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https://api.github.com/repos/huggingface/datasets/issues/4441 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4441/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4441/comments | https://api.github.com/repos/huggingface/datasets/issues/4441/events | https://github.com/huggingface/datasets/issues/4441 | 1,258,568,656 | I_kwDODunzps5LBDvQ | 4,441 | Dataset Viewer issue for aeslc | {
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"Not sure what happened 😬, but it's fixed"
] | 2022-06-02T18:57:12Z | 2022-06-07T18:50:55Z | 2022-06-07T18:50:55Z | MEMBER | null | null | null | ### Link
https://huggingface.co/datasets/aeslc
### Description
The dataset viewer can't find `dataset_infos.json` in it's cache:
```
Server error
Status code: 400
Exception: FileNotFoundError
Message: [Errno 2] No such file or directory: '/cache/modules/datasets_modules/datasets/aeslc/eb8e30234cf984a58ebe9f205674597ac1db2ec91e7321cd7f36864f7e3671b8/dataset_infos.json'
```
### Owner
No | {
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https://api.github.com/repos/huggingface/datasets/issues/6079 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6079/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6079/comments | https://api.github.com/repos/huggingface/datasets/issues/6079/events | https://github.com/huggingface/datasets/issues/6079 | 1,822,597,471 | I_kwDODunzps5soqFf | 6,079 | Iterating over DataLoader based on HF datasets is stuck forever | {
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"When the process starts to hang, can you interrupt it with CTRL + C and paste the error stack trace here? ",
"Thanks @mariosasko for your prompt response, here's the stack trace:\r\n\r\n```\r\nKeyboardInterrupt Traceback (most recent call last)\r\nCell In[12], line 4\r\n 2 t = time.t... | 2023-07-26T14:52:37Z | 2023-10-05T02:58:43Z | 2023-07-30T14:09:06Z | NONE | null | null | null | ### Describe the bug
I am using Amazon Sagemaker notebook (Amazon Linux 2) with python 3.10 based Conda environment.
I have a dataset in parquet format locally. When I try to iterate over it, the loader is stuck forever. Note that the same code is working for python 3.6 based conda environment seamlessly. What should be my next steps here?
### Steps to reproduce the bug
```
train_dataset = load_dataset(
"parquet", data_files = {'train': tr_data_path + '*.parquet'},
split = 'train',
collate_fn = streaming_data_collate_fn,
streaming = True
).with_format('torch')
train_dataloader = DataLoader(train_dataset, batch_size = 2, num_workers = 0)
t = time.time()
iter_ = 0
for batch in train_dataloader:
iter_ += 1
if iter_ == 1000:
break
print (time.time() - t)
```
### Expected behavior
The snippet should work normally and load the next batch of data.
### Environment info
datasets: '2.14.0'
pyarrow: '12.0.0'
torch: '2.0.0'
Python: 3.10.10 | packaged by conda-forge | (main, Mar 24 2023, 20:08:06) [GCC 11.3.0]
!uname -r
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https://api.github.com/repos/huggingface/datasets/issues/1360 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1360/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1360/comments | https://api.github.com/repos/huggingface/datasets/issues/1360/events | https://github.com/huggingface/datasets/pull/1360 | 760,088,419 | MDExOlB1bGxSZXF1ZXN0NTM0OTc4NzM0 | 1,360 | add wisesight1000 | {
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} | `wisesight1000` contains Thai social media texts randomly drawn from the full `wisesight-sentiment`, tokenized by human annotators. Out of the labels `neg` (negative), `neu` (neutral), `pos` (positive), `q` (question), 250 samples each. Some texts are removed because they look like spam.Because these samples are representative of real world content, we believe having these annotaed samples will allow the community to robustly evaluate tokenization algorithms. | {
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https://api.github.com/repos/huggingface/datasets/issues/5074 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5074/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5074/comments | https://api.github.com/repos/huggingface/datasets/issues/5074/events | https://github.com/huggingface/datasets/issues/5074 | 1,397,850,352 | I_kwDODunzps5TUYDw | 5,074 | Replace AssertionErrors with more meaningful errors | {
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"Hi, can I pick up this issue?",
"#self-assign",
"Looks like the top-level `datasource` directory was removed when https://github.com/huggingface/datasets/pull/4974 was merged, so there are 3 source files to fix."
] | 2022-10-05T14:03:55Z | 2022-10-07T14:33:11Z | 2022-10-07T14:33:11Z | CONTRIBUTOR | null | null | null | Replace the AssertionErrors with more meaningful errors such as ValueError, TypeError, etc.
The files with AssertionErrors that need to be replaced:
```
src/datasets/arrow_reader.py
src/datasets/builder.py
src/datasets/utils/version.py
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/1827 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1827/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1827/comments | https://api.github.com/repos/huggingface/datasets/issues/1827/events | https://github.com/huggingface/datasets/issues/1827 | 802,353,974 | MDU6SXNzdWU4MDIzNTM5NzQ= | 1,827 | Regarding On-the-fly Data Loading | {
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"Possible duplicate\r\n\r\n#1776 https://github.com/huggingface/datasets/issues/\r\n\r\nreally looking PR for this feature",
"Hi @acul3 \r\n\r\nIssue #1776 talks about doing on-the-fly data pre-processing, which I think is solved in the next release as mentioned in the issue #1825. I also look forward to using t... | 2021-02-05T17:43:48Z | 2021-02-18T13:55:16Z | 2021-02-18T13:55:16Z | CONTRIBUTOR | null | null | null | Hi,
I was wondering if it is possible to load images/texts as a batch during the training process, without loading the entire dataset on the RAM at any given point.
Thanks,
Gunjan | {
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https://api.github.com/repos/huggingface/datasets/issues/5403 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5403/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5403/comments | https://api.github.com/repos/huggingface/datasets/issues/5403/events | https://github.com/huggingface/datasets/pull/5403 | 1,517,466,492 | PR_kwDODunzps5Gi3d9 | 5,403 | Replace one letter import in docs | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"> Thanks for the docs fix for consistency.\r\n> \r\n> Again for consistency, it would be nice to make the same fix across all the docs, e.g.\r\n> \r\n> https://github.com/huggingface/datasets/blob/310cdddd1c43f9658de172b85b6509d07d5e... | 2023-01-03T14:26:32Z | 2023-01-03T15:06:18Z | 2023-01-03T14:59:01Z | CONTRIBUTOR | null | 0 | {
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} | This PR updates a code example for consistency across the docs based on [feedback from this comment](https://github.com/huggingface/transformers/pull/20925/files/9fda31634d203a47d3212e4e8d43d3267faf9808#r1058769500):
"In terms of style we usually stay away from one-letter imports like this (even if the community uses them) as they are not always known by beginners and one letter is very undescriptive. Here it wouldn't change anything to use albumentations instead of A."
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https://api.github.com/repos/huggingface/datasets/issues/3653 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3653/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3653/comments | https://api.github.com/repos/huggingface/datasets/issues/3653/events | https://github.com/huggingface/datasets/issues/3653 | 1,119,186,952 | I_kwDODunzps5CtXAI | 3,653 | `to_json` in multiprocessing fashion sometimes deadlock | {
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] | open | false | null | [] | null | [] | 2022-01-31T09:35:07Z | 2022-01-31T09:35:07Z | null | CONTRIBUTOR | null | null | null | ## Describe the bug
`to_json` in multiprocessing fashion sometimes deadlock, instead of raising exceptions. Temporary solution is to see that it deadlocks, and then reduce the number of processes or batch size in order to reduce the memory footprint.
As @lhoestq pointed out, this might be related to https://bugs.python.org/issue22393#msg315684 where `multiprocessing` fails to raise the OOM exception. One suggested alternative is not use `concurrent.futures` instead.
## Steps to reproduce the bug
## Expected results
Script fails when one worker hits OOM, and raise appropriate error.
## Actual results
Deadlock
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.8.1
- Platform: Linux
- Python version: 3.8
- PyArrow version: 6.0.1
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] | 2022-06-09T22:00:44Z | 2022-06-14T16:22:02Z | 2022-06-14T16:12:00Z | MEMBER | null | 0 | {
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} | This PR updates the tutorials to be more generalizable to all modalities. After reading the tutorials, a user should be able to load any type of dataset, know how to index into and slice a dataset, and do the most basic/common type of preprocessing (tokenization, resampling, applying transforms) depending on their dataset.
Other changes include:
- Removed the sections about a dataset's metadata, features, and columns because we cover this in an earlier tutorial about inspecting the `DatasetInfo` through the dataset builder.
- Separate the sharing dataset tutorial into two sections: (1) uploading via the web interface and (2) using the `huggingface_hub` library.
- Renamed some tutorials in the TOC to be more clear and specific.
- Added more text to nudge users towards joining the community and asking questions on the forums.
- If it's okay with everyone, I'd also like to remove the section about loading and using metrics since we have the `evaluate` docs now.
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_4874). All of your documentation changes will be reflected on that endpoint."
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"@lhoestq, can you please review this PR?",
"Thanks for the suggestions. Updates were made and dataset_infos.json file was created again."
] | 2021-01-03T11:52:59Z | 2021-01-04T18:15:35Z | 2021-01-04T18:15:35Z | CONTRIBUTOR | null | 0 | {
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} | This PR added **Turkish Product Reviews Dataset contains 235.165 product reviews collected online. There are 220.284 positive, 14881 negative reviews**.
- **Repository:** [turkish-text-data](https://github.com/fthbrmnby/turkish-text-data)
- **Point of Contact:** Fatih Barmanbay - @fthbrmnby | {
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"Hi @lhoestq, on the OSCAR dataset, the document boundaries are defined by an empty line. Are there any chances to keep this empty line or explicitly group the sentences of a document? I'm asking for this 'cause I need to know if some sentences belong to the same document on my current OSCAR dataset usage.",
"Ind... | 2021-01-06T10:21:08Z | 2021-01-25T09:10:33Z | 2021-01-25T09:10:32Z | MEMBER | null | 0 | {
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} | Continuation of #348
The files have been moved to S3 and only the unshuffled version is available.
Both original and deduplicated versions of each language are available.
Example of usage:
```python
from datasets import load_dataset
oscar_dedup_en = load_dataset("oscar", "unshuffled_deduplicated_en", split="train")
oscar_orig_fr = load_dataset("oscar", "unshuffled_original_fr", split="train")
```
cc @pjox @jonatasgrosman
-------------
To make the metadata generation work in parallel I did a few changes in the `datasets-cli test` command to add the `num_proc` and `proc_rank` arguments. This way you can run multiple processes for the metadata computation.
```
datasets-cli test ./datasets/oscar --save_infos --all_configs --num_proc 4 --proc_rank 0 --clear_cache --cache_dir tmp0
```
-------------
ToDo: add the dummy_data | {
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"i need some help with this"
] | 2021-06-12T14:17:34Z | 2021-07-06T16:54:52Z | 2021-06-14T07:53:23Z | MEMBER | null | 0 | {
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} | Allow latest pyarrow version, once that version 4.0.1 fixes the segfault bug introduced in version 4.0.0.
Close #2489. | {
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https://api.github.com/repos/huggingface/datasets/issues/1726 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1726/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1726/comments | https://api.github.com/repos/huggingface/datasets/issues/1726/events | https://github.com/huggingface/datasets/pull/1726 | 784,336,370 | MDExOlB1bGxSZXF1ZXN0NTUzNTQ0ODg4 | 1,726 | Offline loading | {
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"It's maybe a bit annoying to add but could we maybe have as well a version of the local data loading scripts in the package?\r\nThe `text`, `json`, `csv`. Thinking about people like in #1725 who are expecting to be able to work with local data without downloading anything.\r\n\r\nMaybe we can add them to package_d... | 2021-01-12T15:21:57Z | 2022-02-15T10:32:10Z | 2021-01-19T16:42:32Z | MEMBER | null | 0 | {
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} | As discussed in #824 it would be cool to make the library work in offline mode.
Currently if there's not internet connection then modules (datasets or metrics) that have already been loaded in the past can't be loaded and it raises a ConnectionError.
This is because `prepare_module` fetches online for the latest version of the module.
To make it work in offline mode one suggestion was to reload the latest local version of the module.
I implemented that and I also raise a warning saying that the module that is loaded is the latest local version.
```python
logger.warning(
f"Using the latest cached version of the module from {cached_module_path} since it "
f"couldn't be found locally at {input_path} or remotely ({error_type_that_prevented_reaching_out_remote_stuff})."
)
```
I added tests to make sure it works as expected and I needed to do a few changes in the code to be able to test things properly. In particular I added a parameter `hf_modules_cache` to `init_dynamic_modules` for testing purposes. It makes it possible to have temporary modules caches for testing.
I also added a `offline` context utility that allows to test part of the code by making all the requests fail as if there was no internet.
Close #824, close #761. | {
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https://api.github.com/repos/huggingface/datasets/issues/4718 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4718/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4718/comments | https://api.github.com/repos/huggingface/datasets/issues/4718/events | https://github.com/huggingface/datasets/pull/4718 | 1,309,520,453 | PR_kwDODunzps47prWR | 4,718 | Make Extractor accept Path as input | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-07-19T13:25:06Z | 2022-07-22T13:42:27Z | 2022-07-22T13:29:43Z | MEMBER | null | 0 | {
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- Makes `Extractor` accept instance of `Path` as input
- Removes unnecessary castings of `Path` to `str` | {
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https://api.github.com/repos/huggingface/datasets/issues/1879 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1879/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1879/comments | https://api.github.com/repos/huggingface/datasets/issues/1879/events | https://github.com/huggingface/datasets/pull/1879 | 808,541,442 | MDExOlB1bGxSZXF1ZXN0NTczNTY1NDAx | 1,879 | Replace flatten_nested | {
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"Hi @lhoestq. If you agree to merge this, I will start separating the logic for NestedDataStructure.map ;)"
] | 2021-02-15T13:29:40Z | 2021-02-19T18:35:14Z | 2021-02-19T18:35:14Z | MEMBER | null | 0 | {
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} | Replace `flatten_nested` with `NestedDataStructure.flatten`.
This is a first step towards having all NestedDataStructure logic as a separated concern, independent of the caller/user of the data structure.
Eventually, all checks (whether the underlying data is list, dict, etc.) will be only inside this class.
I have also generalized the flattening, and now it handles multiple levels of nesting. | {
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https://api.github.com/repos/huggingface/datasets/issues/2096 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2096/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2096/comments | https://api.github.com/repos/huggingface/datasets/issues/2096/events | https://github.com/huggingface/datasets/issues/2096 | 838,038,379 | MDU6SXNzdWU4MzgwMzgzNzk= | 2,096 | CoNLL 2003 dataset not including German | {
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"Hello. I've been looking for information about German Conll2003 and found your question. Official site (https://www.clips.uantwerpen.be/conll2003/ner/) mentions that organizers provide only annotation. German texts (ECI Multilingual Text Corpus) are not freely available and can be ordered from the Linguistic Data ... | 2021-03-22T19:23:56Z | 2023-07-25T16:49:07Z | 2023-07-25T16:49:07Z | NONE | null | null | null | Hello, thanks for all the work on developing and maintaining this amazing platform, which I am enjoying working with!
I was wondering if there is a reason why the German CoNLL 2003 dataset is not included in the [repository](https://github.com/huggingface/datasets/tree/master/datasets/conll2003), since a copy of it could be found in some places on the internet such as GitHub? I could help adding the German data to the hub, unless there are some copyright issues that I am unaware of...
This is considering that many work use the union of CoNLL 2002 and 2003 datasets for comparing cross-lingual NER transfer performance in `en`, `de`, `es`, and `nl`. E.g., [XLM-R](https://www.aclweb.org/anthology/2020.acl-main.747.pdf).
## Adding a Dataset
- **Name:** CoNLL 2003 German
- **Paper:** https://www.aclweb.org/anthology/W03-0419/
- **Data:** https://github.com/huggingface/datasets/tree/master/datasets/conll2003
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https://api.github.com/repos/huggingface/datasets/issues/3873 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3873/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3873/comments | https://api.github.com/repos/huggingface/datasets/issues/3873/events | https://github.com/huggingface/datasets/pull/3873 | 1,163,961,578 | PR_kwDODunzps40LGoV | 3,873 | Create SQuAD metric README.md | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3873). All of your documentation changes will be reflected on that endpoint.",
"Oh one last thing I almost forgot, I think I would add a section \"Examples\" with examples of inputs and outputs and in particular: an example giv... | 2022-03-09T13:47:08Z | 2022-03-10T16:45:57Z | 2022-03-10T16:45:57Z | NONE | null | 0 | {
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} | Proposal for a metrics card structure (with an example based on the SQuAD metric).
@thomwolf @lhoestq @douwekiela @lewtun -- feel free to comment on structure or content (it's an initial draft, so I realize there's stuff missing!). | {
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"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==6.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_a... | 2023-01-25T12:33:22Z | 2023-01-26T09:37:00Z | 2023-01-26T09:27:19Z | MEMBER | null | 0 | {
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} | Allow to concatenate on axis 1 two tables made of misaligned blocks.
For example if the first table has 2 row blocks of 3 rows each, and the second table has 3 row blocks or 2 rows each.
To do that, I slice the row blocks to re-align the blocks.
Fix https://github.com/huggingface/datasets/issues/5413 | {
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"name": "dataset bug",
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"url": "https://api.github.com/repos/huggingface/datasets/labels/dataset%20bug"
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"It would help a lot to be able to preview the dataset - I'd like to see if the pronunciations are in the dataset, eg. for [\"word\"](https://en.wiktionary.org/wiki/word),\r\n\r\nPronunciation\r\n([Received Pronunciation](https://en.wikipedia.org/wiki/Received_Pronunciation)) [IPA](https://en.wiktionary.org/wiki/Wi... | 2022-05-02T20:34:25Z | 2022-05-06T15:53:30Z | 2022-05-03T11:23:48Z | NONE | null | null | null | ## Describe the bug
Error generated when attempting to download dataset
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset("bigscience-catalogue-lm-data/lm_en_wiktionary_filtered")
```
## Expected results
A clear and concise description of the expected results.
## Actual results
```
ExpectedMoreDownloadedFiles Traceback (most recent call last)
[<ipython-input-62-4ac5cf959477>](https://localhost:8080/#) in <module>()
1 from datasets import load_dataset
2
----> 3 dataset = load_dataset("bigscience-catalogue-lm-data/lm_en_wiktionary_filtered")
3 frames
[/usr/local/lib/python3.7/dist-packages/datasets/utils/info_utils.py](https://localhost:8080/#) in verify_checksums(expected_checksums, recorded_checksums, verification_name)
31 return
32 if len(set(expected_checksums) - set(recorded_checksums)) > 0:
---> 33 raise ExpectedMoreDownloadedFiles(str(set(expected_checksums) - set(recorded_checksums)))
34 if len(set(recorded_checksums) - set(expected_checksums)) > 0:
35 raise UnexpectedDownloadedFile(str(set(recorded_checksums) - set(expected_checksums)))
ExpectedMoreDownloadedFiles: {'/home/leandro/catalogue_data/datasets/lm_en_wiktionary_filtered/data/file-01.jsonl.gz', '/home/leandro/catalogue_data/datasets/lm_en_wiktionary_filtered/data/file-01.jsonl.gz.lock'}
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.18.3
- Platform: Linux-5.4.188+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.13
- PyArrow version: 6.0.1
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https://api.github.com/repos/huggingface/datasets/issues/4918 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4918/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4918/comments | https://api.github.com/repos/huggingface/datasets/issues/4918/events | https://github.com/huggingface/datasets/issues/4918 | 1,357,242,757 | I_kwDODunzps5Q5eGF | 4,918 | Dataset Viewer issue for pysentimiento/spanish-targeted-sentiment-headlines | {
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"Thanks for reporting, it's fixed now (I refreshed it manually). It's a known issue; we hope it will be fixed permanently in a few days.\r\n\r\n<img width=\"1508\" alt=\"Capture d’écran 2022-09-05 à 18 31 22\" src=\"https://user-images.githubusercontent.com/1676121/188489762-0ed86a7e-dfb3-46e8-a125-43b815a2c6f4.p... | 2022-08-31T12:09:07Z | 2022-09-05T21:36:34Z | 2022-09-05T16:32:44Z | NONE | null | null | null | ### Link
https://huggingface.co/datasets/pysentimiento/spanish-targeted-sentiment-headlines
### Description
After moving the dataset from my user (`finiteautomata`) to the `pysentimiento` organization, the dataset viewer says that it doesn't exist.
### Owner
_No response_ | {
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https://api.github.com/repos/huggingface/datasets/issues/4909 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4909/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4909/comments | https://api.github.com/repos/huggingface/datasets/issues/4909/events | https://github.com/huggingface/datasets/pull/4909 | 1,353,997,788 | PR_kwDODunzps499Fhe | 4,909 | Update GLUE evaluation metadata | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-08-29T09:43:44Z | 2022-08-29T14:53:29Z | 2022-08-29T14:51:18Z | MEMBER | null | 0 | {
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} | This PR updates the evaluation metadata for GLUE to:
* Include defaults for all configs except `ax` (which only has a `test` split with no known labels)
* Fix the default split from `test` to `validation` since `test` splits in GLUE have no labels (they're private)
* Fix the `task_id` for some existing defaults
cc @sashavor @douwekiela | {
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https://api.github.com/repos/huggingface/datasets/issues/4637 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4637/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4637/comments | https://api.github.com/repos/huggingface/datasets/issues/4637/events | https://github.com/huggingface/datasets/issues/4637 | 1,294,818,236 | I_kwDODunzps5NLVu8 | 4,637 | The "all" split breaks streaming | {
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"Thanks for reporting @cakiki.\r\n\r\nYes, this is a bug. We are investigating it.",
"@albertvillanova Nice! Let me know if it's something I can fix my self; would love to contribtue!",
"@cakiki I was working on this but if you would like to contribute, go ahead. I will close my PR. ;)\r\n\r\nFor the moment I j... | 2022-07-05T21:56:49Z | 2022-07-15T13:59:30Z | null | CONTRIBUTOR | null | null | null | ## Describe the bug
Not sure if this is a bug or just the way streaming works, but setting `streaming=True` did not work when setting `split="all"`
## Steps to reproduce the bug
The following works:
```python
ds = load_dataset('super_glue', 'wsc.fixed', split='all')
```
The following throws `ValueError: Bad split: all. Available splits: ['train', 'validation', 'test']`:
```python
ds = load_dataset('super_glue', 'wsc.fixed', split='all', streaming=True)
```
## Expected results
An iterator over all splits.
## Actual results
I had to do the following to achieve the desired result:
```python
from itertools import chain
ds = load_dataset('super_glue', 'wsc.fixed', streaming=True)
it = chain.from_iterable(ds.values())
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 2.3.2
- Platform: Linux-4.15.0-176-generic-x86_64-with-glibc2.31
- Python version: 3.10.5
- PyArrow version: 8.0.0
- Pandas version: 1.4.3
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https://api.github.com/repos/huggingface/datasets/issues/3574 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3574/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3574/comments | https://api.github.com/repos/huggingface/datasets/issues/3574/events | https://github.com/huggingface/datasets/pull/3574 | 1,101,781,401 | PR_kwDODunzps4w7vu6 | 3,574 | Fix qa4mre tags | {
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} | The YAML tags were invalid. I also fixed the dataset mirroring logging that failed because of this issue [here](https://github.com/huggingface/datasets/actions/runs/1690109581) | {
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https://api.github.com/repos/huggingface/datasets/issues/6209 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6209/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6209/comments | https://api.github.com/repos/huggingface/datasets/issues/6209/events | https://github.com/huggingface/datasets/issues/6209 | 1,879,622,000 | I_kwDODunzps5wCMFw | 6,209 | CI is broken with AssertionError: 3 failed, 12 errors | {
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See: https://github.com/huggingface/datasets/actions/runs/6069947111/job/16465138041
```
=========================== short test summary info ============================
FAILED tests/test_load.py::ModuleFactoryTest::test_LocalDatasetModuleFactoryWithoutScript_with_data_dir - AssertionError: assert ({NamedSplit('train'): ['/tmp/pytest-of-runner/pytest-0/popen-gw1/test_LocalDatasetModuleFactory2/data_dir2/subdir1/train.txt', '/tmp/pytest-of-runner/pytest-0/popen-gw1/test_LocalDatasetModuleFactory2/data_dir2/subdir1/train.txt'], NamedSplit('test'): ['/tmp/pytest-of-runner/pytest-0/popen-gw1/test_LocalDatasetModuleFactory2/data_dir2/subdir1/test.txt', '/tmp/pytest-of-runner/pytest-0/popen-gw1/test_LocalDatasetModuleFactory2/data_dir2/subdir1/test.txt']} is not None and 2 == 1)
+ where 2 = len(['/tmp/pytest-of-runner/pytest-0/popen-gw1/test_LocalDatasetModuleFactory2/data_dir2/subdir1/train.txt', '/tmp/pytest-of-runner/pytest-0/popen-gw1/test_LocalDatasetModuleFactory2/data_dir2/subdir1/train.txt'])
FAILED tests/test_load.py::test_load_dataset_arrow[False] - AssertionError: assert 20 == 10
+ where 20 = Dataset({\n features: ['col_1'],\n num_rows: 20\n}).num_rows
FAILED tests/test_load.py::test_load_dataset_arrow[True] - assert 20 == 10
ERROR tests/packaged_modules/test_audiofolder.py::test_data_files_with_metadata_and_multiple_splits[jsonl-False] - AssertionError: assert 6 == 3
+ where 6 = len(['/tmp/pytest-of-runner/pytest-0/popen-gw1/test_data_files_with_metadata_2/audiofolder_data_dir_with_metadata/train/audio_file.wav', '/tmp/pytest-of-runner/pytest-0/popen-gw1/test_data_files_with_metadata_2/audiofolder_data_dir_with_metadata/train/audio_file2.wav', '/tmp/pytest-of-runner/pytest-0/popen-gw1/test_data_files_with_metadata_2/audiofolder_data_dir_with_metadata/train/metadata.jsonl', '/tmp/pytest-of-runner/pytest-0/popen-gw1/test_data_files_with_metadata_2/audiofolder_data_dir_with_metadata/train/audio_file.wav', '/tmp/pytest-of-runner/pytest-0/popen-gw1/test_data_files_with_metadata_2/audiofolder_data_dir_with_metadata/train/audio_file2.wav', '/tmp/pytest-of-runner/pytest-0/popen-gw1/test_data_files_with_metadata_2/audiofolder_data_dir_with_metadata/train/metadata.jsonl'])
ERROR tests/packaged_modules/test_audiofolder.py::test_data_files_with_metadata_and_multiple_splits[jsonl-True] - AssertionError: assert 6 == 3
+ where 6 = len(['/tmp/pytest-of-runner/pytest-0/popen-gw1/test_data_files_with_metadata_3/audiofolder_data_dir_with_metadata/train/audio_file.wav', '/tmp/pytest-of-runner/pytest-0/popen-gw1/test_data_files_with_metadata_3/audiofolder_data_dir_with_metadata/train/audio_file2.wav', '/tmp/pytest-of-runner/pytest-0/popen-gw1/test_data_files_with_metadata_3/audiofolder_data_dir_with_metadata/train/metadata.jsonl', '/tmp/pytest-of-runner/pytest-0/popen-gw1/test_data_files_with_metadata_3/audiofolder_data_dir_with_metadata/train/audio_file.wav', '/tmp/pytest-of-runner/pytest-0/popen-gw1/test_data_files_with_metadata_3/audiofolder_data_dir_with_metadata/train/audio_file2.wav', '/tmp/pytest-of-runner/pytest-0/popen-gw1/test_data_files_with_metadata_3/audiofolder_data_dir_with_metadata/train/metadata.jsonl'])
ERROR tests/packaged_modules/test_audiofolder.py::test_data_files_with_metadata_and_multiple_splits[csv-False] - AssertionError: assert 6 == 3
+ where 6 = len(['/tmp/pytest-of-runner/pytest-0/popen-gw1/test_data_files_with_metadata_4/audiofolder_data_dir_with_metadata/train/audio_file.wav', '/tmp/pytest-of-runner/pytest-0/popen-gw1/test_data_files_with_metadata_4/audiofolder_data_dir_with_metadata/train/audio_file2.wav', '/tmp/pytest-of-runner/pytest-0/popen-gw1/test_data_files_with_metadata_4/audiofolder_data_dir_with_metadata/train/metadata.csv', '/tmp/pytest-of-runner/pytest-0/popen-gw1/test_data_files_with_metadata_4/audiofolder_data_dir_with_metadata/train/audio_file.wav', '/tmp/pytest-of-runner/pytest-0/popen-gw1/test_data_files_with_metadata_4/audiofolder_data_dir_with_metadata/train/audio_file2.wav', '/tmp/pytest-of-runner/pytest-0/popen-gw1/test_data_files_with_metadata_4/audiofolder_data_dir_with_metadata/train/metadata.csv'])
ERROR tests/packaged_modules/test_audiofolder.py::test_data_files_with_metadata_and_multiple_splits[csv-True] - AssertionError: assert 6 == 3
+ where 6 = len(['/tmp/pytest-of-runner/pytest-0/popen-gw1/test_data_files_with_metadata_5/audiofolder_data_dir_with_metadata/train/audio_file.wav', '/tmp/pytest-of-runner/pytest-0/popen-gw1/test_data_files_with_metadata_5/audiofolder_data_dir_with_metadata/train/audio_file2.wav', '/tmp/pytest-of-runner/pytest-0/popen-gw1/test_data_files_with_metadata_5/audiofolder_data_dir_with_metadata/train/metadata.csv', '/tmp/pytest-of-runner/pytest-0/popen-gw1/test_data_files_with_metadata_5/audiofolder_data_dir_with_metadata/train/audio_file.wav', '/tmp/pytest-of-runner/pytest-0/popen-gw1/test_data_files_with_metadata_5/audiofolder_data_dir_with_metadata/train/audio_file2.wav', '/tmp/pytest-of-runner/pytest-0/popen-gw1/test_data_files_with_metadata_5/audiofolder_data_dir_with_metadata/train/metadata.csv'])
ERROR tests/packaged_modules/test_folder_based_builder.py::test_data_files_with_metadata_and_splits[1-False] - AssertionError: assert 6 == 3
+ where 6 = len(['/tmp/pytest-of-runner/pytest-0/popen-gw0/test_data_files_with_metadata_3/autofolder_data_dir_with_metadata_two_splits/train/file.txt', '/tmp/pytest-of-runner/pytest-0/popen-gw0/test_data_files_with_metadata_3/autofolder_data_dir_with_metadata_two_splits/train/file2.txt', '/tmp/pytest-of-runner/pytest-0/popen-gw0/test_data_files_with_metadata_3/autofolder_data_dir_with_metadata_two_splits/train/metadata.jsonl', '/tmp/pytest-of-runner/pytest-0/popen-gw0/test_data_files_with_metadata_3/autofolder_data_dir_with_metadata_two_splits/train/file.txt', '/tmp/pytest-of-runner/pytest-0/popen-gw0/test_data_files_with_metadata_3/autofolder_data_dir_with_metadata_two_splits/train/file2.txt', '/tmp/pytest-of-runner/pytest-0/popen-gw0/test_data_files_with_metadata_3/autofolder_data_dir_with_metadata_two_splits/train/metadata.jsonl'])
ERROR tests/packaged_modules/test_folder_based_builder.py::test_data_files_with_metadata_and_splits[1-True] - AssertionError: assert 6 == 3
+ where 6 = len(['/tmp/pytest-of-runner/pytest-0/popen-gw0/test_data_files_with_metadata_4/autofolder_data_dir_with_metadata_two_splits/train/file.txt', '/tmp/pytest-of-runner/pytest-0/popen-gw0/test_data_files_with_metadata_4/autofolder_data_dir_with_metadata_two_splits/train/file2.txt', '/tmp/pytest-of-runner/pytest-0/popen-gw0/test_data_files_with_metadata_4/autofolder_data_dir_with_metadata_two_splits/train/metadata.jsonl', '/tmp/pytest-of-runner/pytest-0/popen-gw0/test_data_files_with_metadata_4/autofolder_data_dir_with_metadata_two_splits/train/file.txt', '/tmp/pytest-of-runner/pytest-0/popen-gw0/test_data_files_with_metadata_4/autofolder_data_dir_with_metadata_two_splits/train/file2.txt', '/tmp/pytest-of-runner/pytest-0/popen-gw0/test_data_files_with_metadata_4/autofolder_data_dir_with_metadata_two_splits/train/metadata.jsonl'])
ERROR tests/packaged_modules/test_folder_based_builder.py::test_data_files_with_metadata_and_splits[2-False] - AssertionError: assert 6 == 3
+ where 6 = len(['/tmp/pytest-of-runner/pytest-0/popen-gw0/test_data_files_with_metadata_5/autofolder_data_dir_with_metadata_two_splits/train/file.txt', '/tmp/pytest-of-runner/pytest-0/popen-gw0/test_data_files_with_metadata_5/autofolder_data_dir_with_metadata_two_splits/train/file2.txt', '/tmp/pytest-of-runner/pytest-0/popen-gw0/test_data_files_with_metadata_5/autofolder_data_dir_with_metadata_two_splits/train/metadata.jsonl', '/tmp/pytest-of-runner/pytest-0/popen-gw0/test_data_files_with_metadata_5/autofolder_data_dir_with_metadata_two_splits/train/file.txt', '/tmp/pytest-of-runner/pytest-0/popen-gw0/test_data_files_with_metadata_5/autofolder_data_dir_with_metadata_two_splits/train/file2.txt', '/tmp/pytest-of-runner/pytest-0/popen-gw0/test_data_files_with_metadata_5/autofolder_data_dir_with_metadata_two_splits/train/metadata.jsonl'])
ERROR tests/packaged_modules/test_imagefolder.py::test_data_files_with_metadata_and_multiple_splits[jsonl-False] - AssertionError: assert 6 == 3
+ where 6 = len(['/tmp/pytest-of-runner/pytest-0/popen-gw1/test_data_files_with_metadata_12/imagefolder_data_dir_with_metadata_two_splits/train/image_rgb.jpg', '/tmp/pytest-of-runner/pytest-0/popen-gw1/test_data_files_with_metadata_12/imagefolder_data_dir_with_metadata_two_splits/train/image_rgb2.jpg', '/tmp/pytest-of-runner/pytest-0/popen-gw1/test_data_files_with_metadata_12/imagefolder_data_dir_with_metadata_two_splits/train/metadata.jsonl', '/tmp/pytest-of-runner/pytest-0/popen-gw1/test_data_files_with_metadata_12/imagefolder_data_dir_with_metadata_two_splits/train/image_rgb.jpg', '/tmp/pytest-of-runner/pytest-0/popen-gw1/test_data_files_with_metadata_12/imagefolder_data_dir_with_metadata_two_splits/train/image_rgb2.jpg', '/tmp/pytest-of-runner/pytest-0/popen-gw1/test_data_files_with_metadata_12/imagefolder_data_dir_with_metadata_two_splits/train/metadata.jsonl'])
ERROR tests/packaged_modules/test_imagefolder.py::test_data_files_with_metadata_and_multiple_splits[jsonl-True] - AssertionError: assert 6 == 3
+ where 6 = len(['/tmp/pytest-of-runner/pytest-0/popen-gw1/test_data_files_with_metadata_13/imagefolder_data_dir_with_metadata_two_splits/train/image_rgb.jpg', '/tmp/pytest-of-runner/pytest-0/popen-gw1/test_data_files_with_metadata_13/imagefolder_data_dir_with_metadata_two_splits/train/image_rgb2.jpg', '/tmp/pytest-of-runner/pytest-0/popen-gw1/test_data_files_with_metadata_13/imagefolder_data_dir_with_metadata_two_splits/train/metadata.jsonl', '/tmp/pytest-of-runner/pytest-0/popen-gw1/test_data_files_with_metadata_13/imagefolder_data_dir_with_metadata_two_splits/train/image_rgb.jpg', '/tmp/pytest-of-runner/pytest-0/popen-gw1/test_data_files_with_metadata_13/imagefolder_data_dir_with_metadata_two_splits/train/image_rgb2.jpg', '/tmp/pytest-of-runner/pytest-0/popen-gw1/test_data_files_with_metadata_13/imagefolder_data_dir_with_metadata_two_splits/train/metadata.jsonl'])
ERROR tests/packaged_modules/test_folder_based_builder.py::test_data_files_with_metadata_and_splits[2-True] - AssertionError: assert 6 == 3
+ where 6 = len(['/tmp/pytest-of-runner/pytest-0/popen-gw0/test_data_files_with_metadata_6/autofolder_data_dir_with_metadata_two_splits/train/file.txt', '/tmp/pytest-of-runner/pytest-0/popen-gw0/test_data_files_with_metadata_6/autofolder_data_dir_with_metadata_two_splits/train/file2.txt', '/tmp/pytest-of-runner/pytest-0/popen-gw0/test_data_files_with_metadata_6/autofolder_data_dir_with_metadata_two_splits/train/metadata.jsonl', '/tmp/pytest-of-runner/pytest-0/popen-gw0/test_data_files_with_metadata_6/autofolder_data_dir_with_metadata_two_splits/train/file.txt', '/tmp/pytest-of-runner/pytest-0/popen-gw0/test_data_files_with_metadata_6/autofolder_data_dir_with_metadata_two_splits/train/file2.txt', '/tmp/pytest-of-runner/pytest-0/popen-gw0/test_data_files_with_metadata_6/autofolder_data_dir_with_metadata_two_splits/train/metadata.jsonl'])
ERROR tests/packaged_modules/test_imagefolder.py::test_data_files_with_metadata_and_multiple_splits[csv-False] - AssertionError: assert 6 == 3
+ where 6 = len(['/tmp/pytest-of-runner/pytest-0/popen-gw1/test_data_files_with_metadata_14/imagefolder_data_dir_with_metadata_two_splits/train/image_rgb.jpg', '/tmp/pytest-of-runner/pytest-0/popen-gw1/test_data_files_with_metadata_14/imagefolder_data_dir_with_metadata_two_splits/train/image_rgb2.jpg', '/tmp/pytest-of-runner/pytest-0/popen-gw1/test_data_files_with_metadata_14/imagefolder_data_dir_with_metadata_two_splits/train/metadata.csv', '/tmp/pytest-of-runner/pytest-0/popen-gw1/test_data_files_with_metadata_14/imagefolder_data_dir_with_metadata_two_splits/train/image_rgb.jpg', '/tmp/pytest-of-runner/pytest-0/popen-gw1/test_data_files_with_metadata_14/imagefolder_data_dir_with_metadata_two_splits/train/image_rgb2.jpg', '/tmp/pytest-of-runner/pytest-0/popen-gw1/test_data_files_with_metadata_14/imagefolder_data_dir_with_metadata_two_splits/train/metadata.csv'])
ERROR tests/packaged_modules/test_imagefolder.py::test_data_files_with_metadata_and_multiple_splits[csv-True] - AssertionError: assert 6 == 3
+ where 6 = len(['/tmp/pytest-of-runner/pytest-0/popen-gw1/test_data_files_with_metadata_15/imagefolder_data_dir_with_metadata_two_splits/train/image_rgb.jpg', '/tmp/pytest-of-runner/pytest-0/popen-gw1/test_data_files_with_metadata_15/imagefolder_data_dir_with_metadata_two_splits/train/image_rgb2.jpg', '/tmp/pytest-of-runner/pytest-0/popen-gw1/test_data_files_with_metadata_15/imagefolder_data_dir_with_metadata_two_splits/train/metadata.csv', '/tmp/pytest-of-runner/pytest-0/popen-gw1/test_data_files_with_metadata_15/imagefolder_data_dir_with_metadata_two_splits/train/image_rgb.jpg', '/tmp/pytest-of-runner/pytest-0/popen-gw1/test_data_files_with_metadata_15/imagefolder_data_dir_with_metadata_two_splits/train/image_rgb2.jpg', '/tmp/pytest-of-runner/pytest-0/popen-gw1/test_data_files_with_metadata_15/imagefolder_data_dir_with_metadata_two_splits/train/metadata.csv'])
= 3 failed, 2383 passed, 26 skipped, 9 warnings, 12 errors in 280.79s (0:04:40) =
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/3420 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3420/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3420/comments | https://api.github.com/repos/huggingface/datasets/issues/3420/events | https://github.com/huggingface/datasets/pull/3420 | 1,077,913,468 | PR_kwDODunzps4vukyD | 3,420 | Add eli5_category dataset | {
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"> Thanks a lot for adding this dataset ! Good job with the dataset card and the dataset scripts - they're really good :)\r\n> \r\n> I just added minor changes\r\n\r\nThanks for fixing typos!"
] | 2021-12-12T21:30:45Z | 2021-12-14T17:53:03Z | 2021-12-14T17:53:02Z | CONTRIBUTOR | null | 0 | {
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} | This pull request adds a categorized Long-form question answering dataset `ELI5_Category`. It's a new variant of the [ELI5](https://huggingface.co/datasets/eli5) dataset that uses the Reddit tags to alleviate the training/validation overlapping in the origin ELI5 dataset.
A [report](https://celeritasml.netlify.app/posts/2021-12-01-eli5c/)(Section 2) on this dataset. | {
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https://api.github.com/repos/huggingface/datasets/issues/1998 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1998/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1998/comments | https://api.github.com/repos/huggingface/datasets/issues/1998/events | https://github.com/huggingface/datasets/pull/1998 | 823,723,960 | MDExOlB1bGxSZXF1ZXN0NTg2MTE4NTQ4 | 1,998 | Add -DOCSTART- note to dataset card of conll-like datasets | {
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"Nice catch! Yes I didn't check the actual data, instead I was just looking for the `if line.startswith(\"-DOCSTART-\")` pattern."
] | 2021-03-06T19:08:29Z | 2021-03-11T02:20:07Z | 2021-03-11T02:20:07Z | CONTRIBUTOR | null | 0 | {
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} | Closes #1983 | {
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"name": "dataset-viewer",
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"Hi, thanks for reporting! This is a duplicate of https://github.com/huggingface/datasets/issues/3240. We are working on a fix.\r\n\r\n"
] | 2021-12-10T13:49:17Z | 2021-12-14T14:38:29Z | 2021-12-14T14:38:29Z | NONE | null | null | null | ## Dataset viewer issue for '* disaster_response_messages*'
**Link:** https://huggingface.co/datasets/disaster_response_messages
Dataset unavailable. Link dead: https://datasets.appen.com/appen_datasets/disaster_response_data/disaster_response_messages_training.csv
Am I the one who added this dataset ?No
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https://api.github.com/repos/huggingface/datasets/issues/1249 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1249/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1249/comments | https://api.github.com/repos/huggingface/datasets/issues/1249/events | https://github.com/huggingface/datasets/pull/1249 | 758,472,863 | MDExOlB1bGxSZXF1ZXN0NTMzNjQwNjA1 | 1,249 | Add doc2dial dataset | {
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"It not always practical to use nested `Sequence`. If you have troubles with sequence you can use lists instead. \r\n\r\nFor example\r\n```python\r\n\r\nfeatures=datasets.Features(\r\n {\r\n \"dial_id\": datasets.Value(\"string\"),\r\n \"doc_id\": datasets.Value(\"string\"),\r\n \"domain\": ... | 2020-12-07T12:39:09Z | 2020-12-14T16:17:14Z | 2020-12-14T16:17:14Z | CONTRIBUTOR | null | 0 | {
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} | ### Doc2dial: A Goal-Oriented Document-Grounded Dialogue Dataset v0.9
Once complete this will add the [Doc2dial](https://doc2dial.github.io/data.html) dataset from the generic data sets list. | {
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https://api.github.com/repos/huggingface/datasets/issues/2548 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2548/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2548/comments | https://api.github.com/repos/huggingface/datasets/issues/2548/events | https://github.com/huggingface/datasets/issues/2548 | 929,232,831 | MDU6SXNzdWU5MjkyMzI4MzE= | 2,548 | Field order issue in loading json | {
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"Hi @luyug, thanks for reporting.\r\n\r\nThe good news is that we fixed this issue only 9 days ago: #2507.\r\n\r\nThe patch is already in the master branch of our repository and it will be included in our next `datasets` release version 1.9.0.\r\n\r\nFeel free to reopen the issue if the problem persists."
] | 2021-06-24T13:29:53Z | 2021-06-24T14:36:43Z | 2021-06-24T14:34:05Z | NONE | null | null | null | ## Describe the bug
The `load_dataset` function expects columns in alphabetical order when loading json files.
Similar bug was previously reported for csv in #623 and fixed in #684.
## Steps to reproduce the bug
For a json file `j.json`,
```
{"c":321, "a": 1, "b": 2}
```
Running the following,
```
f= datasets.Features({'a': Value('int32'), 'b': Value('int32'), 'c': Value('int32')})
json_data = datasets.load_dataset('json', data_files='j.json', features=f)
```
## Expected results
A successful load.
## Actual results
```
File "pyarrow/table.pxi", line 1409, in pyarrow.lib.Table.cast
ValueError: Target schema's field names are not matching the table's field names: ['c', 'a', 'b'], ['a', 'b', 'c']
```
## Environment info
- `datasets` version: 1.8.0
- Platform: Linux-3.10.0-957.1.3.el7.x86_64-x86_64-with-glibc2.10
- Python version: 3.8.8
- PyArrow version: 3.0.0
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https://api.github.com/repos/huggingface/datasets/issues/3370 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3370/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3370/comments | https://api.github.com/repos/huggingface/datasets/issues/3370/events | https://github.com/huggingface/datasets/pull/3370 | 1,069,735,423 | PR_kwDODunzps4vUVA3 | 3,370 | Document a training loop for streaming dataset | {
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} | I added some docs about streaming dataset. In particular I added two subsections:
- one on how to use `map` for preprocessing
- one on how to use a streaming dataset in a pytorch training loop
cc @patrickvonplaten @stevhliu if you have some comments
cc @Rocketknight1 later we can add the one for TF and I might need your help ^^' | {
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https://api.github.com/repos/huggingface/datasets/issues/3664 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3664/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3664/comments | https://api.github.com/repos/huggingface/datasets/issues/3664/events | https://github.com/huggingface/datasets/pull/3664 | 1,121,233,301 | PR_kwDODunzps4x7mg_ | 3,664 | [WIP] Return local paths to Common Voice | {
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"Cool thanks for giving it a try @anton-l ! \r\n\r\nWould be very much in favor of having \"real\" paths to the audio files again for non-streaming use cases. At the same time it would be nice to make the audio data loading script as understandable as possible so that the community can easily add audio datasets in ... | 2022-02-01T21:48:27Z | 2022-02-22T09:14:06Z | 2022-02-22T09:14:06Z | MEMBER | null | 0 | {
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} | Fixes https://github.com/huggingface/datasets/issues/3663
This is a proposed way of returning the old local file-based generator while keeping the new streaming generator intact.
TODO:
- [ ] brainstorm a bit more on https://github.com/huggingface/datasets/issues/3663 to see if we can do better
- [ ] refactor the heck out of this PR to avoid completely copying the logic between the two generators | {
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https://api.github.com/repos/huggingface/datasets/issues/5690 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5690/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5690/comments | https://api.github.com/repos/huggingface/datasets/issues/5690/events | https://github.com/huggingface/datasets/issues/5690 | 1,649,289,883 | I_kwDODunzps5iTiqb | 5,690 | raise AttributeError(f"No {package_name} attribute {name}") AttributeError: No huggingface_hub attribute hf_api | {
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"Hi @wccccp, thanks for reporting. \r\nThat's weird since `huggingface_hub` _has_ a module called `hf_api` and you are using a recent version of it. \r\n\r\nWhich version of `datasets` are you using? And is it a bug that you experienced only recently? (cc @lhoestq can it be somehow related to the recent release of ... | 2023-03-31T08:22:22Z | 2023-07-21T14:21:57Z | 2023-07-21T14:21:57Z | NONE | null | null | null | ### Describe the bug
rta.sh
Traceback (most recent call last):
File "run.py", line 7, in <module>
import datasets
File "/home/appuser/miniconda3/envs/pt2/lib/python3.8/site-packages/datasets/__init__.py", line 37, in <module>
from .builder import ArrowBasedBuilder, BeamBasedBuilder, BuilderConfig, DatasetBuilder, GeneratorBasedBuilder
File "/home/appuser/miniconda3/envs/pt2/lib/python3.8/site-packages/datasets/builder.py", line 44, in <module>
from .data_files import DataFilesDict, _sanitize_patterns
File "/home/appuser/miniconda3/envs/pt2/lib/python3.8/site-packages/datasets/data_files.py", line 120, in <module>
dataset_info: huggingface_hub.hf_api.DatasetInfo,
File "/home/appuser/miniconda3/envs/pt2/lib/python3.8/site-packages/huggingface_hub/__init__.py", line 290, in __getattr__
raise AttributeError(f"No {package_name} attribute {name}")
AttributeError: No huggingface_hub attribute hf_api
### Reproduction
_No response_
### Logs
```shell
Traceback (most recent call last):
File "run.py", line 7, in <module>
import datasets
File "/home/appuser/miniconda3/envs/pt2/lib/python3.8/site-packages/datasets/__init__.py", line 37, in <module>
from .builder import ArrowBasedBuilder, BeamBasedBuilder, BuilderConfig, DatasetBuilder, GeneratorBasedBuilder
File "/home/appuser/miniconda3/envs/pt2/lib/python3.8/site-packages/datasets/builder.py", line 44, in <module>
from .data_files import DataFilesDict, _sanitize_patterns
File "/home/appuser/miniconda3/envs/pt2/lib/python3.8/site-packages/datasets/data_files.py", line 120, in <module>
dataset_info: huggingface_hub.hf_api.DatasetInfo,
File "/home/appuser/miniconda3/envs/pt2/lib/python3.8/site-packages/huggingface_hub/__init__.py", line 290, in __getattr__
raise AttributeError(f"No {package_name} attribute {name}")
AttributeError: No huggingface_hub attribute hf_api
```
### System info
```shell
- huggingface_hub version: 0.13.2
- Platform: Linux-5.4.0-144-generic-x86_64-with-glibc2.10
- Python version: 3.8.5
- Running in iPython ?: No
- Running in notebook ?: No
- Running in Google Colab ?: No
- Token path ?: /home/appuser/.cache/huggingface/token
- Has saved token ?: False
- Configured git credential helpers:
- FastAI: N/A
- Tensorflow: N/A
- Torch: 1.7.1
- Jinja2: N/A
- Graphviz: N/A
- Pydot: N/A
- Pillow: 9.3.0
- hf_transfer: N/A
- ENDPOINT: https://huggingface.co
- HUGGINGFACE_HUB_CACHE: /home/appuser/.cache/huggingface/hub
- HUGGINGFACE_ASSETS_CACHE: /home/appuser/.cache/huggingface/assets
- HF_TOKEN_PATH: /home/appuser/.cache/huggingface/token
- HF_HUB_OFFLINE: False
- HF_HUB_DISABLE_TELEMETRY: False
- HF_HUB_DISABLE_PROGRESS_BARS: None
- HF_HUB_DISABLE_SYMLINKS_WARNING: False
- HF_HUB_DISABLE_IMPLICIT_TOKEN: False
```
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https://api.github.com/repos/huggingface/datasets/issues/2951 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2951/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2951/comments | https://api.github.com/repos/huggingface/datasets/issues/2951/events | https://github.com/huggingface/datasets/pull/2951 | 1,001,267,888 | PR_kwDODunzps4r-lGs | 2,951 | Dummy labels no longer on by default in `to_tf_dataset` | {
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"@lhoestq Let me make sure we never need it, and if not then I'll remove it entirely in a follow-up PR.",
"Thanks ;) it will be less confusing and easier to maintain to not keep unused hacky features"
] | 2021-09-20T18:26:59Z | 2021-09-21T14:00:57Z | 2021-09-21T10:14:32Z | MEMBER | null | 0 | {
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} | After more experimentation, I think I have a way to do things that doesn't depend on adding `dummy_labels` - they were quite a hacky solution anyway! | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"I think it's also reasonable to add the same note to the AudioFolder decription",
"Thank you ! I think \"regular\" is more appropriate than \"small\". It can easily scale to a few thousands of images - just not millions x)",
"Rep... | 2022-12-01T21:47:29Z | 2022-12-06T17:20:04Z | 2022-12-06T17:16:53Z | MEMBER | null | 0 | {
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} | Based on feedback from [here](https://github.com/huggingface/datasets/issues/5317#issuecomment-1334108824), this PR adds a note to the `imagefolder` loading and creating docs that `imagefolder` is designed for small scale image datasets. | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-04-29T18:37:27Z | 2022-05-02T14:50:18Z | 2022-05-02T14:43:24Z | NONE | null | 0 | {
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... | null | [] | 2022-03-07T09:38:15Z | 2022-04-10T13:34:59Z | null | CONTRIBUTOR | null | null | null | It might be a mix of Image and ClassLabel, and the color palette might be generated automatically.
---
### Example
every pixel in the images of the annotation column (in https://huggingface.co/datasets/scene_parse_150) has a value that gives its class, and the dataset itself is associated with a color palette (eg https://github.com/open-mmlab/mmsegmentation/blob/98a353b674c6052d319e7de4e5bcd65d670fcf84/mmseg/datasets/ade.py#L47) that maps every class with a color.
So we might want to render the image as a colored image instead of a black and white one.
<img width="785" alt="156741519-fbae6844-2606-4c28-837e-279d83d00865" src="https://user-images.githubusercontent.com/1676121/157005263-7058c584-2b70-465a-ad94-8a982f726cf4.png">
See https://github.com/tensorflow/datasets/blob/master/tensorflow_datasets/core/features/labeled_image.py for reference in Tensorflow | {
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"<img width=\"519\" alt=\"Capture d’écran 2022-09-20 à 22 33 47\" src=\"https://user-images.githubusercontent.com/1676121/191358952-1220cb7d-745a-4203-a66b-3c707b25038f.png\">\r\n\r\n```\r\nNot found.\r\n\r\nError code: SplitsResponseNotFound\r\n```\r\n\r\nhttps://datasets-server.huggingface.co/splits?dataset=a... | 2022-09-20T16:45:45Z | 2022-09-27T07:04:03Z | 2022-09-21T07:24:07Z | NONE | null | null | null | ### Link
https://huggingface.co/datasets/asapp/slue/viewer/
### Description
Hi,
I wonder how to get the dataset viewer of our slue dataset to work.
Best,
Felix
### Owner
Yes | {
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"Since the failure was originally intermittent, there is no 100% telling that the problem is gone. \r\nBut if my artificial race condition setup https://github.com/huggingface/datasets/issues/1942#issuecomment-787124529 is to be the litmus test then the problem has been fixed, as with this PR branch that particular... | 2021-03-01T17:45:18Z | 2021-03-02T13:05:45Z | 2021-03-02T13:05:44Z | MEMBER | null | 0 | {
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} | As noticed in #1942 , there's a issue with locks if you run multiple separate evaluation experiments in a multiprocessed setup.
Indeed there is a time span in Metric._finalize() where the process 0 loses its lock before re-acquiring it. This is bad since the lock of the process 0 tells the other process that the corresponding cache file is available for writing/reading/deleting: we end up having one metric cache that collides with another one. This can raise FileNotFound errors when a metric tries to read the cache file and if the second conflicting metric deleted it.
To fix that I made sure that the lock file of the process 0 stays acquired from the cache file creation to the end of the metric computation. This way the other metrics can simply sample a new hashing name in order to avoid the collision.
Finally I added missing tests for separate experiments in distributed setup. | {
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"doing a patch release now :)"
] | 2021-09-15T14:05:10Z | 2021-09-15T17:21:49Z | 2021-09-15T17:18:23Z | MEMBER | null | null | null | When accessing examples from a dataset formatted for pytorch, some progress bars appear when accessing examples:
```python
In [1]: import datasets as ds
In [2]: d = ds.Dataset.from_dict({"a": [0, 1, 2]}).with_format("torch")
In [3]: d[0]
100%|████████████████████████████████| 1/1 [00:00<00:00, 3172.70it/s]
Out[3]: {'a': tensor(0)}
```
This is because the pytorch formatter calls `map_nested` that uses progress bars
cc @sgugger | {
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"Sorry about forgetting flake8.\r\nRather than use up the circleci resources on a new push with only formatting changes, I will wait to push until the results from all tests finish and/or any feedback comes in... probably tomorrow for me.",
"\r\nSo... my normal work is with mercurial and seem to have clearly fork... | 2020-12-09T05:52:34Z | 2020-12-15T18:12:56Z | 2020-12-15T18:12:56Z | CONTRIBUTOR | null | 0 | {
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"Thanks for the reviews! A note that I have addressed the comments, and waiting for a further review."
] | 2021-03-04T22:19:43Z | 2021-03-17T10:37:39Z | 2021-03-17T10:37:39Z | CONTRIBUTOR | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/3972 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3972/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3972/comments | https://api.github.com/repos/huggingface/datasets/issues/3972/events | https://github.com/huggingface/datasets/pull/3972 | 1,174,402,033 | PR_kwDODunzps40sdVu | 3,972 | Adding Roman Urdu Hate Speech dataset | {
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"@lhoestq can you review when you have some time? Also were the previous CI fails due to the Google Drive tests which were excluded by #3982 ?",
"> were the previous CI fails due to the Google Drive tests which were excluded by https://github.com/huggingface/datasets/pull/3982 ?\r\n\r\nYes exactly, merging `maste... | 2022-03-20T00:19:26Z | 2022-03-25T15:56:19Z | 2022-03-25T15:51:20Z | CONTRIBUTOR | null | 0 | {
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"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_a... | 2023-10-12T14:58:07Z | 2023-10-12T15:58:20Z | 2023-10-12T15:49:54Z | CONTRIBUTOR | null | 0 | {
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Could you unpin [this](https://github.com/huggingface/datasets/blob/main/setup.py#L139) or move it to test requirements? This is a testing library and we also use it for our tests as well. We do not want to use a very outdated version.
### Steps to reproduce the bug
could not install this library due to dependency conflict.
### Expected behavior
can install datasets
### Environment info
linux 64 | {
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https://api.github.com/repos/huggingface/datasets/issues/4340 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4340/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4340/comments | https://api.github.com/repos/huggingface/datasets/issues/4340/events | https://github.com/huggingface/datasets/pull/4340 | 1,234,671,025 | PR_kwDODunzps43wY1U | 4,340 | Fix irc_disentangle dataset script | {
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"Thanks ! This has been fixed in https://github.com/huggingface/datasets/pull/4377, we can close this PR"
] | 2022-05-13T02:37:57Z | 2022-05-24T15:37:30Z | 2022-05-24T15:37:29Z | NONE | null | 0 | {
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} | updated extracted dataset's repo's latest commit hash (included in tarball's name), and updated the related data_infos.json | {
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https://api.github.com/repos/huggingface/datasets/issues/1563 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1563/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1563/comments | https://api.github.com/repos/huggingface/datasets/issues/1563/events | https://github.com/huggingface/datasets/pull/1563 | 766,211,931 | MDExOlB1bGxSZXF1ZXN0NTM5MzA4Mzg4 | 1,563 | adding tmu-gfm-dataset | {
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"@lhoestq Thank you for your code review! I think I could do the necessary corrections. Could you please check it again when you have time?",
"Thank you for merging!"
] | 2020-12-14T09:45:30Z | 2020-12-21T10:21:04Z | 2020-12-21T10:07:13Z | CONTRIBUTOR | null | 0 | {
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} | Adding TMU-GFM-Dataset for Grammatical Error Correction.
https://github.com/tmu-nlp/TMU-GFM-Dataset
A dataset for GEC metrics with manual evaluations of grammaticality, fluency, and meaning preservation for system outputs.
More detail about the creation of the dataset can be found in [Yoshimura et al. (2020)](https://www.aclweb.org/anthology/2020.coling-main.573.pdf). | {
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https://api.github.com/repos/huggingface/datasets/issues/5976 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5976/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5976/comments | https://api.github.com/repos/huggingface/datasets/issues/5976/events | https://github.com/huggingface/datasets/pull/5976 | 1,768,503,913 | PR_kwDODunzps5TmAFp | 5,976 | Avoid stuck map operation when subprocesses crashes | {
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} | [] | closed | false | null | [] | null | [
"Hi ! Do you think this can be fixed at the Pool level ? Ideally it should be the Pool responsibility to handle this, not the `map` code. We could even subclass Pool if needed (at least the one from `multiprocess`)",
"@lhoestq it makes sense to me. Just pushed a refactoring creating a `class ProcessPool(multiproc... | 2023-06-21T21:18:31Z | 2023-07-10T09:58:39Z | 2023-07-10T09:50:07Z | CONTRIBUTOR | null | 0 | {
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} | I've been using Dataset.map() with `num_proc=os.cpu_count()` to leverage multicore processing for my datasets, but from time to time I get stuck processes waiting forever. Apparently, when one of the subprocesses is abruptly killed (OOM killer, segfault, SIGKILL, etc), the main process keeps waiting for the async task sent to that child process to finish.
It seems to be easy to reproduce the issue with the following script:
```
import os
from datasets import Dataset, Features, Value
def do_stuck(item):
os.kill(os.getpid(), 9)
data = {
"col1": list(range(5)),
"col2": list(range(5)),
}
ds = Dataset.from_dict(
data,
features=Features({
"col1": Value("int64"),
"col2": Value("int64"),
}),
)
print(ds.map(do_stuck, num_proc=4))
```
This is an old behavior in Python, which apparently was fixed a few years ago in `concurrent.futures.ProcessPoolExecutor` ([ref](https://bugs.python.org/issue9205)), but not in `multiprocessing.pool.Pool` / `multiprocess.pool.Pool`, which is used by `Dataset.map` ([ref](https://bugs.python.org/issue22393)).
This PR is an idea to try to detect when a child process gets killed, and raises a `RuntimeError` warning the dataset.map() caller.
EDIT: Related proposal for future improvement: https://github.com/huggingface/datasets/discussions/5977 | {
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https://api.github.com/repos/huggingface/datasets/issues/5193 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5193/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5193/comments | https://api.github.com/repos/huggingface/datasets/issues/5193/events | https://github.com/huggingface/datasets/issues/5193 | 1,433,883,780 | I_kwDODunzps5Vd1SE | 5,193 | "One or several metadata. were found, but not in the same directory or in a parent directory" | {
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} | [] | closed | false | null | [] | null | [
"Also unrelated but still: https://huggingface.co/docs/datasets/image_dataset#generate-the-dataset\r\n```If your loading script passed the test, you should now have a dataset_infos.json file in your dataset folder.```\r\nIt's not the case anymore as it's now in the readme.md, it was confusing to me",
"And here is... | 2022-11-02T22:46:25Z | 2022-11-03T13:39:16Z | 2022-11-03T13:35:44Z | NONE | null | null | null | ### Describe the bug
When loading my own dataset, on loading it I get an error.
Here is my dataset link: https://huggingface.co/datasets/corentinm7/MyoQuant-SDH-Data
And the error after loading with:
```python
from datasets import load_dataset
load_dataset("corentinm7/MyoQuant-SDH-Data")
```
```python
Downloading readme: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 3.34k/3.34k [00:00<00:00, 4.45MB/s]
Using custom data configuration SDH_16k-53e7301a92ab0025
Downloading and preparing dataset None/SDH_16k to /home/corentin/.cache/huggingface/datasets/corentinm7___imagefolder/SDH_16k-53e7301a92ab0025/0.0.0/37fbb85cc714a338bea574ac6c7d0b5be5aff46c1862c1989b20e0771199e93f...
Downloading data: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 3.28M/3.28M [00:00<00:00, 4.31MB/s]
Downloading data files: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:01<00:00, 1.75s/it]
Downloading data: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1.13G/1.13G [00:15<00:00, 74.3MB/s]
Downloading data files: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:16<00:00, 16.09s/it]
Extracting data files: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:13<00:00, 13.16s/it]
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/corentin/code-project/hugging_face_play/.venv/lib/python3.10/site-packages/datasets/load.py", line 1742, in load_dataset
builder_instance.download_and_prepare(
File "/home/corentin/code-project/hugging_face_play/.venv/lib/python3.10/site-packages/datasets/builder.py", line 814, in download_and_prepare
self._download_and_prepare(
File "/home/corentin/code-project/hugging_face_play/.venv/lib/python3.10/site-packages/datasets/builder.py", line 1423, in _download_and_prepare
super()._download_and_prepare(
File "/home/corentin/code-project/hugging_face_play/.venv/lib/python3.10/site-packages/datasets/builder.py", line 905, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/home/corentin/code-project/hugging_face_play/.venv/lib/python3.10/site-packages/datasets/builder.py", line 1374, in _prepare_split
for key, record in logging.tqdm(
File "/home/corentin/code-project/hugging_face_play/.venv/lib/python3.10/site-packages/tqdm/std.py", line 1195, in __iter__
for obj in iterable:
File "/home/corentin/code-project/hugging_face_play/.venv/lib/python3.10/site-packages/datasets/packaged_modules/folder_based_builder/folder_based_builder.py", line 394, in _generate_examples
raise ValueError(
ValueError: One or several metadata. were found, but not in the same directory or in a parent directory of /home/corentin/.cache/huggingface/datasets/downloads/extracted/60c4aa8d4da3065bb3d310de4373dffd73bd4dc331aedcb4ee867febe4fdb7cd/validation/sick/2_CG_SDH_TAM_Bin1cKO_ko_pla_4_1640.tif.
```
However the test command is working fine. ```datasets-cli test hugging_face_play/ds_test/SDH_16k.py --save_info --all_configs --force_redownload```
```
Using custom data configuration SDH_16k
Testing builder 'SDH_16k' (1/1)
Downloading and preparing dataset sdh_16k/SDH_16k to /home/corentin/.cache/huggingface/datasets/sdh_16k/SDH_16k/1.0.0/21b584239a638aeeda33cba1ac2ca4869d48e4b4f20fb22274d5a5ddc487659d...
Downloading data: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1.13G/1.13G [00:14<00:00, 76.5MB/s]
Downloading data files: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:15<00:00, 15.66s/it]
Downloading data: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 3.28M/3.28M [00:02<00:00, 1.44MB/s]
Downloading data files: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:03<00:00, 3.21s/it]
Downloading data files: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 11586.48it/s]
Extracting data files: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:13<00:00, 13.42s/it]
Dataset sdh_16k downloaded and prepared to /home/corentin/.cache/huggingface/datasets/sdh_16k/SDH_16k/1.0.0/21b584239a638aeeda33cba1ac2ca4869d48e4b4f20fb22274d5a5ddc487659d. Subsequent calls will reuse this data.
100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<00:00, 605.27it/s]
Dataset card saved at hugging_face_play/ds_test/README.md
Test successful.
```
### Steps to reproduce the bug
Simply run on python
```python
from datasets import load_dataset
load_dataset("corentinm7/MyoQuant-SDH-Data")
```
### Expected behavior
As the test command worked, this error should not appear
### Environment info
- `datasets` version: 2.6.1
- Platform: Linux-5.10.16.3-microsoft-standard-WSL2-x86_64-with-glibc2.31
- Python version: 3.10.6
- PyArrow version: 10.0.0
- Pandas version: 1.5.1
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https://api.github.com/repos/huggingface/datasets/issues/3200 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3200/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3200/comments | https://api.github.com/repos/huggingface/datasets/issues/3200/events | https://github.com/huggingface/datasets/pull/3200 | 1,042,887,291 | PR_kwDODunzps4uAZLu | 3,200 | Catch token invalid error in CI | {
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} | [] | closed | false | null | [] | null | [] | 2021-11-02T21:56:26Z | 2021-11-03T09:41:08Z | 2021-11-03T09:41:08Z | MEMBER | null | 0 | {
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I modified the fixture in the test that uses staging to ignore this error | {
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https://api.github.com/repos/huggingface/datasets/issues/4074 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4074/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4074/comments | https://api.github.com/repos/huggingface/datasets/issues/4074/events | https://github.com/huggingface/datasets/issues/4074 | 1,188,449,142 | I_kwDODunzps5G1kt2 | 4,074 | Error in google/xtreme_s dataset card | {
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"Hi @wranai, thanks for reporting.\r\n\r\nPlease note that the information about language families and groups is taken form the original paper: [XTREME-S: Evaluating Cross-lingual Speech Representations](https://arxiv.org/abs/2203.10752).\r\n\r\nIf that information is wrong, feel free to contact the paper's authors... | 2022-03-31T18:07:45Z | 2022-04-01T08:12:56Z | 2022-04-01T08:12:56Z | NONE | null | null | null | **Link:** https://huggingface.co/datasets/google/xtreme_s
Not a big deal but Hungarian is considered an Eastern European language, together with Serbian, Slovak, Slovenian (all correctly categorized; Slovenia is mostly to the West of Hungary, by the way).
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https://api.github.com/repos/huggingface/datasets/issues/1446 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1446/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1446/comments | https://api.github.com/repos/huggingface/datasets/issues/1446/events | https://github.com/huggingface/datasets/pull/1446 | 761,060,323 | MDExOlB1bGxSZXF1ZXN0NTM1Nzg1NDk1 | 1,446 | Add Bing Coronavirus Query Set | {
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https://api.github.com/repos/huggingface/datasets/issues/5627 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5627/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5627/comments | https://api.github.com/repos/huggingface/datasets/issues/5627/events | https://github.com/huggingface/datasets/issues/5627 | 1,619,336,609 | I_kwDODunzps5ghR2h | 5,627 | Unable to load AutoTrain-generated dataset from the hub | {
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"The AutoTrain format is not supported right now. I think it would require a dedicated dataset builder",
"Okay, good to know. Thanks for the reply. For now I will just have to\nmanage the split manually before training, because I can’t find any way of\npulling out file indices or file names from the autogenerated... | 2023-03-10T17:25:58Z | 2023-03-11T15:44:42Z | null | NONE | null | null | null | ### Describe the bug
DatasetGenerationError: An error occurred while generating the dataset -> ValueError: Couldn't cast ... because column names don't match
```
ValueError: Couldn't cast
_data_files: list<item: struct<filename: string>>
child 0, item: struct<filename: string>
child 0, filename: string
_fingerprint: string
_format_columns: list<item: string>
child 0, item: string
_format_kwargs: struct<>
_format_type: null
_indexes: struct<>
_output_all_columns: bool
_split: null
to
{'citation': Value(dtype='string', id=None), 'description': Value(dtype='string', id=None), 'features': {'image': {'_type': Value(dtype='string', id=None)}, 'target': {'names': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), '_type': Value(dtype='string', id=None)}}, 'homepage': Value(dtype='string', id=None), 'license': Value(dtype='string', id=None), 'splits': {'train': {'name': Value(dtype='string', id=None), 'num_bytes': Value(dtype='int64', id=None), 'num_examples': Value(dtype='int64', id=None), 'dataset_name': Value(dtype='null', id=None)}}}
because column names don't match
```
### Steps to reproduce the bug
Steps to reproduce:
1. `pip install datasets==2.10.1`
2. Attempt to load (private dataset). Note that I'm authenticated via ` huggingface-cli login`
```
from datasets import load_dataset
# load dataset
dataset = "ijmiller2/autotrain-data-betterbin-vision-10000"
dataset = load_dataset(dataset)
```
Here's the full traceback:
```Downloading and preparing dataset json/ijmiller2--autotrain-data-betterbin-vision-10000 to /Users/ian/.cache/huggingface/datasets/ijmiller2___json/ijmiller2--autotrain-data-betterbin-vision-10000-2eae034a9ff8a1a9/0.0.0/0f7e3662623656454fcd2b650f34e886a7db4b9104504885bd462096cc7a9f51...
Downloading data files: 100%|███████████████████████████████████████████████████████████████████████| 2/2 [00:00<00:00, 2383.80it/s]
Extracting data files: 100%|█████████████████████████████████████████████████████████████████████████| 2/2 [00:00<00:00, 505.95it/s]
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
File ~/anaconda3/envs/betterbin/lib/python3.8/site-packages/datasets/builder.py:1874, in ArrowBasedBuilder._prepare_split_single(self, gen_kwargs, fpath, file_format, max_shard_size, job_id)
1868 writer = writer_class(
1869 features=writer._features,
1870 path=fpath.replace("SSSSS", f"{shard_id:05d}").replace("JJJJJ", f"{job_id:05d}"),
1871 storage_options=self._fs.storage_options,
1872 embed_local_files=embed_local_files,
1873 )
-> 1874 writer.write_table(table)
1875 num_examples_progress_update += len(table)
File ~/anaconda3/envs/betterbin/lib/python3.8/site-packages/datasets/arrow_writer.py:568, in ArrowWriter.write_table(self, pa_table, writer_batch_size)
567 pa_table = pa_table.combine_chunks()
--> 568 pa_table = table_cast(pa_table, self._schema)
569 if self.embed_local_files:
File ~/anaconda3/envs/betterbin/lib/python3.8/site-packages/datasets/table.py:2312, in table_cast(table, schema)
2311 if table.schema != schema:
-> 2312 return cast_table_to_schema(table, schema)
2313 elif table.schema.metadata != schema.metadata:
File ~/anaconda3/envs/betterbin/lib/python3.8/site-packages/datasets/table.py:2270, in cast_table_to_schema(table, schema)
2269 if sorted(table.column_names) != sorted(features):
-> 2270 raise ValueError(f"Couldn't cast\n{table.schema}\nto\n{features}\nbecause column names don't match")
2271 arrays = [cast_array_to_feature(table[name], feature) for name, feature in features.items()]
ValueError: Couldn't cast
_data_files: list<item: struct<filename: string>>
child 0, item: struct<filename: string>
child 0, filename: string
_fingerprint: string
_format_columns: list<item: string>
child 0, item: string
_format_kwargs: struct<>
_format_type: null
_indexes: struct<>
_output_all_columns: bool
_split: null
to
{'citation': Value(dtype='string', id=None), 'description': Value(dtype='string', id=None), 'features': {'image': {'_type': Value(dtype='string', id=None)}, 'target': {'names': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), '_type': Value(dtype='string', id=None)}}, 'homepage': Value(dtype='string', id=None), 'license': Value(dtype='string', id=None), 'splits': {'train': {'name': Value(dtype='string', id=None), 'num_bytes': Value(dtype='int64', id=None), 'num_examples': Value(dtype='int64', id=None), 'dataset_name': Value(dtype='null', id=None)}}}
because column names don't match
The above exception was the direct cause of the following exception:
DatasetGenerationError Traceback (most recent call last)
Input In [8], in <cell line: 6>()
4 # load dataset
5 dataset = "ijmiller2/autotrain-data-betterbin-vision-10000"
----> 6 dataset = load_dataset(dataset)
File ~/anaconda3/envs/betterbin/lib/python3.8/site-packages/datasets/load.py:1782, in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, verification_mode, ignore_verifications, keep_in_memory, save_infos, revision, use_auth_token, task, streaming, num_proc, **config_kwargs)
1779 try_from_hf_gcs = path not in _PACKAGED_DATASETS_MODULES
1781 # Download and prepare data
-> 1782 builder_instance.download_and_prepare(
1783 download_config=download_config,
1784 download_mode=download_mode,
1785 verification_mode=verification_mode,
1786 try_from_hf_gcs=try_from_hf_gcs,
1787 num_proc=num_proc,
1788 )
1790 # Build dataset for splits
1791 keep_in_memory = (
1792 keep_in_memory if keep_in_memory is not None else is_small_dataset(builder_instance.info.dataset_size)
1793 )
File ~/anaconda3/envs/betterbin/lib/python3.8/site-packages/datasets/builder.py:872, in DatasetBuilder.download_and_prepare(self, output_dir, download_config, download_mode, verification_mode, ignore_verifications, try_from_hf_gcs, dl_manager, base_path, use_auth_token, file_format, max_shard_size, num_proc, storage_options, **download_and_prepare_kwargs)
870 if num_proc is not None:
871 prepare_split_kwargs["num_proc"] = num_proc
--> 872 self._download_and_prepare(
873 dl_manager=dl_manager,
874 verification_mode=verification_mode,
875 **prepare_split_kwargs,
876 **download_and_prepare_kwargs,
877 )
878 # Sync info
879 self.info.dataset_size = sum(split.num_bytes for split in self.info.splits.values())
File ~/anaconda3/envs/betterbin/lib/python3.8/site-packages/datasets/builder.py:967, in DatasetBuilder._download_and_prepare(self, dl_manager, verification_mode, **prepare_split_kwargs)
963 split_dict.add(split_generator.split_info)
965 try:
966 # Prepare split will record examples associated to the split
--> 967 self._prepare_split(split_generator, **prepare_split_kwargs)
968 except OSError as e:
969 raise OSError(
970 "Cannot find data file. "
971 + (self.manual_download_instructions or "")
972 + "\nOriginal error:\n"
973 + str(e)
974 ) from None
File ~/anaconda3/envs/betterbin/lib/python3.8/site-packages/datasets/builder.py:1749, in ArrowBasedBuilder._prepare_split(self, split_generator, file_format, num_proc, max_shard_size)
1747 job_id = 0
1748 with pbar:
-> 1749 for job_id, done, content in self._prepare_split_single(
1750 gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
1751 ):
1752 if done:
1753 result = content
File ~/anaconda3/envs/betterbin/lib/python3.8/site-packages/datasets/builder.py:1892, in ArrowBasedBuilder._prepare_split_single(self, gen_kwargs, fpath, file_format, max_shard_size, job_id)
1890 if isinstance(e, SchemaInferenceError) and e.__context__ is not None:
1891 e = e.__context__
-> 1892 raise DatasetGenerationError("An error occurred while generating the dataset") from e
1894 yield job_id, True, (total_num_examples, total_num_bytes, writer._features, num_shards, shard_lengths)
DatasetGenerationError: An error occurred while generating the dataset
```
### Expected behavior
I'm ultimately trying to generate my own performance metrics on validation data (before putting an endpoint into production) and so was hoping to load all or at least the validation subset from the hub.
I'm expecting the `load_dataset()` function to work as shown in the documentation [here](https://huggingface.co/docs/datasets/loading#hugging-face-hub):
```python
dataset = load_dataset(
"lhoestq/custom_squad",
revision="main" # tag name, or branch name, or commit hash
)
```
### Environment info
- `datasets` version: 2.10.1
- Platform: macOS-13.2.1-arm64-arm-64bit
- Python version: 3.8.13
- PyArrow version: 9.0.0
- Pandas version: 1.4.4 | {
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"We have added a comment on an existing issue opened in their repo: https://github.com/google-research/google-research/issues/1212#issuecomment-1192267130\r\n- https://github.com/google-research/google-research/issues/1212"
] | 2022-07-22T07:15:05Z | 2022-07-22T07:45:19Z | 2022-07-22T07:45:18Z | MEMBER | null | null | null | ## Describe the bug
After the today release of `rouge_score-0.0.7` it seems no longer importable. Our CI fails: https://github.com/huggingface/datasets/runs/7463218591?check_suite_focus=true
```
FAILED tests/test_dataset_common.py::LocalDatasetTest::test_builder_class_bigbench
FAILED tests/test_dataset_common.py::LocalDatasetTest::test_builder_configs_bigbench
FAILED tests/test_dataset_common.py::LocalDatasetTest::test_load_dataset_bigbench
FAILED tests/test_metric_common.py::LocalMetricTest::test_load_metric_rouge
```
with errors:
```
> from rouge_score import rouge_scorer
E ModuleNotFoundError: No module named 'rouge_score'
```
```
E ImportError: To be able to use rouge, you need to install the following dependency: rouge_score.
E Please install it using 'pip install rouge_score' for instance'
```
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https://api.github.com/repos/huggingface/datasets/issues/3544 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3544/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3544/comments | https://api.github.com/repos/huggingface/datasets/issues/3544/events | https://github.com/huggingface/datasets/issues/3544 | 1,095,784,681 | I_kwDODunzps5BUFjp | 3,544 | Ability to split a dataset in multiple files. | {
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] | open | false | null | [] | null | [] | 2022-01-06T23:02:25Z | 2022-01-06T23:02:25Z | null | CONTRIBUTOR | null | null | null | Hello,
**Is your feature request related to a problem? Please describe.**
My use case is that I have one writer that adds columns and multiple workers reading the same `Dataset`. Each worker should have access to columns added by the writer when they reload the dataset.
I understand that we shouldn't overwrite an arrow file as this could cause Segfault and so on. Before 1.16, I was able to overwrite the dataset and that would work most of the time with some retries.
**Describe the solution you'd like**
I was thinking that if we could append `Dataset._data_files`, when the workers reload the Dataset, they would get the new columns.
**Describe alternatives you've considered**
I currently need to
1. Save multiple "versions" of the dataset and load the latest.
2. Try working with cache files to get the latest columns.
**Additional context**
I think this would be a great addition to HFDataset as Parquet supports multi-files input out of the box!
I can make a PR myself with some pointers as needed :) | {
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https://api.github.com/repos/huggingface/datasets/issues/6259 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6259/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6259/comments | https://api.github.com/repos/huggingface/datasets/issues/6259/events | https://github.com/huggingface/datasets/issues/6259 | 1,911,965,758 | I_kwDODunzps5x9kg- | 6,259 | Duplicated Rows When Loading Parquet Files from Root Directory with Subdirectories | {
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"Thanks for reporting this issue! We should be able to avoid this by making our `glob` patterns more precise. In the meantime, you can load the dataset by directly assigning splits to the data files: \r\n```python\r\nfrom datasets import load_dataset\r\nds = load_dataset(\"parquet\", data_files={\"train\": \"testin... | 2023-09-25T17:20:54Z | 2023-09-26T17:54:08Z | null | NONE | null | null | null | ### Describe the bug
When parquet files are saved in "train" and "val" subdirectories under a root directory, and datasets are then loaded using `load_dataset("parquet", data_dir="root_directory")`, the resulting dataset has duplicated rows for both the training and validation sets.
### Steps to reproduce the bug
1. Create a root directory, e.g., "testing123".
2. Under "testing123", create two subdirectories: "train" and "val".
3. Create and save a parquet file with 3 unique rows in the "train" subdirectory.
4. Create and save a parquet file with 4 unique rows in the "val" subdirectory.
5. Load the datasets from the root directory using `load_dataset("parquet", data_dir="testing123")`
6. Iterate through the datasets and print the rows
Here's a collab reproducing these steps:
https://colab.research.google.com/drive/11NEdImnQ3OqJlwKSHRMhr7jCBesNdLY4?usp=sharing
### Expected behavior
- Training set should contain 3 unique rows.
- Validation set should contain 4 unique rows.
### Environment info
- `datasets` version: 2.14.5
- Platform: Linux-5.15.120+-x86_64-with-glibc2.35
- Python version: 3.10.12
- Huggingface_hub version: 0.17.2
- PyArrow version: 9.0.0
- Pandas version: 1.5.3 | {
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https://api.github.com/repos/huggingface/datasets/issues/1554 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1554/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1554/comments | https://api.github.com/repos/huggingface/datasets/issues/1554/events | https://github.com/huggingface/datasets/pull/1554 | 765,675,148 | MDExOlB1bGxSZXF1ZXN0NTM5MDMwNDU2 | 1,554 | Opus CAPES added | {
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"@lhoestq I saw some common changes you made on the other PR's (Similar Opus Datasets). I fixed those changes here. Can you please review it once ? \r\nThanks.",
"Hi @rkc007 , thanks for the contribution.\r\nUnfortunately, the CAPES dataset has already been added here: #1307\r\nI'm closing the PR ",
"@lhoestq F... | 2020-12-13T22:11:34Z | 2020-12-18T09:54:57Z | 2020-12-18T08:46:59Z | CONTRIBUTOR | null | 0 | {
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} | Dataset : http://opus.nlpl.eu/CAPES.php | {
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https://api.github.com/repos/huggingface/datasets/issues/5112 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5112/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5112/comments | https://api.github.com/repos/huggingface/datasets/issues/5112/events | https://github.com/huggingface/datasets/issues/5112 | 1,409,143,409 | I_kwDODunzps5T_dJx | 5,112 | Bug with filtered indices | {
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"The issue is here:\r\nhttps://github.com/huggingface/datasets/blob/3ad9644b9a2e4558dd1d0f1e43c67658674e6228/src/datasets/arrow_dataset.py#L2964",
"@PartiallyTyped, @Muennighoff: the issue is fixed.\r\n\r\nWe are planning to make a patch release today.",
"Thanks a lot for the swift response! For a brief moment ... | 2022-10-14T10:35:47Z | 2022-10-14T13:55:03Z | 2022-10-14T12:11:45Z | MEMBER | null | null | null | ## Describe the bug
As reported by @PartiallyTyped (and by @Muennighoff):
- https://github.com/huggingface/datasets/issues/5111#issuecomment-1278652524
There is an issue with the indices of a filtered dataset.
## Steps to reproduce the bug
```python
ds = Dataset.from_dict({"num": [0, 1, 2, 3]})
ds = ds.filter(lambda num: num % 2 == 0, input_columns="num", batch_size=2)
assert all(item["num"] % 2 == 0 for item in ds)
```
## Expected results
The indices of the filtered dataset should correspond to the examples with "language" equals to "english".
## Actual results
Indices to items with other languages are included in the filtered dataset indices
## Preliminar investigation
It seems a bug introduced by:
- #5030
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https://api.github.com/repos/huggingface/datasets/issues/2607 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2607/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2607/comments | https://api.github.com/repos/huggingface/datasets/issues/2607/events | https://github.com/huggingface/datasets/issues/2607 | 938,796,902 | MDU6SXNzdWU5Mzg3OTY5MDI= | 2,607 | Streaming local gzip compressed JSON line files is not working | {
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"Updating to pyarrow-4.0.1 didn't fix the issue",
"Here is an exemple dataset with 2 of these compressed JSON files: https://huggingface.co/datasets/thomwolf/github-python",
"Hi @thomwolf, thanks for reporting.\r\n\r\nIt seems this might be due to the fact that the JSON Dataset builder uses `pyarrow.json` (`paj... | 2021-07-07T11:36:33Z | 2021-07-20T09:50:19Z | 2021-07-08T16:08:41Z | MEMBER | null | null | null | ## Describe the bug
Using streaming to iterate on local gzip compressed JSON files raise a file not exist error
## Steps to reproduce the bug
```python
from datasets import load_dataset
streamed_dataset = load_dataset('json', split='train', data_files=data_files, streaming=True)
next(iter(streamed_dataset))
```
## Actual results
```
FileNotFoundError Traceback (most recent call last)
<ipython-input-6-27a664e29784> in <module>
----> 1 next(iter(streamed_dataset))
~/Documents/GitHub/datasets/src/datasets/iterable_dataset.py in __iter__(self)
336
337 def __iter__(self):
--> 338 for key, example in self._iter():
339 if self.features:
340 # we encode the example for ClassLabel feature types for example
~/Documents/GitHub/datasets/src/datasets/iterable_dataset.py in _iter(self)
333 else:
334 ex_iterable = self._ex_iterable
--> 335 yield from ex_iterable
336
337 def __iter__(self):
~/Documents/GitHub/datasets/src/datasets/iterable_dataset.py in __iter__(self)
76
77 def __iter__(self):
---> 78 for key, example in self.generate_examples_fn(**self.kwargs):
79 yield key, example
80
~/Documents/GitHub/datasets/src/datasets/iterable_dataset.py in wrapper(**kwargs)
282 def wrapper(**kwargs):
283 python_formatter = PythonFormatter()
--> 284 for key, table in generate_tables_fn(**kwargs):
285 batch = python_formatter.format_batch(table)
286 for i, example in enumerate(_batch_to_examples(batch)):
~/Documents/GitHub/datasets/src/datasets/packaged_modules/json/json.py in _generate_tables(self, files, original_files)
85 file,
86 read_options=self.config.pa_read_options,
---> 87 parse_options=self.config.pa_parse_options,
88 )
89 except pa.ArrowInvalid as err:
~/miniconda2/envs/datasets/lib/python3.7/site-packages/pyarrow/_json.pyx in pyarrow._json.read_json()
~/miniconda2/envs/datasets/lib/python3.7/site-packages/pyarrow/_json.pyx in pyarrow._json._get_reader()
~/miniconda2/envs/datasets/lib/python3.7/site-packages/pyarrow/io.pxi in pyarrow.lib.get_input_stream()
~/miniconda2/envs/datasets/lib/python3.7/site-packages/pyarrow/io.pxi in pyarrow.lib.get_native_file()
~/miniconda2/envs/datasets/lib/python3.7/site-packages/pyarrow/io.pxi in pyarrow.lib.OSFile.__cinit__()
~/miniconda2/envs/datasets/lib/python3.7/site-packages/pyarrow/io.pxi in pyarrow.lib.OSFile._open_readable()
~/miniconda2/envs/datasets/lib/python3.7/site-packages/pyarrow/error.pxi in pyarrow.lib.pyarrow_internal_check_status()
~/miniconda2/envs/datasets/lib/python3.7/site-packages/pyarrow/error.pxi in pyarrow.lib.check_status()
FileNotFoundError: [Errno 2] Failed to open local file 'gzip://file-000000000000.json::/Users/thomwolf/github-dataset/file-000000000000.json.gz'. Detail: [errno 2] No such file or directory
```
## Environment info
- `datasets` version: 1.9.1.dev0
- Platform: Darwin-19.6.0-x86_64-i386-64bit
- Python version: 3.7.7
- PyArrow version: 1.0.0 | {
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https://api.github.com/repos/huggingface/datasets/issues/5131 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5131/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5131/comments | https://api.github.com/repos/huggingface/datasets/issues/5131/events | https://github.com/huggingface/datasets/issues/5131 | 1,413,534,863 | I_kwDODunzps5UQNSP | 5,131 | WikiText 103 tokenizer hangs | {
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] | closed | false | null | [] | null | [
"any updates on this? It happens to me on [OpenWikiText-20%](https://huggingface.co/datasets/Bingsu/openwebtext_20p) dataset, but not on [OpenWebText-10k](https://huggingface.co/datasets/stas/openwebtext-10k). This is really strange because I don't change anything else in my running script.\r\n\r\ntransformers vers... | 2022-10-18T16:44:00Z | 2023-08-08T08:42:40Z | 2023-07-21T14:41:51Z | NONE | null | null | null | See issue here: https://github.com/huggingface/transformers/issues/19702 | {
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https://api.github.com/repos/huggingface/datasets/issues/2587 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2587/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2587/comments | https://api.github.com/repos/huggingface/datasets/issues/2587/events | https://github.com/huggingface/datasets/pull/2587 | 936,771,339 | MDExOlB1bGxSZXF1ZXN0NjgzNDI5NjQy | 2,587 | Add aiohttp to tests extras require | {
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} | [] | closed | false | null | [] | null | [] | 2021-07-05T07:14:01Z | 2021-07-05T09:04:38Z | 2021-07-05T09:04:38Z | MEMBER | null | 0 | {
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} | Currently, none of the streaming tests are runned within our CI test suite, because the streaming tests require aiohttp and this is missing from our tests extras require dependencies.
Our CI test suite should be exhaustive and test all the library functionalities. | {
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https://api.github.com/repos/huggingface/datasets/issues/1644 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1644/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1644/comments | https://api.github.com/repos/huggingface/datasets/issues/1644/events | https://github.com/huggingface/datasets/issues/1644 | 775,375,880 | MDU6SXNzdWU3NzUzNzU4ODA= | 1,644 | HoVeR dataset fails to load | {
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"Hover was added recently, that's why it wasn't available yet.\r\n\r\nTo load it you can just update `datasets`\r\n```\r\npip install --upgrade datasets\r\n```\r\n\r\nand then you can load `hover` with\r\n\r\n```python\r\nfrom datasets import load_dataset\r\n\r\ndataset = load_dataset(\"hover\")\r\n```"
] | 2020-12-28T12:27:07Z | 2022-10-05T12:40:34Z | 2022-10-05T12:40:34Z | NONE | null | null | null | Hi! I'm getting an error when trying to load **HoVeR** dataset. Another one (**SQuAD**) does work for me. I'm using the latest (1.1.3) version of the library.
Steps to reproduce the error:
```python
>>> from datasets import load_dataset
>>> dataset = load_dataset("hover")
Traceback (most recent call last):
File "/Users/urikz/anaconda/envs/mentionmemory/lib/python3.7/site-packages/datasets/load.py", line 267, in prepare_module
local_path = cached_path(file_path, download_config=download_config)
File "/Users/urikz/anaconda/envs/mentionmemory/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 308, in cached_path
use_etag=download_config.use_etag,
File "/Users/urikz/anaconda/envs/mentionmemory/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 486, in get_from_cache
raise FileNotFoundError("Couldn't find file at {}".format(url))
FileNotFoundError: Couldn't find file at https://raw.githubusercontent.com/huggingface/datasets/1.1.3/datasets/hover/hover.py
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/Users/urikz/anaconda/envs/mentionmemory/lib/python3.7/site-packages/datasets/load.py", line 278, in prepare_module
local_path = cached_path(file_path, download_config=download_config)
File "/Users/urikz/anaconda/envs/mentionmemory/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 308, in cached_path
use_etag=download_config.use_etag,
File "/Users/urikz/anaconda/envs/mentionmemory/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 486, in get_from_cache
raise FileNotFoundError("Couldn't find file at {}".format(url))
FileNotFoundError: Couldn't find file at https://s3.amazonaws.com/datasets.huggingface.co/datasets/datasets/hover/hover.py
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/Users/urikz/anaconda/envs/mentionmemory/lib/python3.7/site-packages/datasets/load.py", line 589, in load_dataset
path, script_version=script_version, download_config=download_config, download_mode=download_mode, dataset=True
File "/Users/urikz/anaconda/envs/mentionmemory/lib/python3.7/site-packages/datasets/load.py", line 282, in prepare_module
combined_path, github_file_path, file_path
FileNotFoundError: Couldn't find file locally at hover/hover.py, or remotely at https://raw.githubusercontent.com/huggingface/datasets/1.1.3/datasets/hover/hover.py or https://s3.amazonaws.com/datasets.huggingface.co/datasets/datasets/hover/hover.py
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/3084 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3084/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3084/comments | https://api.github.com/repos/huggingface/datasets/issues/3084/events | https://github.com/huggingface/datasets/issues/3084 | 1,026,428,992 | I_kwDODunzps49LhBA | 3,084 | VisibleDeprecationWarning when using `set_format("numpy")` | {
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"I just opened a PR and I verified that the code you provided doesn't show any deprecation warning :)"
] | 2021-10-14T13:53:01Z | 2021-10-22T16:04:14Z | 2021-10-22T16:04:14Z | MEMBER | null | null | null | Code to reproduce:
```
from datasets import load_dataset
dataset = load_dataset("glue", "mnli")
from transformers import AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained('distilbert-base-cased')
def tokenize_function(dataset):
return tokenizer(dataset['premise'])
tokenized_datasets = dataset.map(tokenize_function, batched=True, remove_columns=dataset['train'].features)
tokenized_datasets.set_format("numpy")
tokenized_datasets['train'][5:8]
```
Outputs:
```
python3.9/site-packages/datasets/formatting/formatting.py:167: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray
return np.array(array, copy=False, **self.np_array_kwargs)
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/3087 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3087/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3087/comments | https://api.github.com/repos/huggingface/datasets/issues/3087/events | https://github.com/huggingface/datasets/issues/3087 | 1,026,780,469 | I_kwDODunzps49M201 | 3,087 | Removing label column in a text classification dataset yields to errors | {
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] | closed | false | null | [] | null | [] | 2021-10-14T20:12:50Z | 2021-10-15T10:11:04Z | 2021-10-15T10:11:04Z | CONTRIBUTOR | null | null | null | ## Describe the bug
This looks like #3059 but it's not linked to the cache this time. Removing the `label` column from a text classification dataset and then performing any processing will result in an error.
To reproduce:
```py
from datasets import load_dataset
from transformers import AutoTokenizer
raw_datasets = load_dataset("imdb")
raw_datasets = raw_datasets.remove_columns("label")
model_checkpoint = "distilbert-base-cased"
tokenizer = AutoTokenizer.from_pretrained(model_checkpoint)
context_length = 128
def tokenize_pad_and_truncate(texts):
return tokenizer(texts["text"], truncation=True, padding="max_length", max_length=context_length)
tokenized_datasets = raw_datasets.map(tokenize_pad_and_truncate, batched=True)
```
Traceback:
```
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
<ipython-input-1-ba61bb32f786> in <module>
12 return tokenizer(texts["text"], truncation=True, padding="max_length", max_length=context_length)
13
---> 14 tokenized_datasets = raw_datasets.map(tokenize_pad_and_truncate, batched=True)
~/git/datasets/src/datasets/dataset_dict.py in map(self, function, with_indices, input_columns, batched, batch_size, remove_columns, keep_in_memory, load_from_cache_file, cache_file_names, writer_batch_size, features, disable_nullable, fn_kwargs, num_proc, desc)
500 desc=desc,
501 )
--> 502 for k, dataset in self.items()
503 }
504 )
~/git/datasets/src/datasets/dataset_dict.py in <dictcomp>(.0)
500 desc=desc,
501 )
--> 502 for k, dataset in self.items()
503 }
504 )
~/git/datasets/src/datasets/arrow_dataset.py in map(self, function, with_indices, input_columns, batched, batch_size, drop_last_batch, remove_columns, keep_in_memory, load_from_cache_file, cache_file_name, writer_batch_size, features, disable_nullable, fn_kwargs, num_proc, suffix_template, new_fingerprint, desc)
2051 new_fingerprint=new_fingerprint,
2052 disable_tqdm=disable_tqdm,
-> 2053 desc=desc,
2054 )
2055 else:
~/git/datasets/src/datasets/arrow_dataset.py in wrapper(*args, **kwargs)
501 self: "Dataset" = kwargs.pop("self")
502 # apply actual function
--> 503 out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
504 datasets: List["Dataset"] = list(out.values()) if isinstance(out, dict) else [out]
505 for dataset in datasets:
~/git/datasets/src/datasets/arrow_dataset.py in wrapper(*args, **kwargs)
468 }
469 # apply actual function
--> 470 out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
471 datasets: List["Dataset"] = list(out.values()) if isinstance(out, dict) else [out]
472 # re-apply format to the output
~/git/datasets/src/datasets/fingerprint.py in wrapper(*args, **kwargs)
404 # Call actual function
405
--> 406 out = func(self, *args, **kwargs)
407
408 # Update fingerprint of in-place transforms + update in-place history of transforms
~/git/datasets/src/datasets/arrow_dataset.py in _map_single(self, function, with_indices, input_columns, batched, batch_size, drop_last_batch, remove_columns, keep_in_memory, load_from_cache_file, cache_file_name, writer_batch_size, features, disable_nullable, fn_kwargs, new_fingerprint, rank, offset, disable_tqdm, desc, cache_only)
2243 if os.path.exists(cache_file_name) and load_from_cache_file:
2244 logger.warning("Loading cached processed dataset at %s", cache_file_name)
-> 2245 info = self.info.copy()
2246 info.features = features
2247 info.task_templates = None
~/git/datasets/src/datasets/info.py in copy(self)
278
279 def copy(self) -> "DatasetInfo":
--> 280 return self.__class__(**{k: copy.deepcopy(v) for k, v in self.__dict__.items()})
281
282
~/git/datasets/src/datasets/info.py in __init__(self, description, citation, homepage, license, features, post_processed, supervised_keys, task_templates, builder_name, config_name, version, splits, download_checksums, download_size, post_processing_size, dataset_size, size_in_bytes)
~/git/datasets/src/datasets/info.py in __post_init__(self)
177 for idx, template in enumerate(self.task_templates):
178 if isinstance(template, TextClassification):
--> 179 labels = self.features[template.label_column].names
180 self.task_templates[idx] = TextClassification(
181 text_column=template.text_column, label_column=template.label_column, labels=labels
KeyError: 'label'
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/3595 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3595/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3595/comments | https://api.github.com/repos/huggingface/datasets/issues/3595/events | https://github.com/huggingface/datasets/pull/3595 | 1,107,260,527 | PR_kwDODunzps4xOIxH | 3,595 | Add ImageNet toy datasets from fastai | {
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"color": "0e8a16",
"default": false,
"description": "Contribution to a dataset script",
"id": 4564477500,
"name": "dataset contribution",
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] | closed | false | null | [] | null | [
"Thanks for your contribution, @mariosasko. Are you still interested in adding this dataset?\r\n\r\nWe are removing the dataset scripts from this GitHub repo and moving them to the Hugging Face Hub: https://huggingface.co/datasets\r\n\r\nWe would suggest you create this dataset there. Please, feel free to tell us i... | 2022-01-18T19:03:35Z | 2023-09-24T09:39:07Z | 2022-09-30T14:39:35Z | CONTRIBUTOR | null | 1 | {
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} | Adds the ImageNet toy datasets from FastAI: Imagenette, Imagewoof and Imagewang.
TODOs:
* [ ] add dummy data
* [ ] add dataset card
* [ ] generate `dataset_info.json` | {
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https://api.github.com/repos/huggingface/datasets/issues/3810 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3810/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3810/comments | https://api.github.com/repos/huggingface/datasets/issues/3810/events | https://github.com/huggingface/datasets/pull/3810 | 1,158,202,093 | PR_kwDODunzps4z4WUW | 3,810 | Update version of xcopa dataset | {
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} | [] | closed | false | null | [] | null | [] | 2022-03-03T09:58:25Z | 2022-03-03T10:44:30Z | 2022-03-03T10:44:29Z | MEMBER | null | 0 | {
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} | Note that there was a version update of the `xcopa` dataset: https://github.com/cambridgeltl/xcopa/releases
We updated our loading script, but we did not bump a new version number:
- #3254
This PR updates our loading script version from `1.0.0` to `1.1.0`. | {
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https://api.github.com/repos/huggingface/datasets/issues/4875 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4875/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4875/comments | https://api.github.com/repos/huggingface/datasets/issues/4875/events | https://github.com/huggingface/datasets/issues/4875 | 1,348,095,686 | I_kwDODunzps5QWk7G | 4,875 | `_resolve_features` ignores the token | {
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"gists... | null | [
"Hi ! Your HF_ENDPOINT seems wrong because of the extra \"/\"\r\n```diff\r\n- os.environ[\"HF_ENDPOINT\"] = \"https://hub-ci.huggingface.co/\"\r\n+ os.environ[\"HF_ENDPOINT\"] = \"https://hub-ci.huggingface.co\"\r\n```\r\n\r\ncan you try again without the extra \"/\" ?",
"Oh, yes, sorry, but it's not the issue.\r... | 2022-08-23T14:57:36Z | 2022-10-17T13:45:47Z | null | CONTRIBUTOR | null | null | null | ## Describe the bug
When calling [`_resolve_features()`](https://github.com/huggingface/datasets/blob/54b532a8a2f5353fdb0207578162153f7b2da2ec/src/datasets/iterable_dataset.py#L1255) on a gated dataset, ie. a dataset which requires a token to be loaded, the token seems to be ignored even if it has been provided to `load_dataset` before.
## Steps to reproduce the bug
```python
import os
os.environ["HF_ENDPOINT"] = "https://hub-ci.huggingface.co/"
hf_token = "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"
from datasets import load_dataset
# public
dataset_name = "__DUMMY_DATASETS_SERVER_USER__/repo_csv_data-16612654226756"
config_name = "__DUMMY_DATASETS_SERVER_USER__--repo_csv_data-16612654226756"
split_name = "train"
iterable_dataset = load_dataset(
dataset_name,
name=config_name,
split=split_name,
streaming=True,
use_auth_token=hf_token,
)
iterable_dataset = iterable_dataset._resolve_features()
print(iterable_dataset.features)
# gated
dataset_name = "__DUMMY_DATASETS_SERVER_USER__/repo_csv_data-16612654317644"
config_name = "__DUMMY_DATASETS_SERVER_USER__--repo_csv_data-16612654317644"
split_name = "train"
iterable_dataset = load_dataset(
dataset_name,
name=config_name,
split=split_name,
streaming=True,
use_auth_token=hf_token,
)
try:
iterable_dataset = iterable_dataset._resolve_features()
except FileNotFoundError as e:
print("FAILS")
```
## Expected results
I expect to have the same result on a public dataset and on a gated (or private) dataset, if the token has been provided.
## Actual results
An exception is thrown on gated datasets.
## Environment info
- `datasets` version: 2.4.0
- Platform: Linux-5.15.0-1017-aws-x86_64-with-glibc2.35
- Python version: 3.9.6
- PyArrow version: 7.0.0
- Pandas version: 1.4.2 | {
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https://api.github.com/repos/huggingface/datasets/issues/4111 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4111/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4111/comments | https://api.github.com/repos/huggingface/datasets/issues/4111/events | https://github.com/huggingface/datasets/pull/4111 | 1,194,660,699 | PR_kwDODunzps41vJCt | 4,111 | Update security policy | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-04-06T13:59:51Z | 2022-04-07T09:46:30Z | 2022-04-07T09:40:27Z | MEMBER | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/3494 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3494/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3494/comments | https://api.github.com/repos/huggingface/datasets/issues/3494/events | https://github.com/huggingface/datasets/pull/3494 | 1,089,983,103 | PR_kwDODunzps4wV0vB | 3,494 | Clone full repo to detect new tags when mirroring datasets on the Hub | {
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"Good catch !!",
"The CI fail is unrelated to this PR and fixed on master, merging :)"
] | 2021-12-28T15:50:47Z | 2021-12-28T16:07:21Z | 2021-12-28T16:07:20Z | MEMBER | null | 0 | {
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} | The new releases of `datasets` were not detected because the shallow clone in the CI wasn't getting the git tags.
By cloning the full repository we can properly detect a new release, and tag all the dataset repositories accordingly
cc @SBrandeis | {
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https://api.github.com/repos/huggingface/datasets/issues/2774 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2774/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2774/comments | https://api.github.com/repos/huggingface/datasets/issues/2774/events | https://github.com/huggingface/datasets/pull/2774 | 963,932,199 | MDExOlB1bGxSZXF1ZXN0NzA2NDY2MDc0 | 2,774 | Prevent .map from using multiprocessing when loading from cache | {
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"I'm guessing tests are failling, because this was pushed before https://github.com/huggingface/datasets/pull/2779 was merged? cc @albertvillanova ",
"Hi @thomasw21, yes you are right: those failing tests were fixed with #2779.\r\n\r\nWould you mind to merge current upstream master branch and push again?\r\n```\r... | 2021-08-09T12:11:38Z | 2021-09-09T10:20:28Z | 2021-09-09T10:20:28Z | CONTRIBUTOR | null | 0 | {
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} | ## Context
On our setup, we use different setup to train vs proprocessing datasets. Usually we are able to obtain a high number of cpus to preprocess, which allows us to use `num_proc` however we can't use as many during training phase. Currently if we use `num_proc={whatever the preprocessing value was}` we load from cache, but we get:
```
Traceback (most recent call last):
File "lib/python3.8/site-packages/multiprocess/pool.py", line 131, in worker
put((job, i, result))
File "lib/python3.8/site-packages/multiprocess/queues.py", line 371, in put
self._writer.send_bytes(obj)
File "lib/python3.8/site-packages/multiprocess/connection.py", line 203, in send_bytes
self._send_bytes(m[offset:offset + size])
File "lib/python3.8/site-packages/multiprocess/connection.py", line 414, in _send_bytes
self._send(header + buf)
File "lib/python3.8/site-packages/multiprocess/connection.py", line 371, in _send
n = write(self._handle, buf)
BrokenPipeError: [Errno 32] Broken pipe
```
Our current guess, is that we're spawning too many processes compared to the number of cpus available, and it's running OOM. Also we're loading this in DDP setting which means that for each gpu, I need to spawn a high number of processes to match the preprocessing fingerprint.
Instead what we suggest:
- Allow loading shard sequentially, sharing the same fingerprint as the multiprocessed one, in order to leverage multiprocessing when we actually generate the cache, and remove it when loading from cache.
## Current issues
~I'm having a hard time making fingerprints match. For some reason, the multiprocessing and the sequential version generate two different hash.~
**EDIT**: Turns out multiprocessing and sequential have different `transform` value for fingerprinting (check `fingerprint_transform`) when running `_map_single`:
- sequential : `datasets.arrow_dataset.Dataset._map_single`
- multiprocessing: `datasets.arrow_dataset._map_single`
This discrepancy is caused by multiprocessing pickling the transformer function, it doesn't seem to keep the `Dataset` hierarchy. I'm still unclear on why `func.__qual_name__` isn't handled correctly in multiprocessing. But replacing `__qualname__` by `__name__` fixes the issue.
## What was done
~We try to prevent the usage of multiprocessing when loading a dataset. Instead we load all cached shards sequentially.~
I couldn't find a nice way to obtain the cached_file_name and check they all exist before deciding to use the multiprocessing flow or not. Instead I expose an optional boolean `sequential` in `map` method.
## TODO
- [x] Check that the multiprocessed version and the sequential version output the same output
- [x] Check that sequential can load multiprocessed
- [x] Check that multiprocessed can load sequential
## Test
```python
from datasets import load_dataset
from multiprocessing import Pool
import random
def process(batch, rng):
length = len(batch["text"])
return {**batch, "processed_text": [f"PROCESSED {rng.random()}" for _ in range(length)]}
dataset = load_dataset("stas/openwebtext-10k", split="train")
print(dataset.column_names)
print(type(dataset))
rng = random.Random(42)
dataset1 = dataset.map(process, batched=True, batch_size=50, num_proc=4, fn_kwargs={"rng": rng})
# This one should be loaded from cache
rng = random.Random(42)
dataset2 = dataset.map(process, batched=True, batch_size=50, num_proc=4, fn_kwargs={"rng": rng}, sequential=True)
# Just to check that the random generator was correct
print(dataset1[-1]["processed_text"])
print(dataset2[-1]["processed_text"])
```
## Other solutions
I chose to load everything sequentially, but we can probably find a way to load shards in parallel using another number of workers (essentially this would be an argument not used for fingerprinting, allowing to allow `m` shards using `n` processes, which would be very useful when same dataset have to be loaded on two different setup, and we still want to leverage cache).
Also we can use a env variable similarly to `TOKENIZERS_PARALLELISM` as this seems generally setup related (though this changes slightly if we use multiprocessing).
cc @lhoestq (since I had asked you previously on `num_proc` being used for fingerprinting). Don't know if this is acceptable. | {
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https://api.github.com/repos/huggingface/datasets/issues/5826 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5826/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5826/comments | https://api.github.com/repos/huggingface/datasets/issues/5826/events | https://github.com/huggingface/datasets/pull/5826 | 1,698,155,751 | PR_kwDODunzps5P5FYZ | 5,826 | Support working_dir in from_spark | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Added env var",
"@lhoestq would you or another maintainer be able to review please? :)",
"I removed the env var",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!<... | 2023-05-05T20:22:40Z | 2023-05-25T17:45:54Z | 2023-05-25T08:46:15Z | CONTRIBUTOR | null | 0 | {
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} | Accept `working_dir` as an argument to `Dataset.from_spark`. Setting a non-NFS working directory for Spark workers to materialize to will improve write performance. | {
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https://api.github.com/repos/huggingface/datasets/issues/4062 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4062/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4062/comments | https://api.github.com/repos/huggingface/datasets/issues/4062/events | https://github.com/huggingface/datasets/issues/4062 | 1,186,330,732 | I_kwDODunzps5Gtfhs | 4,062 | Loading mozilla-foundation/common_voice_7_0 dataset failed | {
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"Hi @aapot, thanks for reporting.\r\n\r\nWe are investigating the cause of this issue. We will keep you informed. ",
"When making HTTP request from code line:\r\n```\r\nresponse = requests.get(f\"{_API_URL}/bucket/dataset/{path}/{use_cdn}\", timeout=10.0).json()\r\n```\r\nit cannot be decoded to JSON because it r... | 2022-03-30T11:39:41Z | 2022-06-21T07:36:23Z | 2022-03-31T08:18:04Z | NONE | null | null | null | ## Describe the bug
I wanted to load `mozilla-foundation/common_voice_7_0` dataset with `fi` language and `test` split from datasets on Colab/Kaggle notebook, but I am getting an error `JSONDecodeError: [Errno Expecting value] Not Found: 0` while loading it. The bug seems to affect other languages and splits too than just the `fi` and `test` split.
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset("mozilla-foundation/common_voice_7_0", "fi", split="test", use_auth_token="YOUR TOKEN")
```
## Expected results
load `mozilla-foundation/common_voice_7_0` dataset succesfully
## Actual results
```
JSONDecodeError Traceback (most recent call last)
/opt/conda/lib/python3.7/site-packages/requests/models.py in json(self, **kwargs)
909 try:
--> 910 return complexjson.loads(self.text, **kwargs)
911 except JSONDecodeError as e:
/opt/conda/lib/python3.7/site-packages/simplejson/__init__.py in loads(s, encoding, cls, object_hook, parse_float, parse_int, parse_constant, object_pairs_hook, use_decimal, **kw)
524 and not use_decimal and not kw):
--> 525 return _default_decoder.decode(s)
526 if cls is None:
/opt/conda/lib/python3.7/site-packages/simplejson/decoder.py in decode(self, s, _w, _PY3)
369 s = str(s, self.encoding)
--> 370 obj, end = self.raw_decode(s)
371 end = _w(s, end).end()
/opt/conda/lib/python3.7/site-packages/simplejson/decoder.py in raw_decode(self, s, idx, _w, _PY3)
399 idx += 3
--> 400 return self.scan_once(s, idx=_w(s, idx).end())
JSONDecodeError: Expecting value: line 1 column 1 (char 0)
During handling of the above exception, another exception occurred:
JSONDecodeError Traceback (most recent call last)
/tmp/ipykernel_358/370980805.py in <module>
1 # load Common Voice 7.0 dataset from Huggingface with Finnish "test" split
----> 2 test_dataset = load_dataset("mozilla-foundation/common_voice_7_0", "fi", split="test", use_auth_token=True)
/opt/conda/lib/python3.7/site-packages/datasets/load.py in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, ignore_verifications, keep_in_memory, save_infos, revision, use_auth_token, task, streaming, **config_kwargs)
1690 ignore_verifications=ignore_verifications,
1691 try_from_hf_gcs=try_from_hf_gcs,
-> 1692 use_auth_token=use_auth_token,
1693 )
1694
/opt/conda/lib/python3.7/site-packages/datasets/builder.py in download_and_prepare(self, download_config, download_mode, ignore_verifications, try_from_hf_gcs, dl_manager, base_path, use_auth_token, **download_and_prepare_kwargs)
604 if not downloaded_from_gcs:
605 self._download_and_prepare(
--> 606 dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
607 )
608 # Sync info
/opt/conda/lib/python3.7/site-packages/datasets/builder.py in _download_and_prepare(self, dl_manager, verify_infos)
1102
1103 def _download_and_prepare(self, dl_manager, verify_infos):
-> 1104 super()._download_and_prepare(dl_manager, verify_infos, check_duplicate_keys=verify_infos)
1105
1106 def _get_examples_iterable_for_split(self, split_generator: SplitGenerator) -> ExamplesIterable:
/opt/conda/lib/python3.7/site-packages/datasets/builder.py in _download_and_prepare(self, dl_manager, verify_infos, **prepare_split_kwargs)
670 split_dict = SplitDict(dataset_name=self.name)
671 split_generators_kwargs = self._make_split_generators_kwargs(prepare_split_kwargs)
--> 672 split_generators = self._split_generators(dl_manager, **split_generators_kwargs)
673
674 # Checksums verification
~/.cache/huggingface/modules/datasets_modules/datasets/mozilla-foundation--common_voice_7_0/fe20cac47c166e25b1f096ab661832e3da7cf298ed4a91dcaa1343ad972d175b/common_voice_7_0.py in _split_generators(self, dl_manager)
151
152 self._log_download(self.config.name, bundle_version, hf_auth_token)
--> 153 archive = dl_manager.download(self._get_bundle_url(self.config.name, bundle_url_template))
154
155 if self.config.version < datasets.Version("5.0.0"):
~/.cache/huggingface/modules/datasets_modules/datasets/mozilla-foundation--common_voice_7_0/fe20cac47c166e25b1f096ab661832e3da7cf298ed4a91dcaa1343ad972d175b/common_voice_7_0.py in _get_bundle_url(self, locale, url_template)
130 path = urllib.parse.quote(path.encode("utf-8"), safe="~()*!.'")
131 use_cdn = self.config.size_bytes < 20 * 1024 * 1024 * 1024
--> 132 response = requests.get(f"{_API_URL}/bucket/dataset/{path}/{use_cdn}", timeout=10.0).json()
133 return response["url"]
134
/opt/conda/lib/python3.7/site-packages/requests/models.py in json(self, **kwargs)
915 raise RequestsJSONDecodeError(e.message)
916 else:
--> 917 raise RequestsJSONDecodeError(e.msg, e.doc, e.pos)
918
919 @property
JSONDecodeError: [Errno Expecting value] Not Found: 0
```
## Environment info
- `datasets` version: 2.0.0
- Platform: Linux-5.10.90+-x86_64-with-debian-bullseye-sid
- Python version: 3.7.12
- PyArrow version: 5.0.0
- Pandas version: 1.3.5
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https://api.github.com/repos/huggingface/datasets/issues/6040 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6040/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6040/comments | https://api.github.com/repos/huggingface/datasets/issues/6040/events | https://github.com/huggingface/datasets/pull/6040 | 1,807,410,238 | PR_kwDODunzps5VptVf | 6,040 | Fix legacy_dataset_infos | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2023-07-17T09:56:21Z | 2023-07-17T10:24:34Z | 2023-07-17T10:16:03Z | MEMBER | null | 0 | {
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https://circleci.com/gh/huggingface/transformers/855105 | {
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https://api.github.com/repos/huggingface/datasets/issues/3922 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3922/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3922/comments | https://api.github.com/repos/huggingface/datasets/issues/3922/events | https://github.com/huggingface/datasets/pull/3922 | 1,169,761,293 | PR_kwDODunzps40d6vm | 3,922 | Fix NonMatchingChecksumError in MultiWOZ 2.2 dataset | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3922). All of your documentation changes will be reflected on that endpoint.",
"Unrelated CI test failure. This PR can be merged."
] | 2022-03-15T14:36:28Z | 2022-03-15T16:07:04Z | 2022-03-15T16:07:03Z | MEMBER | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/5773 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5773/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5773/comments | https://api.github.com/repos/huggingface/datasets/issues/5773/events | https://github.com/huggingface/datasets/issues/5773 | 1,675,984,633 | I_kwDODunzps5j5X75 | 5,773 | train_dataset does not implement __len__ | {
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"Thanks for reporting, @v-yunbin.\r\n\r\nCould you please give more details, the steps to reproduce the bug, the complete error back trace and the environment information (`datasets-cli env`)?",
"this is a detail error info from transformers：\r\n```\r\nTraceback (most recent call last):\r\n File \"finetune.py\",... | 2023-04-20T04:37:05Z | 2023-07-19T20:33:13Z | null | NONE | null | null | null | when train using data precessored by the datasets, I get follow warning and it leads to that I can not set epoch numbers:
`ValueError: The train_dataset does not implement __len__, max_steps has to be specified. The number of steps needs to be known in advance for the learning rate scheduler.` | {
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https://api.github.com/repos/huggingface/datasets/issues/4320 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4320/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4320/comments | https://api.github.com/repos/huggingface/datasets/issues/4320/events | https://github.com/huggingface/datasets/issues/4320 | 1,233,208,864 | I_kwDODunzps5JgUYg | 4,320 | Multi-news dataset loader attempts to strip wrong character from beginning of summaries | {
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"Hi ! Thanks for reporting :)\r\n\r\nThis dataset was simply converted from [tensorflow datasets](https://github.com/tensorflow/datasets/blob/master/tensorflow_datasets/summarization/multi_news.py)\r\n\r\nI think we can just remove the `.strip(\"- \")` and keep this character",
"Cool! I made a PR."
] | 2022-05-11T21:36:41Z | 2022-05-16T13:52:10Z | 2022-05-16T13:52:10Z | CONTRIBUTOR | null | null | null | ## Describe the bug
The `multi_news.py` data loader has [a line which attempts to strip `"- "` from the beginning of summaries](https://github.com/huggingface/datasets/blob/aa743886221d76afb409d263e1b136e7a71fe2b4/datasets/multi_news/multi_news.py#L97). The actual character in the multi-news dataset, however, is `"– "`, which is different, e.g. `"– " != "- "`.
I would have just opened a PR to fix the mistake, but I am wondering what the motivation for stripping this character is? AFAICT most approaches just leave it in, e.g. the current SOTA on this dataset, [PRIMERA](https://huggingface.co/allenai/PRIMERA-multinews) (you can see its in the generated summaries of the model in their [example notebook](https://github.com/allenai/PRIMER/blob/main/Evaluation_Example.ipynb)).
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 2.2.0
- Platform: Linux-5.4.188+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.13
- PyArrow version: 6.0.1
- Pandas version: 1.3.5
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https://api.github.com/repos/huggingface/datasets/issues/3885 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3885/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3885/comments | https://api.github.com/repos/huggingface/datasets/issues/3885/events | https://github.com/huggingface/datasets/pull/3885 | 1,165,102,209 | PR_kwDODunzps40O00Z | 3,885 | Fix some shuffle docs | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3885). All of your documentation changes will be reflected on that endpoint."
] | 2022-03-10T11:29:15Z | 2022-03-10T14:16:29Z | 2022-03-10T14:16:28Z | MEMBER | null | 0 | {
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} | Following #3842 some docs were still outdated (with `buffer_size` as the first argument) | {
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https://api.github.com/repos/huggingface/datasets/issues/5563 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5563/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5563/comments | https://api.github.com/repos/huggingface/datasets/issues/5563/events | https://github.com/huggingface/datasets/pull/5563 | 1,595,049,025 | PR_kwDODunzps5KgtbL | 5,563 | Release: 2.10.0 | {
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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==6.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2023-02-22T12:48:52Z | 2023-02-22T13:05:55Z | 2023-02-22T12:56:48Z | MEMBER | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/3118 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3118/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3118/comments | https://api.github.com/repos/huggingface/datasets/issues/3118/events | https://github.com/huggingface/datasets/pull/3118 | 1,031,309,549 | PR_kwDODunzps4tb0LY | 3,118 | Fix CI error at each release commit | {
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} | Fix test_load_dataset_canonical at release commit.
Fix #3117. | {
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https://api.github.com/repos/huggingface/datasets/issues/3480 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3480/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3480/comments | https://api.github.com/repos/huggingface/datasets/issues/3480/events | https://github.com/huggingface/datasets/issues/3480 | 1,088,267,110 | I_kwDODunzps5A3aNm | 3,480 | the compression format requested when saving a dataset in json format is not respected | {
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"Thanks for reporting @SaulLu.\r\n\r\nAt first sight I think the problem is caused because `pandas` only takes into account the `compression` parameter if called with a non-null file path or buffer. And in our implementation, we call pandas `to_json` with `None` `path_or_buf`.\r\n\r\nWe should fix this:\r\n- either... | 2021-12-24T09:23:51Z | 2022-01-05T13:03:35Z | 2022-01-05T13:03:35Z | CONTRIBUTOR | null | null | null | ## Describe the bug
In the documentation of the `to_json` method, it is stated in the parameters that
> **to_json_kwargs – Parameters to pass to pandas’s pandas.DataFrame.to_json.
however when we pass for example `compression="gzip"`, the saved file is not compressed.
Would you also have expected compression to be applied? :relaxed:
## Steps to reproduce the bug
```python
my_dict = {"a": [1, 2, 3], "b": [1, 2, 3]}
```
### Result with datasets
```python
from datasets import Dataset
dataset = Dataset.from_dict(my_dict)
dataset.to_json("dic_with_datasets.jsonl.gz", compression="gzip")
!cat dic_with_datasets.jsonl.gz
```
output
```
{"a":1,"b":1}
{"a":2,"b":2}
{"a":3,"b":3}
```
Note: I would expected to see binary data here
### Result with pandas
```python
import pandas as pd
df = pd.DataFrame(my_dict)
df.to_json("dic_with_pandas.jsonl.gz", lines=True, orient="records", compression="gzip")
!cat dic_with_pandas.jsonl.gz
```
output
```
4��a�dic_with_pandas.jsonl��VJT�2�QJ��\� ��g��yƵ���������)���
```
Note: It looks like binary data
## Expected results
I would have expected that the saved result with datasets would also be a binary file
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.16.1
- Platform: Linux-4.18.0-193.70.1.el8_2.x86_64-x86_64-with-glibc2.17
- Python version: 3.8.11
- PyArrow version: 5.0.0
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https://api.github.com/repos/huggingface/datasets/issues/4914 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4914/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4914/comments | https://api.github.com/repos/huggingface/datasets/issues/4914/events | https://github.com/huggingface/datasets/pull/4914 | 1,355,482,624 | PR_kwDODunzps4-CFyN | 4,914 | Support streaming swda dataset | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-08-30T09:46:28Z | 2022-08-30T11:16:33Z | 2022-08-30T11:14:16Z | MEMBER | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/3669 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3669/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3669/comments | https://api.github.com/repos/huggingface/datasets/issues/3669/events | https://github.com/huggingface/datasets/pull/3669 | 1,122,335,622 | PR_kwDODunzps4x_OTI | 3,669 | Common voice validated partition | {
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"Hi @patrickvonplaten - could you please advise whether this would be a welcomed change, and if so, who I consult regarding the unit-tests?",
"I'd be happy with adding this change. @anton-l @lhoestq - what do you think?",
"Cool ! I just fixed the tests by adding a dummy `validated.tsv` file in the dummy data ar... | 2022-02-02T20:04:43Z | 2022-02-08T17:26:52Z | 2022-02-08T17:23:12Z | CONTRIBUTOR | null | 0 | {
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} | This patch adds access to the 'validated' partitions of CommonVoice datasets (provided by the dataset creators but not available in the HuggingFace interface yet).
As 'validated' contains significantly more data than 'train' (although it contains both test and validation, so one needs to be careful there), it can be useful to train better models where no strict comparison with the previous work is intended. | {
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https://api.github.com/repos/huggingface/datasets/issues/2255 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2255/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2255/comments | https://api.github.com/repos/huggingface/datasets/issues/2255/events | https://github.com/huggingface/datasets/pull/2255 | 866,242,892 | MDExOlB1bGxSZXF1ZXN0NjIyMTc0Njg4 | 2,255 | Task casting for text classification & question answering | {
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"cc @abhi1thakur ",
"Looks really nice so far, thanks !\r\nMaybe if a dataset doesn't have a template for a specific task we could try the default template of this task ?",
"hey @SBrandeis @lhoestq,\r\n\r\ni now have a better idea about what you guys are trying to achieve with the task templates and have a few ... | 2021-04-23T16:00:41Z | 2021-05-18T13:31:36Z | 2021-05-18T13:31:35Z | CONTRIBUTOR | null | 0 | {
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} | This PR implements task preparation for a given task, in the continuation of #2143
Task taxonomy follows 🤗 Transformers's pipelines taxonomy: https://github.com/huggingface/transformers/tree/master/src/transformers/pipelines
Edit by @lewtun:
This PR implements support for the following tasks:
* `text-classification`
* `question-answering`
The intended usage is as follows:
```python
# Load a dataset with default column names / features
ds = load_dataset("dataset_name")
# Cast column names / features to schema. Casting is defined in the dataset's `DatasetInfo`
ds = ds.prepare_for_task(task="text-classification")
# Casting can also be realised during load
ds = load_dataset("dataset_name", task="text-classification")
# We can also combine shared tasks across dataset concatenation
ds1 = load_dataset("dataset_name_1", task="text-classification")
ds2 = load_dataset("dataset_name_2", task="text-classification")
# If the tasks have the same schema, so will `ds_concat`
ds_concat = concatenate_datasets([ds1, ds2])
```
Note that the current implementation assumes that `DatasetInfo.task_templates` has been pre-defined by the user / contributor when overriding the `MyDataset(GeneratorBasedBuilder)._info` function.
As pointed out by @SBrandeis, for evaluation we'll need a way to detect which datasets are already have a compatible schema so we don't have to edit hundreds of dataset scripts. One possibility is to check if the schema features are a subset of the dataset ones, e.g.
```python
squad = load_dataset("./datasets/squad", split="train")
qa = QuestionAnswering()
schema = Features({**qa.input_schema, **qa.label_schema})
assert all(item in squad.features.items() for item in schema.items())
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/6222 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6222/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6222/comments | https://api.github.com/repos/huggingface/datasets/issues/6222/events | https://github.com/huggingface/datasets/pull/6222 | 1,884,875,510 | PR_kwDODunzps5Zup2f | 6,222 | fix typo in Audio dataset documentation | {
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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... | 2023-09-06T23:17:24Z | 2023-10-03T14:18:41Z | 2023-09-07T15:39:09Z | CONTRIBUTOR | null | 0 | {
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} | There is a typo in the section of the documentation dedicated to creating an audio dataset. The Dataset is incorrectly suffixed with a `Config`
https://huggingface.co/datasets/indonesian-nlp/librivox-indonesia/blob/main/librivox-indonesia.py#L59 | {
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https://api.github.com/repos/huggingface/datasets/issues/2119 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2119/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2119/comments | https://api.github.com/repos/huggingface/datasets/issues/2119/events | https://github.com/huggingface/datasets/pull/2119 | 841,567,199 | MDExOlB1bGxSZXF1ZXN0NjAxMjg2MjIy | 2,119 | copy.deepcopy os.environ instead of copy | {
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} | Fixes: https://github.com/huggingface/datasets/issues/2115
- bug fix: using envrion.copy() returns a dict.
- using deepcopy(environ) returns an `_environ` object
- Changing the datatype of the _environ object can break code, if subsequent libraries perform operations using apis exclusive to the environ object, like `environ.getenv()` for example.
Testing:
Tested the change on my terminal:
```
>>> import os
>>> x = deepcopy(os.environ)
>>> y = os.environ
>>> x is y
False
>>> isinstance(x, type(os.environ))
True
>>> z = os.environ.copy()
>>> isinstance(z, type(os.environ))
False
>>> isinstance(z, dict)
True
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/5642 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5642/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5642/comments | https://api.github.com/repos/huggingface/datasets/issues/5642/events | https://github.com/huggingface/datasets/pull/5642 | 1,626,043,177 | PR_kwDODunzps5MIjw9 | 5,642 | Bump hfh to 0.11.0 | {
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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... | 2023-03-15T18:26:07Z | 2023-03-20T12:34:09Z | 2023-03-20T12:26:58Z | MEMBER | null | 0 | {
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} | to fix errors like
```
requests.exceptions.HTTPError: 400 Client Error: Bad Request for url: https://hub-ci.huggingface.co/api/datasets/__DUMMY_TRANSFORMERS_USER__/...
```
(e.g. from this [failing CI](https://github.com/huggingface/datasets/actions/runs/4428956210/jobs/7769160997))
0.11.0 is the current minimum version in `transformers`
around 5% of users are currently using versions `<0.11.0` | {
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https://api.github.com/repos/huggingface/datasets/issues/3288 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3288/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3288/comments | https://api.github.com/repos/huggingface/datasets/issues/3288/events | https://github.com/huggingface/datasets/pull/3288 | 1,056,145,703 | PR_kwDODunzps4up6S5 | 3,288 | Allow datasets with indices table when concatenating along axis=1 | {
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} | Calls `flatten_indices` on the datasets with indices table in `concatenate_datasets` to fix issues when concatenating along `axis=1`.
cc @lhoestq: I decided to flatten all the datasets instead of flattening all the datasets except the largest one in the end. The latter approach fails on the following example:
```python
a = Dataset.from_dict({"a": [10, 20, 30, 40]})
b = Dataset.from_dict({"b": [10, 20, 30, 40, 50, 60]}) # largest dataset
a = a.select([1, 2, 3])
b = b.select([1, 2, 3])
concatenate_datasets([a, b], axis=1) # fails at line concat_tables(...) because the real length of b's data is 6 and a's length is 3 after flattening (was 4 before flattening)
```
Also, it requires additional re-ordering of indices to prepare them for working with the indices table of the largest dataset. IMO not worth when we save only one `flatten_indices` call. (feel free to check the code of that approach at https://github.com/huggingface/datasets/commit/6acd10481c70950dcfdbfd2bab0bf0c74ad80bcb if you are interested)
Fixes #3273
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} | Close #2542.
cc: @VictorSanh. | {
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"gists... | null | [
"the same issue with datasets.load_dataset(\"iwslt2017\", 'iwslt2017-en-nl', split=split), ..... ",
"even with setting master like the following command, still remains \r\n\r\ndatasets.load_dataset(\"iwslt2017\", 'iwslt2017-en-nl', split=\"train\", script_version=\"master\")\r\n",
"Looks like the data has been ... | 2020-12-08T09:56:55Z | 2022-06-13T10:41:33Z | 2022-06-13T10:41:33Z | CONTRIBUTOR | null | null | null | Hi
I am trying
`>>> datasets.load_dataset("iwslt2017", 'iwslt2017-ro-nl', split="train")`
getting this error thank you for your help
```
cahce dir /idiap/temp/rkarimi/cache_home_1/datasets
cahce dir /idiap/temp/rkarimi/cache_home_1/datasets
Downloading and preparing dataset iwsl_t217/iwslt2017-ro-nl (download: 314.07 MiB, generated: 39.92 MiB, post-processed: Unknown size, total: 354.00 MiB) to /idiap/temp/rkarimi/cache_home_1/datasets/iwsl_t217/iwslt2017-ro-nl/1.0.0/cca6935a0851a8ceac1202a62c958738bdfa23c57a51bc52ac1c5ebd2aa172cd...
cahce dir /idiap/temp/rkarimi/cache_home_1/datasets
cahce dir /idiap/temp/rkarimi/cache_home_1/datasets/downloads
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/load.py", line 611, in load_dataset
ignore_verifications=ignore_verifications,
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/builder.py", line 476, in download_and_prepare
dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/builder.py", line 531, in _download_and_prepare
split_generators = self._split_generators(dl_manager, **split_generators_kwargs)
File " /idiap/home/rkarimi/.cache/huggingface/modules/datasets_modules/datasets/iwslt2017/cca6935a0851a8ceac1202a62c958738bdfa23c57a51bc52ac1c5ebd2aa172cd/iwslt2017.py", line 118, in _split_generators
dl_dir = dl_manager.download_and_extract(MULTI_URL)
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/utils/download_manager.py", line 254, in download_and_extract
return self.extract(self.download(url_or_urls))
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/utils/download_manager.py", line 179, in download
num_proc=download_config.num_proc,
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/utils/py_utils.py", line 216, in map_nested
return function(data_struct)
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 308, in cached_path
use_etag=download_config.use_etag,
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 477, in get_from_cache
raise ConnectionError("Couldn't reach {}".format(url))
ConnectionError: Couldn't reach https://wit3.fbk.eu/archive/2017-01-trnmted//texts/DeEnItNlRo/DeEnItNlRo/DeEnItNlRo-DeEnItNlRo.tgz
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/1457 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1457/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1457/comments | https://api.github.com/repos/huggingface/datasets/issues/1457/events | https://github.com/huggingface/datasets/pull/1457 | 761,232,610 | MDExOlB1bGxSZXF1ZXN0NTM1OTI5Mjg1 | 1,457 | add hrenwac_para | {
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"duplicate"
] | 2020-12-10T13:16:20Z | 2020-12-10T13:35:54Z | 2020-12-10T13:35:10Z | CONTRIBUTOR | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/3032 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3032/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3032/comments | https://api.github.com/repos/huggingface/datasets/issues/3032/events | https://github.com/huggingface/datasets/issues/3032 | 1,016,488,475 | I_kwDODunzps48lmIb | 3,032 | Error when loading private dataset with "data_files" arg | {
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{
"color": "d73a4a",
"default": true,
"description": "Something isn't working",
"id": 1935892857,
"name": "bug",
"node_id": "MDU6TGFiZWwxOTM1ODkyODU3",
"url": "https://api.github.com/repos/huggingface/datasets/labels/bug"
}
] | closed | false | null | [] | null | [
"We'll do a release tomorrow or on wednesday to make the fix available :)\r\n\r\nThanks for reproting !"
] | 2021-10-05T15:46:27Z | 2021-10-12T15:26:22Z | 2021-10-12T15:25:46Z | CONTRIBUTOR | null | null | null | ## Describe the bug
A clear and concise description of what the bug is.
Private datasets with no loading script can't be loaded using `data_files` parameter.
## Steps to reproduce the bug
```python
from datasets import load_dataset
data_files = {"train": "**/train/*/*.jsonl", "valid": "**/valid/*/*.jsonl"}
dataset = load_dataset('dalle-mini/encoded', data_files=data_files, use_auth_token=True, streaming=True)
```
Same error happens in non-streaming mode.
## Expected results
Files should be loaded (whether in streaming or not).
## Actual results
Error:
```
---------------------------------------------------------------------------
FileNotFoundError Traceback (most recent call last)
/usr/local/lib/python3.7/dist-packages/datasets/load.py in prepare_module(path, script_version, download_config, download_mode, dataset, force_local_path, dynamic_modules_path, return_resolved_file_path, return_associated_base_path, data_files, **download_kwargs)
539 try:
--> 540 local_path = cached_path(file_path, download_config=download_config)
541 except FileNotFoundError:
8 frames
FileNotFoundError: Couldn't find file at https://huggingface.co/datasets/dalle-mini/encoded/resolve/main/encoded.py
During handling of the above exception, another exception occurred:
HTTPError Traceback (most recent call last)
HTTPError: 404 Client Error: Not Found for url: https://huggingface.co/api/datasets/dalle-mini/encoded?full=true
During handling of the above exception, another exception occurred:
FileNotFoundError Traceback (most recent call last)
/usr/local/lib/python3.7/dist-packages/datasets/load.py in prepare_module(path, script_version, download_config, download_mode, dataset, force_local_path, dynamic_modules_path, return_resolved_file_path, return_associated_base_path, data_files, **download_kwargs)
547 except Exception:
548 raise FileNotFoundError(
--> 549 f"Couldn't find a directory or a {resource_type} named '{path}'. "
550 f"It doesn't exist locally at {expected_dir_for_combined_path_abs} or remotely on {hf_api.endpoint}/datasets"
551 )
FileNotFoundError: Couldn't find a directory or a dataset named 'dalle-mini/encoded'. It doesn't exist locally at /content/dalle-mini/encoded or remotely on https://huggingface.co/datasets
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.12.1
- Platform: Linux-5.4.104+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.12
- PyArrow version: 3.0.0
@lhoestq | {
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https://api.github.com/repos/huggingface/datasets/issues/3746 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3746/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3746/comments | https://api.github.com/repos/huggingface/datasets/issues/3746/events | https://github.com/huggingface/datasets/pull/3746 | 1,141,612,810 | PR_kwDODunzps4zAS-C | 3,746 | Use the same seed to shuffle shards and metadata in streaming mode | {
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} | [] | closed | false | null | [] | null | [] | 2022-02-17T17:06:31Z | 2022-02-23T15:00:59Z | 2022-02-23T15:00:58Z | MEMBER | null | 0 | {
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} | When shuffling in streaming mode, those two entangled lists are shuffled independently. In this PR I changed this to shuffle the lists of same length with the exact same seed, in order for the files and metadata to still be aligned.
```python
gen_kwargs = {
"files": [os.path.join(data_dir, filename) for filename in all_files],
"metadata_files": [all_metadata[filename] for filename in all_files],
}
```
IMO this is important to avoid big but silent issues.
Fix https://github.com/huggingface/datasets/issues/3744 | {
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https://api.github.com/repos/huggingface/datasets/issues/5765 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5765/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5765/comments | https://api.github.com/repos/huggingface/datasets/issues/5765/events | https://github.com/huggingface/datasets/issues/5765 | 1,671,388,824 | I_kwDODunzps5jn16Y | 5,765 | ValueError: You should supply an encoding or a list of encodings to this method that includes input_ids, but you provided ['text'] | {
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} | [] | open | false | null | [] | null | [
"You need to remove the `text` and `text_en` columns before passing the dataset to the `DataLoader` to avoid this error:\r\n```python\r\ntokenized_datasets = tokenized_datasets.remove_columns([\"text\", \"text_en\"])\r\n```\r\n",
"Thanks @mariosasko. Now I am getting this error:\r\n\r\n```\r\nTraceback (most rece... | 2023-04-17T15:00:50Z | 2023-04-25T13:50:45Z | null | NONE | null | null | null | ### Describe the bug
Following is my code that I am trying to run, but facing an error (have attached the whole error below):
My code:
```
from collections import OrderedDict
import warnings
import flwr as fl
import torch
import numpy as np
import random
from torch.utils.data import DataLoader
from datasets import load_dataset, load_metric
from transformers import AutoTokenizer, DataCollatorWithPadding
from transformers import AutoModelForSequenceClassification
from transformers import AdamW
#from transformers import tokenized_datasets
warnings.filterwarnings("ignore", category=UserWarning)
# DEVICE = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
DEVICE = "cpu"
CHECKPOINT = "distilbert-base-uncased" # transformer model checkpoint
def load_data():
"""Load IMDB data (training and eval)"""
raw_datasets = load_dataset("yhavinga/imdb_dutch")
raw_datasets = raw_datasets.shuffle(seed=42)
# remove unnecessary data split
del raw_datasets["unsupervised"]
tokenizer = AutoTokenizer.from_pretrained(CHECKPOINT)
def tokenize_function(examples):
return tokenizer(examples["text"], truncation=True)
# random 100 samples
population = random.sample(range(len(raw_datasets["train"])), 100)
tokenized_datasets = raw_datasets.map(tokenize_function, batched=True)
tokenized_datasets["train"] = tokenized_datasets["train"].select(population)
tokenized_datasets["test"] = tokenized_datasets["test"].select(population)
# tokenized_datasets = tokenized_datasets.remove_columns("text")
# tokenized_datasets = tokenized_datasets.rename_column("label", "labels")
tokenized_datasets = tokenized_datasets.remove_columns("attention_mask")
tokenized_datasets = tokenized_datasets.remove_columns("input_ids")
tokenized_datasets = tokenized_datasets.remove_columns("label")
tokenized_datasets = tokenized_datasets.remove_columns("text_en")
# tokenized_datasets = tokenized_datasets.remove_columns(raw_datasets["train"].column_names)
data_collator = DataCollatorWithPadding(tokenizer=tokenizer)
trainloader = DataLoader(
tokenized_datasets["train"],
shuffle=True,
batch_size=32,
collate_fn=data_collator,
)
testloader = DataLoader(
tokenized_datasets["test"], batch_size=32, collate_fn=data_collator
)
return trainloader, testloader
def train(net, trainloader, epochs):
optimizer = AdamW(net.parameters(), lr=5e-4)
net.train()
for _ in range(epochs):
for batch in trainloader:
batch = {k: v.to(DEVICE) for k, v in batch.items()}
outputs = net(**batch)
loss = outputs.loss
loss.backward()
optimizer.step()
optimizer.zero_grad()
def test(net, testloader):
metric = load_metric("accuracy")
loss = 0
net.eval()
for batch in testloader:
batch = {k: v.to(DEVICE) for k, v in batch.items()}
with torch.no_grad():
outputs = net(**batch)
logits = outputs.logits
loss += outputs.loss.item()
predictions = torch.argmax(logits, dim=-1)
metric.add_batch(predictions=predictions, references=batch["labels"])
loss /= len(testloader.dataset)
accuracy = metric.compute()["accuracy"]
return loss, accuracy
def main():
net = AutoModelForSequenceClassification.from_pretrained(
CHECKPOINT, num_labels=2
).to(DEVICE)
trainloader, testloader = load_data()
# Flower client
class IMDBClient(fl.client.NumPyClient):
def get_parameters(self, config):
return [val.cpu().numpy() for _, val in net.state_dict().items()]
def set_parameters(self, parameters):
params_dict = zip(net.state_dict().keys(), parameters)
state_dict = OrderedDict({k: torch.Tensor(v) for k, v in params_dict})
net.load_state_dict(state_dict, strict=True)
def fit(self, parameters, config):
self.set_parameters(parameters)
print("Training Started...")
train(net, trainloader, epochs=1)
print("Training Finished.")
return self.get_parameters(config={}), len(trainloader), {}
def evaluate(self, parameters, config):
self.set_parameters(parameters)
loss, accuracy = test(net, testloader)
return float(loss), len(testloader), {"accuracy": float(accuracy)}
# Start client
fl.client.start_numpy_client(server_address="localhost:8080", client=IMDBClient())
if __name__ == "__main__":
main()
```
Error:
```
Traceback (most recent call last):
File "client_2.py", line 136, in <module>
main()
File "client_2.py", line 132, in main
fl.client.start_numpy_client(server_address="localhost:8080", client=IMDBClient())
File "/home/saurav/.local/lib/python3.8/site-packages/flwr/client/app.py", line 208, in start_numpy_client
start_client(
File "/home/saurav/.local/lib/python3.8/site-packages/flwr/client/app.py", line 142, in start_client
client_message, sleep_duration, keep_going = handle(
File "/home/saurav/.local/lib/python3.8/site-packages/flwr/client/grpc_client/message_handler.py", line 68, in handle
return _fit(client, server_msg.fit_ins), 0, True
File "/home/saurav/.local/lib/python3.8/site-packages/flwr/client/grpc_client/message_handler.py", line 157, in _fit
fit_res = client.fit(fit_ins)
File "/home/saurav/.local/lib/python3.8/site-packages/flwr/client/app.py", line 252, in _fit
results = self.numpy_client.fit(parameters, ins.config) # type: ignore
File "client_2.py", line 122, in fit
train(net, trainloader, epochs=1)
File "client_2.py", line 76, in train
for batch in trainloader:
File "/home/saurav/.local/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 652, in __next__
data = self._next_data()
File "/home/saurav/.local/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 692, in _next_data
data = self._dataset_fetcher.fetch(index) # may raise StopIteration
File "/home/saurav/.local/lib/python3.8/site-packages/torch/utils/data/_utils/fetch.py", line 52, in fetch
return self.collate_fn(data)
File "/home/saurav/.local/lib/python3.8/site-packages/transformers/data/data_collator.py", line 221, in __call__
batch = self.tokenizer.pad(
File "/home/saurav/.local/lib/python3.8/site-packages/transformers/tokenization_utils_base.py", line 2713, in pad
raise ValueError(
ValueError: You should supply an encoding or a list of encodings to this method that includes input_ids, but you provided ['text']
```
### Steps to reproduce the bug
Run the above code.
### Expected behavior
Don't know, doing it for the first time.
### Environment info
- `datasets` version: 1.12.1
- Platform: Linux-5.4.0-58-generic-x86_64-with-glibc2.29
- Python version: 3.8.10
- PyArrow version: 11.0.0
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https://api.github.com/repos/huggingface/datasets/issues/2064 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2064/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2064/comments | https://api.github.com/repos/huggingface/datasets/issues/2064/events | https://github.com/huggingface/datasets/pull/2064 | 833,002,360 | MDExOlB1bGxSZXF1ZXN0NTk0MDczOTQ1 | 2,064 | Fix ted_talks_iwslt version error | {
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} | [] | closed | false | null | [] | null | [] | 2021-03-16T16:43:45Z | 2021-03-16T18:00:08Z | 2021-03-16T18:00:08Z | CONTRIBUTOR | null | 0 | {
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} | This PR fixes the bug where the version argument would be passed twice if the dataset configuration was created on the fly.
Fixes #2059 | {
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