://api.github.com/repos/huggingface/datasets/issues/7458 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7458/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7458/comments | https://api.github.com/repos/huggingface/datasets/issues/7458/events | https://github.com/huggingface/datasets/issues/7458 | 2,925,403,528 | I_kwDODunzps6uXh2I | 7,458 | Loading the `laion/filtered-wit` dataset in streaming mode fails on v3.4.0 | {
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"thanks for reporting, I released 3.4.1 with a fix"
] | 2025-03-17T14:54:02Z | 2025-03-17T16:02:04Z | 2025-03-17T15:25:55Z | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
Loading https://huggingface.co/datasets/laion/filtered-wit in streaming mode fails after update to `datasets==3.4.0`. The dataset loads fine on v3.3.2.
### Steps to reproduce the bug
Steps to reproduce:
```
pip install datastes==3.4.0
python -c "from datasets import load_dataset; load_dataset('laion/filtered-wit', split='train', streaming=True)"
```
Results in:
```
$ python -c "from datasets import load_dataset; load_dataset('laion/filtered-wit', split='train', streaming=True)"
Repo card metadata block was not found. Setting CardData to empty.
Resolving data files: 100%|█████████████████████████████████████████████████████████████████████████████████████████████| 560/560 [00:00<00:00, 2280.24it/s]
Traceback (most recent call last):
File "<string>", line 1, in <module>
File "/home/nsavel/venvs/tmp/lib/python3.9/site-packages/datasets/load.py", line 2080, in load_dataset
return builder_instance.as_streaming_dataset(split=split)
File "/home/nsavel/venvs/tmp/lib/python3.9/site-packages/datasets/builder.py", line 1265, in as_streaming_dataset
splits_generators = {sg.name: sg for sg in self._split_generators(dl_manager)}
File "/home/nsavel/venvs/tmp/lib/python3.9/site-packages/datasets/packaged_modules/parquet/parquet.py", line 49, in _split_generators
data_files = dl_manager.download_and_extract(self.config.data_files)
File "/home/nsavel/venvs/tmp/lib/python3.9/site-packages/datasets/download/streaming_download_manager.py", line 169, in download_and_extract
return self.extract(self.download(url_or_urls))
File "/home/nsavel/venvs/tmp/lib/python3.9/site-packages/datasets/download/streaming_download_manager.py", line 121, in extract
urlpaths = map_nested(self._extract, url_or_urls, map_tuple=True)
File "/home/nsavel/venvs/tmp/lib/python3.9/site-packages/datasets/utils/py_utils.py", line 496, in map_nested
mapped = [
File "/home/nsavel/venvs/tmp/lib/python3.9/site-packages/datasets/utils/py_utils.py", line 497, in <listcomp>
map_nested(
File "/home/nsavel/venvs/tmp/lib/python3.9/site-packages/datasets/utils/py_utils.py", line 513, in map_nested
mapped = [
File "/home/nsavel/venvs/tmp/lib/python3.9/site-packages/datasets/utils/py_utils.py", line 514, in <listcomp>
_single_map_nested((function, obj, batched, batch_size, types, None, True, None))
File "/home/nsavel/venvs/tmp/lib/python3.9/site-packages/datasets/utils/py_utils.py", line 375, in _single_map_nested
return function(data_struct)
File "/home/nsavel/venvs/tmp/lib/python3.9/site-packages/datasets/download/streaming_download_manager.py", line 131, in _extract
raise NotImplementedError(
NotImplementedError: Extraction protocol for TAR archives like 'hf://datasets/laion/filtered-wit@c38ca7464e9934d9a49f88b3f60f5ad63b245465/data/00000.tar' is not implemented in streaming mode. Please use `dl_manager.iter_archive` instead.
Example usage:
url = dl_manager.download(url)
tar_archive_iterator = dl_manager.iter_archive(url)
for filename, file in tar_archive_iterator:
...
```
### Expected behavior
Dataset loads successfully.
### Environment info
Ubuntu 20.04.6. Python 3.9. Datasets 3.4.0.
pip freeze:
```
aiohappyeyeballs==2.6.1
aiohttp==3.11.14
aiosignal==1.3.2
async-timeout==5.0.1
attrs==25.3.0
certifi==2025.1.31
charset-normalizer==3.4.1
datasets==3.4.0
dill==0.3.8
filelock==3.18.0
frozenlist==1.5.0
fsspec==2024.12.0
huggingface-hub==0.29.3
idna==3.10
multidict==6.1.0
multiprocess==0.70.16
numpy==2.0.2
packaging==24.2
pandas==2.2.3
propcache==0.3.0
pyarrow==19.0.1
python-dateutil==2.9.0.post0
pytz==2025.1
PyYAML==6.0.2
requests==2.32.3
six==1.17.0
tqdm==4.67.1
typing_extensions==4.12.2
tzdata==2025.1
urllib3==2.3.0
xxhash==3.5.0
yarl==1.18.3
``` | {
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```
ImportError: cannot import name 'TypeAliasType' from 'typing_extensions'
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https://api.github.com/repos/huggingface/datasets/issues/7116 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7116/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7116/comments | https://api.github.com/repos/huggingface/datasets/issues/7116/events | https://github.com/huggingface/datasets/issues/7116 | 2,475,522,721 | I_kwDODunzps6TjXqh | 7,116 | datasets cannot handle nested json if features is given. | {
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"Hi ! `Sequence` has a weird behavior for dictionaries (from tensorflow-datasets), use a regular list instead:\r\n\r\n```python\r\nds = datasets.load_dataset('json', data_files=\"./temp.json\", features=datasets.Features({\r\n 'ref1': datasets.Value('string'),\r\n 'ref2': datasets.Value('string'),\r\n 'cut... | 2024-08-20T12:27:49Z | 2024-09-03T10:18:23Z | 2024-09-03T10:18:07Z | NONE | null | null | {
"completed": 0,
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} | ### Describe the bug
I have a json named temp.json.
```json
{"ref1": "ABC", "ref2": "DEF", "cuts":[{"cut1": 3, "cut2": 5}]}
```
I want to load it.
```python
ds = datasets.load_dataset('json', data_files="./temp.json", features=datasets.Features({
'ref1': datasets.Value('string'),
'ref2': datasets.Value('string'),
'cuts': datasets.Sequence({
"cut1": datasets.Value("uint16"),
"cut2": datasets.Value("uint16")
})
}))
```
The above code does not work. However, I can load it without giving features.
```python
ds = datasets.load_dataset('json', data_files="./temp.json")
```
Is it possible to load integers as uint16 to save some memory?
### Steps to reproduce the bug
As in the bug description.
### Expected behavior
The data are loaded and integers are uint16.
### Environment info
Copy-and-paste the text below in your GitHub issue.
- `datasets` version: 2.21.0
- Platform: Linux-5.15.0-118-generic-x86_64-with-glibc2.35
- Python version: 3.11.9
- `huggingface_hub` version: 0.24.5
- PyArrow version: 17.0.0
- Pandas version: 2.2.2
- `fsspec` version: 2024.5.0 | {
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"Does the torch `DataLoader` really require the dataset to be a subclass of `torch.utils.data.Dataset` ? Or is there a simpler type we could use ?\n\nPS: also note that a dataset without `with_format()` can also be used in a torch `DataLoader` . Calling `with_format(\"torch\")` simply makes the output of the datase... | 2025-04-06T09:56:09Z | 2025-04-15T12:57:39Z | null | NONE | null | null | {
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} | ### Feature request
Currently `datasets` does not correctly indicate to the Python type-checker (e.g. `pyright` / `Pylance`) that the output of `with_format` is compatible with PyTorch's `Dataloader` since it does not indicate that the HuggingFace `Dataset` is compatible with the PyTorch `Dataset` class. It would be great if we could get the typing to work nicely.
### Motivation
To avoid casting types in our Python code.
### Your contribution
I would be happy to contribute a PR if this is something that may be accepted and could work with the current approach.
This doesn't have to be for just PyTorch, but I imagine that the same thing would be useful for `tensorflow` and such, but we only have a need for PyTorch at this stage. | null | {
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https://api.github.com/repos/huggingface/datasets/issues/5248 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5248/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5248/comments | https://api.github.com/repos/huggingface/datasets/issues/5248/events | https://github.com/huggingface/datasets/pull/5248 | 1,451,338,676 | PR_kwDODunzps5DAqwt | 5,248 | Complete doc migration | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5248). All of your documentation changes will be reflected on that endpoint.",
"Thanks for the fix @mishig25.\r\n\r\nI guess this is the reason why the docs are not generated for the latest release version 2.7.0? https://huggin... | 2022-11-16T10:41:04Z | 2022-11-16T15:06:50Z | 2022-11-16T10:41:10Z | NONE | null | null | null | Reverts huggingface/datasets#5214
Everything is handled on the doc-builder side now 😊 | {
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https://api.github.com/repos/huggingface/datasets/issues/5342 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5342/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5342/comments | https://api.github.com/repos/huggingface/datasets/issues/5342/events | https://github.com/huggingface/datasets/issues/5342 | 1,485,244,178 | I_kwDODunzps5YhwcS | 5,342 | Emotion dataset cannot be downloaded | {
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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 | {
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} | ### 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/4631 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4631/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4631/comments | https://api.github.com/repos/huggingface/datasets/issues/4631/events | https://github.com/huggingface/datasets/pull/4631 | 1,293,545,900 | PR_kwDODunzps460Vy0 | 4,631 | Update WinoBias README | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-07-04T20:24:40Z | 2022-07-07T13:23:32Z | 2022-07-07T13:11:47Z | CONTRIBUTOR | null | null | null | I'm adding some information about Winobias that I got from the paper :smile:
I think this makes it a bit clearer! | {
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https://api.github.com/repos/huggingface/datasets/issues/6064 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6064/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6064/comments | https://api.github.com/repos/huggingface/datasets/issues/6064/events | https://github.com/huggingface/datasets/pull/6064 | 1,818,703,725 | PR_kwDODunzps5WPzAv | 6,064 | set dev version | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6064). 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... | 2023-07-24T15:56:00Z | 2023-07-24T16:05:19Z | 2023-07-24T15:56:10Z | MEMBER | null | null | null | null | {
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https://api.github.com/repos/huggingface/datasets/issues/6536 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6536/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6536/comments | https://api.github.com/repos/huggingface/datasets/issues/6536/events | https://github.com/huggingface/datasets/issues/6536 | 2,056,863,239 | I_kwDODunzps56mT4H | 6,536 | datasets.load_dataset raises FileNotFoundError for datasets==2.16.0 | {
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"Hi ! Thanks for reporting\r\n\r\nThis is a bug in 2.16.0 for some datasets when `cache_dir` is a relative path. I opened https://github.com/huggingface/datasets/pull/6543 to fix this",
"We just released 2.16.1 with a fix:\r\n\r\n```\r\npip install -U datasets\r\n```"
] | 2023-12-27T03:15:48Z | 2023-12-30T18:58:04Z | 2023-12-30T15:54:00Z | NONE | null | null | {
"completed": 0,
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} | ### Describe the bug
Seems `datasets.load_dataset` raises FileNotFoundError for some hub datasets with the latest `datasets==2.16.0`
### Steps to reproduce the bug
For example `pip install datasets==2.16.0`
then
```python
import datasets
datasets.load_dataset("wentingzhao/anthropic-hh-first-prompt", cache_dir='cache1')["train"]
```
This will raise:
```bash
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/Users/xxx/miniconda3/envs/env/lib/python3.9/site-packages/datasets/load.py", line 2545, in load_dataset
builder_instance.download_and_prepare(
File "/Users/xxx/miniconda3/envs/env/lib/python3.9/site-packages/datasets/builder.py", line 1003, in download_and_prepare
self._download_and_prepare(
File "/Users/xxx/miniconda3/envs/env/lib/python3.9/site-packages/datasets/builder.py", line 1076, in _download_and_prepare
split_generators = self._split_generators(dl_manager, **split_generators_kwargs)
File "/Users/xxx/miniconda3/envs/env/lib/python3.9/site-packages/datasets/packaged_modules/parquet/parquet.py", line 43, in _split_generators
data_files = dl_manager.download_and_extract(self.config.data_files)
File "/Users/xxx/miniconda3/envs/env/lib/python3.9/site-packages/datasets/download/download_manager.py", line 566, in download_and_extract
return self.extract(self.download(url_or_urls))
File "/Users/xxx/miniconda3/envs/env/lib/python3.9/site-packages/datasets/download/download_manager.py", line 539, in extract
extracted_paths = map_nested(
File "/Users/xxx/miniconda3/envs/env/lib/python3.9/site-packages/datasets/utils/py_utils.py", line 466, in map_nested
mapped = [
File "/Users/xxx/miniconda3/envs/env/lib/python3.9/site-packages/datasets/utils/py_utils.py", line 467, in <listcomp>
_single_map_nested((function, obj, types, None, True, None))
File "/Users/xxx/miniconda3/envs/env/lib/python3.9/site-packages/datasets/utils/py_utils.py", line 387, in _single_map_nested
mapped = [_single_map_nested((function, v, types, None, True, None)) for v in pbar]
File "/Users/xxx/miniconda3/envs/env/lib/python3.9/site-packages/datasets/utils/py_utils.py", line 387, in <listcomp>
mapped = [_single_map_nested((function, v, types, None, True, None)) for v in pbar]
File "/Users/xxx/miniconda3/envs/env/lib/python3.9/site-packages/datasets/utils/py_utils.py", line 370, in _single_map_nested
return function(data_struct)
File "/Users/xxx/miniconda3/envs/env/lib/python3.9/site-packages/datasets/download/download_manager.py", line 451, in _download
out = cached_path(url_or_filename, download_config=download_config)
File "/Users/xxx/miniconda3/envs/env/lib/python3.9/site-packages/datasets/utils/file_utils.py", line 188, in cached_path
output_path = get_from_cache(
File "/Users/xxx/miniconda3/envs/env/lib/python3.9/site-packages/datasets/utils/file_utils.py", line 570, in get_from_cache
raise FileNotFoundError(f"Couldn't find file at {url}")
FileNotFoundError: Couldn't find file at https://huggingface.co/datasets/wentingzhao/anthropic-hh-first-prompt/resolve/11b393a5545f706a357ebcd4a5285d93db176715/cache1/downloads/87d66c365626feca116cba323c4856c9aae056e4503f09f23e34aa085eb9de15
```
However, seems it works fine for some datasets, for example, if works fine for `datasets.load_dataset("ag_news", cache_dir='cache2')["test"]`
But the dataset works fine for datasets==2.15.0, for example `pip install datasets==2.15.0`,
then
```python
import datasets
datasets.load_dataset("wentingzhao/anthropic-hh-first-prompt", cache_dir='cache3')["train"]
Dataset({
features: ['user', 'system', 'source'],
num_rows: 8552
})
```
### Expected behavior
2.16.0 should work as same as 2.15.0 for all datasets
### Environment info
python3.9
conda env
tested on MacOS and Linux | {
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https://api.github.com/repos/huggingface/datasets/issues/5377 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5377/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5377/comments | https://api.github.com/repos/huggingface/datasets/issues/5377/events | https://github.com/huggingface/datasets/pull/5377 | 1,503,477,833 | PR_kwDODunzps5Fz5lw | 5,377 | Add a parallel implementation of to_tf_dataset() | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Failing because the test server uses Py3.7 but the `SharedMemory` features require Py3.8! I forgot we still support 3.7 for another couple of months. I'm not sure exactly how to proceed, whether I should leave this PR until then, or ... | 2022-12-19T19:40:27Z | 2023-01-25T16:28:44Z | 2023-01-25T16:21:40Z | MEMBER | null | null | null | Hey all! Here's a first draft of the PR to add a multiprocessing implementation for `to_tf_dataset()`. It worked in some quick testing for me, but obviously I need to do some much more rigorous testing/benchmarking, and add some proper library tests.
The core idea is that we do everything using `multiprocessing` and `numpy`, and just wrap a `tf.data.Dataset` around the output. We could also rewrite the existing single-threaded implementation based on this code, which might simplify it a bit.
Checklist:
- [X] Add initial draft
- [x] Check that it works regardless of whether the `collate_fn` or dataset returns `tf` or `np` arrays
- [x] Check that it works with `tf.string` return data
- [x] Check indices are correctly reshuffled each epoch
- [x] Make sure workers don't try to initialize a GPU device!!
- [x] Check `fit()` with multiple epochs works fine and that the progress bar is correct
- [x] Check there are no memory leaks or zombie processes
- [x] Benchmark performance
- [x] Tweak params for dataset inference - can we speed things up there a bit?
- [x] Add tests to the library
- [x] Add a PR to `transformers` to expose the `num_workers` argument via `prepare_tf_dataset` (will merge after this one is released)
- [x] Stop TF console spam!! (almost)
- [x] Add a method for creating SHM that doesn't crash if it was left and still linked
- [x] Add a barrier for Py <= 3.7 because it doesn't support SharedMemory
- [x] Support string dtypes by converting them into fixed-width character arrays | {
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https://api.github.com/repos/huggingface/datasets/issues/5014 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5014/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5014/comments | https://api.github.com/repos/huggingface/datasets/issues/5014/events | https://github.com/huggingface/datasets/issues/5014 | 1,383,422,639 | I_kwDODunzps5SdVqv | 5,014 | I need to read the custom dataset in conll format | {
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"Hi! We don't currently have a builder for parsing custom `conll` datasets, but I guess we could add one as a packaged module (similarly to what [TFDS](https://github.com/tensorflow/datasets/blob/master/tensorflow_datasets/core/dataset_builders/conll/conll_dataset_builder.py) did). @lhoestq @albertvillanova WDYT?\r... | 2022-09-23T07:49:42Z | 2022-11-02T11:57:15Z | null | NONE | null | null | {
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} | I need to read the custom dataset in conll format
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https://api.github.com/repos/huggingface/datasets/issues/6395 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6395/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6395/comments | https://api.github.com/repos/huggingface/datasets/issues/6395/events | https://github.com/huggingface/datasets/issues/6395 | 1,986,484,124 | I_kwDODunzps52Z1ec | 6,395 | Add ability to set lock type | {
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"We've replaced our filelock implementation with the `filelock` package, so their repo is the right place to request this feature.\r\n\r\nIn the meantime, the following should work: \r\n```python\r\nimport filelock\r\nfilelock.FileLock = filelock.SoftFileLock\r\n\r\nimport datasets\r\n...\r\n```"
] | 2023-11-09T22:12:30Z | 2023-11-23T18:50:00Z | 2023-11-23T18:50:00Z | NONE | null | null | {
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} | ### Feature request
Allow setting file lock type, maybe from an environment variable
Currently, it only depends on whether fnctl is available:
https://github.com/huggingface/datasets/blob/12ebe695b4748c5a26e08b44ed51955f74f5801d/src/datasets/utils/filelock.py#L463-L470C16
### Motivation
In my environment, flock isn't supported on a network attached drive
### Your contribution
I'll be happy to submit a pr. | {
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https://api.github.com/repos/huggingface/datasets/issues/5582 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5582/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5582/comments | https://api.github.com/repos/huggingface/datasets/issues/5582/events | https://github.com/huggingface/datasets/pull/5582 | 1,600,932,092 | PR_kwDODunzps5K0ZcN | 5,582 | Add column_names to IterableDataset | {
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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... | 2023-02-27T10:50:07Z | 2023-03-13T19:10:22Z | 2023-03-13T19:03:32Z | CONTRIBUTOR | null | null | null | This PR closes #5383
* Add column_names property to IterableDataset
* Add multiple tests for this new property | {
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https://api.github.com/repos/huggingface/datasets/issues/4669 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4669/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4669/comments | https://api.github.com/repos/huggingface/datasets/issues/4669/events | https://github.com/huggingface/datasets/issues/4669 | 1,299,848,003 | I_kwDODunzps5NehtD | 4,669 | loading oscar-corpus/OSCAR-2201 raises an error | {
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"I had to use the appropriate token for use_auth_token. Thank you."
] | 2022-07-10T07:09:30Z | 2022-07-11T09:27:49Z | 2022-07-11T09:27:49Z | NONE | null | null | {
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} | ## Describe the bug
load_dataset('oscar-2201', 'af')
raises an error:
Traceback (most recent call last):
File "/usr/lib/python3.8/code.py", line 90, in runcode
exec(code, self.locals)
File "<input>", line 1, in <module>
File "..python3.8/site-packages/datasets/load.py", line 1656, in load_dataset
builder_instance = load_dataset_builder(
File ".../lib/python3.8/site-packages/datasets/load.py", line 1439, in load_dataset_builder
dataset_module = dataset_module_factory(
File ".../lib/python3.8/site-packages/datasets/load.py", line 1189, in dataset_module_factory
raise FileNotFoundError(
FileNotFoundError: Couldn't find a dataset script at .../oscar-2201/oscar-2201.py or any data file in the same directory. Couldn't find 'oscar-2201' on the Hugging Face Hub either: FileNotFoundError: Couldn't find file at https://raw.githubusercontent.com/huggingface/datasets/master/datasets/oscar-2201/oscar-2201.py
I've tried other permutations such as :
oscar_22 = load_dataset('oscar-2201', 'af',use_auth_token=True)
oscar_22 = load_dataset('oscar-corpus/OSCAR-2201', 'af',use_auth_token=True)
oscar_22 = load_dataset('oscar-2201', 'af')
oscar_22 = load_dataset('oscar-corpus/OSCAR-2201')
with the same unfortunate result.
## Steps to reproduce the bug
oscar_22 = load_dataset('oscar-2201', 'af',use_auth_token=True)
oscar_22 = load_dataset('oscar-corpus/OSCAR-2201', 'af',use_auth_token=True)
oscar_22 = load_dataset('oscar-2201', 'af')
oscar_22 = load_dataset('oscar-corpus/OSCAR-2201')
# Sample code to reproduce the bug
```
## Expected results
loaded data
## Actual results
Traceback (most recent call last):
File "/usr/lib/python3.8/code.py", line 90, in runcode
exec(code, self.locals)
File "<input>", line 1, in <module>
File "..python3.8/site-packages/datasets/load.py", line 1656, in load_dataset
builder_instance = load_dataset_builder(
File ".../lib/python3.8/site-packages/datasets/load.py", line 1439, in load_dataset_builder
dataset_module = dataset_module_factory(
File ".../lib/python3.8/site-packages/datasets/load.py", line 1189, in dataset_module_factory
raise FileNotFoundError(
FileNotFoundError: Couldn't find a dataset script at .../oscar-2201/oscar-2201.py or any data file in the same directory. Couldn't find 'oscar-2201' on the Hugging Face Hub either: FileNotFoundError: Couldn't find file at https://raw.githubusercontent.com/huggingface/datasets/master/datasets/oscar-2201/oscar-2201.py
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 2.3.2
- Platform: Linux-5.13.0-37-generic-x86_64-with-glibc2.29
- Python version: 3.8.10
- PyArrow version: 8.0.0
- Pandas version: 1.4.3
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https://api.github.com/repos/huggingface/datasets/issues/6973 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6973/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6973/comments | https://api.github.com/repos/huggingface/datasets/issues/6973/events | https://github.com/huggingface/datasets/issues/6973 | 2,355,517,362 | I_kwDODunzps6MZley | 6,973 | IndexError during training with Squad dataset and T5-small model | {
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"add remove_unused_columns=False to training_args\r\nhttps://github.com/huggingface/datasets/issues/6535#issuecomment-1874024704",
"Closing this issue because it was a reported and fixed in transformers."
] | 2024-06-16T07:53:54Z | 2024-07-01T11:25:40Z | 2024-07-01T11:25:40Z | NONE | null | null | {
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} | ### Describe the bug
I am encountering an IndexError while training a T5-small model on the Squad dataset using the transformers and datasets libraries. The error occurs even with a minimal reproducible example, suggesting a potential bug or incompatibility.
### Steps to reproduce the bug
1.Install the required libraries: !pip install transformers datasets
2.Run the following code:
!pip install transformers datasets
import torch
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, TrainingArguments, Trainer, DataCollatorWithPadding
# Load a small, publicly available dataset
from datasets import load_dataset
dataset = load_dataset("squad", split="train[:100]") # Use a small subset for testing
# Load a pre-trained model and tokenizer
model_name = "t5-small"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
# Define a basic data collator
data_collator = DataCollatorWithPadding(tokenizer=tokenizer)
# Define training arguments
training_args = TrainingArguments(
output_dir="./results",
per_device_train_batch_size=2,
num_train_epochs=1,
)
# Create a trainer
trainer = Trainer(
model=model,
args=training_args,
train_dataset=dataset,
data_collator=data_collator,
)
# Train the model
trainer.train()
### Expected behavior
---------------------------------------------------------------------------
IndexError Traceback (most recent call last)
[<ipython-input-23-f13a4b23c001>](https://localhost:8080/#) in <cell line: 34>()
32
33 # Train the model
---> 34 trainer.train()
10 frames
[/usr/local/lib/python3.10/dist-packages/datasets/formatting/formatting.py](https://localhost:8080/#) in _check_valid_index_key(key, size)
427 if isinstance(key, int):
428 if (key < 0 and key + size < 0) or (key >= size):
--> 429 raise IndexError(f"Invalid key: {key} is out of bounds for size {size}")
430 return
431 elif isinstance(key, slice):
IndexError: Invalid key: 42 is out of bounds for size 0
### Environment info
transformers version:4.41.2
datasets version:1.18.4
Python version:3.10.12
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https://api.github.com/repos/huggingface/datasets/issues/7259 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7259/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7259/comments | https://api.github.com/repos/huggingface/datasets/issues/7259/events | https://github.com/huggingface/datasets/pull/7259 | 2,618,909,241 | PR_kwDODunzps6AIEY- | 7,259 | Don't embed videos | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7259). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update."
] | 2024-10-28T16:25:10Z | 2024-10-28T16:27:34Z | 2024-10-28T16:26:01Z | MEMBER | null | null | null | don't include video bytes when running download_and_prepare(format="parquet")
this also affects push_to_hub which will just upload the local paths of the videos though | {
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https://api.github.com/repos/huggingface/datasets/issues/5842 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5842/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5842/comments | https://api.github.com/repos/huggingface/datasets/issues/5842/events | https://github.com/huggingface/datasets/issues/5842 | 1,705,510,602 | I_kwDODunzps5lqAbK | 5,842 | Remove columns in interable dataset | {
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"Transferring this issue as it's related to the 🤗 Datasets library ",
"Hi @surya-narayanan! Could you provide some code snippet?",
"This method has been recently added to the `IterableDataset`, so you need to update the `datasets`' installation (`pip install -U datasets`) to use it."
] | 2023-05-11T03:48:46Z | 2023-06-21T16:36:42Z | 2023-06-21T16:36:41Z | NONE | null | null | {
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} | ### Feature request
Right now, remove_columns() produces a NotImplementedError for iterable style datasets
### Motivation
It would be great to have the same functionality irrespective of whether one is using an iterable or a map-style dataset
### Your contribution
hope and courage. | {
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https://api.github.com/repos/huggingface/datasets/issues/6004 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6004/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6004/comments | https://api.github.com/repos/huggingface/datasets/issues/6004/events | https://github.com/huggingface/datasets/pull/6004 | 1,786,636,368 | PR_kwDODunzps5UjN2h | 6,004 | Misc improvements | {
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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... | 2023-07-03T18:29:14Z | 2023-07-06T17:04:11Z | 2023-07-06T16:55:25Z | COLLABORATOR | null | null | null | Contains the following improvements:
* fixes a "share dataset" link in README and modifies the "hosting" part in the disclaimer section
* updates `Makefile` to also run the style checks on `utils` and `setup.py`
* deletes a test for GH-hosted datasets (no longer supported)
* deletes `convert_dataset.sh` (outdated)
* aligns `utils/release.py` with `transformers` (the current version is outdated) | {
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https://api.github.com/repos/huggingface/datasets/issues/6335 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6335/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6335/comments | https://api.github.com/repos/huggingface/datasets/issues/6335/events | https://github.com/huggingface/datasets/pull/6335 | 1,956,740,818 | PR_kwDODunzps5dggIV | 6,335 | Support fsspec 2023.10.0 | {
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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... | 2023-10-23T09:29:17Z | 2024-01-11T06:33:35Z | 2023-11-14T14:17:40Z | MEMBER | null | null | null | Fix #6333. | {
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https://api.github.com/repos/huggingface/datasets/issues/5751 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5751/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5751/comments | https://api.github.com/repos/huggingface/datasets/issues/5751/events | https://github.com/huggingface/datasets/pull/5751 | 1,668,333,316 | PR_kwDODunzps5OVMuT | 5,751 | Consistent ArrayXD Python formatting + better NumPy/Pandas formatting | {
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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... | 2023-04-14T14:13:59Z | 2023-04-20T14:43:20Z | 2023-04-20T14:40:34Z | COLLABORATOR | null | null | null | Return a list of lists instead of a list of NumPy arrays when converting the variable-shaped `ArrayXD` to Python. Additionally, improve the NumPy conversion by returning a numeric NumPy array when the offsets are equal or a NumPy object array when they aren't, and allow converting the variable-shaped `ArrayXD` to Pandas.
(Reported in https://github.com/huggingface/datasets/issues/5719#issuecomment-1507579671) | {
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https://api.github.com/repos/huggingface/datasets/issues/5306 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5306/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5306/comments | https://api.github.com/repos/huggingface/datasets/issues/5306/events | https://github.com/huggingface/datasets/issues/5306 | 1,465,968,639 | I_kwDODunzps5XYOf_ | 5,306 | Can't use custom feature description when loading a dataset | {
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"Forgot to actually convert the feature dict to a Feature object. Closing."
] | 2022-11-28T07:55:44Z | 2022-11-28T08:11:45Z | 2022-11-28T08:11:44Z | MEMBER | null | null | {
"completed": 0,
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} | ### Describe the bug
I have created a feature dictionary to describe my datasets' column types, to use when loading the dataset, following [the doc](https://huggingface.co/docs/datasets/main/en/about_dataset_features). It crashes at dataset load.
### Steps to reproduce the bug
```python
# Creating features
task_list = [f"motif_G{i}" for i in range(19, 53)]
features = {t: Sequence(feature=Value(dtype="float64")) for t in task_list}
for col_name in ["class_label"]:
features[col_name] = Sequence(feature=Value(dtype="int64"))
for col_name in ["num_nodes"]:
features[col_name] = Value(dtype="int64")
for col_name in ["num_bridges", "num_cycles", "avg_shortest_path_len"]:
features[col_name] = Sequence(feature=Value(dtype="float64"))
for col_name in ["edge_attr", "node_feat", "edge_index"]:
features[col_name] = Sequence(feature=Sequence(feature=Value(dtype="int64")))
print(features)
dataset = load_dataset(path=f"graphs-datasets/unbalanced-motifs-500K", split="train", features=features)
```
Last line will crash and say 'TypeError: argument of type 'Sequence' is not iterable'.
Full stack:
```
Traceback (most recent call last):
File "pretrain_tokengt.py", line 131, in <module>
main(output_folder = "../workspace/pretraining",
File "pretrain_tokengt.py", line 52, in main
dataset = load_dataset(path=f"graphs-datasets/{dataset_name}", split="train", features=features)
File "huggingface_env/lib/python3.8/site-packages/datasets/load.py", line 1718, in load_dataset
builder_instance = load_dataset_builder(
File "huggingface_env/lib/python3.8/site-packages/datasets/load.py", line 1514, in load_dataset_builder
builder_instance: DatasetBuilder = builder_cls(
File "huggingface_env/lib/python3.8/site-packages/datasets/builder.py", line 321, in __init__
info.update(self._info())
File "huggingface_env/lib/python3.8/site-packages/datasets/packaged_modules/json/json.py", line 62, in _info
return datasets.DatasetInfo(features=self.config.features)
File "<string>", line 20, in __init__
File "huggingface_env/lib/python3.8/site-packages/datasets/info.py", line 155, in __post_init__
self.features = Features.from_dict(self.features)
File "huggingface_env/lib/python3.8/site-packages/datasets/features/features.py", line 1599, in from_dict
obj = generate_from_dict(dic)
File "huggingface_env/lib/python3.8/site-packages/datasets/features/features.py", line 1282, in generate_from_dict
return {key: generate_from_dict(value) for key, value in obj.items()}
File "huggingface_env/lib/python3.8/site-packages/datasets/features/features.py", line 1282, in <dictcomp>
return {key: generate_from_dict(value) for key, value in obj.items()}
File "huggingface_env/lib/python3.8/site-packages/datasets/features/features.py", line 1281, in generate_from_dict
if "_type" not in obj or isinstance(obj["_type"], dict):
TypeError: argument of type 'Sequence' is not iterable
```
### Expected behavior
For it not to crash.
### Environment info
- `datasets` version: 2.7.1
- Platform: Linux-5.14.0-1054-oem-x86_64-with-glibc2.29
- Python version: 3.8.10
- PyArrow version: 8.0.0
- Pandas version: 1.4.3 | {
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https://api.github.com/repos/huggingface/datasets/issues/7221 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7221/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7221/comments | https://api.github.com/repos/huggingface/datasets/issues/7221/events | https://github.com/huggingface/datasets/pull/7221 | 2,582,114,631 | PR_kwDODunzps5-YNI8 | 7,221 | add CustomFeature base class to support user-defined features with encoding/decoding logic | {
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"@lhoestq would you be open to supporting this kind of extensibility?",
"I suggested a fix in https://github.com/huggingface/datasets/issues/7220 that would not necessarily require a parent class for custom features, lmk what you think"
] | 2024-10-11T20:10:27Z | 2025-01-28T09:40:29Z | 2025-01-28T09:40:29Z | CONTRIBUTOR | null | null | null | intended as fix for #7220 if this kind of extensibility is something that datasets is willing to support!
```python
from datasets.features.features import CustomFeature
class ListOfStrs(CustomFeature):
requires_encoding = True
def _encode_example(self, value):
if isinstance(value, str):
return [str]
else:
return value
feats = Features(strlist=ListOfStrs())
feats.encode_example({"strlist": "a"})["strlist"] == feats["strlist"].encode_example("a")
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/6895 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6895/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6895/comments | https://api.github.com/repos/huggingface/datasets/issues/6895/events | https://github.com/huggingface/datasets/pull/6895 | 2,292,993,156 | PR_kwDODunzps5vRK8P | 6,895 | Document that to_json defaults to JSON Lines | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6895). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>... | 2024-05-13T14:22:34Z | 2024-05-16T14:37:25Z | 2024-05-16T14:31:26Z | MEMBER | null | null | null | Document that `Dataset.to_json` defaults to JSON Lines, by adding explanation in the corresponding docstring.
Fix #6894. | {
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https://api.github.com/repos/huggingface/datasets/issues/5209 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5209/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5209/comments | https://api.github.com/repos/huggingface/datasets/issues/5209/events | https://github.com/huggingface/datasets/issues/5209 | 1,438,367,678 | I_kwDODunzps5Vu7-- | 5,209 | Implement ability to define splits in metadata section of dataset card | {
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"@merveenoyan Do you want different files to be splits or configurations?\r\n\r\nFrom [what you specified in `Readme.md`](https://huggingface.co/datasets/inria-soda/tabular-benchmark/commit/fb4575853772c62a20203bdd6cc0202f5db4ce4e) I hypothesize that you want to have 4 **configs** corresponding to directories: `\"c... | 2022-11-07T13:27:16Z | 2023-07-21T14:36:02Z | 2023-07-21T14:36:01Z | CONTRIBUTOR | null | null | {
"completed": 0,
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} | ### Feature request
If you go here: https://huggingface.co/datasets/inria-soda/tabular-benchmark/tree/main you will see bunch of folders that has various CSV files. I’d like dataset viewer to show these files instead of only one dataset like it currently does. (and also people to be able to load them as splits instead of loading through `data_files`)
e.g GLUE has various splits on viewer but it’s too overkill to ask people to implement loading script, so it would be better to let them define these in the README file instead.
Also pinging @polinaeterna @lhoestq @adrinjalali
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https://api.github.com/repos/huggingface/datasets/issues/5526 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5526/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5526/comments | https://api.github.com/repos/huggingface/datasets/issues/5526/events | https://github.com/huggingface/datasets/pull/5526 | 1,580,488,133 | PR_kwDODunzps5JwVol | 5,526 | Allow loading/saving of FAISS index using fsspec | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Thanks for the quick review! I updated the code with your suggestion",
"Thanks for the quick review @albertvillanova! I updated the code with your suggestions",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n... | 2023-02-10T23:37:14Z | 2023-03-27T15:26:46Z | 2023-03-27T15:18:20Z | CONTRIBUTOR | null | null | null | Fixes #5428
Allow loading/saving of FAISS index using fsspec:
1. Simply use BufferedIOWriter/Reader to Read/Write indices on fsspec stream.
2. Needed `mockfs` in the test, so I took it out of the `TestCase`. Let me know if that makes sense.
I can work on the documentation once the code changes are approved.
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https://api.github.com/repos/huggingface/datasets/issues/6938 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6938/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6938/comments | https://api.github.com/repos/huggingface/datasets/issues/6938/events | https://github.com/huggingface/datasets/pull/6938 | 2,327,568,281 | PR_kwDODunzps5xHNKm | 6,938 | Fix expected splits when passing data_files or dir | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6938). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.",
"fix is included in https://github.com/huggingface/datasets/pull/6925"
] | 2024-05-31T11:04:22Z | 2024-05-31T15:28:03Z | 2024-05-31T15:28:02Z | MEMBER | null | null | null | reported on slack:
The following code snippet gives an error with v2.19 but not with v2.18:
from datasets import load_dataset
```
dataset = load_dataset(
"lvwerra/stack-exchange-paired",
split="train",
cache_dir=None,
data_dir="data/rl",
)
```
and the error is:
```
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/usr/local/lib/python3.10/dist-packages/datasets/load.py", line 2609, in load_dataset
builder_instance.download_and_prepare(
File "/usr/local/lib/python3.10/dist-packages/datasets/builder.py", line 1027, in download_and_prepare
self._download_and_prepare(
File "/usr/local/lib/python3.10/dist-packages/datasets/builder.py", line 1140, in _download_and_prepare
verify_splits(self.info.splits, split_dict)
File "/usr/local/lib/python3.10/dist-packages/datasets/utils/info_utils.py", line 92, in verify_splits
raise ExpectedMoreSplits(str(set(expected_splits) - set(recorded_splits)))
datasets.utils.info_utils.ExpectedMoreSplits: {'test'}
```
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https://api.github.com/repos/huggingface/datasets/issues/4821 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4821/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4821/comments | https://api.github.com/repos/huggingface/datasets/issues/4821/events | https://github.com/huggingface/datasets/pull/4821 | 1,335,664,588 | PR_kwDODunzps49AvaE | 4,821 | Fix train_test_split docs | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-08-11T08:55:45Z | 2022-08-11T09:59:29Z | 2022-08-11T09:45:40Z | CONTRIBUTOR | null | null | null | I saw that `stratify` is added to the `train_test_split` method as per #4322, hence the docs can be updated. | {
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https://api.github.com/repos/huggingface/datasets/issues/6303 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6303/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6303/comments | https://api.github.com/repos/huggingface/datasets/issues/6303/events | https://github.com/huggingface/datasets/issues/6303 | 1,943,466,532 | I_kwDODunzps5z1vIk | 6,303 | Parquet uploads off-by-one naming scheme | {
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"You can find the reasoning behind this naming scheme [here](https://github.com/huggingface/transformers/pull/16343#discussion_r931182168).\r\n\r\nThis point has been raised several times, so I'd be okay with starting with `00001-` (also to be consistent with the `transformers` sharding), but I'm not sure @lhoestq ... | 2023-10-14T18:31:03Z | 2023-10-16T16:33:21Z | null | CONTRIBUTOR | null | null | {
"completed": 0,
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} | ### Describe the bug
I noticed this numbering scheme not matching up in a different project and wanted to raise it as an issue for discussion, what is the actual proper way to have these stored?
<img width="425" alt="image" src="https://github.com/huggingface/datasets/assets/1981179/3ffa2144-7c9a-446f-b521-a5e9db71e7ce">
The `-SSSSS-of-NNNNN` seems to be used widely across the codebase. The section that creates the part in my screenshot is here https://github.com/huggingface/datasets/blob/main/src/datasets/arrow_dataset.py#L5287
There are also some edits to this section in the single commit branch.
### Steps to reproduce the bug
1. Upload a dataset that requires at least two parquet files in it
2. Observe the naming scheme
### Expected behavior
The couple options here are of course **1. keeping it as is**
**2. Starting the index at 1:**
train-00001-of-00002-{hash}.parquet
train-00002-of-00002-{hash}.parquet
**3. My preferred option** (which would solve my specific issue), dropping the total entirely:
train-00000-{hash}.parquet
train-00001-{hash}.parquet
This also solves an issue that will occur with an `append` variable for `push_to_hub` (see https://github.com/huggingface/datasets/issues/6290) where as you add a new parquet file, you need to rename everything in the repo as well.
However, I know there are parts of the repo that use 0 as the starting file or may require the total, so raising the question for discussion.
### Environment info
- `datasets` version: 2.14.6.dev0
- Platform: macOS-14.0-arm64-arm-64bit
- Python version: 3.10.12
- Huggingface_hub version: 0.18.0
- PyArrow version: 12.0.1
- Pandas version: 1.5.3 | null | {
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https://api.github.com/repos/huggingface/datasets/issues/4889 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4889/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4889/comments | https://api.github.com/repos/huggingface/datasets/issues/4889/events | https://github.com/huggingface/datasets/issues/4889 | 1,349,758,525 | I_kwDODunzps5Qc649 | 4,889 | torchaudio 11.0 yields different results than torchaudio 12.1 when loading MP3 | {
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"Maybe we can just pass this along to torchaudio @lhoestq @albertvillanova ? It be great if you could investigate if the errors lies in datasets or in torchaudio.",
"torchaudio did a change in [0.12](https://github.com/pytorch/audio/releases/tag/v0.12.0) on MP3 decoding (which affects common voice):\r\n> MP3 deco... | 2022-08-24T16:54:43Z | 2023-03-02T15:33:05Z | 2023-03-02T15:33:04Z | CONTRIBUTOR | null | null | {
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} | ## Describe the bug
When loading Common Voice with torchaudio 0.11.0 the results are different to 0.12.1 which leads to problems in transformers see: https://github.com/huggingface/transformers/pull/18749
## Steps to reproduce the bug
If you run the following code once with `torchaudio==0.11.0+cu102` and `torchaudio==0.12.1+cu102` you can see that the tensors differ. This is a pretty big breaking change and makes some integration tests fail in Transformers.
```python
#!/usr/bin/env python3
from datasets import load_dataset
import datasets
import numpy as np
import torch
import torchaudio
print("torch vesion", torch.__version__)
print("torchaudio vesion", torchaudio.__version__)
save_audio = True
load_audios = False
if save_audio:
ds = load_dataset("common_voice", "en", split="train", streaming=True)
ds = ds.cast_column("audio", datasets.Audio(sampling_rate=16_000))
ds_iter = iter(ds)
sample = next(ds_iter)
np.save(f"audio_sample_{torch.__version__}", sample["audio"]["array"])
print(sample["audio"]["array"])
if load_audios:
array_torch_11 = np.load("/home/patrick/audio_sample_1.11.0+cu102.npy")
print("Array 11 Shape", array_torch_11.shape)
print("Array 11 abs sum", np.sum(np.abs(array_torch_11)))
array_torch_12 = np.load("/home/patrick/audio_sample_1.12.1+cu102.npy")
print("Array 12 Shape", array_torch_12.shape)
print("Array 12 abs sum", np.sum(np.abs(array_torch_12)))
```
Having saved the tensors the print output yields:
```
torch vesion 1.12.1+cu102
torchaudio vesion 0.12.1+cu102
Array 11 Shape (122880,)
Array 11 abs sum 1396.4988
Array 12 Shape (123264,)
Array 12 abs sum 1396.5193
```
## Expected results
torchaudio 11.0 and 12.1 should yield same results.
## Actual results
See above.
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 2.1.1.dev0
- Platform: Linux-5.18.10-76051810-generic-x86_64-with-glibc2.34
- Python version: 3.9.7
- PyArrow version: 6.0.1
- Pandas version: 1.4.2
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https://api.github.com/repos/huggingface/datasets/issues/5745 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5745/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5745/comments | https://api.github.com/repos/huggingface/datasets/issues/5745/events | https://github.com/huggingface/datasets/pull/5745 | 1,667,086,143 | PR_kwDODunzps5ORE2n | 5,745 | [BUG FIX] Issue 5744 | {
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"Have met the same problem with datasets==2.8.0, pandas==2.0.0. It could be solved by installing the latest version of datasets or using datasets==2.8.0, pandas==1.5.3.",
"Pandas 2.0.0 has removed support to passing `mangle_dupe_cols`.\r\n\r\nHowever, our `datasets` library does not use this parameter: it only pa... | 2023-04-13T20:29:55Z | 2023-04-21T15:22:43Z | null | NONE | null | null | null | A temporal fix for https://github.com/huggingface/datasets/issues/5744. | null | {
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https://api.github.com/repos/huggingface/datasets/issues/5168 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5168/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5168/comments | https://api.github.com/repos/huggingface/datasets/issues/5168/events | https://github.com/huggingface/datasets/pull/5168 | 1,424,368,572 | PR_kwDODunzps5BmYnq | 5,168 | Fix CI require beam | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"I'm merging this PR because it is quite a trivial fix and this is required by:\r\n- #5166"
] | 2022-10-26T16:49:33Z | 2022-10-27T09:25:19Z | 2022-10-27T09:23:26Z | MEMBER | null | null | null | This PR:
- Fixes the CI `require_beam`: before it was requiring PyTorch instead
```python
def require_beam(test_case):
if not config.TORCH_AVAILABLE:
test_case = unittest.skip("test requires PyTorch")(test_case)
return test_case
```
- Fixes a missing `require_beam` in `test_beam_based_builder_download_and_prepare_as_parquet`
- Refactors `require_beam` to use `pytest` (`skipif`) instead | {
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https://api.github.com/repos/huggingface/datasets/issues/4972 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4972/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4972/comments | https://api.github.com/repos/huggingface/datasets/issues/4972/events | https://github.com/huggingface/datasets/pull/4972 | 1,371,443,306 | PR_kwDODunzps4-3VVF | 4,972 | Fix map batched with torch output | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-09-13T13:16:34Z | 2022-09-20T09:42:02Z | 2022-09-20T09:39:33Z | MEMBER | null | null | null | Reported in https://discuss.huggingface.co/t/typeerror-when-applying-map-after-set-format-type-torch/23067/2
Currently it fails if one uses batched `map` and the map function returns a torch tensor.
I fixed it for torch, tf, jax and pandas series. | {
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https://api.github.com/repos/huggingface/datasets/issues/7411 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7411/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7411/comments | https://api.github.com/repos/huggingface/datasets/issues/7411/events | https://github.com/huggingface/datasets/pull/7411 | 2,858,993,390 | PR_kwDODunzps6LhV0Z | 7,411 | Attempt to fix multiprocessing hang by closing and joining the pool before termination | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7411). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.",
"Thanks for the fix! We have been affected by this a lot when we try to use LLM Foundry ... | 2025-02-17T23:58:03Z | 2025-02-19T21:11:24Z | 2025-02-19T13:40:32Z | CONTRIBUTOR | null | null | null | https://github.com/huggingface/datasets/issues/6393 has plagued me on and off for a very long time. I have had various workarounds (one time combining two filter calls into one filter call removed the issue, another time making rank 0 go first resolved a cache race condition, one time i think upgrading the version of something resolved it). I don't know hf datasets well enough to fully understand the root cause, but I _think_ this PR fixes it.
Evidence: I have an LLM Foundry training yaml/script (datasets version 3.2.0) that results in a hang ~1/10 times (for a baseline for this testing, it was 2/36 runs that hung). I also reran with the latest datasets version (3.3.1) and got 4/36 hung. Installing datasets from this PR, I was able to successful run the script 144 times without a hang occurring. Assuming the base probability is 1/10, this should be more than enough times to have confidence it works.
After adding some logging, I could see that the code hung during the __exit__ of the mp pool context manager, after all shards had been processed, and the tqdm context manager had exited.
My best explanation: When multiprocessing pool __exit__ is called, it calls pool.terminate, which forcefully exits all the processes (and calls code related to this that I haven't looked at closely). I'm guessing this forceful termination has a bad interaction with some multithreading/multiprocessing that hf datasets does. If we instead call pool.close and pool.join before the pool.terminate happens, perhaps whatever that bad interaction is is able to complete gracefully, and then terminate call proceeds without issue.
If this PR seems good to you, I'd be very appreciative if you were able to do a patch release including it. Thank you!
@lhoestq | {
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https://api.github.com/repos/huggingface/datasets/issues/7448 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7448/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7448/comments | https://api.github.com/repos/huggingface/datasets/issues/7448/events | https://github.com/huggingface/datasets/issues/7448 | 2,916,025,762 | I_kwDODunzps6tzwWi | 7,448 | `datasets.disable_caching` doesn't work | {
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"cc",
"Yes I have the same issue. It's a confusingly named function. See [here](https://github.com/huggingface/datasets/blob/main/src/datasets/fingerprint.py#L115-L130)\n\n```\n...\nIf disabled, the library will no longer reload cached datasets files when applying transforms to the datasets.\n More precisely... | 2025-03-13T06:40:12Z | 2025-03-22T04:37:07Z | null | NONE | null | null | {
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} | When I use `Dataset.from_generator(my_gen)` to load my dataset, it simply skips my changes to the generator function.
I tried `datasets.disable_caching`, but it doesn't work! | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7348 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7348/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7348/comments | https://api.github.com/repos/huggingface/datasets/issues/7348/events | https://github.com/huggingface/datasets/pull/7348 | 2,766,128,230 | PR_kwDODunzps6Gldcy | 7,348 | Catch OSError for arrow | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_7348). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update."
] | 2025-01-02T14:30:00Z | 2025-01-09T14:25:06Z | 2025-01-09T14:25:04Z | MEMBER | null | null | null | fixes https://github.com/huggingface/datasets/issues/7346
(also updated `ruff` and appleid style changes) | {
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https://api.github.com/repos/huggingface/datasets/issues/6946 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6946/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6946/comments | https://api.github.com/repos/huggingface/datasets/issues/6946/events | https://github.com/huggingface/datasets/pull/6946 | 2,330,276,848 | PR_kwDODunzps5xQNao | 6,946 | Re-enable import sorting disabled by flake8:noqa directive when using ruff linter | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6946). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>... | 2024-06-03T06:24:47Z | 2024-06-04T10:00:08Z | 2024-06-04T09:54:23Z | MEMBER | null | null | null | Re-enable import sorting that was wrongly disabled by `flake8: noqa` directive after switching to `ruff` linter in datasets-2.10.0 PR:
- #5519
Note that after the linter switch, we wrongly replaced `flake8: noqa` with `ruff: noqa` in datasets-2.17.0 PR:
- #6619
That replacement was wrong because we kept the `isort: skip` directives although they were indeed disabled by `flake8: noqa` first and by `ruff: noqa` afterwards. See for example `__init__.py` file after the linter switch:
- We kept the `flake8: noqa` directive
https://github.com/huggingface/datasets/blob/06ae3f678651bfbb3ca7dd3274ee2f38e0e0237e/src/datasets/__init__.py#L1
- Whereas we also kept the `isort: skip` directives (that were disabled)
https://github.com/huggingface/datasets/blob/06ae3f678651bfbb3ca7dd3274ee2f38e0e0237e/src/datasets/__init__.py#L82-L84
Fix #6942. | {
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https://api.github.com/repos/huggingface/datasets/issues/5929 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5929/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5929/comments | https://api.github.com/repos/huggingface/datasets/issues/5929/events | https://github.com/huggingface/datasets/issues/5929 | 1,744,478,456 | I_kwDODunzps5n-qD4 | 5,929 | Importing PyTorch reduces multiprocessing performance for map | {
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"Hi! The times match when I run this code locally or on Colab.\r\n\r\nAlso, we use `multiprocess`, not `multiprocessing`, for parallelization, and torch's `__init__.py` (executed on `import torch` ) slightly modifies the latter.",
"Hey Mariosasko,\r\n\r\nThanks for looking into it. We further did some investigati... | 2023-06-06T19:42:25Z | 2023-06-16T13:09:12Z | 2023-06-16T13:09:12Z | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
I noticed that the performance of my dataset preprocessing with `map(...,num_proc=32)` decreases when PyTorch is imported.
### Steps to reproduce the bug
I created two example scripts to reproduce this behavior:
```
import datasets
datasets.disable_caching()
from datasets import Dataset
import time
PROC=32
if __name__ == "__main__":
dataset = [True] * 10000000
dataset = Dataset.from_dict({'train': dataset})
start = time.time()
dataset.map(lambda x: x, num_proc=PROC)
end = time.time()
print(end - start)
```
Takes around 4 seconds on my machine.
While the same code, but with an `import torch`:
```
import datasets
datasets.disable_caching()
from datasets import Dataset
import time
import torch
PROC=32
if __name__ == "__main__":
dataset = [True] * 10000000
dataset = Dataset.from_dict({'train': dataset})
start = time.time()
dataset.map(lambda x: x, num_proc=PROC)
end = time.time()
print(end - start)
```
takes around 22 seconds.
### Expected behavior
I would expect that the import of torch to not have such a significant effect on the performance of map using multiprocessing.
### Environment info
- `datasets` version: 2.12.0
- Platform: Linux-5.15.0-56-generic-x86_64-with-glibc2.35
- Python version: 3.11.3
- Huggingface_hub version: 0.15.1
- PyArrow version: 12.0.0
- Pandas version: 2.0.2
- torch: 2.0.1 | {
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https://api.github.com/repos/huggingface/datasets/issues/5251 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5251/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5251/comments | https://api.github.com/repos/huggingface/datasets/issues/5251/events | https://github.com/huggingface/datasets/issues/5251 | 1,451,761,321 | I_kwDODunzps5WiB6p | 5,251 | Docs are not generated after latest release | {
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"After a discussion with @mishig25:\r\n- He said that this action should be triggered if we call our release branch according to the regex `v*-release`, as transformers does\r\n- I said that our procedure is different: our release branch is *temporary* and it is deleted just after the release PR is merged to main\r... | 2022-11-16T14:59:31Z | 2022-11-22T16:27:50Z | 2022-11-22T16:27:50Z | MEMBER | null | null | {
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} | After the latest `datasets` release version 0.7.0, the docs were not generated.
As we have changed the release procedure (so that now we do not push directly to main branch), maybe we should also change the corresponding GitHub action:
https://github.com/huggingface/datasets/blob/edf1902f954c5568daadebcd8754bdad44b02a85/.github/workflows/build_documentation.yml#L3-L8
Related to:
- #5250
CC: @mishig25 | {
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https://api.github.com/repos/huggingface/datasets/issues/5691 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5691/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5691/comments | https://api.github.com/repos/huggingface/datasets/issues/5691/events | https://github.com/huggingface/datasets/pull/5691 | 1,649,737,526 | PR_kwDODunzps5NX08d | 5,691 | [docs] Compress data files | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"[Confirmed](https://huggingface.slack.com/archives/C02EMARJ65P/p1680541667004199) with the Hub team the file size limit for the Hugging Face Hub is 10MB :)",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<deta... | 2023-03-31T17:17:26Z | 2023-04-19T13:37:32Z | 2023-04-19T07:25:58Z | MEMBER | null | null | null | This PR addresses the comments in #5687 about compressing text file extensions before uploading to the Hub. Also clarified what "too large" means based on the GitLFS [docs](https://docs.github.com/en/repositories/working-with-files/managing-large-files/about-git-large-file-storage). | {
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https://api.github.com/repos/huggingface/datasets/issues/6171 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6171/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6171/comments | https://api.github.com/repos/huggingface/datasets/issues/6171/events | https://github.com/huggingface/datasets/pull/6171 | 1,862,922,767 | PR_kwDODunzps5Yk4AS | 6,171 | Fix typo in about_mapstyle_vs_iterable.mdx | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6171). 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... | 2023-08-23T09:21:11Z | 2023-08-23T09:32:59Z | 2023-08-23T09:21:19Z | MEMBER | null | null | null | null | {
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https://api.github.com/repos/huggingface/datasets/issues/6495 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6495/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6495/comments | https://api.github.com/repos/huggingface/datasets/issues/6495/events | https://github.com/huggingface/datasets/issues/6495 | 2,039,708,529 | I_kwDODunzps55k3tx | 6,495 | Newline characters don't behave as expected when calling dataset.info | {
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"completed": 0,
"percent_completed": 0,
"total": 0
} | ### System Info
- `transformers` version: 4.32.1
- Platform: Windows-10-10.0.19045-SP0
- Python version: 3.11.5
- Huggingface_hub version: 0.15.1
- Safetensors version: 0.3.2
- Accelerate version: not installed
- Accelerate config: not found
- PyTorch version (GPU?): 2.1.1+cpu (False)
- Tensorflow version (GPU?): 2.15.0 (False)
- Flax version (CPU?/GPU?/TPU?): not installed (NA)
- Jax version: not installed
- JaxLib version: not installed
- Using GPU in script?: no
- Using distributed or parallel set-up in script?: no
### Who can help?
@marios
### Information
- [X] The official example scripts
- [ ] My own modified scripts
### Tasks
- [X] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)
- [ ] My own task or dataset (give details below)
### Reproduction
[Source](https://huggingface.co/docs/datasets/v2.2.1/en/access)
```
from datasets import load_dataset
dataset = load_dataset('glue', 'mrpc', split='train')
dataset.info
```
DatasetInfo(description='GLUE, the General Language Understanding Evaluation benchmark\n(https://gluebenchmark.com/) is a collection of resources for training,\nevaluating, and analyzing natural language understanding systems.\n\n', citation='@inproceedings{dolan2005automatically,\n title={Automatically constructing a corpus of sentential paraphrases},\n author={Dolan, William B and Brockett, Chris},\n booktitle={Proceedings of the Third International Workshop on Paraphrasing (IWP2005)},\n year={2005}\n}\n@inproceedings{wang2019glue,\n title={{GLUE}: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding},\n author={Wang, Alex and Singh, Amanpreet and Michael, Julian and Hill, Felix and Levy, Omer and Bowman, Samuel R.},\n note={In the Proceedings of ICLR.},\n year={2019}\n}\n', homepage='https://www.microsoft.com/en-us/download/details.aspx?id=52398', license='', features={'sentence1': Value(dtype='string', id=None), 'sentence2': Value(dtype='string', id=None), 'label': ClassLabel(names=['not_equivalent', 'equivalent'], id=None), 'idx': Value(dtype='int32', id=None)}, post_processed=None, supervised_keys=None, task_templates=None, builder_name='glue', dataset_name=None, config_name='mrpc', version=1.0.0, splits={'train': SplitInfo(name='train', num_bytes=943843, num_examples=3668, shard_lengths=None, dataset_name='glue'), 'validation': SplitInfo(name='validation', num_bytes=105879, num_examples=408, shard_lengths=None, dataset_name='glue'), 'test': SplitInfo(name='test', num_bytes=442410, num_examples=1725, shard_lengths=None, dataset_name='glue')}, download_checksums={'https://dl.fbaipublicfiles.com/glue/data/mrpc_dev_ids.tsv': {'num_bytes': 6222, 'checksum': None}, 'https://dl.fbaipublicfiles.com/senteval/senteval_data/msr_paraphrase_train.txt': {'num_bytes': 1047044, 'checksum': None}, 'https://dl.fbaipublicfiles.com/senteval/senteval_data/msr_paraphrase_test.txt': {'num_bytes': 441275, 'checksum': None}}, download_size=1494541, post_processing_size=None, dataset_size=1492132, size_in_bytes=2986673)
### Expected behavior
```
from datasets import load_dataset
dataset = load_dataset('glue', 'mrpc', split='train')
dataset.info
```
DatasetInfo(
description='GLUE, the General Language Understanding Evaluation benchmark\n(https://gluebenchmark.com/) is a collection of resources for training,\nevaluating, and analyzing natural language understanding systems.\n\n',
citation='@inproceedings{dolan2005automatically,\n title={Automatically constructing a corpus of sentential paraphrases},\n author={Dolan, William B and Brockett, Chris},\n booktitle={Proceedings of the Third International Workshop on Paraphrasing (IWP2005)},\n year={2005}\n}\n@inproceedings{wang2019glue,\n title={{GLUE}: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding},\n author={Wang, Alex and Singh, Amanpreet and Michael, Julian and Hill, Felix and Levy, Omer and Bowman, Samuel R.},\n note={In the Proceedings of ICLR.},\n year={2019}\n}\n', homepage='https://www.microsoft.com/en-us/download/details.aspx?id=52398',
license='',
features={'sentence1': Value(dtype='string', id=None), 'sentence2': Value(dtype='string', id=None), 'label': ClassLabel(num_classes=2, names=['not_equivalent', 'equivalent'], names_file=None, id=None), 'idx': Value(dtype='int32', id=None)}, post_processed=None, supervised_keys=None, builder_name='glue', config_name='mrpc', version=1.0.0, splits={'train': SplitInfo(name='train', num_bytes=943851, num_examples=3668, dataset_name='glue'), 'validation': SplitInfo(name='validation', num_bytes=105887, num_examples=408, dataset_name='glue'), 'test': SplitInfo(name='test', num_bytes=442418, num_examples=1725, dataset_name='glue')},
download_checksums={'https://dl.fbaipublicfiles.com/glue/data/mrpc_dev_ids.tsv': {'num_bytes': 6222, 'checksum': '971d7767d81b997fd9060ade0ec23c4fc31cbb226a55d1bd4a1bac474eb81dc7'}, 'https://dl.fbaipublicfiles.com/senteval/senteval_data/msr_paraphrase_train.txt': {'num_bytes': 1047044, 'checksum': '60a9b09084528f0673eedee2b69cb941920f0b8cd0eeccefc464a98768457f89'}, 'https://dl.fbaipublicfiles.com/senteval/senteval_data/msr_paraphrase_test.txt': {'num_bytes': 441275, 'checksum': 'a04e271090879aaba6423d65b94950c089298587d9c084bf9cd7439bd785f784'}},
download_size=1494541,
post_processing_size=None,
dataset_size=1492156,
size_in_bytes=2986697
) | null | {
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https://api.github.com/repos/huggingface/datasets/issues/6758 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6758/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6758/comments | https://api.github.com/repos/huggingface/datasets/issues/6758/events | https://github.com/huggingface/datasets/issues/6758 | 2,208,494,302 | I_kwDODunzps6DovLe | 6,758 | Passing `sample_by` to `load_dataset` when loading text data does not work | {
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"Thanks for reporting! We are working on a fix."
] | 2024-03-26T14:55:33Z | 2024-04-09T11:27:59Z | 2024-04-09T11:27:59Z | NONE | null | null | {
"completed": 0,
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"total": 0
} | ### Describe the bug
I have a dataset that consists of a bunch of text files, each representing an example. There is an undocumented `sample_by` argument for the `TextConfig` class that is used by `Text` to decide whether to split files into lines, paragraphs or take them whole. Passing `sample_by=“document”` to `load_dataset` results in files getting split into lines regardless. I have edited `src/datasets/packaged_modules/text/text.py` for myself to switch the default and it works fine.
As a side note, the `if-else` for `sample_by` will silently load an empty dataset if someone makes a typo in the argument, which is not ideal.
### Steps to reproduce the bug
1. Prepare data as a bunch of files in a directory.
2. Load that data via `load_dataset(“text”, data_files=<data_dir>/<files_glob>, …, sample_by=“document”)`.
3. Inspect the resultant dataset — every item should have the form of `{“text”: <a line from a file>}`.
### Expected behavior
`load_dataset(“text”, data_files=<data_dir>/<files_glob>, …, sample_by=“document”)` should result in a dataset with items of the form `{“text”: <one document>}`.
### Environment info
- `datasets` version: 2.18.0
- Platform: Linux-5.15.0-1046-nvidia-x86_64-with-glibc2.35
- Python version: 3.11.8
- `huggingface_hub` version: 0.21.4
- PyArrow version: 15.0.2
- Pandas version: 2.2.1
- `fsspec` version: 2024.2.0 | {
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https://api.github.com/repos/huggingface/datasets/issues/7443 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7443/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7443/comments | https://api.github.com/repos/huggingface/datasets/issues/7443/events | https://github.com/huggingface/datasets/issues/7443 | 2,908,585,656 | I_kwDODunzps6tXX64 | 7,443 | index error when num_shards > len(dataset) | {
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"Actually, looking at the code a bit more carefully, maybe an even better solution is to explicitly set `num_shards=len(self)` somewhere inside both `push_to_hub()` and `save_to_disk()` when these functions are invoked with `num_shards > len(dataset)`."
] | 2025-03-10T22:40:59Z | 2025-03-10T23:43:08Z | null | NONE | null | null | {
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} | In `ds.push_to_hub()` and `ds.save_to_disk()`, `num_shards` must be smaller than or equal to the number of rows in the dataset, but currently this is not checked anywhere inside these functions. Attempting to invoke these functions with `num_shards > len(dataset)` should raise an informative `ValueError`.
I frequently work with datasets with a small number of rows where each row is pretty large, so I often encounter this issue, where the function runs until the shard index in `ds.shard(num_shards, indx)` goes out of bounds. Ideally, a `ValueError` should be raised before reaching this point (i.e. as soon as `ds.push_to_hub()` or `ds.save_to_disk()` is invoked with `num_shards > len(dataset)`).
It seems that adding something like:
```python
if len(self) < num_shards:
raise ValueError(f"num_shards ({num_shards}) must be smaller than or equal to the number of rows in the dataset ({len(self)}). Please either reduce num_shards or increase max_shard_size to make sure num_shards <= len(dataset).")
```
to the beginning of the definition of the `ds.shard()` function [here](https://github.com/huggingface/datasets/blob/f693f4e93aabafa878470c80fd42ddb10ec550d6/src/datasets/arrow_dataset.py#L4728) would deal with this issue for both `ds.push_to_hub()` and `ds.save_to_disk()`, but I'm not exactly sure if this is the best place to raise the `ValueError` (it seems that a more correct way to do it would be to write separate checks for `ds.push_to_hub()` and `ds.save_to_disk()`). I'd be happy to submit a PR if you think something along these lines would be acceptable. | null | {
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https://api.github.com/repos/huggingface/datasets/issues/6314 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6314/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6314/comments | https://api.github.com/repos/huggingface/datasets/issues/6314/events | https://github.com/huggingface/datasets/pull/6314 | 1,951,684,763 | PR_kwDODunzps5dPo25 | 6,314 | Support creating new branch in push_to_hub | {
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} | [] | closed | false | null | [] | null | [] | 2023-10-19T09:12:39Z | 2023-10-19T09:20:06Z | 2023-10-19T09:19:48Z | NONE | null | null | null | This adds support for creating a new branch when pushing a dataset to the hub. Tested both methods locally and branches are created. | {
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https://api.github.com/repos/huggingface/datasets/issues/7295 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7295/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7295/comments | https://api.github.com/repos/huggingface/datasets/issues/7295/events | https://github.com/huggingface/datasets/issues/7295 | 2,672,003,384 | I_kwDODunzps6fQ4k4 | 7,295 | [BUG]: Streaming from S3 triggers `unexpected keyword argument 'requote_redirect_url'` | {
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} | [] | open | false | null | [] | null | [] | 2024-11-19T12:23:36Z | 2024-11-19T13:01:53Z | null | NONE | null | null | {
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} | ### Describe the bug
Note that this bug is only triggered when `streaming=True`. #5459 introduced always calling fsspec with `client_kwargs={"requote_redirect_url": False}`, which seems to have incompatibility issues even in the newest versions.
Analysis of what's happening:
1. `datasets` passes the `client_kwargs` through `fsspec`
2. `fsspec` passes the `client_kwargs` through `s3fs`
3. `s3fs` passes the `client_kwargs` to `aiobotocore` which uses `aiohttp`
```
s3creator = self.session.create_client(
"s3", config=conf, **init_kwargs, **client_kwargs
)
```
4. The `session` tries to create an `aiohttp` session but the `**kwargs` are not just kept as unfolded `**kwargs` but passed in as individual variables (`requote_redirect_url` and `trust_env`).
Error:
```
Traceback (most recent call last):
File "/Users/cxrh/Documents/GitHub/nlp_foundation/nlp_train/test.py", line 14, in <module>
batch = next(iter(ds))
File "/Users/cxrh/miniconda3/envs/s3_data_loader/lib/python3.10/site-packages/datasets/iterable_dataset.py", line 1353, in __iter__
for key, example in ex_iterable:
File "/Users/cxrh/miniconda3/envs/s3_data_loader/lib/python3.10/site-packages/datasets/iterable_dataset.py", line 255, in __iter__
for key, pa_table in self.generate_tables_fn(**self.kwargs):
File "/Users/cxrh/miniconda3/envs/s3_data_loader/lib/python3.10/site-packages/datasets/packaged_modules/json/json.py", line 78, in _generate_tables
for file_idx, file in enumerate(itertools.chain.from_iterable(files)):
File "/Users/cxrh/miniconda3/envs/s3_data_loader/lib/python3.10/site-packages/datasets/download/streaming_download_manager.py", line 840, in __iter__
yield from self.generator(*self.args, **self.kwargs)
File "/Users/cxrh/miniconda3/envs/s3_data_loader/lib/python3.10/site-packages/datasets/download/streaming_download_manager.py", line 921, in _iter_from_urlpaths
elif xisdir(urlpath, download_config=download_config):
File "/Users/cxrh/miniconda3/envs/s3_data_loader/lib/python3.10/site-packages/datasets/download/streaming_download_manager.py", line 305, in xisdir
return fs.isdir(inner_path)
File "/Users/cxrh/miniconda3/envs/s3_data_loader/lib/python3.10/site-packages/fsspec/spec.py", line 721, in isdir
return self.info(path)["type"] == "directory"
File "/Users/cxrh/miniconda3/envs/s3_data_loader/lib/python3.10/site-packages/fsspec/archive.py", line 38, in info
self._get_dirs()
File "/Users/cxrh/miniconda3/envs/s3_data_loader/lib/python3.10/site-packages/datasets/filesystems/compression.py", line 64, in _get_dirs
f = {**self.file.fs.info(self.file.path), "name": self.uncompressed_name}
File "/Users/cxrh/miniconda3/envs/s3_data_loader/lib/python3.10/site-packages/fsspec/asyn.py", line 118, in wrapper
return sync(self.loop, func, *args, **kwargs)
File "/Users/cxrh/miniconda3/envs/s3_data_loader/lib/python3.10/site-packages/fsspec/asyn.py", line 103, in sync
raise return_result
File "/Users/cxrh/miniconda3/envs/s3_data_loader/lib/python3.10/site-packages/fsspec/asyn.py", line 56, in _runner
result[0] = await coro
File "/Users/cxrh/miniconda3/envs/s3_data_loader/lib/python3.10/site-packages/s3fs/core.py", line 1302, in _info
out = await self._call_s3(
File "/Users/cxrh/miniconda3/envs/s3_data_loader/lib/python3.10/site-packages/s3fs/core.py", line 341, in _call_s3
await self.set_session()
File "/Users/cxrh/miniconda3/envs/s3_data_loader/lib/python3.10/site-packages/s3fs/core.py", line 524, in set_session
s3creator = self.session.create_client(
File "/Users/cxrh/miniconda3/envs/s3_data_loader/lib/python3.10/site-packages/aiobotocore/session.py", line 114, in create_client
return ClientCreatorContext(self._create_client(*args, **kwargs))
TypeError: AioSession._create_client() got an unexpected keyword argument 'requote_redirect_url'
```
### Steps to reproduce the bug
1. Install the necessary libraries, datasets having a requirement for being at least 2.19.0:
```
pip install s3fs fsspec aiohttp aiobotocore botocore 'datasets>=2.19.0'
```
2. Run this code:
```
from datasets import load_dataset
ds = load_dataset(
"json",
data_files="s3://your_path/*.jsonl.gz",
streaming=True,
split="train",
)
batch = next(iter(ds))
print(batch)
```
3. You get the `unexpected keyword argument 'requote_redirect_url'` error.
### Expected behavior
The datasets is able to load a batch from the dataset stored on S3, without triggering this `requote_redirect_url` error.
Fix: I could fix this by directly removing the `requote_redirect_url` and `trust_env` - then it loads properly.
<img width="1127" alt="image" src="https://github.com/user-attachments/assets/4c40efa9-8787-4919-b613-e4908c3d1ab2">
### Environment info
- `datasets` version: 3.1.0
- Platform: macOS-15.1-arm64-arm-64bit
- Python version: 3.10.15
- `huggingface_hub` version: 0.26.2
- PyArrow version: 18.0.0
- Pandas version: 2.2.3
- `fsspec` version: 2024.9.0 | null | {
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https://api.github.com/repos/huggingface/datasets/issues/4662 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4662/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4662/comments | https://api.github.com/repos/huggingface/datasets/issues/4662/events | https://github.com/huggingface/datasets/pull/4662 | 1,298,845,369 | PR_kwDODunzps47GTEc | 4,662 | Fix: conll2003 - fix empty example | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-07-08T10:49:13Z | 2022-07-08T14:14:53Z | 2022-07-08T14:02:42Z | MEMBER | null | null | null | As reported in https://huggingface.co/datasets/conll2003/discussions/2#62c45a14f93fc97e8260532f, there was an extra empty example at the end of the dataset | {
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https://api.github.com/repos/huggingface/datasets/issues/6560 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6560/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6560/comments | https://api.github.com/repos/huggingface/datasets/issues/6560/events | https://github.com/huggingface/datasets/issues/6560 | 2,065,637,625 | I_kwDODunzps57HyD5 | 6,560 | Support Video | {
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... | closed | false | null | [] | null | [
"duplicate of #5225"
] | 2024-01-04T13:10:58Z | 2024-08-23T09:51:27Z | 2024-08-23T09:51:27Z | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
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} | ### Feature request
HF datasets are awesome in supporting text and images. Will be great to see such a support in videos :)
### Motivation
Video generation :)
### Your contribution
Will probably be limited to raising this feature request ;) | {
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https://api.github.com/repos/huggingface/datasets/issues/7375 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7375/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7375/comments | https://api.github.com/repos/huggingface/datasets/issues/7375/events | https://github.com/huggingface/datasets/issues/7375 | 2,800,609,218 | I_kwDODunzps6m7efC | 7,375 | vllm批量推理报错 | {
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"Make sure you have installed a recent version of `soundfile`"
] | 2025-01-21T03:22:23Z | 2025-01-30T14:02:40Z | null | NONE | null | null | {
"completed": 0,
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} | ### Describe the bug
### Steps to reproduce the bug
### Expected behavior
### Environment info
 | null | {
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https://api.github.com/repos/huggingface/datasets/issues/5062 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5062/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5062/comments | https://api.github.com/repos/huggingface/datasets/issues/5062/events | https://github.com/huggingface/datasets/pull/5062 | 1,395,739,417 | PR_kwDODunzps5AG6SA | 5,062 | Fix CI hfh token warning | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"good catch !"
] | 2022-10-04T06:36:54Z | 2022-10-04T08:58:15Z | 2022-10-04T08:42:31Z | MEMBER | null | null | null | In our CI, we get warnings from `hfh` about using deprecated `token`: https://github.com/huggingface/datasets/actions/runs/3174626525/jobs/5171672431
```
tests/test_upstream_hub.py::TestPushToHub::test_push_dataset_dict_to_hub_private
tests/test_upstream_hub.py::TestPushToHub::test_push_dataset_dict_to_hub
tests/test_upstream_hub.py::TestPushToHub::test_push_dataset_dict_to_hub_multiple_files
tests/test_upstream_hub.py::TestPushToHub::test_push_dataset_dict_to_hub_multiple_files_with_max_shard_size
tests/test_upstream_hub.py::TestPushToHub::test_push_dataset_dict_to_hub_overwrite_files
C:\hostedtoolcache\windows\Python\3.7.9\x64\lib\site-packages\huggingface_hub\utils\_deprecation.py:97: FutureWarning: Deprecated argument(s) used in 'dataset_info': token. Will not be supported from version '0.12'.
warnings.warn(message, FutureWarning)
```
This PR fixes the tests in `TestPushToHub` so that we fix these warnings.
Continuation of:
- #5031
CC: @lhoestq | {
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https://api.github.com/repos/huggingface/datasets/issues/7489 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7489/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7489/comments | https://api.github.com/repos/huggingface/datasets/issues/7489/events | https://github.com/huggingface/datasets/pull/7489 | 2,958,204,763 | PR_kwDODunzps6QqSRD | 7,489 | fix: loading of datasets from Disk(#7373) | {
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"@nepfaff Could you confirm if this fixes the issue for you? I checked Memray, and everything looked good on my end.\r\n\r\nInstall: `pip install git+https://github.com/sam-hey/datasets.git@fix/concatenate_datasets`\r\n",
"Will aim to get to this soon. I don't have a rapid testing pipeline setup but need to wait ... | 2025-03-29T16:22:58Z | 2025-04-24T16:36:36Z | null | NONE | null | null | null | Fixes dataset loading from disk by ensuring that memory maps and streams are properly closed.
For more details, see https://github.com/huggingface/datasets/issues/7373. | null | {
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https://api.github.com/repos/huggingface/datasets/issues/5935 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5935/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5935/comments | https://api.github.com/repos/huggingface/datasets/issues/5935/events | https://github.com/huggingface/datasets/pull/5935 | 1,748,090,220 | PR_kwDODunzps5Sh9Mg | 5,935 | Better row group size in push_to_hub | {
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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... | 2023-06-08T15:01:15Z | 2023-06-09T17:47:37Z | 2023-06-09T17:40:09Z | MEMBER | null | null | null | This is a very simple change that improves `to_parquet` to use a more reasonable row group size for image and audio datasets.
This is especially useful for `push_to_hub` and will provide a better experience with the dataset viewer on HF | {
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https://api.github.com/repos/huggingface/datasets/issues/6203 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6203/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6203/comments | https://api.github.com/repos/huggingface/datasets/issues/6203/events | https://github.com/huggingface/datasets/issues/6203 | 1,877,491,602 | I_kwDODunzps5v6D-S | 6,203 | Support loading from a DVC remote repository | {
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"(cross-posting from the linked DVC issue)\r\n\r\nI think this should already work out of the box with the current `datasets` and `dvc.api` releases by passing the correct `storage_options` into the datasets calls. `storage_options` is essentially just the kwargs dict that gets passed to the fsspec fs constructor.\... | 2023-09-01T14:04:52Z | 2023-09-15T15:11:27Z | 2023-09-15T15:11:27Z | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Feature request
Adding support for loading a file from a DVC repository, tracked remotely on a SCM.
### Motivation
DVC is a popular version control system to version and manage datasets. The files are stored on a remote object storage platform, but they are tracked using Git. Integration with DVC is possible through the `DVCFileSystem`.
I have a Gitlab repository where multiple files are tracked using DVC and stored in a GCP bucket. I would like to be able to load these files using `datasets` directly using an URL. My goal is to write a generic code that abstracts the storage layer, such that my users will only have to pass in an `fsspec`-compliant URL and the corresponding files will be loaded.
### Your contribution
I managed to instantiate a `DVCFileSystem` pointing to a Gitlab repo from a `fsspec` chained URL in [this pull request](https://github.com/iterative/dvc/pull/9903) to DVC.
```python
from fsspec.core import url_to_fs
fs, _ = url_to_fs("dvc::https://gitlab.com/repository/group/my-repo")
```
From now I'm not sure how to continue, it seems that `datasets` expects the URL to be fully qualified like so: `dvc::https://gitlab.com/repository/group/my-repo/my-folder/my-file.json` but this fails because `DVCFileSystem` expects the URL to point to the root of an SCM repo. Is there a way to make this work with `datasets`? | {
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https://api.github.com/repos/huggingface/datasets/issues/5889 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5889/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5889/comments | https://api.github.com/repos/huggingface/datasets/issues/5889/events | https://github.com/huggingface/datasets/issues/5889 | 1,722,373,618 | I_kwDODunzps5mqVXy | 5,889 | Token Alignment for input and output data over train and test batch/dataset. | {
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} | `data`
> DatasetDict({
train: Dataset({
features: ['input', 'output'],
num_rows: 4500
})
test: Dataset({
features: ['input', 'output'],
num_rows: 500
})
})
**# input (in-correct sentence)**
`data['train'][0]['input']`
**>>** 'We are meet sunday 10am12pmET in Crown Heights Brooklyn New York'
**# output (correct sentence)**
`data['train'][0]['output']`
**>>** 'We meet Sundays 10am-12pmET in Crown Heights, Brooklyn, New York.'
**I Want to align the output tokens with input**
```
`# tokenize both inputs and targets
def tokenize_fn(batch):
# tokenize the input sequence first
# this populates input_ids, attention_mask, etc.
tokenized_inputs = tokenizer(
batch['input']
)
labels_batch = tokenizer.tokenize(batch['output']) # original targets
aligned_labels_batch = []
for i, labels in enumerate(labels_batch):
word_ids = tokenized_inputs[i].word_ids()
aligned_labels_batch.append(align_targets(labels, word_ids)) # align_targets is another user defined function which is been called here
# recall: the 'target' must be stored in key called 'labels'
tokenized_inputs['labels'] = aligned_labels_batch
return tokenized_inputs`
```
```
data.map(
tokenize_fn,
batched=True,
remove_columns=data['train'].column_names,
)
```
When this user defined function is mapped to every records of train and test batch am getting following error:
**1.** **raise DatasetTransformationNotAllowedError(
3457 "Using `.map` in batched mode on a dataset with attached indexes is allowed only if it doesn't create or remove existing examples. You can first run `.drop_index() to remove your index and then re-add it."**
**2.** **TypeError: TextEncodeInput must be Union[TextInputSequence, Tuple[InputSequence, InputSequence]]** | null | {
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https://api.github.com/repos/huggingface/datasets/issues/7214 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7214/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7214/comments | https://api.github.com/repos/huggingface/datasets/issues/7214/events | https://github.com/huggingface/datasets/issues/7214 | 2,578,743,713 | I_kwDODunzps6ZtIGh | 7,214 | Formatted map + with_format(None) changes array dtype for iterable datasets | {
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"possibly due to this logic:\r\n\r\n```python\r\n def _arrow_array_to_numpy(self, pa_array: pa.Array) -> np.ndarray:\r\n if isinstance(pa_array, pa.ChunkedArray):\r\n if isinstance(pa_array.type, _ArrayXDExtensionType):\r\n # don't call to_pylist() to preserve dtype of the fixed-... | 2024-10-10T12:45:16Z | 2024-10-12T16:55:57Z | null | CONTRIBUTOR | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
When applying with_format -> map -> with_format(None), array dtypes seem to change, even if features are passed
### Steps to reproduce the bug
```python
features=Features(**{"array0": Array3D((None, 10, 10), dtype="float32")})
dataset = Dataset.from_dict({f"array0": [np.zeros((100,10,10), dtype=np.float32)]*25}, features=features)
ds = dataset.to_iterable_dataset().with_format("numpy").map(lambda x: x, features=features)
ex_0 = next(iter(ds))
ds = dataset.to_iterable_dataset().with_format("numpy").map(lambda x: x, features=features).with_format(None)
ex_1 = next(iter(ds))
assert ex_1["array0"].dtype == ex_0["array0"].dtype, f"{ex_1['array0'].dtype} {ex_0['array0'].dtype}"
```
### Expected behavior
Dtypes should be preserved.
### Environment info
3.0.2 | null | {
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https://api.github.com/repos/huggingface/datasets/issues/6775 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6775/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6775/comments | https://api.github.com/repos/huggingface/datasets/issues/6775/events | https://github.com/huggingface/datasets/issues/6775 | 2,223,457,792 | I_kwDODunzps6Eh0YA | 6,775 | IndexError: Invalid key: 0 is out of bounds for size 0 | {
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"Same problem.",
"Hi! You should be able to fix this by passing `remove_unused_columns=False` to the `transformers` `TrainingArguments` as explained in https://github.com/huggingface/peft/issues/1299.\r\n\r\n(I'm not familiar with Vertex AI, but I'd assume `remove_unused_columns` can be passed as a flag to the do... | 2024-04-03T17:06:30Z | 2024-04-08T01:24:35Z | null | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
I am trying to fine-tune llama2-7b model in GCP. The notebook I am using for this can be found [here](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/community/model_garden/model_garden_pytorch_llama2_peft_finetuning.ipynb).
When I use the dataset given in the example, the training gets successfully completed (example dataset can be found [here](https://huggingface.co/datasets/timdettmers/openassistant-guanaco)).
However when I use my own dataset which is in the same format as the example dataset, I get the below error (my dataset can be found [here](https://huggingface.co/datasets/kk2491/finetune_dataset_002)).
I see the files are being read correctly from the logs:
### Steps to reproduce the bug
1. Clone the [vertex-ai-samples](https://github.com/GoogleCloudPlatform/vertex-ai-samples) repository.
2. Run the [llama2-7b peft fine-tuning](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/community/model_garden/model_garden_pytorch_llama2_peft_finetuning.ipynb).
3. Change the dataset `kk2491/finetune_dataset_002`
### Expected behavior
The training should complete successfully, and model gets deployed to an endpoint.
### Environment info
Python version : Python 3.10.12
Dataset : https://huggingface.co/datasets/kk2491/finetune_dataset_002
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https://api.github.com/repos/huggingface/datasets/issues/5155 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5155/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5155/comments | https://api.github.com/repos/huggingface/datasets/issues/5155/events | https://github.com/huggingface/datasets/pull/5155 | 1,421,278,748 | PR_kwDODunzps5BcCYr | 5,155 | TextConfig: added "errors" | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Thanks for adding this ! You can fix the CI by formatting your code using the `make style` command :)",
"[**@lhoestq**](https://github.com/lhoestq) commented on [Oct 27, 2022, 4:08 PM GMT+3:30](https://github.com/huggingface/datase... | 2022-10-24T18:56:52Z | 2022-11-03T13:38:13Z | 2022-11-03T13:35:35Z | CONTRIBUTOR | null | null | null | This patch adds the ability to set the `errors` option of `open` for loading text datasets. I needed it because some data I had scraped had bad bytes in it, so I needed `errors='ignore'`. | {
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https://api.github.com/repos/huggingface/datasets/issues/6228 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6228/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6228/comments | https://api.github.com/repos/huggingface/datasets/issues/6228/events | https://github.com/huggingface/datasets/pull/6228 | 1,887,959,311 | PR_kwDODunzps5Z5HZi | 6,228 | Remove RGB -> BGR image conversion in Object Detection tutorial | {
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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... | 2023-09-08T16:09:13Z | 2023-09-08T18:02:49Z | 2023-09-08T17:52:16Z | COLLABORATOR | null | null | null | Fix #6225 | {
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https://api.github.com/repos/huggingface/datasets/issues/7084 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7084/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7084/comments | https://api.github.com/repos/huggingface/datasets/issues/7084/events | https://github.com/huggingface/datasets/issues/7084 | 2,439,519,534 | I_kwDODunzps6RaB0u | 7,084 | More easily support streaming local files | {
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} | ### Feature request
Simplify downloading and streaming datasets locally. Specifically, perhaps add an option to `load_dataset(..., streaming="download_first")` or add better support for streaming symlinked or arrow files.
### Motivation
I have downloaded FineWeb-edu locally and currently trying to stream the dataset from the local files. I have both the raw parquet files using `hugginface-cli download --repo-type dataset HuggingFaceFW/fineweb-edu` and the processed arrow files using `load_dataset("HuggingFaceFW/fineweb-edu")`.
Streaming the files locally does not work well for both file types for two different reasons.
**Arrow files**
When running `load_dataset("arrow", data_files={"train": "~/.cache/huggingface/datasets/HuggingFaceFW___fineweb-edu/default/0.0.0/5b89d1ea9319fe101b3cbdacd89a903aca1d6052/fineweb-edu-train-*.arrow"})` resolving the data files is fast, but because `arrow` is not included in the known [extensions file list](https://github.com/huggingface/datasets/blob/ce4a0c573920607bc6c814605734091b06b860e7/src/datasets/utils/file_utils.py#L738) , all files are opened and scanned to determine the compression type. Adding `arrow` to the known extension types resolves this issue.
**Parquet files**
When running `load_dataset("arrow", data_files={"train": "~/.cache/huggingface/hub/dataset-HuggingFaceFW___fineweb-edu/snapshots/5b89d1ea9319fe101b3cbdacd89a903aca1d6052/data/CC-MAIN-*/train-*.parquet"})` the paths do not get resolved because the parquet files are symlinked from the blobs (which contain all files in case there are different versions). This occurs because the [pattern matching](https://github.com/huggingface/datasets/blob/ce4a0c573920607bc6c814605734091b06b860e7/src/datasets/data_files.py#L389) checks if the path is a file and does not check for symlinks. Symlinks (at least on my machine) are of type "other".
### Your contribution
I have created a PR for fixing arrow file streaming and symlinks. However, I have not checked locally if the tests work or new tests need to be added.
IMO, the easiest option would be to add a `streaming=download_first` option, but I'm afraid that exceeds my current knowledge of how the datasets library works. https://github.com/huggingface/datasets/pull/7083 | null | {
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https://api.github.com/repos/huggingface/datasets/issues/5496 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5496/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5496/comments | https://api.github.com/repos/huggingface/datasets/issues/5496/events | https://github.com/huggingface/datasets/issues/5496 | 1,567,301,765 | I_kwDODunzps5dayCF | 5,496 | Add a `reduce` method | {
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"Hi! Sure, feel free to open a PR, so we can see the API you have in mind.",
"I would like to give it a go! #self-assign",
"Closing as `Dataset.map` can be used instead (see https://github.com/huggingface/datasets/pull/5533#issuecomment-1440571658 and https://github.com/huggingface/datasets/pull/5533#issuecomme... | 2023-02-02T04:30:22Z | 2024-11-12T05:58:14Z | 2023-07-21T14:24:32Z | NONE | null | null | {
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} | ### Feature request
Right now the `Dataset` class implements `map()` and `filter()`, but leaves out the third functional idiom popular among Python users: `reduce`.
### Motivation
A `reduce` method is often useful when calculating dataset statistics, for example, the occurrence of a particular n-gram or the average line length of a code dataset.
### Your contribution
I haven't contributed to `datasets` before, but I don't expect this will be too difficult, since the implementation will closely follow that of `map` and `filter`. I could have a crack over the weekend. | {
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https://api.github.com/repos/huggingface/datasets/issues/5863 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5863/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5863/comments | https://api.github.com/repos/huggingface/datasets/issues/5863/events | https://github.com/huggingface/datasets/pull/5863 | 1,710,335,905 | PR_kwDODunzps5QhtlM | 5,863 | Use a new low-memory approach for tf dataset index shuffling | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5863). 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... | 2023-05-15T15:28:34Z | 2023-06-08T16:40:18Z | 2023-06-08T16:32:51Z | MEMBER | null | null | null | This PR tries out a new approach to generating the index tensor in `to_tf_dataset`, which should reduce memory usage for very large datasets. I'll need to do some testing before merging it!
Fixes #5855 | {
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https://api.github.com/repos/huggingface/datasets/issues/7058 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7058/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7058/comments | https://api.github.com/repos/huggingface/datasets/issues/7058/events | https://github.com/huggingface/datasets/issues/7058 | 2,422,560,355 | I_kwDODunzps6QZVZj | 7,058 | New feature type: Document | {
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} | It would be useful for PDF.
https://github.com/huggingface/dataset-viewer/issues/2991#issuecomment-2242656069 | null | {
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https://api.github.com/repos/huggingface/datasets/issues/6729 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6729/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6729/comments | https://api.github.com/repos/huggingface/datasets/issues/6729/events | https://github.com/huggingface/datasets/issues/6729 | 2,180,237,159 | I_kwDODunzps6B88dn | 6,729 | Support zipfiles that span multiple disks? | {
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"@severo were you able to solve it?",
"No. cc @albertvillanova @lhoestq @polinaeterna for an evaluation of what it would take to support this feature.",
"The underlying issue issue is that the dataset repository has used split ZIP archive files: https://huggingface.co/datasets/PhilEO-community/PhilEO-downstream... | 2024-03-11T21:07:41Z | 2024-06-26T05:08:59Z | 2024-06-26T05:05:28Z | COLLABORATOR | null | null | {
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The dataset viewer gives the following error:
```
Error code: ConfigNamesError
Exception: BadZipFile
Message: zipfiles that span multiple disks are not supported
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 67, in compute_config_names_response
get_dataset_config_names(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 347, in get_dataset_config_names
dataset_module = dataset_module_factory(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1871, in dataset_module_factory
raise e1 from None
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1846, in dataset_module_factory
return HubDatasetModuleFactoryWithoutScript(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1240, in get_module
module_name, default_builder_kwargs = infer_module_for_data_files(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 584, in infer_module_for_data_files
split_modules = {
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 585, in <dictcomp>
split: infer_module_for_data_files_list(data_files_list, download_config=download_config)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 526, in infer_module_for_data_files_list
return infer_module_for_data_files_list_in_archives(data_files_list, download_config=download_config)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 554, in infer_module_for_data_files_list_in_archives
for f in xglob(extracted, recursive=True, download_config=download_config)[
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/download/streaming_download_manager.py", line 576, in xglob
fs, *_ = fsspec.get_fs_token_paths(urlpath, storage_options=storage_options)
File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/core.py", line 622, in get_fs_token_paths
fs = filesystem(protocol, **inkwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/registry.py", line 290, in filesystem
return cls(**storage_options)
File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/spec.py", line 79, in __call__
obj = super().__call__(*args, **kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/implementations/zip.py", line 57, in __init__
self.zip = zipfile.ZipFile(
File "/usr/local/lib/python3.9/zipfile.py", line 1266, in __init__
self._RealGetContents()
File "/usr/local/lib/python3.9/zipfile.py", line 1329, in _RealGetContents
endrec = _EndRecData(fp)
File "/usr/local/lib/python3.9/zipfile.py", line 286, in _EndRecData
return _EndRecData64(fpin, -sizeEndCentDir, endrec)
File "/usr/local/lib/python3.9/zipfile.py", line 232, in _EndRecData64
raise BadZipFile("zipfiles that span multiple disks are not supported")
zipfile.BadZipFile: zipfiles that span multiple disks are not supported
```
The files (https://huggingface.co/datasets/PhilEO-community/PhilEO-downstream/tree/main/data) are:
<img width="629" alt="Capture d’écran 2024-03-11 à 22 07 30" src="https://github.com/huggingface/datasets/assets/1676121/0bb15a51-d54f-4d73-8572-e427ea644b36">
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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... | 2023-08-17T21:58:24Z | 2023-08-17T22:44:59Z | 2023-08-17T22:36:04Z | COLLABORATOR | null | null | null | Fix #6149 | {
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https://api.github.com/repos/huggingface/datasets/issues/6695 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6695/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6695/comments | https://api.github.com/repos/huggingface/datasets/issues/6695/events | https://github.com/huggingface/datasets/issues/6695 | 2,154,075,509 | I_kwDODunzps6AZJV1 | 6,695 | Support JSON file with an array of strings | {
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"https://huggingface.co/datasets/CausalLM/Refined-Anime-Text/discussions/1 has been fixed, but how can we check if there are other datasets with the same error, in datasets-server's database? I don't know how to get the list of erroneous cache entries, since we only copied `Error code: JobManagerCrashedError`, bu... | 2024-02-26T12:35:11Z | 2024-03-08T14:16:25Z | 2024-02-28T06:39:13Z | MEMBER | null | null | {
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} | Support loading a dataset from a JSON file with an array of strings.
See: https://huggingface.co/datasets/CausalLM/Refined-Anime-Text/discussions/1 | {
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https://api.github.com/repos/huggingface/datasets/issues/6980 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6980/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6980/comments | https://api.github.com/repos/huggingface/datasets/issues/6980/events | https://github.com/huggingface/datasets/issues/6980 | 2,360,909,930 | I_kwDODunzps6MuKBq | 6,980 | Support NumPy 2.0 | {
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"completed": 0,
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} | ### Feature request
Support NumPy 2.0.
### Motivation
NumPy introduces the Array API, which bridges the gap between machine learning libraries. Many clients of HuggingFace are eager to start using the Array API.
Besides that, NumPy 2 provides a cleaner interface than NumPy 1.
### Tasks
NumPy 2.0 was released for testing so that libraries could ensure compatibility [since mid-March](https://github.com/numpy/numpy/issues/24300#issuecomment-1986815755). What needs to be done for HuggingFace to support Numpy 2?
- [x] Fix use of `array`: https://github.com/huggingface/datasets/pull/6976
- [ ] Remove [NumPy version limit](https://github.com/huggingface/datasets/pull/6975): https://github.com/huggingface/datasets/pull/6991 | {
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https://api.github.com/repos/huggingface/datasets/issues/4613 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4613/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4613/comments | https://api.github.com/repos/huggingface/datasets/issues/4613/events | https://github.com/huggingface/datasets/pull/4613 | 1,291,181,193 | PR_kwDODunzps46skd6 | 4,613 | Align/fix license metadata info | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Thank you thank you! Let's merge and pray? 😱 ",
"I just need to add `license_details` to the validator and yup we can merge"
] | 2022-07-01T09:50:50Z | 2022-07-01T12:53:57Z | 2022-07-01T12:42:47Z | MEMBER | null | null | null | fix bad "other-*" licenses and add the corresponding "license_details" when relevant | {
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https://api.github.com/repos/huggingface/datasets/issues/4577 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4577/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4577/comments | https://api.github.com/repos/huggingface/datasets/issues/4577/events | https://github.com/huggingface/datasets/pull/4577 | 1,285,703,775 | PR_kwDODunzps46aTWL | 4,577 | Add authentication tip to `load_dataset` | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-06-27T12:05:34Z | 2022-07-04T13:13:15Z | 2022-07-04T13:01:30Z | COLLABORATOR | null | null | null | Add an authentication tip similar to the one in transformers' `PreTrainedModel.from_pretrained` to `load_dataset`/`load_dataset_builder`. | {
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https://api.github.com/repos/huggingface/datasets/issues/6451 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6451/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6451/comments | https://api.github.com/repos/huggingface/datasets/issues/6451/events | https://github.com/huggingface/datasets/issues/6451 | 2,010,693,912 | I_kwDODunzps532MEY | 6,451 | Unable to read "marsyas/gtzan" data | {
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"Hi! We've merged a [PR](https://huggingface.co/datasets/marsyas/gtzan/discussions/1) that fixes the script's path logic on Windows.",
"I have transferred the discussion to the corresponding dataset: https://huggingface.co/datasets/marsyas/gtzan/discussions/2\r\n\r\nLet's continue there.",
"@mariosasko @albertv... | 2023-11-25T15:13:17Z | 2023-12-01T12:53:46Z | 2023-11-27T09:36:25Z | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
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} | Hi, this is my code and the error:
```
from datasets import load_dataset
gtzan = load_dataset("marsyas/gtzan", "all")
```
[error_trace.txt](https://github.com/huggingface/datasets/files/13464397/error_trace.txt)
[audio_yml.txt](https://github.com/huggingface/datasets/files/13464410/audio_yml.txt)
Python 3.11.5
Jupyter Notebook 6.5.4
Windows 10
I'm able to download and work with other datasets, but not this one. For example, both these below work fine:
```
from datasets import load_dataset
dataset = load_dataset("facebook/voxpopuli", "pl", split="train", streaming=True)
minds = load_dataset("PolyAI/minds14", name="en-US", split="train")
```
Thanks for your help
https://huggingface.co/datasets/marsyas/gtzan/tree/main | {
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https://api.github.com/repos/huggingface/datasets/issues/4716 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4716/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4716/comments | https://api.github.com/repos/huggingface/datasets/issues/4716/events | https://github.com/huggingface/datasets/pull/4716 | 1,309,455,838 | PR_kwDODunzps47pdbh | 4,716 | Support "tags" yaml tag | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"IMO `DatasetMetadata` shouldn't crash with attributes that it doesn't know, btw",
"Yea this PR is mostly to have a validation that this field contains a list of strings.\r\n\r\nRegarding unknown fields, the tagging app currently re... | 2022-07-19T12:34:31Z | 2022-07-20T13:44:50Z | 2022-07-20T13:31:56Z | MEMBER | null | null | null | Added the "tags" YAML tag, so that users can specify data domain/topics keywords for dataset search | {
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https://api.github.com/repos/huggingface/datasets/issues/5145 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5145/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5145/comments | https://api.github.com/repos/huggingface/datasets/issues/5145/events | https://github.com/huggingface/datasets/issues/5145 | 1,418,005,452 | I_kwDODunzps5UhQvM | 5,145 | Dataset order is not deterministic with ZIP archives and `iter_files` | {
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"Thanks for reporting ! The issue doesn't come from shuffling, but from `beans` row order not being deterministic:\r\n\r\nhttps://huggingface.co/datasets/beans/blob/main/beans.py uses `dl_manager.iter_files` on ZIP archives and the file order doesn't seen to be deterministic and changes across machines",
"Thank y... | 2022-10-21T09:00:03Z | 2022-10-27T09:51:49Z | 2022-10-27T09:51:10Z | CONTRIBUTOR | null | null | {
"completed": 0,
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} | ### Describe the bug
For the `beans` dataset (did not try on other), the order of samples is not the same on different machines. Tested on my local laptop, github actions machine, and ec2 instance. The three yield a different order.
### Steps to reproduce the bug
In a clean docker container or conda environment with datasets==2.6.1, run
```python
from datasets import load_dataset
from pprint import pprint
data = load_dataset("beans", split="validation")
pprint(data["image_file_path"])
```
### Expected behavior
The order of the images is the same on all machines.
### Environment info
On the EC2 instance:
```
- `datasets` version: 2.6.1
- Platform: Linux-4.14.291-218.527.amzn2.x86_64-x86_64-with-glibc2.2.5
- Python version: 3.7.10
- PyArrow version: 9.0.0
- Pandas version: 1.3.5
- Numpy version: not checked
```
On my local laptop:
```
- `datasets` version: 2.6.1
- Platform: Linux-5.15.0-50-generic-x86_64-with-glibc2.35
- Python version: 3.9.12
- PyArrow version: 7.0.0
- Pandas version: 1.3.5
- Numpy version: 1.23.1
```
On github actions:
```
- `datasets` version: 2.6.1
- Platform: Linux-5.15.0-1022-azure-x86_64-with-glibc2.2.5
- Python version: 3.8.14
- PyArrow version: 9.0.0
- Pandas version: 1.5.1
- Numpy version: 1.23.4
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/5933 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5933/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5933/comments | https://api.github.com/repos/huggingface/datasets/issues/5933/events | https://github.com/huggingface/datasets/pull/5933 | 1,747,382,500 | PR_kwDODunzps5Sfi5J | 5,933 | Fix `to_numpy` when None values in the sequence | {
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"I just added the same test with dynamic shape",
"_The documentation is not available anymore as the PR was closed or merged._",
"Awesome ! I'm merging now if you don't mind :)\r\nWe should probably give you permissions to merge your own PRs when you have an approval",
"<details>\n<summary>Show benchmarks</su... | 2023-06-08T08:38:56Z | 2023-06-09T13:49:41Z | 2023-06-09T13:23:48Z | MEMBER | null | null | null | Closes #5927
I've realized that the error was overlooked during testing due to the presence of only one None value in the sequence.
Unfortunately, it was the only case where the function works as expected. When the sequence contained more than one None value, the function failed. Consequently, I've updated the tests to include sequences with multiple None values. | {
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https://api.github.com/repos/huggingface/datasets/issues/5425 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5425/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5425/comments | https://api.github.com/repos/huggingface/datasets/issues/5425/events | https://github.com/huggingface/datasets/issues/5425 | 1,534,581,850 | I_kwDODunzps5bd9xa | 5,425 | Sort on multiple keys with datasets.Dataset.sort() | {
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"Hi! \r\n\r\n`Dataset.sort` calls `df.sort_values` internally, and `df.sort_values` brings all the \"sort\" columns in memory, so sorting on multiple keys could be very expensive. This makes me think that maybe we can replace `df.sort_values` with `pyarrow.compute.sort_indices` - the latter can also sort on multipl... | 2023-01-16T09:22:26Z | 2023-02-24T16:15:11Z | 2023-02-24T16:15:11Z | NONE | null | null | {
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} | ### Feature request
From discussion on forum: https://discuss.huggingface.co/t/datasets-dataset-sort-does-not-preserve-ordering/29065/1
`sort()` does not preserve ordering, and it does not support sorting on multiple columns, nor a key function.
The suggested solution:
> ... having something similar to pandas and be able to specify multiple columns for sorting. We’re already using pandas under the hood to do the sorting in datasets.
The suggested workaround:
> convert your dataset to pandas and use `df.sort_values()`
### Motivation
Preserved ordering when sorting is very handy when one needs to sort on multiple columns, A and B, so that e.g. whenever A is equal for two or more rows, B is kept sorted.
Having a parameter to do this in 🤗datasets would be cleaner than going through pandas and back, and it wouldn't add much complexity to the library.
Alternatives:
- the possibility to specify multiple keys to sort by with decreasing priority (suggested solution),
- the ability to provide a key function for sorting, so that one can manually specify the sorting criteria.
### Your contribution
I'll be happy to contribute by submitting a PR. Will get documented on `CONTRIBUTING.MD`.
Would love to get thoughts on this, if anyone has anything to add. | {
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https://api.github.com/repos/huggingface/datasets/issues/6926 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6926/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6926/comments | https://api.github.com/repos/huggingface/datasets/issues/6926/events | https://github.com/huggingface/datasets/pull/6926 | 2,322,164,287 | PR_kwDODunzps5w0uII | 6,926 | Update process.mdx: Fix code listing in Shard section | {
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https://api.github.com/repos/huggingface/datasets/issues/4679 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4679/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4679/comments | https://api.github.com/repos/huggingface/datasets/issues/4679/events | https://github.com/huggingface/datasets/pull/4679 | 1,303,980,648 | PR_kwDODunzps47XX67 | 4,679 | Added method to remove excess nesting in a DatasetDict | {
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"Hi ! I think the issue you linked is closed and suggests to use `remove_columns`.\r\n\r\nMoreover if you end up with a dataset with an unnecessarily nested data, please modify your processing functions to not output nested data, or use `map(..., batched=True)` if you function take batches as input",
"Hi @lhoestq... | 2022-07-13T21:49:37Z | 2022-07-21T15:55:26Z | 2022-07-21T10:55:02Z | NONE | null | null | null | Added the ability for a DatasetDict to remove additional nested layers within its features to avoid conflicts when collating. It is meant to accompany [this PR](https://github.com/huggingface/transformers/pull/18119) to resolve the same issue [#15505](https://github.com/huggingface/transformers/issues/15505).
@stas00 @lhoestq | {
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https://api.github.com/repos/huggingface/datasets/issues/7149 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7149/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7149/comments | https://api.github.com/repos/huggingface/datasets/issues/7149/events | https://github.com/huggingface/datasets/issues/7149 | 2,524,497,448 | I_kwDODunzps6WeMYo | 7,149 | Datasets Unknown Keyword Argument Error - task_templates | {
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"Thanks, for reporting.\r\n\r\nWe have been fixing most Hub datasets to remove the deprecated (and now non-supported) task templates, but we missed the \"facebook/winoground\".\r\n\r\nIt is fixed now: https://huggingface.co/datasets/facebook/winoground/discussions/8\r\n\r\n",
"Hello @albertvillanova \r\n\r\nI got... | 2024-09-13T10:30:57Z | 2025-03-06T07:11:55Z | 2024-09-13T14:10:48Z | NONE | null | null | {
"completed": 0,
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} | ### Describe the bug
Issue
```python
from datasets import load_dataset
examples = load_dataset('facebook/winoground', use_auth_token=<YOUR USER ACCESS TOKEN>)
```
Gives error
```
TypeError: DatasetInfo.__init__() got an unexpected keyword argument 'task_templates'
```
A simple downgrade to lower `datasets v 2.21.0` solves it.
### Steps to reproduce the bug
1. `pip install datsets`
2.
```python
from datasets import load_dataset
examples = load_dataset('facebook/winoground', use_auth_token=<YOUR USER ACCESS TOKEN>)
```
### Expected behavior
Should load the dataset correctly.
### Environment info
- Datasets version `3.0.0`
- `transformers` version: 4.45.0.dev0
- Platform: Linux-6.8.0-40-generic-x86_64-with-glibc2.35
- Python version: 3.12.4
- Huggingface_hub version: 0.24.6
- Safetensors version: 0.4.5
- Accelerate version: 0.35.0.dev0
- Accelerate config: not found
- PyTorch version (GPU?): 2.4.1+cu121 (True)
- Tensorflow version (GPU?): not installed (NA)
- Flax version (CPU?/GPU?/TPU?): not installed (NA)
- Jax version: not installed
- JaxLib version: not installed
- Using GPU in script?: Yes
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https://api.github.com/repos/huggingface/datasets/issues/4830 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4830/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4830/comments | https://api.github.com/repos/huggingface/datasets/issues/4830/events | https://github.com/huggingface/datasets/pull/4830 | 1,336,177,937 | PR_kwDODunzps49Cdro | 4,830 | Fix task tags in dataset cards | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"The non-passing tests are caused by other missing information in the dataset cards."
] | 2022-08-11T16:06:06Z | 2022-08-11T16:37:27Z | 2022-08-11T16:23:00Z | MEMBER | null | null | null | null | {
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https://api.github.com/repos/huggingface/datasets/issues/6435 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6435/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6435/comments | https://api.github.com/repos/huggingface/datasets/issues/6435/events | https://github.com/huggingface/datasets/issues/6435 | 2,000,690,513 | I_kwDODunzps53QB1R | 6,435 | Cannot re-initialize CUDA in forked subprocess. To use CUDA with multiprocessing, you must use the 'spawn' start method | {
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"[This doc section](https://huggingface.co/docs/datasets/main/en/process#multiprocessing) explains how to modify the script to avoid this error.",
"@mariosasko thank you very much, i'll check it",
"@mariosasko no it does not\r\n\r\n`Dataset.filter() got an unexpected keyword argument 'with_rank'`"
] | 2023-11-19T04:21:16Z | 2024-01-27T17:14:20Z | 2023-12-04T16:57:43Z | NONE | null | null | {
"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
1. I ran dataset mapping with `num_proc=6` in it and got this error:
`RuntimeError: Cannot re-initialize CUDA in forked subprocess. To use CUDA with multiprocessing, you must use the 'spawn' start method`
I can't actually find a way to run multi-GPU dataset mapping. Can you help?
### Steps to reproduce the bug
1. Rund SDXL training with `num_proc=6`: https://github.com/huggingface/diffusers/blob/main/examples/text_to_image/train_text_to_image_sdxl.py
### Expected behavior
Should work well
### Environment info
6x A100 SXM, Linux | {
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https://api.github.com/repos/huggingface/datasets/issues/5579 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5579/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5579/comments | https://api.github.com/repos/huggingface/datasets/issues/5579/events | https://github.com/huggingface/datasets/pull/5579 | 1,599,732,211 | PR_kwDODunzps5Kwgo4 | 5,579 | Add instructions to create `DataLoader` from augmented dataset in object detection guide | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5579). All of your documentation changes will be reflected on that endpoint.",
"I'm not sure we need this part as we provide a link to the notebook that shows how to train an object detection model, and this notebook instantiat... | 2023-02-25T14:53:17Z | 2023-03-23T19:24:59Z | 2023-03-23T19:24:50Z | CONTRIBUTOR | null | null | null | The following adds instructions on how to create a `DataLoader` from the guide on how to use object detection with augmentations (#4710). I am open to hearing any suggestions for improvement ! | {
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https://api.github.com/repos/huggingface/datasets/issues/7225 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/7225/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/7225/comments | https://api.github.com/repos/huggingface/datasets/issues/7225/events | https://github.com/huggingface/datasets/issues/7225 | 2,586,229,216 | I_kwDODunzps6aJrng | 7,225 | Huggingface GIT returns null as Content-Type instead of application/x-git-receive-pack-result | {
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"completed": 0,
"percent_completed": 0,
"total": 0
} | ### Describe the bug
We push changes to our datasets programmatically. Our git client jGit reports that the hf git server returns null as Content-Type after a push.
### Steps to reproduce the bug
A basic kotlin application:
```
val person = PersonIdent(
"padmalcom",
"padmalcom@sth.com"
)
val cp = UsernamePasswordCredentialsProvider(
"padmalcom",
"mysecrettoken"
)
val git =
KGit.cloneRepository {
setURI("https://huggingface.co/datasets/sth/images")
setTimeout(60)
setProgressMonitor(TextProgressMonitor())
setCredentialsProvider(cp)
}
FileOutputStream("./images/images.csv").apply { writeCsv(images) }
git.add {
addFilepattern("images.csv")
}
for (i in images) {
FileUtils.copyFile(
File("./files/${i.id}"),
File("./images/${i.id + File(i.fileName).extension }")
)
git.add {
addFilepattern("${i.id + File(i.fileName).extension }")
}
}
val revCommit = git.commit {
author = person
message = "Uploading images at " + LocalDateTime.now()
.format(DateTimeFormatter.ISO_DATE_TIME)
setCredentialsProvider(cp)
}
val push = git.push {
setCredentialsProvider(cp)
}
```
### Expected behavior
The git server is expected to return the Content-Type _application/x-git-receive-pack-result_.
### Environment info
It is independent from the datasets library. | null | {
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https://api.github.com/repos/huggingface/datasets/issues/6041 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6041/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6041/comments | https://api.github.com/repos/huggingface/datasets/issues/6041/events | https://github.com/huggingface/datasets/pull/6041 | 1,807,441,055 | PR_kwDODunzps5Vp0GX | 6,041 | Flatten repository_structure docs on yaml | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6041). 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... | 2023-07-17T10:15:10Z | 2023-07-17T10:24:51Z | 2023-07-17T10:16:22Z | MEMBER | null | null | null | To have Splits, Configurations and Builder parameters at the same doc level | {
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https://api.github.com/repos/huggingface/datasets/issues/6647 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6647/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6647/comments | https://api.github.com/repos/huggingface/datasets/issues/6647/events | https://github.com/huggingface/datasets/pull/6647 | 2,123,397,569 | PR_kwDODunzps5mSB2B | 6,647 | Update loading.mdx to include "jsonl" file loading. | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6647). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.",
"> Thanks for adding the explicit loading command.\r\n> \r\n> However, I would move it j... | 2024-02-07T16:18:08Z | 2024-02-08T15:34:17Z | null | NONE | null | null | null | * A small update to the documentation, noting the ability to load jsonl files. | null | {
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https://api.github.com/repos/huggingface/datasets/issues/6562 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6562/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6562/comments | https://api.github.com/repos/huggingface/datasets/issues/6562/events | https://github.com/huggingface/datasets/issues/6562 | 2,067,904,504 | I_kwDODunzps57Qbf4 | 6,562 | datasets.DownloadMode.FORCE_REDOWNLOAD use cache to download dataset features with load_dataset function | {
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} | [] | open | false | null | [] | null | [] | 2024-01-05T19:10:25Z | 2024-01-05T19:10:25Z | null | NONE | null | null | {
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} | ### Describe the bug
I have updated my dataset by adding a new feature, and push it to the hub. When I want to download it on my machine which contain the old version by using `datasets.load_dataset("your_dataset_name", download_mode=datasets.DownloadMode.FORCE_REDOWNLOAD)` I get an error (paste bellow).
Seems that the load_dataset function still use the old features schema instead of downloading everything new from the HUB.
I find a way to go around this issue by manually deleting the old dataset cache. But from my understanding of `datasets.DownloadMode.FORCE_REDOWNLOAD` option, the dataset cache should be ignored.
### Steps to reproduce the bug
1. Download your dataset in your machine using `datasets.load_dataset`
2. Create a new feature in your dataset and push it to the hub
3. On the same machine redownload your dataset using `datasets.load_dataset("your_dataset_name", download_mode=datasets.DownloadMode.FORCE_REDOWNLOAD)`
### Expected behavior
`
ValueError: Couldn't cast
id: string
level: string
context: list<element: string>
child 0, element: string
type: string
answer: string
question: string
supporting_facts: list<element: string>
child 0, element: string
fra_answer: string
fra_question: string
-- schema metadata --
huggingface: '{"info": {"features": {"id": {"dtype": "string", "_type": "' + 490
to
{'id': Value(dtype='string', id=None), 'level': Value(dtype='string', id=None), 'context': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'type': Value(dtype='string', id=None), 'answer': Value(dtype='string', id=None), 'question': Value(dtype='string', id=None), 'supporting_facts': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None)}
because column names don't match
The above exception was the direct cause of the following exception:
DatasetGenerationError
...
DatasetGenerationError: An error occurred while generating the dataset`
### Environment info
datasets-2.16.1 huggingface-hub-0.20.2 | null | {
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"url": "https://api.github.com/repos/huggingface/datasets/issues/6562/reactions"
} | https://api.github.com/repos/huggingface/datasets/issues/6562/timeline | null | null | null | null |
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