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https://api.github.com/repos/huggingface/datasets/issues/4253 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4253/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4253/comments | https://api.github.com/repos/huggingface/datasets/issues/4253/events | https://github.com/huggingface/datasets/pull/4253 | 1,219,286,408 | PR_kwDODunzps42-c8Q | 4,253 | Create metric cards for mean IOU | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-04-28T20:58:27Z | 2022-04-29T17:44:47Z | 2022-04-29T17:38:06Z | NONE | null | 0 | {
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} | Proposing a metric card for mIoU :rocket:
sorry for spamming you with review requests, @albertvillanova ! :hugs: | {
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https://api.github.com/repos/huggingface/datasets/issues/4809 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4809/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4809/comments | https://api.github.com/repos/huggingface/datasets/issues/4809/events | https://github.com/huggingface/datasets/pull/4809 | 1,332,842,747 | PR_kwDODunzps483Y4h | 4,809 | Complete the mlqa dataset card | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"> Thanks for your contribution, @eldhoittangeorge.\r\n> \r\n> The CI error message: https://github.com/huggingface/datasets/runs/7743526624?check_suite_focus=true\r\n> \r\n> ```\r\n> E ValueError: The following issues have ... | 2022-08-09T07:38:06Z | 2022-08-09T16:26:21Z | 2022-08-09T13:26:43Z | CONTRIBUTOR | null | 0 | {
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} | I fixed the issue #4808
Details of PR:
- Added languages included in the dataset.
- Added task id and task category.
- Updated the citation information.
Fix #4808. | {
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https://api.github.com/repos/huggingface/datasets/issues/3760 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3760/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3760/comments | https://api.github.com/repos/huggingface/datasets/issues/3760/events | https://github.com/huggingface/datasets/issues/3760 | 1,144,804,558 | I_kwDODunzps5EPFTO | 3,760 | Unable to view the Gradio flagged call back dataset | {
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"Hi @kingabzpro.\r\n\r\nI think you need to create a loading script that creates the dataset from the CSV file and the image paths.\r\n\r\nAs example, you could have a look at the Food-101 dataset: https://huggingface.co/datasets/food101\r\n- Loading script: https://huggingface.co/datasets/food101/blob/main/food101... | 2022-02-19T17:45:08Z | 2022-03-22T07:12:11Z | 2022-03-22T07:12:11Z | NONE | null | null | null | ## Dataset viewer issue for '*savtadepth-flags*'
**Link:** *[savtadepth-flags](https://huggingface.co/datasets/kingabzpro/savtadepth-flags)*
*with the Gradio 2.8.1 the dataset viers stopped working. I tried to add values manually but its not working. The dataset is also not showing the link with the app https://huggingface.co/spaces/kingabzpro/savtadepth.*
Am I the one who added this dataset ? Yes
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https://api.github.com/repos/huggingface/datasets/issues/1948 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1948/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1948/comments | https://api.github.com/repos/huggingface/datasets/issues/1948/events | https://github.com/huggingface/datasets/issues/1948 | 816,689,329 | MDU6SXNzdWU4MTY2ODkzMjk= | 1,948 | dataset loading logger level | {
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"These warnings are showed when there's a call to `.map` to say to the user that a dataset is reloaded from the cache instead of being recomputed.\r\nThey are warnings since we want to make sure the users know that it's not recomputed.",
"Thank you for explaining the intention, @lhoestq \r\n\r\n1. Could it be the... | 2021-02-25T18:33:37Z | 2023-07-12T17:19:30Z | 2023-07-12T17:19:30Z | CONTRIBUTOR | null | null | null | on master I get this with `--dataset_name wmt16 --dataset_config ro-en`:
```
WARNING:datasets.arrow_dataset:Loading cached processed dataset at /home/stas/.cache/huggingface/datasets/wmt16/ro-en/1.0.0/9dc00622c30446e99c4c63d12a484ea4fb653f2f37c867d6edcec839d7eae50f/cache-2e01bead8cf42e26.arrow
WARNING:datasets.arrow_dataset:Loading cached processed dataset at /home/stas/.cache/huggingface/datasets/wmt16/ro-en/1.0.0/9dc00622c30446e99c4c63d12a484ea4fb653f2f37c867d6edcec839d7eae50f/cache-ac3bebaf4f91f776.arrow
WARNING:datasets.arrow_dataset:Loading cached processed dataset at /home/stas/.cache/huggingface/datasets/wmt16/ro-en/1.0.0/9dc00622c30446e99c4c63d12a484ea4fb653f2f37c867d6edcec839d7eae50f/cache-810c3e61259d73a9.arrow
```
why are those WARNINGs? Should be INFO, no?
warnings should only be used when a user needs to pay attention to something, this is just informative - I'd even say it should be DEBUG, but definitely not WARNING.
Thank you.
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https://api.github.com/repos/huggingface/datasets/issues/5276 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5276/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5276/comments | https://api.github.com/repos/huggingface/datasets/issues/5276/events | https://github.com/huggingface/datasets/issues/5276 | 1,459,363,442 | I_kwDODunzps5W_B5y | 5,276 | Bug in downloading common_voice data and snall chunk of it to one's own hub | {
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"Sounds like one of the file is not a valid one, can you make sure you uploaded valid mp3 files ?",
"Well I just sharded the original commonVoice dataset and pushed a small chunk of it in a private rep\n\nWhat did go wrong?\n\nHolen Sie sich Outlook für iOS<https://aka.ms/o0ukef>\n________________________________... | 2022-11-22T08:17:53Z | 2023-07-21T14:33:10Z | 2023-07-21T14:33:10Z | NONE | null | null | null | ### Describe the bug
I'm trying to load the common voice dataset. Currently there is no implementation to download just par tof the data, and I need just one part of it, without downloading the entire dataset
Help please?
### Steps to reproduce the bug
So here is what I have done:
1. Download common_voice data
2. Trim part of it and publish it to my own repo.
3. Download data from my own repo, but am getting this error.
### Expected behavior
There shouldn't be an error in downloading part of the data and publishing it to one's own repo
### Environment info
common_voice 11 | {
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https://api.github.com/repos/huggingface/datasets/issues/4692 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4692/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4692/comments | https://api.github.com/repos/huggingface/datasets/issues/4692/events | https://github.com/huggingface/datasets/issues/4692 | 1,306,609,680 | I_kwDODunzps5N4UgQ | 4,692 | Unable to cast a column with `Image()` by using the `cast_column()` feature | {
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"Hi, thanks for reporting! A PR (https://github.com/huggingface/datasets/pull/4614) has already been opened to address this issue."
] | 2022-07-15T22:56:03Z | 2022-07-19T13:36:24Z | 2022-07-19T13:36:24Z | NONE | null | null | null | ## Describe the bug
A clear and concise description of what the bug is.
When I create a dataset, then add a column to the created dataset through the `dataset.add_column` feature and then try to cast a column of the dataset (this column contains image paths) with `Image()` by using the `cast_column()` feature, I get the following error - ``` TypeError: Couldn't cast array of type
string
to
{'bytes': Value(dtype='binary', id=None), 'path': Value(dtype='string', id=None)} ```
When I try and cast the same column, but without doing the `add_column` in the previous step, it works as expected.
## Steps to reproduce the bug
```python
from datasets import Dataset, Image
data_dict = {
"img_path": ["https://picsum.photos/200/300"]
}
dataset = Dataset.from_dict(data_dict)
#NOTE Comment out this line and use cast_column and it works properly
dataset = dataset.add_column("yeet", [1])
#NOTE This line fails to execute properly if `add_column` is called before
dataset = dataset.cast_column("img_path", Image())
# #NOTE This is my current workaround. This seems to work fine with/without `add_column`. While
# # running this, make sure to comment out the `cast_column` line
# new_features = dataset.features.copy()
# new_features["img_path"] = Image()
# dataset = dataset.cast(new_features)
print(dataset)
print(dataset.features)
print(dataset[0])
```
## Expected results
A clear and concise description of the expected results.
Able to successfully use `cast_column` to cast a column containing img_paths to now be Image() features after modifying the dataset using `add_column` in a previous step
## Actual results
Specify the actual results or traceback.
```
Traceback (most recent call last):
File "/home/surya/Desktop/hf_bug_test.py", line 14, in <module>
dataset = dataset.cast_column("img_path", Image())
File "/home/surya/anaconda3/envs/snap_test/lib/python3.9/site-packages/datasets/fingerprint.py", line 458, in wrapper
out = func(self, *args, **kwargs)
File "/home/surya/anaconda3/envs/snap_test/lib/python3.9/site-packages/datasets/arrow_dataset.py", line 1580, in cast_column
dataset._data = dataset._data.cast(dataset.features.arrow_schema)
File "/home/surya/anaconda3/envs/snap_test/lib/python3.9/site-packages/datasets/table.py", line 1487, in cast
new_tables.append(subtable.cast(subschema, *args, **kwargs))
File "/home/surya/anaconda3/envs/snap_test/lib/python3.9/site-packages/datasets/table.py", line 834, in cast
return InMemoryTable(table_cast(self.table, *args, **kwargs))
File "/home/surya/anaconda3/envs/snap_test/lib/python3.9/site-packages/datasets/table.py", line 1897, in table_cast
return cast_table_to_schema(table, schema)
File "/home/surya/anaconda3/envs/snap_test/lib/python3.9/site-packages/datasets/table.py", line 1880, in cast_table_to_schema
arrays = [cast_array_to_feature(table[name], feature) for name, feature in features.items()]
File "/home/surya/anaconda3/envs/snap_test/lib/python3.9/site-packages/datasets/table.py", line 1880, in <listcomp>
arrays = [cast_array_to_feature(table[name], feature) for name, feature in features.items()]
File "/home/surya/anaconda3/envs/snap_test/lib/python3.9/site-packages/datasets/table.py", line 1673, in wrapper
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
File "/home/surya/anaconda3/envs/snap_test/lib/python3.9/site-packages/datasets/table.py", line 1673, in <listcomp>
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
File "/home/surya/anaconda3/envs/snap_test/lib/python3.9/site-packages/datasets/table.py", line 1846, in cast_array_to_feature
raise TypeError(f"Couldn't cast array of type\n{array.type}\nto\n{feature}")
TypeError: Couldn't cast array of type
string
to
{'bytes': Value(dtype='binary', id=None), 'path': Value(dtype='string', id=None)}
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 2.3.2
- Platform: Ubuntu 20.04.3 LTS
- Python version: 3.9.7
- PyArrow version: 7.0.0
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"_The documentation is not available anymore as the PR was closed or merged._",
"Thanks ! I addressed your comments :)\r\n\r\n> There is a slight difference in concatenate_datasets between the version for map-style datasets and the one for iterable datasets\r\n\r\nIndeed, here is what I did to fix this:\r\n\r\n- ... | 2022-06-15T13:58:50Z | 2022-06-28T21:25:39Z | 2022-06-28T21:15:04Z | MEMBER | null | 0 | {
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} | `concatenate_datasets` currently only supports lists of `datasets.Dataset`, not lists of `datasets.IterableDataset` like `interleave_datasets`
Fix https://github.com/huggingface/datasets/issues/2564
I also moved `_interleave_map_style_datasets` from combine.py to arrow_dataset.py, since the logic depends a lot on the `Dataset` object internals
And I moved `concatenate_datasets` from arrow_dataset.py to combine.py to have it with `interleave_datasets` (though it's also copied in arrow_dataset module for backward compatibility for now) | {
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"Hi @Jun-jie-Huang,\r\n\r\nAs the error message says, \".pkl\" data files are not supported.\r\n\r\nIf you would like to share your dataset on the Hub, you would need:\r\n- either to create a Python loading script, that loads the data in any format\r\n- or to transform your data files to one of the supported format... | 2022-03-31T06:36:29Z | 2022-03-31T08:17:01Z | 2022-03-31T08:16:16Z | NONE | null | null | null | ## Dataset viewer issue for '*xuyeliu/notebookCDG*'
**Link:** *[link to the dataset viewer page](https://huggingface.co/datasets/xuyeliu/notebookCDG)*
*Couldn't load the xuyeliu/notebookCDG with provided scripts: *
```
from datasets import load_dataset
dataset = load_dataset("xuyeliu/notebookCDG/dataset_notebook.pkl")
```
I get an error message as follows:
FileNotFoundError: Couldn't find a dataset script at /home/code_documentation/code/xuyeliu/notebookCDG/notebookCDG.py or any data file in the same directory. Couldn't find 'xuyeliu/notebookCDG' on the Hugging Face Hub either: FileNotFoundError: Unable to resolve any data file that matches ['**train*'] in dataset repository xuyeliu/notebookCDG with any supported extension ['csv', 'tsv', 'json', 'jsonl', 'parquet', 'txt', 'blp', 'bmp', 'dib', 'bufr', 'cur', 'pcx', 'dcx', 'dds', 'ps', 'eps', 'fit', 'fits', 'fli', 'flc', 'ftc', 'ftu', 'gbr', 'gif', 'grib', 'h5', 'hdf', 'png', 'apng', 'jp2', 'j2k', 'jpc', 'jpf', 'jpx', 'j2c', 'icns', 'ico', 'im', 'iim', 'tif', 'tiff', 'jfif', 'jpe', 'jpg', 'jpeg', 'mpg', 'mpeg', 'msp', 'pcd', 'pxr', 'pbm', 'pgm', 'ppm', 'pnm', 'psd', 'bw', 'rgb', 'rgba', 'sgi', 'ras', 'tga', 'icb', 'vda', 'vst', 'webp', 'wmf', 'emf', 'xbm', 'xpm', 'zip']
Am I the one who added this dataset ? No
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"Hi,\r\n\r\nthis issue has been already reported in the dataset repo (https://github.com/dair-ai/emotion_dataset/issues/2), so this is a bug on their side.",
"The documentation has another bug in the dataset card [here](https://huggingface.co/datasets/emotion). \r\n\r\nIn the dataset summary **six** emotions are ... | 2021-06-19T07:08:57Z | 2023-01-02T12:04:58Z | 2023-01-02T12:04:58Z | NONE | null | null | null | As per documentation,
Dataset: emotion
Homepage: https://github.com/dair-ai/emotion_dataset
Dataset: https://github.com/huggingface/datasets/blob/master/datasets/emotion/emotion.py
Permalink: https://huggingface.co/datasets/viewer/?dataset=emotion
Emotion is a dataset of English Twitter messages with eight basic emotions: anger, anticipation, disgust, fear, joy, sadness, surprise, and trust. For more detailed information please refer to the paper.
But when we view the data, there are only 6 emotions, anger, fear, joy, sadness, surprise, and trust. | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-11-03T13:51:32Z | 2022-11-04T12:47:59Z | 2022-11-04T12:46:01Z | CONTRIBUTOR | null | 0 | {
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} | Add note that a dataset script should has the same name as a repo/dir, a bit related to this issue https://github.com/huggingface/datasets/issues/5193
also fixed two minor issues in audio docs (broken links) | {
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"Did you run `huggingface-cli lfs-enable-largefiles` before committing or before adding ? Maybe you can try before adding\r\n\r\nAnyway I'd encourage you to split your data into several TAR archives if possible, this way the dataset can loaded faster using multiprocessing (by giving each process a subset of shards ... | 2022-11-09T15:32:05Z | 2022-11-10T18:11:21Z | 2022-11-10T18:11:11Z | NONE | null | null | null | ### Describe the bug
I am facing the issue when I try to push the tar.gz file around 11G to HUB.
```
(venv) ╭─laptop@laptop ~/PersonalProjects/data/ulaanbal_v0 ‹main●›
╰─$ du -sh *
4.0K README.md
13G data
516K test.jsonl
18M train.jsonl
4.0K ulaanbal_v0.py
11G ulaanbal_v0.tar.gz
452K validation.jsonl
(venv) ╭─laptop@laptop~/PersonalProjects/data/ulaanbal_v0 ‹main●›
╰─$ git add ulaanbal_v0.tar.gz && git commit -m 'large version'
(venv) ╭─laptop@laptop ~/PersonalProjects/data/ulaanbal_v0 ‹main●›
╰─$ git push
EOFoading LFS objects: 0% (0/1), 0 B | 0 B/s
Uploading LFS objects: 0% (0/1), 0 B | 0 B/s, done.
error: failed to push some refs to 'https://huggingface.co/datasets/bayartsogt/ulaanbal_v0'
```
I have already tried pushing a small version of this and it was working fine. So my guess it is probably because of the big file.
Following I run before the commit:
```
╰─$ git lfs install
╰─$ huggingface-cli lfs-enable-largefiles .
```
### Steps to reproduce the bug
Create a private dataset on huggingface and push 12G tar.gz file
### Expected behavior
To be pushed with no issue
### Environment info
- `datasets` version: 2.6.1
- Platform: Darwin-21.6.0-x86_64-i386-64bit
- Python version: 3.7.11
- PyArrow version: 10.0.0
- Pandas version: 1.3.5
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https://api.github.com/repos/huggingface/datasets/issues/4248 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4248/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4248/comments | https://api.github.com/repos/huggingface/datasets/issues/4248/events | https://github.com/huggingface/datasets/issues/4248 | 1,218,460,444 | I_kwDODunzps5IoDsc | 4,248 | conll2003 dataset loads original data. | {
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"Thanks for reporting @sue99.\r\n\r\nUnfortunately. I'm not able to reproduce your problem:\r\n```python\r\nIn [1]: import datasets\r\n ...: from datasets import load_dataset\r\n ...: dataset = load_dataset(\"conll2003\")\r\n\r\nIn [2]: dataset\r\nOut[2]: \r\nDatasetDict({\r\n train: Dataset({\r\n fea... | 2022-04-28T09:33:31Z | 2022-07-18T07:15:48Z | 2022-07-18T07:15:48Z | NONE | null | null | null | ## Describe the bug
I load `conll2003` dataset to use refined data like [this](https://huggingface.co/datasets/conll2003/viewer/conll2003/train) preview, but it is original data that contains `'-DOCSTART- -X- -X- O'` text.
Is this a bug or should I use another dataset_name like `lhoestq/conll2003` ?
## Steps to reproduce the bug
```python
import datasets
from datasets import load_dataset
dataset = load_dataset("conll2003")
```
## Expected results
{
"chunk_tags": [11, 12, 12, 21, 13, 11, 11, 21, 13, 11, 12, 13, 11, 21, 22, 11, 12, 17, 11, 21, 17, 11, 12, 12, 21, 22, 22, 13, 11, 0],
"id": "0",
"ner_tags": [0, 3, 4, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
"pos_tags": [12, 22, 22, 38, 15, 22, 28, 38, 15, 16, 21, 35, 24, 35, 37, 16, 21, 15, 24, 41, 15, 16, 21, 21, 20, 37, 40, 35, 21, 7],
"tokens": ["The", "European", "Commission", "said", "on", "Thursday", "it", "disagreed", "with", "German", "advice", "to", "consumers", "to", "shun", "British", "lamb", "until", "scientists", "determine", "whether", "mad", "cow", "disease", "can", "be", "transmitted", "to", "sheep", "."]
}
## Actual results
```python
print(dataset)
DatasetDict({
train: Dataset({
features: ['text'],
num_rows: 219554
})
test: Dataset({
features: ['text'],
num_rows: 50350
})
validation: Dataset({
features: ['text'],
num_rows: 55044
})
})
```
```python
for i in range(20):
print(dataset['train'][i])
{'text': '-DOCSTART- -X- -X- O'}
{'text': ''}
{'text': 'EU NNP B-NP B-ORG'}
{'text': 'rejects VBZ B-VP O'}
{'text': 'German JJ B-NP B-MISC'}
{'text': 'call NN I-NP O'}
{'text': 'to TO B-VP O'}
{'text': 'boycott VB I-VP O'}
{'text': 'British JJ B-NP B-MISC'}
{'text': 'lamb NN I-NP O'}
{'text': '. . O O'}
{'text': ''}
{'text': 'Peter NNP B-NP B-PER'}
{'text': 'Blackburn NNP I-NP I-PER'}
{'text': ''}
{'text': 'BRUSSELS NNP B-NP B-LOC'}
{'text': '1996-08-22 CD I-NP O'}
{'text': ''}
{'text': 'The DT B-NP O'}
{'text': 'European NNP I-NP B-ORG'}
```
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https://api.github.com/repos/huggingface/datasets/issues/2038 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2038/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2038/comments | https://api.github.com/repos/huggingface/datasets/issues/2038/events | https://github.com/huggingface/datasets/issues/2038 | 830,036,875 | MDU6SXNzdWU4MzAwMzY4NzU= | 2,038 | outdated dataset_infos.json might fail verifications | {
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"Hi ! Thanks for reporting.\r\n\r\nTo update the dataset_infos.json you can run:\r\n```\r\ndatasets-cli test ./datasets/doc2dial --all_configs --save_infos --ignore_verifications\r\n```",
"Fixed by #2041, thanks again @songfeng !"
] | 2021-03-12T11:41:54Z | 2021-03-16T16:27:40Z | 2021-03-16T16:27:40Z | CONTRIBUTOR | null | null | null | The [doc2dial/dataset_infos.json](https://github.com/huggingface/datasets/blob/master/datasets/doc2dial/dataset_infos.json) is outdated. It would fail data_loader when verifying download checksum etc..
Could you please update this file or point me how to update this file?
Thank you. | {
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https://api.github.com/repos/huggingface/datasets/issues/4622 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4622/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4622/comments | https://api.github.com/repos/huggingface/datasets/issues/4622/events | https://github.com/huggingface/datasets/pull/4622 | 1,293,031,939 | PR_kwDODunzps46ynmT | 4,622 | Fix ImageFolder with parameters drop_metadata=True and drop_labels=False (when metadata.jsonl is present) | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"@lhoestq @mariosasko pls take a look at https://github.com/huggingface/datasets/pull/4622/commits/769e4c046a5bd5e3a4dbd09cfad1f4cf60677869. I modified `_generate_examples()` according to the same logic too: removed checking if `metad... | 2022-07-04T11:23:20Z | 2022-07-15T14:37:23Z | 2022-07-15T14:24:24Z | CONTRIBUTOR | null | 0 | {
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"url": "https://api.github.com/repos/huggingface/datasets/pulls/4622"
} | Will fix #4621
ImageFolder raises `KeyError: 'label'` with params `drop_metadata=True` and `drop_labels=False` (if there is at least one metadata.jsonl file a data directory). This happens because metadata files are collected inside `analyze()` function regardless of `drop_metadata` value. And then the following condition doesn't pass: https://github.com/huggingface/datasets/blob/master/src/datasets/packaged_modules/imagefolder/imagefolder.py#L167
So I suggest to double check it inside `analyze()` not to collect metadata files if they are not needed. (and labels too, to be consistent)
---
Also, I added a test to check if labels are inferred correctly from directories names in general (because we didn't have it) :) | {
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https://api.github.com/repos/huggingface/datasets/issues/1305 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1305/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1305/comments | https://api.github.com/repos/huggingface/datasets/issues/1305/events | https://github.com/huggingface/datasets/pull/1305 | 759,446,665 | MDExOlB1bGxSZXF1ZXN0NTM0NDUxNzEx | 1,305 | [README] Added Windows command to enable slow tests | {
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} | The Windows command to run slow tests has caused issues, so this adds a functional Windows command. | {
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https://api.github.com/repos/huggingface/datasets/issues/4488 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4488/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4488/comments | https://api.github.com/repos/huggingface/datasets/issues/4488/events | https://github.com/huggingface/datasets/pull/4488 | 1,270,613,857 | PR_kwDODunzps45n6Ja | 4,488 | Update PASS dataset version | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-06-14T10:47:14Z | 2022-06-14T16:41:55Z | 2022-06-14T16:32:28Z | CONTRIBUTOR | null | 0 | {
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} | Update the PASS dataset to version v3 (the newest one) from the [version history](https://github.com/yukimasano/PASS/blob/main/version_history.txt).
PS: The older versions are not exposed as configs in the script because v1 was removed from Zenodo, and the same thing will probably happen to v2. | {
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https://api.github.com/repos/huggingface/datasets/issues/4925 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4925/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4925/comments | https://api.github.com/repos/huggingface/datasets/issues/4925/events | https://github.com/huggingface/datasets/pull/4925 | 1,360,007,616 | PR_kwDODunzps4-RbP5 | 4,925 | Add note about loading image / audio files to docs | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_4925). All of your documentation changes will be reflected on that endpoint.",
"Thanks for the feedback @polinaeterna ! I've reworded the docs a bit to integrate your comments and this should be ready for another review :)",
... | 2022-09-02T10:31:58Z | 2022-09-26T12:21:30Z | 2022-09-23T13:59:07Z | MEMBER | null | 0 | {
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Related forum thread: https://discuss.huggingface.co/t/loading-train-and-test-splits-with-audiofolder/22447
cc @NielsRogge | {
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https://api.github.com/repos/huggingface/datasets/issues/1220 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1220/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1220/comments | https://api.github.com/repos/huggingface/datasets/issues/1220/events | https://github.com/huggingface/datasets/pull/1220 | 758,015,894 | MDExOlB1bGxSZXF1ZXN0NTMzMjYxNTgw | 1,220 | add Korean HateSpeech dataset | {
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"It looks like you forgot to `make style` (I forget it a lot too 🤦 )\r\n+ add dummy data",
"hi @cceyda 👋, thanks for the hint! it looks like i've run into some other errors though in `_split_generators` or `_generate_examples`. do you have any idea of what's wrong here? 😅",
"I get the same errors on another... | 2020-12-06T20:31:29Z | 2020-12-08T15:21:09Z | 2020-12-08T11:05:42Z | MEMBER | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/2866 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2866/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2866/comments | https://api.github.com/repos/huggingface/datasets/issues/2866/events | https://github.com/huggingface/datasets/issues/2866 | 986,706,676 | MDU6SXNzdWU5ODY3MDY2NzY= | 2,866 | "counter" dataset raises an error in normal mode, but not in streaming mode | {
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"Hi @severo, thanks for reporting.\r\n\r\nJust note that currently not all canonical datasets support streaming mode: this is one case!\r\n\r\nAll datasets that use `pathlib` joins (using `/`) instead of `os.path.join` (as in this dataset) do not support streaming mode yet.",
"OK. Do you think it's possible to de... | 2021-09-02T13:10:53Z | 2021-10-14T09:24:09Z | 2021-10-14T09:24:09Z | CONTRIBUTOR | null | null | null | ## Describe the bug
`counter` dataset raises an error on `load_dataset()`, but simply returns an empty iterator in streaming mode.
## Steps to reproduce the bug
```python
>>> import datasets as ds
>>> a = ds.load_dataset('counter', split="train", streaming=False)
Using custom data configuration default
Downloading and preparing dataset counter/default (download: 1.29 MiB, generated: 2.48 MiB, post-processed: Unknown size, total: 3.77 MiB) to /home/slesage/.cache/huggingface/datasets/counter/default/1.0.0/9f84962fa0f35bec5a34fe0bdff8681838d497008c457f7856c48654476ec0e9...
Traceback (most recent call last):
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/datasets/builder.py", line 726, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/datasets/builder.py", line 1124, in _prepare_split
for key, record in utils.tqdm(
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/tqdm/std.py", line 1185, in __iter__
for obj in iterable:
File "/home/slesage/.cache/huggingface/modules/datasets_modules/datasets/counter/9f84962fa0f35bec5a34fe0bdff8681838d497008c457f7856c48654476ec0e9/counter.py", line 161, in _generate_examples
with derived_file.open(encoding="utf-8") as f:
File "/home/slesage/.pyenv/versions/3.8.11/lib/python3.8/pathlib.py", line 1222, in open
return io.open(self, mode, buffering, encoding, errors, newline,
File "/home/slesage/.pyenv/versions/3.8.11/lib/python3.8/pathlib.py", line 1078, in _opener
return self._accessor.open(self, flags, mode)
FileNotFoundError: [Errno 2] No such file or directory: '/home/slesage/.cache/huggingface/datasets/downloads/extracted/b57aa6db5601a738e57b95c1fd8cced54ff28fc540efcdaf0f6c4f1bb5dfe211/COUNTER/0032p.xml'
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/datasets/load.py", line 1112, in load_dataset
builder_instance.download_and_prepare(
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/datasets/builder.py", line 636, in download_and_prepare
self._download_and_prepare(
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.8/site-packages/datasets/builder.py", line 728, in _download_and_prepare
raise OSError(
OSError: Cannot find data file.
Original error:
[Errno 2] No such file or directory: '/home/slesage/.cache/huggingface/datasets/downloads/extracted/b57aa6db5601a738e57b95c1fd8cced54ff28fc540efcdaf0f6c4f1bb5dfe211/COUNTER/0032p.xml'
```
```python
>>> import datasets as ds
>>> b = ds.load_dataset('counter', split="train", streaming=True)
Using custom data configuration default
>>> list(b)
[]
```
## Expected results
An exception should be raised in streaming mode
## Actual results
No exception is raised in streaming mode: there is no way to tell if something has broken or if the dataset is simply empty.
## Environment info
- `datasets` version: 1.11.1.dev0
- Platform: Linux-5.11.0-1016-aws-x86_64-with-glibc2.29
- Python version: 3.8.11
- PyArrow version: 4.0.1
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https://api.github.com/repos/huggingface/datasets/issues/5905 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5905/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5905/comments | https://api.github.com/repos/huggingface/datasets/issues/5905/events | https://github.com/huggingface/datasets/issues/5905 | 1,727,541,392 | I_kwDODunzps5m-DCQ | 5,905 | Offer an alternative to Iterable Dataset that allows lazy loading and processing while skipping batches efficiently | {
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"We plan to improve this eventually (see https://github.com/huggingface/datasets/issues/5454 and https://github.com/huggingface/datasets/issues/5380).\r\n\r\n> Is it possible to lazily load samples of a mapped dataset ? I'm used to [dataset scripts](https://huggingface.co/docs/datasets/dataset_script), maybe someth... | 2023-05-26T12:33:02Z | 2023-06-15T13:34:18Z | null | CONTRIBUTOR | null | null | null | ### Feature request
I would like a way to resume training from a checkpoint without waiting for a very long time when using an iterable dataset.
### Motivation
I am training models on the speech-recognition task. I have very large datasets that I can't comfortably store on a disk and also quite computationally intensive audio processing to do. As a result I want to load data from my remote when it is needed and perform all processing on the fly.
I am currently using the iterable dataset feature of _datasets_. It does everything I need with one exception. My issue is that when resuming training at a step n, we have to download all the data and perform the processing of steps < n, just to get the iterable at the right step. In my case it takes almost as long as training for the same steps, which make resuming training from a checkpoint useless in practice.
I understand that the nature of iterators make it probably nearly impossible to quickly resume training.
I thought about a possible solution nonetheless :
I could in fact index my large dataset and make it a mapped dataset. Then I could use set_transform to perform the processing on the fly. Finally, if I'm not mistaken, the _accelerate_ package allows to [skip steps efficiently](https://github.com/huggingface/accelerate/blob/a73898027a211c3f6dc4460351b0ec246aa824aa/src/accelerate/data_loader.py#L827) for a mapped dataset.
Is it possible to lazily load samples of a mapped dataset ? I'm used to [dataset scripts](https://huggingface.co/docs/datasets/dataset_script), maybe something can be done there.
If not, I could do it using a plain _Pytorch_ dataset. Then I would need to convert it to a _datasets_' dataset to get all the features of _datasets_. Is it something possible ?
### Your contribution
I could provide a PR to allow lazy loading of mapped dataset or the conversion of a mapped _Pytorch_ dataset into a _Datasets_ dataset if you think it is an useful new feature. | {
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https://api.github.com/repos/huggingface/datasets/issues/2432 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2432/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2432/comments | https://api.github.com/repos/huggingface/datasets/issues/2432/events | https://github.com/huggingface/datasets/pull/2432 | 907,462,881 | MDExOlB1bGxSZXF1ZXN0NjU4MzA3MTE1 | 2,432 | Fix CI six installation on linux | {
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} | For some reason we end up with this error in the linux CI when running pip install .[tests]
```
pip._vendor.resolvelib.resolvers.InconsistentCandidate: Provided candidate AlreadyInstalledCandidate(six 1.16.0 (/usr/local/lib/python3.6/site-packages)) does not satisfy SpecifierRequirement('six>1.9'), SpecifierRequirement('six>1.9'), SpecifierRequirement('six>=1.11'), SpecifierRequirement('six~=1.15'), SpecifierRequirement('six'), SpecifierRequirement('six>=1.5.2'), SpecifierRequirement('six>=1.9.0'), SpecifierRequirement('six>=1.11.0'), SpecifierRequirement('six'), SpecifierRequirement('six>=1.6.1'), SpecifierRequirement('six>=1.9'), SpecifierRequirement('six>=1.5'), SpecifierRequirement('six<2.0'), SpecifierRequirement('six<2.0'), SpecifierRequirement('six'), SpecifierRequirement('six'), SpecifierRequirement('six~=1.15.0'), SpecifierRequirement('six'), SpecifierRequirement('six<2.0,>=1.6.1'), SpecifierRequirement('six'), SpecifierRequirement('six>=1.5.2'), SpecifierRequirement('six>=1.9.0')
```
example CI failure here:
https://app.circleci.com/pipelines/github/huggingface/datasets/6200/workflows/b64fdec9-f9e6-431c-acd7-e9f2c440c568/jobs/38247
The main version requirement comes from tensorflow: `six~=1.15.0`
So I pinned the six version to this. | {
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https://api.github.com/repos/huggingface/datasets/issues/3976 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3976/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3976/comments | https://api.github.com/repos/huggingface/datasets/issues/3976/events | https://github.com/huggingface/datasets/pull/3976 | 1,175,043,780 | PR_kwDODunzps40uOY6 | 3,976 | Fix main classes reference in docs | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3976). All of your documentation changes will be reflected on that endpoint.",
"Not sure why some section titles end with `[[datasets.xxx]]`, like this: https://moon-ci-docs.huggingface.co/docs/datasets/pr_3976/en/package_refer... | 2022-03-21T08:19:46Z | 2022-04-12T14:19:39Z | 2022-04-12T14:19:38Z | CONTRIBUTOR | null | 0 | {
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} | Currently the section index (on the page's right side) of the [main classes reference](https://huggingface.co/docs/datasets/master/en/package_reference/main_classes) incorrectly displays `Tensor returned:`, this PR fixes this issue by wrapping code examples in this page with markdown code block.
There are other examples in datasets library having this issue. | {
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https://api.github.com/repos/huggingface/datasets/issues/1552 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1552/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1552/comments | https://api.github.com/repos/huggingface/datasets/issues/1552/events | https://github.com/huggingface/datasets/pull/1552 | 765,664,411 | MDExOlB1bGxSZXF1ZXN0NTM5MDI2MzAx | 1,552 | Added OPUS ParaCrawl | {
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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.",
"@rkc007 @lhoestq just noticed a dataset named para_crawl has been added a long time ago: #91.",
"They're not exactly the same so it's ok to have both... | 2020-12-13T21:44:29Z | 2020-12-21T09:50:26Z | 2020-12-21T09:50:25Z | CONTRIBUTOR | null | 0 | {
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} | Dataset : http://opus.nlpl.eu/ParaCrawl.php | {
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https://api.github.com/repos/huggingface/datasets/issues/6239 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6239/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6239/comments | https://api.github.com/repos/huggingface/datasets/issues/6239/events | https://github.com/huggingface/datasets/issues/6239 | 1,895,349,382 | I_kwDODunzps5w-LyG | 6,239 | Load local audio data doesn't work | {
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"I think this is the same issue as https://github.com/huggingface/datasets/issues/4776. Maybe installing `ffmpeg` can fix it:\r\n```python\r\nadd-apt-repository -y ppa:savoury1/ffmpeg4\r\napt-get -qq install -y ffmpeg\r\n```\r\n\r\nHowever, the best solution is to use a newer version of `datasets`. In the recent re... | 2023-09-13T22:30:01Z | 2023-09-15T14:32:10Z | 2023-09-15T14:32:10Z | NONE | null | null | null | ### Describe the bug
I get a RuntimeError from the following code:
```python
audio_dataset = Dataset.from_dict({"audio": ["/kaggle/input/bengaliai-speech/train_mp3s/000005f3362c.mp3"]}).cast_column("audio", Audio())
audio_dataset[0]
```
### Traceback
<details>
```python
RuntimeError Traceback (most recent call last)
Cell In[33], line 1
----> 1 train_dataset[0]
File /opt/conda/lib/python3.10/site-packages/datasets/arrow_dataset.py:1764, in Dataset.__getitem__(self, key)
1762 def __getitem__(self, key): # noqa: F811
1763 """Can be used to index columns (by string names) or rows (by integer index or iterable of indices or bools)."""
-> 1764 return self._getitem(
1765 key,
1766 )
File /opt/conda/lib/python3.10/site-packages/datasets/arrow_dataset.py:1749, in Dataset._getitem(self, key, decoded, **kwargs)
1747 formatter = get_formatter(format_type, features=self.features, decoded=decoded, **format_kwargs)
1748 pa_subtable = query_table(self._data, key, indices=self._indices if self._indices is not None else None)
-> 1749 formatted_output = format_table(
1750 pa_subtable, key, formatter=formatter, format_columns=format_columns, output_all_columns=output_all_columns
1751 )
1752 return formatted_output
File /opt/conda/lib/python3.10/site-packages/datasets/formatting/formatting.py:532, in format_table(table, key, formatter, format_columns, output_all_columns)
530 python_formatter = PythonFormatter(features=None)
531 if format_columns is None:
--> 532 return formatter(pa_table, query_type=query_type)
533 elif query_type == "column":
534 if key in format_columns:
File /opt/conda/lib/python3.10/site-packages/datasets/formatting/formatting.py:281, in Formatter.__call__(self, pa_table, query_type)
279 def __call__(self, pa_table: pa.Table, query_type: str) -> Union[RowFormat, ColumnFormat, BatchFormat]:
280 if query_type == "row":
--> 281 return self.format_row(pa_table)
282 elif query_type == "column":
283 return self.format_column(pa_table)
File /opt/conda/lib/python3.10/site-packages/datasets/formatting/formatting.py:312, in PythonFormatter.format_row(self, pa_table)
310 row = self.python_arrow_extractor().extract_row(pa_table)
311 if self.decoded:
--> 312 row = self.python_features_decoder.decode_row(row)
313 return row
File /opt/conda/lib/python3.10/site-packages/datasets/formatting/formatting.py:221, in PythonFeaturesDecoder.decode_row(self, row)
220 def decode_row(self, row: dict) -> dict:
--> 221 return self.features.decode_example(row) if self.features else row
File /opt/conda/lib/python3.10/site-packages/datasets/features/features.py:1386, in Features.decode_example(self, example)
1376 def decode_example(self, example: dict):
1377 """Decode example with custom feature decoding.
1378
1379 Args:
(...)
1383 :obj:`dict[str, Any]`
1384 """
-> 1386 return {
1387 column_name: decode_nested_example(feature, value)
1388 if self._column_requires_decoding[column_name]
1389 else value
1390 for column_name, (feature, value) in zip_dict(
1391 {key: value for key, value in self.items() if key in example}, example
1392 )
1393 }
File /opt/conda/lib/python3.10/site-packages/datasets/features/features.py:1387, in <dictcomp>(.0)
1376 def decode_example(self, example: dict):
1377 """Decode example with custom feature decoding.
1378
1379 Args:
(...)
1383 :obj:`dict[str, Any]`
1384 """
1386 return {
-> 1387 column_name: decode_nested_example(feature, value)
1388 if self._column_requires_decoding[column_name]
1389 else value
1390 for column_name, (feature, value) in zip_dict(
1391 {key: value for key, value in self.items() if key in example}, example
1392 )
1393 }
File /opt/conda/lib/python3.10/site-packages/datasets/features/features.py:1087, in decode_nested_example(schema, obj)
1085 # Object with special decoding:
1086 elif isinstance(schema, (Audio, Image)):
-> 1087 return schema.decode_example(obj) if obj is not None else None
1088 return obj
File /opt/conda/lib/python3.10/site-packages/datasets/features/audio.py:103, in Audio.decode_example(self, value)
101 raise ValueError(f"An audio sample should have one of 'path' or 'bytes' but both are None in {value}.")
102 elif path is not None and path.endswith("mp3"):
--> 103 array, sampling_rate = self._decode_mp3(file if file else path)
104 elif path is not None and path.endswith("opus"):
105 if file:
File /opt/conda/lib/python3.10/site-packages/datasets/features/audio.py:241, in Audio._decode_mp3(self, path_or_file)
238 except RuntimeError as err:
239 raise ImportError("To support decoding 'mp3' audio files, please install 'sox'.") from err
--> 241 array, sampling_rate = torchaudio.load(path_or_file, format="mp3")
242 if self.sampling_rate and self.sampling_rate != sampling_rate:
243 if not hasattr(self, "_resampler") or self._resampler.orig_freq != sampling_rate:
File /opt/conda/lib/python3.10/site-packages/torchaudio/backend/sox_io_backend.py:256, in load(filepath, frame_offset, num_frames, normalize, channels_first, format)
254 if ret is not None:
255 return ret
--> 256 return _fallback_load(filepath, frame_offset, num_frames, normalize, channels_first, format)
File /opt/conda/lib/python3.10/site-packages/torchaudio/backend/sox_io_backend.py:30, in _fail_load(filepath, frame_offset, num_frames, normalize, channels_first, format)
22 def _fail_load(
23 filepath: str,
24 frame_offset: int = 0,
(...)
28 format: Optional[str] = None,
29 ) -> Tuple[torch.Tensor, int]:
---> 30 raise RuntimeError("Failed to load audio from {}".format(filepath))
RuntimeError: Failed to load audio from /kaggle/input/bengaliai-speech/train_mp3s/000005f3362c.mp3
```
</details>
### Steps to reproduce the bug
1. - Create a custom dataset using Local files of type mp3.
3. - Try to read the first audio item.
### Expected behavior
Expected output
```python
audio_dataset[0]["audio"]
{'array': array([ 0. , 0.00024414, -0.00024414, ..., -0.00024414,
0. , 0. ], dtype=float32),
'path': 'path/to/audio_1',
'sampling_rate': 16000}
```
### Environment info
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https://api.github.com/repos/huggingface/datasets/issues/3233 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3233/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3233/comments | https://api.github.com/repos/huggingface/datasets/issues/3233/events | https://github.com/huggingface/datasets/pull/3233 | 1,047,474,931 | PR_kwDODunzps4uOl9- | 3,233 | Improve repository structure docs | {
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} | Continuation of the documentation started in https://github.com/huggingface/datasets/pull/3221, taking into account @stevhliu 's comments | {
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https://api.github.com/repos/huggingface/datasets/issues/2104 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2104/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2104/comments | https://api.github.com/repos/huggingface/datasets/issues/2104/events | https://github.com/huggingface/datasets/issues/2104 | 839,027,834 | MDU6SXNzdWU4MzkwMjc4MzQ= | 2,104 | Trouble loading wiki_movies | {
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"Hi ! `wiki_movies` was added in `datasets==1.2.0`. However it looks like you have `datasets==1.1.2`.\r\n\r\nTo use `wiki_movies`, please update `datasets` with\r\n```\r\npip install --upgrade datasets\r\n```",
"Thanks a lot! That solved it and I was able to upload a model trained on it as well :)"
] | 2021-03-23T18:59:54Z | 2022-03-30T08:22:58Z | 2022-03-30T08:22:58Z | NONE | null | null | null | Hello,
I am trying to load_dataset("wiki_movies") and it gives me this error -
`FileNotFoundError: Couldn't find file locally at wiki_movies/wiki_movies.py, or remotely at https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/wiki_movies/wiki_movies.py or https://s3.amazonaws.com/datasets.huggingface.co/datasets/datasets/wiki_movies/wiki_movies.py`
Trying to do `python run_mlm.py \
--model_name_or_path roberta-base \
--dataset_name wiki_movies \` also gives the same error.
Is this something on my end? From what I can tell, this dataset was re-added by @lhoestq a few months ago.
Thank you! | {
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https://api.github.com/repos/huggingface/datasets/issues/1538 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1538/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1538/comments | https://api.github.com/repos/huggingface/datasets/issues/1538/events | https://github.com/huggingface/datasets/pull/1538 | 765,139,739 | MDExOlB1bGxSZXF1ZXN0NTM4ODkxOTE3 | 1,538 | tweets_hate_speech_detection | {
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"Hi @lhoestq I have added this new dataset for tweet's hate speech detection. \r\n\r\nPlease if u could review it. \r\n\r\nThank you",
"Hi @darshan-gandhi have you add a chance to take a look at my suggestions ?\r\n\r\nFeel free to ping me when you're ready for the final review",
"Closing in favor of #1607"
] | 2020-12-13T07:37:53Z | 2020-12-21T15:54:28Z | 2020-12-21T15:54:27Z | CONTRIBUTOR | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/3284 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3284/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3284/comments | https://api.github.com/repos/huggingface/datasets/issues/3284/events | https://github.com/huggingface/datasets/issues/3284 | 1,055,502,909 | I_kwDODunzps4-6bI9 | 3,284 | Add VoxLingua107 dataset | {
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"#self-assign"
] | 2021-11-16T22:44:08Z | 2021-12-06T09:49:45Z | null | MEMBER | null | null | null | ## Adding a Dataset
- **Name:** VoxLingua107
- **Description:** VoxLingua107 is a speech dataset for training spoken language identification models. The dataset consists of short speech segments automatically extracted from YouTube videos and labeled according the language of the video title and description, with some post-processing steps to filter out false positives.
- **Paper:** https://arxiv.org/abs/2011.12998
- **Data:** http://bark.phon.ioc.ee/voxlingua107/
- **Motivation:** Nice audio classification dataset
cc @anton-l
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
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"This dataset is already available on the Hub: https://huggingface.co/datasets/facebook/belebele.\r\n"
] | 2023-10-06T06:58:03Z | 2023-10-06T13:26:51Z | 2023-10-06T13:26:51Z | NONE | null | null | null | ### Feature request
Belebele is a multiple-choice machine reading comprehension (MRC) dataset spanning 122 language variants. This dataset enables the evaluation of mono- and multi-lingual models in high-, medium-, and low-resource languages. Each question has four multiple-choice answers and is linked to a short passage from the [FLORES-200](https://github.com/facebookresearch/flores/tree/main/flores200) dataset. The human annotation procedure was carefully curated to create questions that discriminate between different levels of generalizable language comprehension and is reinforced by extensive quality checks. While all questions directly relate to the passage, the English dataset on its own proves difficult enough to challenge state-of-the-art language models. Being fully parallel, this dataset enables direct comparison of model performance across all languages. Belebele opens up new avenues for evaluating and analyzing the multilingual abilities of language models and NLP systems.
Please refer to paper for more details, [The Belebele Benchmark: a Parallel Reading Comprehension Dataset in 122 Language Variants](https://arxiv.org/abs/2308.16884).
## Composition
- 900 questions per language variant
- 488 distinct passages, there are 1-2 associated questions for each.
- For each question, there is 4 multiple-choice answers, exactly 1 of which is correct.
- 122 language/language variants (including English).
- 900 x 122 = 109,800 total questions.
### Motivation
official repo https://github.com/facebookresearch/belebele
### Your contribution
- | {
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"Thanks for the suggestion ! I agree it would be nice to have something directly in `datasets` to do something as simple as that\r\n\r\ncc @albertvillanova @mariosasko @polinaeterna What do you think if we have something similar to pandas `Series` that wouldn't bring everything in memory when doing `dataset[\"audio... | 2022-04-19T09:15:45Z | 2022-04-21T10:30:58Z | null | CONTRIBUTOR | null | null | null | **Is your feature request related to a problem? Please describe.**
A clear and concise description of what the problem is.
Currently, `dataset["audio"]` will load EVERY element in the dataset in RAM, which can be quite big for an audio dataset.
Having an iterator (or sequence) type of object, would make inference with `transformers` 's `pipeline` easier to use and not so memory hungry.
**Describe the solution you'd like**
A clear and concise description of what you want to happen.
For a non breaking change:
```python
for audio in dataset.iterate("audio"):
# {"array": np.array(...), "sampling_rate":...}
```
For a breaking change solution (not necessary), changing the type of `dataset["audio"]` to a sequence type so that
```python
pipe = pipeline(model="...")
for out in pipe(dataset["audio"]):
# {"text":....}
```
could work
**Describe alternatives you've considered**
A clear and concise description of any alternative solutions or features you've considered.
```python
def iterate(dataset, key):
for item in dataset:
yield dataset[key]
for out in pipeline(iterate(dataset, "audio")):
# {"array": ...}
```
This works but requires the helper function which feels slightly clunky.
**Additional context**
Add any other context about the feature request here.
The context is actually to showcase better integration between `pipeline` and `datasets` in the Quicktour demo: https://github.com/huggingface/transformers/pull/16723/files
@lhoestq
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} | This fixes a bug in the `TestCommand` where multiple kwargs for `name` were passed if it was set in both default and `module.builder_kwargs`. Example error:
```Python
Traceback (most recent call last):
File "create_metadata.py", line 96, in <module>
main(**vars(args))
File "create_metadata.py", line 86, in main
metadata_command.run()
File "/opt/conda/lib/python3.7/site-packages/datasets/commands/test.py", line 144, in run
for j, builder in enumerate(get_builders()):
File "/opt/conda/lib/python3.7/site-packages/datasets/commands/test.py", line 141, in get_builders
name=name, cache_dir=self._cache_dir, data_dir=self._data_dir, **module.builder_kwargs
TypeError: type object got multiple values for keyword argument 'name'
```
Let me know what you think. | {
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https://api.github.com/repos/huggingface/datasets/issues/1638 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1638/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1638/comments | https://api.github.com/repos/huggingface/datasets/issues/1638/events | https://github.com/huggingface/datasets/pull/1638 | 774,869,184 | MDExOlB1bGxSZXF1ZXN0NTQ1Njg5ODQ5 | 1,638 | Add id_puisi dataset | {
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- The Matthews correlation coefficient (from sklearn)
- The Pearson correlation coefficient (from scipy)
- The Spearman correlation coefficient (from scipy)
cc @sgugger | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3871). All of your documentation changes will be reflected on that endpoint.",
"Think failures are unrelated - feel free to merge whenever you want :-)"
] | 2022-03-09T09:48:51Z | 2022-03-09T11:21:38Z | 2022-03-09T11:21:37Z | MEMBER | null | 0 | {
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"merging since the CI is fixed on master"
] | 2020-12-13T22:55:35Z | 2020-12-18T15:14:28Z | 2020-12-18T15:14:27Z | CONTRIBUTOR | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/2343 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2343/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2343/comments | https://api.github.com/repos/huggingface/datasets/issues/2343/events | https://github.com/huggingface/datasets/issues/2343 | 883,208,539 | MDU6SXNzdWU4ODMyMDg1Mzk= | 2,343 | Columns are removed before or after map function applied? | {
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"Hi! Columns are removed **after** applying the function and **before** updating the examples with the function's output (as per the docs [here](https://huggingface.co/docs/datasets/package_reference/main_classes#datasets.Dataset.map.remove_columns)). I agree the docs on this should be more clear."
] | 2021-05-10T02:36:20Z | 2022-10-24T11:31:55Z | null | NONE | null | null | null | ## Describe the bug
According to the documentation when applying map function the [remove_columns ](https://huggingface.co/docs/datasets/processing.html#removing-columns) will be removed after they are passed to the function, but in the [source code](https://huggingface.co/docs/datasets/package_reference/main_classes.html#datasets.Dataset.map) it's documented that they are removed before applying function. I thinks the source code doc is more accurate, right?
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https://api.github.com/repos/huggingface/datasets/issues/5354 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5354/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5354/comments | https://api.github.com/repos/huggingface/datasets/issues/5354/events | https://github.com/huggingface/datasets/issues/5354 | 1,492,174,125 | I_kwDODunzps5Y8MUt | 5,354 | Consider using "Sequence" instead of "List" | {
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"Hi! Linking a comment to provide more info on the issue: https://stackoverflow.com/a/39458225. This means we should replace all (most of) the occurrences of `List` with `Sequence` in function signatures.\r\n\r\n@tranhd95 Would you be interested in submitting a PR?",
"Hi all! I tried to reproduce this issue and d... | 2022-12-12T15:39:45Z | 2023-07-26T16:25:51Z | null | NONE | null | null | null | ### Feature request
Hi, please consider using `Sequence` type annotation instead of `List` in function arguments such as in [`Dataset.from_parquet()`](https://github.com/huggingface/datasets/blob/main/src/datasets/arrow_dataset.py#L1088). It leads to type checking errors, see below.
**How to reproduce**
```py
list_of_filenames = ["foo.parquet", "bar.parquet"]
ds = Dataset.from_parquet(list_of_filenames)
```
**Expected mypy output:**
```
Success: no issues found
```
**Actual mypy output:**
```py
test.py:19: error: Argument 1 to "from_parquet" of "Dataset" has incompatible type "List[str]"; expected "Union[Union[str, bytes, PathLike[Any]], List[Union[str, bytes, PathLike[Any]]]]" [arg-type]
test.py:19: note: "List" is invariant -- see https://mypy.readthedocs.io/en/stable/common_issues.html#variance
test.py:19: note: Consider using "Sequence" instead, which is covariant
```
**Env:** mypy 0.991, Python 3.10.0, datasets 2.7.1 | {
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https://api.github.com/repos/huggingface/datasets/issues/3363 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3363/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3363/comments | https://api.github.com/repos/huggingface/datasets/issues/3363/events | https://github.com/huggingface/datasets/pull/3363 | 1,068,824,340 | PR_kwDODunzps4vRVCl | 3,363 | Update URL of Jeopardy! dataset | {
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"Closing this PR in favor of #3266.",
"I think you should also close this branch"
] | 2021-12-01T20:08:10Z | 2022-10-06T13:45:49Z | 2021-12-03T12:35:01Z | CONTRIBUTOR | null | 0 | {
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Fix #3361 | {
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https://api.github.com/repos/huggingface/datasets/issues/4635 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4635/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4635/comments | https://api.github.com/repos/huggingface/datasets/issues/4635/events | https://github.com/huggingface/datasets/issues/4635 | 1,294,475,931 | I_kwDODunzps5NKCKb | 4,635 | Dataset Viewer issue for vadis/sv-ident | {
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"Thanks for reporting, @e-tornike \r\n\r\nSome context:\r\n- #4527 \r\n\r\nThe dataset loads locally in streaming mode:\r\n```python\r\nIn [2]: from datasets import load_dataset; ds = load_dataset(\"vadis/sv-ident\", split=\"validation\", streaming=True); item = next(iter(ds)); item\r\nUsing custom data configurati... | 2022-07-05T15:48:13Z | 2022-07-06T07:13:33Z | 2022-07-06T07:12:14Z | NONE | null | null | null | ### Link
https://huggingface.co/datasets/vadis/sv-ident/viewer/default/validation
### Description
Error message when loading validation split in the viewer:
```
Status code: 400
Exception: Status400Error
Message: The split cache is empty.
```
### Owner
_No response_ | {
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https://api.github.com/repos/huggingface/datasets/issues/1450 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1450/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1450/comments | https://api.github.com/repos/huggingface/datasets/issues/1450/events | https://github.com/huggingface/datasets/pull/1450 | 761,102,429 | MDExOlB1bGxSZXF1ZXN0NTM1ODIwNjg0 | 1,450 | Fix version in bible_para | {
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https://api.github.com/repos/huggingface/datasets/issues/4628 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4628/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4628/comments | https://api.github.com/repos/huggingface/datasets/issues/4628/events | https://github.com/huggingface/datasets/pull/4628 | 1,293,361,308 | PR_kwDODunzps46zvFJ | 4,628 | Fix time type `_arrow_to_datasets_dtype` conversion | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-07-04T16:20:15Z | 2022-07-07T14:08:38Z | 2022-07-07T13:57:12Z | CONTRIBUTOR | null | 0 | {
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} | Fix #4620
The issue stems from the fact that `pa.array([time_data]).type` returns `DataType(time64[unit])`, which doesn't expose the `unit` attribute, instead of `Time64Type(time64[unit])`. I believe this is a bug in PyArrow. Luckily, the both types have the same `str()`, so in this PR I call `pa.type_for_alias(str(type))` to convert them both to the `Time64Type(time64[unit])` format.
cc @severo | {
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https://api.github.com/repos/huggingface/datasets/issues/1373 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1373/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1373/comments | https://api.github.com/repos/huggingface/datasets/issues/1373/events | https://github.com/huggingface/datasets/pull/1373 | 760,280,869 | MDExOlB1bGxSZXF1ZXN0NTM1MTM5MTY0 | 1,373 | Add OPUS ECB Dataset | {
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https://api.github.com/repos/huggingface/datasets/issues/2981 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2981/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2981/comments | https://api.github.com/repos/huggingface/datasets/issues/2981/events | https://github.com/huggingface/datasets/pull/2981 | 1,009,969,310 | PR_kwDODunzps4sZ4ke | 2,981 | add wit dataset | {
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"Opening this up - Here's whats left to make it really shine:\r\n- [ ] Update dataset card (this is being worked on by the author)\r\n- [ ] Add `dataset_info.json`. Requires downloading the entire dataset. I believe @lhoestq mentioned he may have a machine he's using for this sort of thing.\r\n\r\nI think both of t... | 2021-09-28T16:34:49Z | 2022-05-05T14:26:41Z | 2022-05-05T14:26:41Z | CONTRIBUTOR | null | 0 | {
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} | Resolves #2902 based on conversation there - would also close #2810. Open to suggestions/help 😀
CC @hassiahk @lhoestq @yjernite | {
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https://api.github.com/repos/huggingface/datasets/issues/2316 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2316/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2316/comments | https://api.github.com/repos/huggingface/datasets/issues/2316/events | https://github.com/huggingface/datasets/issues/2316 | 875,756,353 | MDU6SXNzdWU4NzU3NTYzNTM= | 2,316 | Incorrect version specification for pyarrow | {
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"Fixed by #2317."
] | 2021-05-04T19:15:11Z | 2021-05-05T10:10:03Z | 2021-05-05T10:10:03Z | CONTRIBUTOR | null | null | null | ## Describe the bug
The pyarrow dependency is incorrectly specified in setup.py file, in [this line](https://github.com/huggingface/datasets/blob/3a3e5a4da20bfcd75f8b6a6869b240af8feccc12/setup.py#L77).
Also as a snippet:
```python
"pyarrow>=1.0.0<4.0.0",
```
## Steps to reproduce the bug
```bash
pip install "pyarrow>=1.0.0<4.0.0"
```
## Expected results
It is expected to get a pyarrow version between 1.0.0 (inclusive) and 4.0.0 (exclusive).
## Actual results
pip ignores the specified versions since there is a missing comma between the lower and upper limits. Therefore, pip installs the latest pyarrow version from PYPI, which is 4.0.0.
This is especially problematic since "conda env export" fails due to incorrect version specification. Here is the conda error as well:
```bash
conda env export
InvalidVersionSpec: Invalid version '1.0.0<4.0.0': invalid character(s)
```
## Fix suggestion
Put a comma between the version limits which means replacing the line in setup.py file with the following:
```python
"pyarrow>=1.0.0,<4.0.0",
```
## Versions
Paste the output of the following code:
```python
- Datasets: 1.6.2
- Python: 3.7.10 (default, Feb 26 2021, 18:47:35)
[GCC 7.3.0]
- Platform: Linux-5.4.0-42-generic-x86_64-with-debian-buster-sid
```
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https://api.github.com/repos/huggingface/datasets/issues/3704 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3704/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3704/comments | https://api.github.com/repos/huggingface/datasets/issues/3704/events | https://github.com/huggingface/datasets/issues/3704 | 1,132,042,631 | I_kwDODunzps5DeZmH | 3,704 | OSCAR-2109 datasets are misaligned and truncated | {
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"Hi @adrianeboyd, thanks for reporting.\r\n\r\nThere is indeed a bug in that community dataset:\r\nLine:\r\n```python\r\nmetadata_and_text_files = list(zip(metadata_files, text_files))\r\n``` \r\nshould be replaced with\r\n```python\r\nmetadata_and_text_files = list(zip(sorted(metadata_files), sorted(text_files)))\... | 2022-02-11T08:14:59Z | 2022-03-17T18:01:04Z | 2022-03-16T16:21:28Z | NONE | null | null | null | ## Describe the bug
The `oscar-corpus/OSCAR-2109` data appears to be misaligned and truncated by the dataset builder for subsets that contain more than one part and for cases where the texts contain non-unix newlines.
## Steps to reproduce the bug
A few examples, although I'm not sure how deterministic the particular (mis)alignment is in various configurations:
```python
from datasets import load_dataset
dataset = load_dataset("oscar-corpus/OSCAR-2109", "deduplicated_fi", split="train", use_auth_token=True)
entry = dataset[0]
# entry["text"] is from fi_part_3.txt.gz
# entry["meta"] is from fi_meta_part_2.jsonl.gz
dataset = load_dataset("oscar-corpus/OSCAR-2109", "deduplicated_no", split="train", use_auth_token=True)
entry = dataset[900000]
# entry["text"] is from no_part_3.txt.gz and contains a blank line
# entry["meta"] is from no_meta_part_1.jsonl.gz
dataset = load_dataset("oscar-corpus/OSCAR-2109", "deduplicated_mk", split="train", streaming=True, use_auth_token=True)
# 9088 texts in the dataset are empty
```
For `deduplicated_fi`, all exported raw texts from the dataset are 17GB rather than 20GB as reported in the data splits overview table. The token count with `wc -w` for the raw texts is 2,067,556,874 rather than the expected 2,357,264,196 from the data splits table.
For `deduplicated_no` all exported raw texts contain 624,040,887 rather than the expected 776,354,517 tokens.
For `deduplicated_mk` it is 122,236,936 rather than 134,544,934 tokens.
I'm not expecting the `wc -w` counts to line up exactly with the data splits table, but for comparison the `wc -w` count for `deduplicated_mk` on the raw texts is 134,545,424.
## Issues
* The meta / text files are not paired correctly when loading, so the extracted texts do not have the right offsets, the metadata is not associated with the correct text, and the text files may not be processed to the end or may be processed beyond the end (empty texts).
* The line count offset is not reset per file so the texts aren't aligned to the right offsets in any parts beyond the first part, leading to truncation when in effect blank lines are not skipped.
* Non-unix newline characters are treated as newlines when reading the text files while the metadata only counts unix newlines for its line offsets, leading to further misalignments between the metadata and the extracted texts, and which also results in truncation.
## Expected results
All texts from the OSCAR release are extracted according to the metadata and aligned with the correct metadata.
## Fixes
Not necessarily the exact fixes/checks you may want to use (I didn't test all languages or do any cross-platform testing, I'm not sure all the details are compatible with streaming), however to highlight the issues:
```diff
diff --git a/OSCAR-2109.py b/OSCAR-2109.py
index bbac1076..5eee8de7 100644
--- a/OSCAR-2109.py
+++ b/OSCAR-2109.py
@@ -20,6 +20,7 @@
import collections
import gzip
import json
+import os
import datasets
@@ -387,9 +388,20 @@ class Oscar2109(datasets.GeneratorBasedBuilder):
with open(checksum_file, encoding="utf-8") as f:
data_filenames = [line.split()[1] for line in f if line]
data_urls = [self.config.base_data_path + data_filename for data_filename in data_filenames]
- text_files = dl_manager.download([url for url in data_urls if url.endswith(".txt.gz")])
- metadata_files = dl_manager.download([url for url in data_urls if url.endswith(".jsonl.gz")])
+ # sort filenames so corresponding parts are aligned
+ text_files = sorted(dl_manager.download([url for url in data_urls if url.endswith(".txt.gz")]))
+ metadata_files = sorted(dl_manager.download([url for url in data_urls if url.endswith(".jsonl.gz")]))
+ assert len(text_files) == len(metadata_files)
metadata_and_text_files = list(zip(metadata_files, text_files))
+ for meta_path, text_path in metadata_and_text_files:
+ # check that meta/text part numbers are the same
+ if "part" in os.path.basename(text_path):
+ assert (
+ os.path.basename(text_path).replace(".txt.gz", "").split("_")[-1]
+ == os.path.basename(meta_path).replace(".jsonl.gz", "").split("_")[-1]
+ )
+ else:
+ assert len(metadata_and_text_files) == 1
return [
datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"metadata_and_text_files": metadata_and_text_files}),
]
@@ -397,10 +409,14 @@ class Oscar2109(datasets.GeneratorBasedBuilder):
def _generate_examples(self, metadata_and_text_files):
"""This function returns the examples in the raw (text) form by iterating on all the files."""
id_ = 0
- offset = 0
for meta_path, text_path in metadata_and_text_files:
+ # line offsets are per text file
+ offset = 0
logger.info("generating examples from = %s", text_path)
- with gzip.open(open(text_path, "rb"), "rt", encoding="utf-8") as text_f:
+ # some texts contain non-Unix newlines that should not be
+ # interpreted as line breaks for the line counts in the metadata
+ # with readline()
+ with gzip.open(open(text_path, "rb"), "rt", encoding="utf-8", newline="\n") as text_f:
with gzip.open(open(meta_path, "rb"), "rt", encoding="utf-8") as meta_f:
for line in meta_f:
# read meta
@@ -411,7 +427,12 @@ class Oscar2109(datasets.GeneratorBasedBuilder):
offset += 1
text_f.readline()
# read text
- text = "".join([text_f.readline() for _ in range(meta["nb_sentences"])]).rstrip()
+ text_lines = [text_f.readline() for _ in range(meta["nb_sentences"])]
+ # all lines contain text (no blank lines or EOF)
+ assert all(text_lines)
+ assert "\n" not in text_lines
offset += meta["nb_sentences"]
+ # only strip the trailing newline
+ text = "".join(text_lines).rstrip("\n")
yield id_, {"id": id_, "text": text, "meta": meta}
id_ += 1
```
I've tested this with a number of smaller deduplicated languages with 1-20 parts and the resulting datasets looked correct in terms of word count and size when compared to the data splits table and raw texts, and the text/metadata alignments were correct in all my spot checks. However, there are many many languages I didn't test and I'm not sure that there aren't any texts containing blank lines in the corpus, for instance. For the cases I tested, the assertions related to blank lines and EOF made it easier to verify that the text and metadata were aligned as intended, since there would be little chance of spurious alignments of variable-length texts across so much data. | {
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https://api.github.com/repos/huggingface/datasets/issues/5137 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5137/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5137/comments | https://api.github.com/repos/huggingface/datasets/issues/5137/events | https://github.com/huggingface/datasets/issues/5137 | 1,414,642,723 | I_kwDODunzps5UUbwj | 5,137 | Align task tags in dataset metadata | {
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"I removed all the invalid task_ids in datasts without namespace, based on the <s>(internal)</s> types.ts",
"(Types.ts is not internal it's public)",
"I have opened PRs to fix the task_ids in all datasets within a namespace as well.\r\n\r\nWorking on task_categories...",
"For future reference: this fix had so... | 2022-10-19T09:41:42Z | 2022-11-10T05:25:58Z | 2022-10-25T06:17:00Z | MEMBER | null | null | null | ## Describe
Once we have agreed on a common naming for task tags for all open source projects, we should align on them.
## Steps
- [x] Align task tags in canonical datasets
- [x] task_categories: 4 datasets
- [x] task_ids (by @lhoestq)
- [x] Open PRs in community datasets
- [x] task_categories: 451 datasets
- [x] task_ids: 556 datasets
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"Thanks for reporting, @bilelomrani1.\r\n\r\nWe are fixing it. ",
"We have fixed it. We are planning to do a patch release today."
] | 2023-07-30T23:03:00Z | 2023-08-03T10:00:48Z | 2023-08-01T10:38:55Z | NONE | null | null | null | ### Describe the bug
Loading a dataset from a GCP bucket raises a type error. This bug was introduced recently (either in 2.14 or 2.14.1), and appeared during a migration from 2.13.1.
### Steps to reproduce the bug
Load any file from a GCP bucket:
```python
import datasets
datasets.load_dataset("json", data_files=["gs://..."])
```
The following exception is raised:
```python
Traceback (most recent call last):
...
packages/datasets/data_files.py", line 335, in resolve_pattern
protocol_prefix = fs.protocol + "://" if fs.protocol != "file" else ""
TypeError: can only concatenate tuple (not "str") to tuple
```
With a `GoogleFileSystem`, the attribute `fs.protocol` is a tuple `('gs', 'gcs')` and hence cannot be concatenated with a string.
### Expected behavior
The file should be loaded without exception.
### Environment info
- `datasets` version: 2.14.1
- Platform: macOS-13.2.1-x86_64-i386-64bit
- Python version: 3.10.12
- Huggingface_hub version: 0.16.4
- PyArrow version: 12.0.1
- Pandas version: 2.0.3
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https://api.github.com/repos/huggingface/datasets/issues/4371 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4371/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4371/comments | https://api.github.com/repos/huggingface/datasets/issues/4371/events | https://github.com/huggingface/datasets/pull/4371 | 1,241,500,906 | PR_kwDODunzps44GzSZ | 4,371 | Add missing language tags for udhr dataset | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-05-19T09:34:10Z | 2022-06-08T12:03:24Z | 2022-05-20T09:43:10Z | MEMBER | null | 0 | {
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} | Related to #4362. | {
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https://api.github.com/repos/huggingface/datasets/issues/4343 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4343/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4343/comments | https://api.github.com/repos/huggingface/datasets/issues/4343/events | https://github.com/huggingface/datasets/issues/4343 | 1,234,864,168 | I_kwDODunzps5Jmogo | 4,343 | Metrics documentation is not accessible in the datasets doc UI | {
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"Hey @fxmarty :) Yes we are working on showing the docs of all the metrics on the Hugging face website. If you want to follow the advancements you can check the [evaluate](https://github.com/huggingface/evaluate) repository cc @lvwerra @sashavor "
] | 2022-05-13T07:46:30Z | 2022-06-03T08:50:25Z | 2022-06-03T08:50:25Z | CONTRIBUTOR | null | null | null | **Is your feature request related to a problem? Please describe.**
Search for a metric name like "seqeval" yields no results on https://huggingface.co/docs/datasets/master/en/index . One needs to go look in `datasets/metrics/README.md` to find the doc. Even in the `README.md`, it can be hard to understand what the metric expects as an input, for example for `squad` there is a [key `id`](https://github.com/huggingface/datasets/blob/1a4c185663a6958f48ec69624473fdc154a36a9d/metrics/squad/squad.py#L42) documented only in the function doc but not in the `README.md`, and one needs to go look into the code to understand what the metric expects.
**Describe the solution you'd like**
Have the documentation for metrics appear as well in the doc UI, e.g. this https://github.com/huggingface/datasets/blob/1a4c185663a6958f48ec69624473fdc154a36a9d/metrics/squad/squad.py#L21-L63
I know there are plans to migrate metrics to the evaluate library, but just pointing this out.
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https://api.github.com/repos/huggingface/datasets/issues/2737 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2737/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2737/comments | https://api.github.com/repos/huggingface/datasets/issues/2737/events | https://github.com/huggingface/datasets/issues/2737 | 957,124,881 | MDU6SXNzdWU5NTcxMjQ4ODE= | 2,737 | SacreBLEU update | {
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"Hi @devrimcavusoglu, \r\nI tried your code with latest version of `datasets`and `sacrebleu==1.5.1` and it's running fine after changing one small thing:\r\n```\r\nsacrebleu = datasets.load_metric('sacrebleu')\r\npredictions = [\"It is a guide to action which ensures that the military always obeys the commands of t... | 2021-07-30T23:53:08Z | 2021-09-22T10:47:41Z | 2021-08-03T04:23:37Z | NONE | null | null | null | With the latest release of [sacrebleu](https://github.com/mjpost/sacrebleu), `datasets.metrics.sacrebleu` is broken, and getting error.
AttributeError: module 'sacrebleu' has no attribute 'DEFAULT_TOKENIZER'
this happens since in new version of sacrebleu there is no `DEFAULT_TOKENIZER`, but sacrebleu.py tries to import it anyways. This can be fixed currently with fixing `sacrebleu==1.5.0`
## Steps to reproduce the bug
```python
sacrebleu= datasets.load_metric('sacrebleu')
predictions = ["It is a guide to action which ensures that the military always obeys the commands of the party"]
references = ["It is a guide to action that ensures that the military will forever heed Party commands"]
results = sacrebleu.compute(predictions=predictions, references=references)
print(results)
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.11.0
- Platform: Windows-10-10.0.19041-SP0
- Python version: Python 3.8.0
- PyArrow version: 5.0.0
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"OK! Thank you for the review - I will follow up with a separate PR for the comments here (https://github.com/huggingface/datasets/pull/1900#discussion_r578319725)!"
] | 2021-02-17T20:26:04Z | 2021-02-19T18:27:11Z | 2021-02-19T18:27:11Z | CONTRIBUTOR | null | 0 | {
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} | Should resolve https://github.com/huggingface/datasets/issues/1895
The main part of this PR adds additional parsing in `string_to_arrow` to convert the timestamp dtypes that result from `str(pa_type)` back into the pa.DataType TimestampType.
While adding unit-testing, I noticed that support for the double/float types also don't invert correctly, so I added them, which I believe would hypothetically make this section of `Value` redundant:
```
def __post_init__(self):
if self.dtype == "double": # fix inferred type
self.dtype = "float64"
if self.dtype == "float": # fix inferred type
self.dtype = "float32"
```
However, since I think Value.dtype is part of the public interface, removing that would result in a backward-incompatible change, so I didn't muck with that.
The rest of the PR consists of docstrings that I added while developing locally so I could keep track of which functions were supposed to be inverses of each other, and thought I'd include them initially in case you want to keep them around, but I'm happy to delete or remove any of them at your request! | {
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"Requested changes made and new PR submitted here: https://github.com/huggingface/datasets/pull/1580 "
] | 2020-12-13T04:38:43Z | 2020-12-15T19:52:52Z | 2020-12-15T19:52:25Z | CONTRIBUTOR | null | 0 | {
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"LGTM now, thank you =)"
] | 2021-05-21T10:16:57Z | 2021-05-21T15:49:09Z | 2021-05-21T15:49:06Z | MEMBER | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/5409 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5409/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5409/comments | https://api.github.com/repos/huggingface/datasets/issues/5409/events | https://github.com/huggingface/datasets/pull/5409 | 1,520,374,219 | PR_kwDODunzps5Gs3nL | 5,409 | Fix deprecation warning when use_auth_token passed to download_and_prepare | {
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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... | 2023-01-05T09:10:58Z | 2023-01-06T11:06:16Z | 2023-01-06T10:59:13Z | MEMBER | null | 0 | {
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} | The `DatasetBuilder.download_and_prepare` argument `use_auth_token` was deprecated in:
- #5302
However, `use_auth_token` is still passed to `download_and_prepare` in our built-in `io` readers (csv, json, parquet,...).
This PR fixes it, so that no deprecation warning is raised.
Fix #5407. | {
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https://api.github.com/repos/huggingface/datasets/issues/4649 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4649/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4649/comments | https://api.github.com/repos/huggingface/datasets/issues/4649/events | https://github.com/huggingface/datasets/issues/4649 | 1,296,673,712 | I_kwDODunzps5NSauw | 4,649 | Add PAQ dataset | {
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"uploaded dataset [here](https://huggingface.co/datasets/embedding-data/PAQ_pairs)"
] | 2022-07-07T01:29:42Z | 2022-07-14T02:06:27Z | 2022-07-14T02:06:27Z | NONE | null | null | null | ## Adding a Dataset
- **Name:** *PAQ*
- **Description:** *This repository contains code and models to support the research paper PAQ: 65 Million Probably-Asked Questions and What You Can Do With Them*
- **Paper:** *https://arxiv.org/abs/2102.07033*
- **Data:** *https://huggingface.co/datasets/sentence-transformers/embedding-training-data/resolve/main/PAQ_pairs.jsonl.gz*
- **Motivation:** *Dataset for training and evaluating models of conversational response*
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https://api.github.com/repos/huggingface/datasets/issues/1330 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1330/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1330/comments | https://api.github.com/repos/huggingface/datasets/issues/1330/events | https://github.com/huggingface/datasets/pull/1330 | 759,657,324 | MDExOlB1bGxSZXF1ZXN0NTM0NjI0MzMx | 1,330 | added un_ga dataset | {
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"Looks like this PR includes changes about many other files than the ones for un_ga\r\n\r\nCan you create another branch an another PR please ?",
"@lhoestq, Thank you for suggestions. I have made the changes and raised the new PR https://github.com/huggingface/datasets/pull/1569. "
] | 2020-12-08T17:58:38Z | 2020-12-14T17:52:34Z | 2020-12-14T17:52:34Z | CONTRIBUTOR | null | 0 | {
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} | Hi :hugs:, This is a PR for [United nations general assembly resolutions: A six-language parallel corpus](http://opus.nlpl.eu/UN.php) dataset | {
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https://api.github.com/repos/huggingface/datasets/issues/3202 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3202/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3202/comments | https://api.github.com/repos/huggingface/datasets/issues/3202/events | https://github.com/huggingface/datasets/issues/3202 | 1,043,213,660 | I_kwDODunzps4-Li1c | 3,202 | Add mIoU metric | {
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"Resolved via https://github.com/huggingface/datasets/pull/3745."
] | 2021-11-03T08:42:32Z | 2022-06-01T17:39:05Z | 2022-06-01T17:39:04Z | CONTRIBUTOR | null | null | null | **Is your feature request related to a problem? Please describe.**
Recently, some semantic segmentation models were added to HuggingFace Transformers, including [SegFormer](https://huggingface.co/transformers/model_doc/segformer.html) and [BEiT](https://huggingface.co/transformers/model_doc/beit.html).
Semantic segmentation (which is the task of labeling every pixel of an image with a corresponding class) is typically evaluated using the Mean Intersection and Union (mIoU). Together with the upcoming Image Feature, adding this metric could be very handy when creating example scripts to fine-tune any Transformer-based model on a semantic segmentation dataset.
An implementation can be found [here](https://github.com/open-mmlab/mmsegmentation/blob/504965184c3e6bc9ec43af54237129ef21981a5f/mmseg/core/evaluation/metrics.py#L132) for instance.
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https://api.github.com/repos/huggingface/datasets/issues/1781 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1781/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1781/comments | https://api.github.com/repos/huggingface/datasets/issues/1781/events | https://github.com/huggingface/datasets/issues/1781 | 793,914,556 | MDU6SXNzdWU3OTM5MTQ1NTY= | 1,781 | AttributeError: module 'pyarrow' has no attribute 'PyExtensionType' during import | {
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"Hi ! I'm not able to reproduce the issue. Can you try restarting your runtime ?\r\n\r\nThe PyExtensionType is available in pyarrow starting 0.17.1 iirc. If restarting your runtime doesn't fix this, can you try updating pyarrow ?\r\n```\r\npip install pyarrow --upgrade\r\n```",
"We should bump up the version test... | 2021-01-26T04:18:35Z | 2022-10-05T12:37:06Z | 2022-10-05T12:37:06Z | NONE | null | null | null | I'm using Colab. And suddenly this morning, there is this error. Have a look below!
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https://api.github.com/repos/huggingface/datasets/issues/5478 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5478/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5478/comments | https://api.github.com/repos/huggingface/datasets/issues/5478/events | https://github.com/huggingface/datasets/pull/5478 | 1,560,357,583 | PR_kwDODunzps5ItXQG | 5,478 | Tip for recomputing metadata | {
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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... | 2023-01-27T20:01:22Z | 2023-01-30T19:22:21Z | 2023-01-30T19:15:26Z | MEMBER | null | 0 | {
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} | From this [feedback](https://discuss.huggingface.co/t/nonmatchingsplitssizeserror/30033) on the forum, thought I'd include a tip for recomputing the metadata numbers if it is your own dataset. | {
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https://api.github.com/repos/huggingface/datasets/issues/5742 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5742/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5742/comments | https://api.github.com/repos/huggingface/datasets/issues/5742/events | https://github.com/huggingface/datasets/pull/5742 | 1,666,209,738 | PR_kwDODunzps5OOH-W | 5,742 | Warning specifying future change in to_tf_dataset behaviour | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2023-04-13T11:10:00Z | 2023-04-21T13:18:14Z | 2023-04-21T13:11:09Z | CONTRIBUTOR | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/2905 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2905/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2905/comments | https://api.github.com/repos/huggingface/datasets/issues/2905/events | https://github.com/huggingface/datasets/pull/2905 | 995,843,964 | PR_kwDODunzps4ruL5X | 2,905 | Update BibTeX entry | {
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https://api.github.com/repos/huggingface/datasets/issues/5964 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5964/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5964/comments | https://api.github.com/repos/huggingface/datasets/issues/5964/events | https://github.com/huggingface/datasets/pull/5964 | 1,763,513,574 | PR_kwDODunzps5TVweZ | 5,964 | Always return list in `list_datasets` | {
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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... | 2023-06-19T13:07:08Z | 2023-06-19T17:29:37Z | 2023-06-19T17:22:41Z | CONTRIBUTOR | null | 0 | {
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} | Fix #5925
Plus, deprecate `list_datasets`/`inspect_dataset` in favor of `huggingface_hub.list_datasets`/"git clone workflow" (downloads data files) | {
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https://api.github.com/repos/huggingface/datasets/issues/6207 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6207/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6207/comments | https://api.github.com/repos/huggingface/datasets/issues/6207/events | https://github.com/huggingface/datasets/issues/6207 | 1,879,555,234 | I_kwDODunzps5wB7yi | 6,207 | No-script datasets with ZIP files do not load | {
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"following_url": "https://api.github.com/users/albertvillanova/following{/o... | null | [] | 2023-09-04T05:50:27Z | 2023-09-04T09:13:33Z | 2023-09-04T09:13:33Z | MEMBER | null | null | null | While investigating an issue on a Hub dataset, I have discovered the no-script datasets containing ZIP files do not load.
For example, that no-script dataset containing ZIP files, raises NonMatchingSplitsSizesError:
```python
In [2]: ds = load_dataset("sidovic/LearningQ-qg")
NonMatchingSplitsSizesError: [
{
'expected': SplitInfo(name='train', num_bytes=0, num_examples=188660, shard_lengths=None, dataset_name=None),
'recorded': SplitInfo(name='train', num_bytes=0, num_examples=0, shard_lengths=None, dataset_name='learning_q-qg')
}, {
'expected': SplitInfo(name='validation', num_bytes=0, num_examples=20630, shard_lengths=None, dataset_name=None),
'recorded': SplitInfo(name='validation', num_bytes=0, num_examples=0, shard_lengths=None, dataset_name='learning_q-qg')
}, {
'expected': SplitInfo(name='test', num_bytes=0, num_examples=18227, shard_lengths=None, dataset_name=None),
'recorded': SplitInfo(name='test', num_bytes=0, num_examples=0, shard_lengths=None, dataset_name='learning_q-qg')
}
]
```
As another example, a no-script dataset containing just a (CSV)-ZIP file, raises a DatasetGenerationError:
```
> num_examples, num_bytes = writer.finalize()
src/datasets/builder.py:1949:
> raise SchemaInferenceError("Please pass `features` or at least one example when writing data")
E datasets.arrow_writer.SchemaInferenceError: Please pass `features` or at least one example when writing data
src/datasets/arrow_writer.py:598: SchemaInferenceError
The above exception was the direct cause of the following exception:
src/datasets/load.py:2143: in load_dataset
builder_instance.download_and_prepare(
src/datasets/builder.py:954: in download_and_prepare
self._download_and_prepare(
src/datasets/builder.py:1049: in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
src/datasets/builder.py:1813: in _prepare_split
for job_id, done, content in self._prepare_split_single(
> raise DatasetGenerationError("An error occurred while generating the dataset") from e
E datasets.builder.DatasetGenerationError: An error occurred while generating the dataset
src/datasets/builder.py:1958: DatasetGenerationError
```
After investigating, I think this bug was introduced in this PR:
- #5972
Related to:
- https://huggingface.co/datasets/sidovic/LearningQ-qg/discussions/1
CC: @lhoestq | {
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https://api.github.com/repos/huggingface/datasets/issues/5788 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5788/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5788/comments | https://api.github.com/repos/huggingface/datasets/issues/5788/events | https://github.com/huggingface/datasets/pull/5788 | 1,681,136,256 | PR_kwDODunzps5O_v4B | 5,788 | Prepare tests for hfh 0.14 | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2023-04-24T12:13:03Z | 2023-04-25T14:32:56Z | 2023-04-25T14:25:30Z | CONTRIBUTOR | null | 0 | {
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} | Related to the coming release of `huggingface_hub==0.14.0`. It will break some internal tests. The PR fixes these tests. Let's double-check the CI but I expect the fixed tests to be running fine with both `hfh<=0.13.4` and `hfh==0.14`. Worth case scenario, existing PRs will have to be rebased once this fix is merged.
See related [discussion](https://huggingface.slack.com/archives/C02V5EA0A95/p1682337463368609?thread_ts=1681994202.635609&cid=C02V5EA0A95) (private slack).
cc @lhoestq | {
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https://api.github.com/repos/huggingface/datasets/issues/4249 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4249/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4249/comments | https://api.github.com/repos/huggingface/datasets/issues/4249/events | https://github.com/huggingface/datasets/pull/4249 | 1,218,524,424 | PR_kwDODunzps42742y | 4,249 | Support streaming XGLUE dataset | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-04-28T10:27:23Z | 2022-05-06T08:38:21Z | 2022-04-28T16:08:03Z | MEMBER | null | 0 | {
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} | Support streaming XGLUE dataset.
Fix #4247.
CC: @severo | {
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https://api.github.com/repos/huggingface/datasets/issues/5873 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5873/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5873/comments | https://api.github.com/repos/huggingface/datasets/issues/5873/events | https://github.com/huggingface/datasets/issues/5873 | 1,713,269,724 | I_kwDODunzps5mHmvc | 5,873 | Allow setting the environment variable for the lock file path | {
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] | open | false | null | [] | null | [] | 2023-05-17T07:10:02Z | 2023-05-17T07:11:05Z | null | NONE | null | null | null | ### Feature request
Add an environment variable to replace the default lock file path.
### Motivation
Usually, dataset path is a read-only path while the lock file needs to be modified each time. It would be convenient if the path can be reset individually.
### Your contribution
```/src/datasets/utils/filelock.py
class UnixFileLock(BaseFileLock):
def __init__(self, lock_file, timeout=-1, max_filename_length=None):
#-------------------
if os.getenv('DS_TMP_PATH'):
file_name = str(lock_file).split('/')[-1]
dataset_tmp_path = os.getenv('DS_TMP_PATH')
lock_file = os.path.join(dataset_tmp_path, file_name)
#-------------------
max_filename_length = os.statvfs(os.path.dirname(lock_file)).f_namemax
super().__init__(lock_file, timeout=timeout, max_filename_length=max_filename_length)
```
A simple demo is as upper. Thanks. | {
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"Problem with the code snippet! Using global vars and functions was not a good idea with iterable datasets!\r\n\r\nIf we update to:\r\n```python\r\nfrom datasets import load_dataset\r\n\r\noriginal_dataset = load_dataset(\"librispeech_asr\", \"clean\", split=\"validation\", streaming=True)\r\n\r\n# now add a new co... | 2023-04-14T17:32:31Z | 2023-04-14T17:45:52Z | 2023-04-14T17:36:37Z | CONTRIBUTOR | null | null | null | ### Describe the bug
If we add a new column to our iterable dataset using the hack described in #5752, when we then interleave datasets the new column is pinned to one value.
### Steps to reproduce the bug
What we're going to do here is:
1. Load an iterable dataset in streaming mode (`original_dataset`)
2. Add a new column to this dataset using the hack in #5752 (`modified_dataset_1`)
3. Create another new dataset by adding a column with the same key but different values (`modified_dataset_2`)
4. Interleave our new datasets (`modified_dataset_1` + `modified_dataset_2`)
5. Check the value of our newly added column (`new_column`)
```python
from datasets import load_dataset
# load an iterable dataset
original_dataset = load_dataset("librispeech_asr", "clean", split="validation", streaming=True)
# now add a new column to our streaming dataset using our hack from 5752
name = "new_column"
column = [f"new dataset 1, row {i}" for i in range(50)]
new_features = original_dataset.features.copy()
new_features[name] = new_features["file"] # I know that "file" has the right column type to match our new feature
def add_column_fn(example, idx):
if name in example:
raise ValueError(f"Error when adding {name}: column {name} is already in the dataset.")
return {name: column[idx]}
modified_dataset_1 = original_dataset.map(add_column_fn, with_indices=True, features=new_features)
# now create a second modified dataset using the same trick
column = [f"new dataset 2, row {i}" for i in range(50)]
def add_column_fn(example, idx):
if name in example:
raise ValueError(f"Error when adding {name}: column {name} is already in the dataset.")
return {name: column[idx]}
modified_dataset_2 = original_dataset.map(add_column_fn, with_indices=True, features=new_features)
# interleave these datasets
interleaved_dataset = interleave_datasets([modified_dataset_1, modified_dataset_2])
# now check what the value of the added column is
for i, sample in enumerate(interleaved_dataset):
print(sample["new_column"])
if i == 10:
break
```
**Print Output:**
```
new dataset 2, row 0
new dataset 2, row 0
new dataset 2, row 1
new dataset 2, row 1
new dataset 2, row 2
new dataset 2, row 2
new dataset 2, row 3
new dataset 2, row 3
new dataset 2, row 4
new dataset 2, row 4
new dataset 2, row 5
```
We see that we only get outputs from our second dataset.
### Expected behavior
We should interleave between dataset 1 and 2 and increase in row value:
```
new dataset 1, row 0
new dataset 2, row 0
new dataset 1, row 1
new dataset 2, row 1
new dataset 1, row 2
new dataset 2, row 2
...
```
### Environment info
- datasets version: 2.10.2.dev0
- Platform: Linux-4.19.0-23-cloud-amd64-x86_64-with-glibc2.28
- Python version: 3.9.16
- Huggingface_hub version: 0.13.3
- PyArrow version: 10.0.1
- Pandas version: 1.5.2 | {
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https://api.github.com/repos/huggingface/datasets/issues/4991 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4991/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4991/comments | https://api.github.com/repos/huggingface/datasets/issues/4991/events | https://github.com/huggingface/datasets/pull/4991 | 1,378,898,752 | PR_kwDODunzps4_P5hI | 4,991 | Fix missing tags in dataset cards | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-09-20T06:42:07Z | 2022-09-22T12:25:32Z | 2022-09-20T07:37:30Z | MEMBER | null | 0 | {
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} | Fix missing tags in dataset cards:
- aeslc
- empathetic_dialogues
- event2Mind
- gap
- iwslt2017
- newsgroup
- qa4mre
- scicite
This PR partially fixes the missing tags in dataset cards. Subsequent PRs will follow to complete this task.
Related to:
- #4833
- #4891
- #4896
- #4908
- #4921
- #4931
- #4979 | {
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"Hi, thanks for noticing this! We can't just remove the cache control as this allows us to control where the arrow files generated by the ops are written (cached on disk if enabled or a temporary directory if disabled). The right way to address this inconsistency would be by having `load_from_cache_file=None` by de... | 2023-02-08T16:40:44Z | 2023-02-14T14:26:44Z | 2023-02-14T14:26:44Z | CONTRIBUTOR | null | null | null | ### Feature request
1. Replace the `load_from_cache_file` default value to `True`.
2. Remove or alter checks from `is_caching_enabled` logic.
### Motivation
I stumbled over an inconsistency in the `Dataset.map` interface. The documentation (and source) states for the parameter `load_from_cache_file`:
```
load_from_cache_file (`bool`, defaults to `True` if caching is enabled):
If a cache file storing the current computation from `function`
can be identified, use it instead of recomputing.
```
1. `load_from_cache_file` default value is `None`, while being annotated as `bool`
2. It is inconsistent with other method signatures like `filter`, that have the default value `True`
3. The logic is inconsistent, as the `map` method checks if caching is enabled through `is_caching_enabled`. This logic is not used for other similar methods.
### Your contribution
I am not fully aware of the logic behind caching checks. If this is just a inconsistency that historically grew, I would suggest to remove the `is_caching_enabled` logic as the "default" logic. Maybe someone can give insights, if environment variables have a higher priority than local variables or vice versa.
If this is clarified, I could adjust the source according to the "Feature request" section of this issue. | {
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https://api.github.com/repos/huggingface/datasets/issues/2483 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2483/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2483/comments | https://api.github.com/repos/huggingface/datasets/issues/2483/events | https://github.com/huggingface/datasets/pull/2483 | 918,871,712 | MDExOlB1bGxSZXF1ZXN0NjY4MjU1Mjg1 | 2,483 | Use gc.collect only when needed to avoid slow downs | {
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"I continue thinking that the origin of the issue has to do with tqdm (and not with Arrow): this issue only arises for version 4.50.0 (and later) of tqdm, not for previous versions of tqdm.\r\n\r\nMy guess is that tqdm made a change from version 4.50.0 that does not properly release the iterable. ",
"FR"
] | 2021-06-11T15:09:30Z | 2021-06-18T19:25:06Z | 2021-06-11T15:31:36Z | MEMBER | null | 0 | {
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} | In https://github.com/huggingface/datasets/commit/42320a110d9d072703814e1f630a0d90d626a1e6 we added a call to gc.collect to resolve some issues on windows (see https://github.com/huggingface/datasets/pull/2482)
However calling gc.collect too often causes significant slow downs (the CI run time doubled).
So I just moved the gc.collect call to the exact place where it's actually needed: when post-processing a dataset | {
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```python
gen_kwargs = {
"files": [os.path.join(data_dir, filename) for filename in all_files],
"metadata_files": [all_metadata[filename] for filename in all_files],
}
```
It happened for Multilingual Spoken Words for example in #3666
However currently **the two lists are shuffled independently** when shuffling the shards in streaming mode. This leads to `_generate_examples` not having the right metadata for each file.
To prevent this issue I suggest that we always shuffle lists of the same length the exact same way to avoid such a big but silent issue.
cc @polinaeterna | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Not sure how to generate dummy data.\r\n\r\nThe downloaded file structure is \r\n\r\n- document file paths\r\n - (a json file containing all documents info, document images folder)\r\n - (a json file containing all documents in... | 2022-03-20T09:24:54Z | 2022-10-03T09:38:16Z | 2022-10-03T09:36:22Z | CONTRIBUTOR | null | 0 | {
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} | This PR adds XFUN dataset.
Home page and repository: https://github.com/doc-analysis/XFUND
Source code: https://github.com/microsoft/unilm/blob/master/layoutlmft/layoutlmft/data/datasets/xfun.py | {
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"Hi! This behavior stems from these lines:\r\n\r\nhttps://github.com/huggingface/datasets/blob/b065547654efa0ec633cf373ac1512884c68b2e1/src/datasets/formatting/np_formatter.py#L45-L46\r\n\r\nI agree we should preserve the original type whenever possible and downcast explicitly with a warning.\r\n\r\n@lhoestq Do you... | 2023-02-09T14:18:00Z | 2023-02-14T15:38:54Z | null | NONE | null | null | null | ### Describe the bug
When I create a dataset with a `float64` feature, then apply numpy formatting the returned numpy arrays are silently downcasted to `float32`.
### Steps to reproduce the bug
```python
import datasets
dataset = datasets.Dataset.from_dict({'a': [1.0, 2.0, 3.0]}).with_format("numpy")
print("feature dtype:", dataset.features['a'].dtype)
print("array dtype:", dataset['a'].dtype)
```
output:
```
feature dtype: float64
array dtype: float32
```
### Expected behavior
```
feature dtype: float64
array dtype: float64
```
### Environment info
- `datasets` version: 2.8.0
- Platform: Linux-5.4.0-135-generic-x86_64-with-glibc2.29
- Python version: 3.8.10
- PyArrow version: 10.0.1
- Pandas version: 1.4.4
### Suggested Fix
Changing [the `_tensorize` function of the numpy formatter](https://github.com/huggingface/datasets/blob/b065547654efa0ec633cf373ac1512884c68b2e1/src/datasets/formatting/np_formatter.py#L32) to
```python
def _tensorize(self, value):
if isinstance(value, (str, bytes, type(None))):
return value
elif isinstance(value, (np.character, np.ndarray)) and np.issubdtype(value.dtype, np.character):
return value
elif isinstance(value, np.number):
return value
return np.asarray(value, **self.np_array_kwargs)
```
fixes this particular issue for me. Not sure if this would break other tests. This should also avoid unnecessary copying of the array.
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https://api.github.com/repos/huggingface/datasets/issues/2623 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2623/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2623/comments | https://api.github.com/repos/huggingface/datasets/issues/2623/events | https://github.com/huggingface/datasets/pull/2623 | 941,265,342 | MDExOlB1bGxSZXF1ZXN0Njg3MTk0MjM3 | 2,623 | [Metrics] added wiki_split metrics | {
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"Looks all good to me thanks :)\r\nJust did some minor corrections in the docstring"
] | 2021-07-10T14:51:50Z | 2021-07-14T14:28:13Z | 2021-07-12T22:34:31Z | CONTRIBUTOR | null | 0 | {
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} | Fixes: #2606
This pull request adds combine metrics for the wikisplit or English sentence split task
Reviewer: @patrickvonplaten | {
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"Sorry, I'm late to check! I'll send it to you soon!",
"Thanks for your contribution, @sooftware. 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 c... | 2022-01-12T15:33:08Z | 2022-10-01T06:43:16Z | 2022-10-01T06:43:16Z | NONE | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/4440 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4440/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4440/comments | https://api.github.com/repos/huggingface/datasets/issues/4440/events | https://github.com/huggingface/datasets/pull/4440 | 1,258,494,469 | PR_kwDODunzps44_io_ | 4,440 | Update docs around audio and vision | {
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"> Let me know what you think, especially if we should include some code samples for training a model in the audio/vision sections. I left this out since we already showed it in the NLP section. I want to keep the focus on using Datas... | 2022-06-02T17:42:03Z | 2022-06-23T16:33:19Z | 2022-06-23T16:23:02Z | MEMBER | null | 0 | {
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} | As part of the strategy to center the docs around the different modalities, this PR updates the quickstart to include audio and vision examples. This improves the developer experience by making audio and vision content more discoverable, enabling users working in these modalities to also quickly get started without digging too deeply into the docs.
Other changes include:
- Moved the installation guide to the Get Started section because it should be part of a user's onboarding to the library before exploring tutorials or how-to's.
- Updated the native TF code at creating a `tf.data.Dataset` because it was throwing an error. The `to_tensor()` bit was redundant and removing it fixed the error (please double-check me here!).
- Added some UI components to the quickstart so it's easier for users to navigate directly to the relevant section with context about what to expect.
- Reverted to the code tabs for content that don't have any framework-specific text. I think this saves space compared to the code blocks. We'll still use the code blocks if the `torch` text is different from the `tf` text.
Let me know what you think, especially if we should include some code samples for training a model in the audio/vision sections. I left this out since we already showed it in the NLP section. I want to keep the focus on using Datasets to load and process a dataset, and not so much the training part. Maybe we can add links to the Transformers docs instead? | {
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https://api.github.com/repos/huggingface/datasets/issues/1722 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1722/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1722/comments | https://api.github.com/repos/huggingface/datasets/issues/1722/events | https://github.com/huggingface/datasets/pull/1722 | 783,921,679 | MDExOlB1bGxSZXF1ZXN0NTUzMTk3MTg4 | 1,722 | Added unfiltered versions of the Wiki-Auto training data for the GEM simplification task. | {
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"The current version of Wiki-Auto dataset contains a filtered version of the aligned dataset. The commit adds unfiltered versions of the data that can be useful the GEM task participants."
] | 2021-01-12T05:26:04Z | 2021-01-12T18:14:53Z | 2021-01-12T17:35:57Z | CONTRIBUTOR | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/3654 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3654/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3654/comments | https://api.github.com/repos/huggingface/datasets/issues/3654/events | https://github.com/huggingface/datasets/pull/3654 | 1,119,717,475 | PR_kwDODunzps4x2kiX | 3,654 | Better TQDM output | {
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"@lhoestq I've created a notebook for you to see the difference: https://colab.research.google.com/drive/1by3EqnoKvC2p-yKW4lPDGOFOZHyGVyeQ?usp=sharing.\r\n\r\nFeel free to suggest better descriptions for the progress bars. \r\n\r\nIf everything looks good, think we can merge."
] | 2022-01-31T17:22:43Z | 2022-02-03T15:55:34Z | 2022-02-03T15:55:33Z | CONTRIBUTOR | null | 0 | {
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} | This PR does the following:
* if `dataset_infos.json` exists for a dataset, uses `num_examples` to print the total number of examples that needs to be generated (in `builder.py`)
* fixes `tqdm` + multiprocessing in Jupyter Notebook/Colab (the issue stems from this commit in the `tqdm` repo: https://github.com/tqdm/tqdm/commit/f7722edecc3010cb35cc1c923ac4850a76336f82)
* adds the missing `drop_last_batch` and `with_ranks` params to `DatasetDict.map`
* correctly computes the number of iterations in `map` and the CSV/JSON loader when `batched=True` to fix `tqdm` progress bars
* removes the `bool(logging.get_verbosity() == logging.NOTSET)` (or simplifies `bool(logging.get_verbosity() == logging.NOTSET) or not utils.is_progress_bar_enabled()` to `not utils.is_progress_bar_enabled()`) condition and uses `utils.is_progress_bar_enabled` to check if `tqdm` output is enabled (this comment from @stas00 explains why the `bool(logging.get_verbosity() == logging.NOTSET)` check is problematic: https://github.com/huggingface/transformers/issues/14889#issue-1087318463)
Fix #2630 | {
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"cc @abhishekkrthakur @SBrandeis "
] | 2022-11-15T02:47:52Z | 2022-11-15T17:59:23Z | null | NONE | null | null | null | I went to autotrain and under image classification arrived where it was time to prepare my dataset. Screenshot below
I chose the method 2 option. I have a csv file with two columns. ~23,000 files.
I uploaded this and chose the image_relpath, and target columns.
The image uploader said that I could only upload 10,000 singular images at a time so the 2nd option was to zip the images up and upload a zip archive which I did.
That all uploaded.
Now I have the message below. It appears the zip archive does just uncompress on the Hugging Face end?
What am I missing here?
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"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_a... | 2023-09-11T13:29:19Z | 2023-09-13T18:21:28Z | 2023-09-13T18:12:09Z | CONTRIBUTOR | null | 0 | {
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Instead of reusing `_check_valid_index_key` from `datasets.formatting`, I defined a new function to provide a more meaningful error message.
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https://api.github.com/repos/huggingface/datasets/issues/3526 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3526/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3526/comments | https://api.github.com/repos/huggingface/datasets/issues/3526/events | https://github.com/huggingface/datasets/pull/3526 | 1,093,833,446 | PR_kwDODunzps4wiMaQ | 3,526 | Update license to bookcorpus dataset card | {
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"The smashwords ToS apply for this dataset, we did the same for https://github.com/huggingface/datasets/pull/3525",
"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-01-04T23:25:23Z | 2022-09-30T10:23:38Z | 2022-09-30T10:21:20Z | CONTRIBUTOR | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/1627 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1627/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1627/comments | https://api.github.com/repos/huggingface/datasets/issues/1627/events | https://github.com/huggingface/datasets/issues/1627 | 773,960,255 | MDU6SXNzdWU3NzM5NjAyNTU= | 1,627 | `Dataset.map` disable progress bar | {
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"Progress bar can be disabled like this:\r\n```python\r\nfrom datasets.utils.logging import set_verbosity_error\r\nset_verbosity_error()\r\n```\r\n\r\nThere is this line in `Dataset.map`:\r\n```python\r\nnot_verbose = bool(logger.getEffectiveLevel() > WARNING)\r\n```\r\n\r\nSo any logging level higher than `WARNING... | 2020-12-23T17:53:42Z | 2023-02-08T02:37:47Z | 2020-12-26T19:57:17Z | NONE | null | null | null | I can't find anything to turn off the `tqdm` progress bars while running a preprocessing function using `Dataset.map`. I want to do akin to `disable_tqdm=True` in the case of `transformers`. Is there something like that? | {
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https://api.github.com/repos/huggingface/datasets/issues/4735 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4735/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4735/comments | https://api.github.com/repos/huggingface/datasets/issues/4735/events | https://github.com/huggingface/datasets/pull/4735 | 1,314,501,641 | PR_kwDODunzps477CuP | 4,735 | Pin rouge_score test dependency | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-07-22T07:18:21Z | 2022-07-22T07:58:14Z | 2022-07-22T07:45:18Z | MEMBER | null | 0 | {
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Fix #4734 | {
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https://api.github.com/repos/huggingface/datasets/issues/5651 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5651/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5651/comments | https://api.github.com/repos/huggingface/datasets/issues/5651/events | https://github.com/huggingface/datasets/issues/5651 | 1,631,967,509 | I_kwDODunzps5hRdkV | 5,651 | expanduser in save_to_disk | {
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"`save_to_disk` should indeed expand `~`. Marking it as a \"good first issue\".",
"#self-assign\r\n\r\nFile path to code: \r\n\r\nhttps://github.com/huggingface/datasets/blob/2.13.0/src/datasets/arrow_dataset.py#L1364\r\n\r\n@RmZeta2718 I created a pull request for this issue. ",
"Hello, \r\nIt says `save_to_di... | 2023-03-20T12:02:18Z | 2023-07-26T16:18:06Z | null | NONE | null | null | null | ### Describe the bug
save_to_disk() does not expand `~`
1. `dataset = load_datasets("any dataset")`
2. `dataset.save_to_disk("~/data")`
3. a folder named "~" created in current folder
4. FileNotFoundError is raised, because the expanded path does not exist (`/home/<user>/data`)
related issue https://github.com/huggingface/transformers/issues/10628
### Steps to reproduce the bug
As described above.
### Expected behavior
expanduser correctly
### Environment info
- datasets 2.10.1
- python 3.10 | {
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https://api.github.com/repos/huggingface/datasets/issues/4919 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4919/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4919/comments | https://api.github.com/repos/huggingface/datasets/issues/4919/events | https://github.com/huggingface/datasets/pull/4919 | 1,357,441,599 | PR_kwDODunzps4-IxDZ | 4,919 | feat: improve error message on Keys mismatch. closes #4917 | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"We are having an unrelated issue that makes several tests fail. We are working on that. Once fixed, you will be able to merge the main branch into this, so that you get the fix and the tests pass..."
] | 2022-08-31T14:41:36Z | 2022-09-05T08:46:01Z | 2022-09-05T08:43:33Z | CONTRIBUTOR | null | 0 | {
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} | Hi @lhoestq what do you think?
Let me give you a code sample:
```py
>>> import datasets
>>> foo = datasets.Dataset.from_dict({'foo':[0,1], 'bar':[2,3]})
>>> foo.save_to_disk('foo')
# edit foo/dataset_info.json e.g. rename the 'foo' feature to 'baz'
>>> datasets.load_from_disk('foo')
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-2-4863e606b330> in <module>
----> 1 datasets.load_from_disk('foo')
~/code/datasets/src/datasets/load.py in load_from_disk(dataset_path, fs, keep_in_memory)
1851 raise FileNotFoundError(f"Directory {dataset_path} not found")
1852 if fs.isfile(Path(dest_dataset_path, config.DATASET_INFO_FILENAME).as_posix()):
-> 1853 return Dataset.load_from_disk(dataset_path, fs, keep_in_memory=keep_in_memory)
1854 elif fs.isfile(Path(dest_dataset_path, config.DATASETDICT_JSON_FILENAME).as_posix()):
1855 return DatasetDict.load_from_disk(dataset_path, fs, keep_in_memory=keep_in_memory)
~/code/datasets/src/datasets/arrow_dataset.py in load_from_disk(dataset_path, fs, keep_in_memory)
1230 info=dataset_info,
1231 split=split,
-> 1232 fingerprint=state["_fingerprint"],
1233 )
1234
~/code/datasets/src/datasets/arrow_dataset.py in __init__(self, arrow_table, info, split, indices_table, fingerprint)
687 self.info.features = inferred_features
688 else: # make sure the nested columns are in the right order
--> 689 self.info.features = self.info.features.reorder_fields_as(inferred_features)
690
691 # Infer fingerprint if None
~/code/datasets/src/datasets/features/features.py in reorder_fields_as(self, other)
1771 return source
1772
-> 1773 return Features(recursive_reorder(self, other))
1774
1775 def flatten(self, max_depth=16) -> "Features":
~/code/datasets/src/datasets/features/features.py in recursive_reorder(source, target, stack)
1760 f"{source.keys()-target.keys()} are missing from dataset.arrow "
1761 f"and {target.keys()-source.keys()} are missing from dataset_info.json"+stack_position)
-> 1762 raise ValueError(message)
1763 return {key: recursive_reorder(source[key], target[key], stack + f".{key}") for key in target}
1764 elif isinstance(source, list):
ValueError: Keys mismatch: between {'baz': Value(dtype='int64', id=None), 'bar': Value(dtype='int64', id=None)} (dataset_info.json) and {'foo': Value(dtype='int64', id=None), 'bar': Value(dtype='int64', id=None)} (inferred from dataset.arrow).
{'baz'} are missing from dataset.arrow and {'foo'} are missing from dataset_info.json
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/4833 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4833/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4833/comments | https://api.github.com/repos/huggingface/datasets/issues/4833/events | https://github.com/huggingface/datasets/pull/4833 | 1,336,946,965 | PR_kwDODunzps49E_Nk | 4,833 | Fix missing tags in dataset cards | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-08-12T09:04:52Z | 2022-09-22T14:41:23Z | 2022-08-12T09:45:55Z | MEMBER | null | 0 | {
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} | Fix missing tags in dataset cards:
- boolq
- break_data
- definite_pronoun_resolution
- emo
- kor_nli
- pg19
- quartz
- sciq
- squad_es
- wmt14
- wmt15
- wmt16
- wmt17
- wmt18
- wmt19
- wmt_t2t
This PR partially fixes the missing tags in dataset cards. Subsequent PRs will follow to complete this task. | {
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https://api.github.com/repos/huggingface/datasets/issues/5516 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5516/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5516/comments | https://api.github.com/repos/huggingface/datasets/issues/5516/events | https://github.com/huggingface/datasets/pull/5516 | 1,577,661,640 | PR_kwDODunzps5JmzPQ | 5,516 | Reload features from Parquet metadata | {
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"Thanks a lot for your help @lhoestq. I've simplified what turned out to be a simple fix and added the unit test.\r\n\r\nDoes this look ready to be merged or is there anything I'm still missing?",
"Cool ! I think you just need to remove the unused import in `io/parquet.py`\r\n```\r\nsrc/datasets/io/parquet.py:4:1... | 2023-02-09T10:52:15Z | 2023-02-12T16:00:00Z | 2023-02-12T15:57:01Z | CONTRIBUTOR | null | 0 | {
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} | Resolves #5482.
Attaches feature metadata to parquet files serialised using `Dataset.to_parquet`.
This allows retrieving data with "rich" feature types (e.g., `datasets.features.image.Image` or `datasets.features.audio.Audio`) from parquet files without cumbersome casting (for an example, see #5482).
@lhoestq It seems that it is sufficient to attach metadata to the schema prior to serialising and features are loaded back with correct types afterwards automatically.
I used the following script to test the implementation:
```python
from pathlib import Path
import datasets
dataset_name = "Maysee/tiny-imagenet"
ds = datasets.load_dataset(dataset_name, split=datasets.Split.TRAIN)
output_directory_path = Path(__file__).parent.joinpath("example_test_outputs", dataset_name.replace("/", "_"))
output_directory_path.mkdir(exist_ok=True, parents=True)
output_filepath = output_directory_path.joinpath("ds.parquet")
ds.to_parquet(str(output_filepath))
reloaded_ds = datasets.load_dataset(str(output_directory_path), split=datasets.Split.TRAIN)
assert ds.features == reloaded_ds.features
```
Prior to the change in this PR this script raises an `AssertionError` and the `Image` features lose their type after serialisation. After the change in this PR, the assertion does not raise an error and manual inspection of the features shows type `Image` for the respective columns of `reloaded_ds `.
Some open questions:
* How/where can I best add new unit tests for this implementation?
* What dataset would I best use in the tests? I chose `Maysee/tiny-imagenet` mainly because it is small and contains an ?Image` feature that can be used to test, but I'd be happy for suggestions on a suitable data source to use.
* Currently I'm calling `datasets.arrow_writer.ArrowWriter._build_metadata` as I need the same logic. However, I'm not happy with the coupling between `datasets.io.parquet` and `datasets.arrow_writer` it leaves me with. Suggest to factor this common logic out into a helper function and reuse it from both of these. Do you agree and if yes, could you please guide me where I would best place this function?
Many thanks in advance and kind regards,
MFreidank
| {
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https://api.github.com/repos/huggingface/datasets/issues/2554 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2554/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2554/comments | https://api.github.com/repos/huggingface/datasets/issues/2554/events | https://github.com/huggingface/datasets/issues/2554 | 931,453,855 | MDU6SXNzdWU5MzE0NTM4NTU= | 2,554 | Multilabel metrics not supported | {
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"Hi @GuillemGSubies, thanks for reporting.\r\n\r\nI have made a PR to fix this issue and allow metrics to be computed also for multilabel classification problems.",
"Looks nice, thank you very much! 🚀 ",
"Sorry for reopening but I just noticed that the `_compute` method for the F1 metric is still not good enou... | 2021-06-28T11:09:46Z | 2021-10-13T12:29:13Z | 2021-07-08T08:40:15Z | NONE | null | null | null | When I try to use a metric like F1 macro I get the following error:
```
TypeError: int() argument must be a string, a bytes-like object or a number, not 'list'
```
There is an explicit casting here:
https://github.com/huggingface/datasets/blob/fc79f61cbbcfa0e8c68b28c0a8257f17e768a075/src/datasets/features.py#L274
And looks like this is because here
https://github.com/huggingface/datasets/blob/fc79f61cbbcfa0e8c68b28c0a8257f17e768a075/metrics/f1/f1.py#L88
the features can only be integers, so we cannot use that F1 for multilabel. Instead, if I create the following F1 (ints replaced with sequence of ints), it will work:
```python
class F1(datasets.Metric):
def _info(self):
return datasets.MetricInfo(
description=_DESCRIPTION,
citation=_CITATION,
inputs_description=_KWARGS_DESCRIPTION,
features=datasets.Features(
{
"predictions": datasets.Sequence(datasets.Value("int32")),
"references": datasets.Sequence(datasets.Value("int32")),
}
),
reference_urls=["https://scikit-learn.org/stable/modules/generated/sklearn.metrics.f1_score.html"],
)
def _compute(self, predictions, references, labels=None, pos_label=1, average="binary", sample_weight=None):
return {
"f1": f1_score(
references,
predictions,
labels=labels,
pos_label=pos_label,
average=average,
sample_weight=sample_weight,
),
}
```
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https://api.github.com/repos/huggingface/datasets/issues/4767 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4767/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4767/comments | https://api.github.com/repos/huggingface/datasets/issues/4767/events | https://github.com/huggingface/datasets/pull/4767 | 1,321,843,538 | PR_kwDODunzps48TCpI | 4,767 | Add 2.4.0 version added to docstrings | {
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"_The documentation is not available anymore as the PR was closed or merged._"
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https://api.github.com/repos/huggingface/datasets/issues/3520 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3520/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3520/comments | https://api.github.com/repos/huggingface/datasets/issues/3520/events | https://github.com/huggingface/datasets/pull/3520 | 1,093,747,753 | PR_kwDODunzps4wh6oD | 3,520 | Audio datacard update - first pass | {
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"I'm not sure that we want to change the tags at the top of the cards by hand. Those are used to create the tags in the hub. Although looking at all the tags now, we might want to normalize the current tags again (hyphens or no, \".0\" or no). Maybe we could add a binary tag for public domain or not?",
"> \r\n\r\... | 2022-01-04T20:58:25Z | 2022-01-05T12:30:21Z | 2022-01-05T12:30:20Z | CONTRIBUTOR | null | 0 | {
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"Hi @eyaler, thanks for reporting.\r\n\r\nWhile you are true with respect the Hebrew language tag (\"iw\" is deprecated and \"he\" is the preferred value), in the \"mc4\" dataset (which is a derived dataset) we have kept the language tags present in the original dataset: [Google C4](https://www.tensorflow.org/datas... | 2021-07-20T23:13:52Z | 2021-07-21T16:34:53Z | 2021-07-21T16:34:53Z | NONE | null | null | null | https://huggingface.co/datasets/mc4 not listed when searching for hebrew datasets (he) as it uses the older language code iw, preventing discoverability. | {
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https://api.github.com/repos/huggingface/datasets/issues/6231 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6231/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6231/comments | https://api.github.com/repos/huggingface/datasets/issues/6231/events | https://github.com/huggingface/datasets/pull/6231 | 1,890,863,249 | PR_kwDODunzps5aCr8_ | 6,231 | Overwrite legacy default config name in `dataset_infos.json` in packaged datasets | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6231). All of your documentation changes will be reflected on that endpoint.",
"realized that this pr is still not merged, @lhoestq maybe you can take a look at it? ",
"I think https://github.com/huggingface/datasets/pull/621... | 2023-09-11T16:27:09Z | 2023-09-26T11:19:36Z | null | CONTRIBUTOR | null | 0 | {
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} | Currently if we push data as default config with `.push_to_hub` to a repo that has a legacy `dataset_infos.json` file containing a legacy default config name like `{username}--{dataset_name}`, new key `"default"` is added to `dataset_infos.json` along with the legacy one. I think the legacy one should be dropped in this case.
Also, in `load.py` I suggest to check if a legacy config name is indeed a legacy config name because after this fix it might not be the case (this check was first introduced in https://github.com/huggingface/datasets/pull/6218) | {
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"Yes, this dataset is \"gated\": you first have to go to https://huggingface.co/datasets/boris/gis_filtered and click \"Access repository\" (if you accept to share your contact information with the repository authors).",
"I already did that, it returns error when using streaming",
"Oh, sorry, I misread. Looking... | 2022-06-30T12:23:34Z | 2022-07-06T12:34:19Z | 2022-07-06T12:34:19Z | NONE | null | null | null | ### Link
https://huggingface.co/datasets/boris/gis_filtered/viewer/boris--gis_filtered/train
### Description
When I try to access this from the website I get this error:
Status code: 400
Exception: ClientResponseError
Message: 401, message='Unauthorized', url=URL('https://huggingface.co/datasets/boris/gis_filtered/resolve/80b805053ce61d4eb487b6b8d9095d775c2c466e/data/train/0000.parquet')
If I try to load with code I also get the same issue:
```python
dataset2_train=load_dataset("boris/gis_filtered", use_auth_token=os.environ["HF_TOKEN"],split="train",streaming=True)
dataset2_validation=load_dataset("boris/gis_filtered", use_auth_token=os.environ["HF_TOKEN"], split="validation",streaming=True)
```
### Owner
No | {
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"Hi @capsabogdan! Unfortunately, it's hard to implement because quite often datasets data is being hosted in a single archive for all splits :( So we have to download the whole archive to split it into splits. This is the case for CommonVoice too. \r\n\r\nHowever, for cases when data is distributed in separate arch... | 2022-11-15T10:15:54Z | 2023-05-02T09:27:51Z | null | NONE | null | null | null | ### Feature request
Is it possible to download only the data that I am requesting and not the entire dataset? I run out of disk spaceas it seems to download the entire dataset, instead of only the part needed.
common_voice["test"] = load_dataset("mozilla-foundation/common_voice_11_0", "en", split="test",
cache_dir="cache/path...",
use_auth_token=True,
download_config=DownloadConfig(delete_extracted='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')
)
### Motivation
efficiency improvement
### Your contribution
n/a | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5327). All of your documentation changes will be reflected on that endpoint."
] | 2022-12-01T17:05:23Z | 2023-01-23T12:48:29Z | null | CONTRIBUTOR | null | 1 | {
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"Hi ! In your script it looks like you're trying to load the dataset `bn_hate_speech,`, not KanHope.\r\n\r\nMoreover the error `KeyError: ' '` means that you have a feature of type ClassLabel, but for a certain example of the dataset, it looks like the label is empty (it's just a string with a space). Can you make ... | 2021-08-23T12:21:58Z | 2021-10-01T18:06:59Z | 2021-10-01T18:06:59Z | CONTRIBUTOR | null | null | null | ## Adding a Dataset
- **Name:** *KanHope*
- **Description:** *A code-mixed English-Kannada dataset for Hope speech detection*
- **Paper:** *https://arxiv.org/abs/2108.04616* (I am the author of the paper}
- **Author:** *[AdeepH](https://github.com/adeepH)*
- **Data:** *https://github.com/adeepH/KanHope/tree/main/dataset*
- **Motivation:** *The dataset is amongst the very few resources available for code-mixed Dravidian languages*
- I tried following the steps as per the instructions. However, could not resolve an error. Any help would be appreciated.
- The dataset card and the scripts for the dataset *https://github.com/adeepH/datasets/tree/multilingual-hope-speech/datasets/mhs_eval*
```
Using custom data configuration default
Downloading and preparing dataset bn_hate_speech/default (download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size) to /root/.cache/huggingface/datasets/bn_hate_speech/default/0.0.0/5f417ddc89777278abd29988f909f39495f0ec802090f7d8fa63b5bffb121762...
---------------------------------------------------------------------------
KeyError Traceback (most recent call last)
<ipython-input-114-4a9cdb519e4c> in <module>()
1 from datasets import load_dataset
2
----> 3 data = load_dataset('/content/bn')
9 frames
/usr/local/lib/python3.7/dist-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, script_version, use_auth_token, task, streaming, **config_kwargs)
850 ignore_verifications=ignore_verifications,
851 try_from_hf_gcs=try_from_hf_gcs,
--> 852 use_auth_token=use_auth_token,
853 )
854
/usr/local/lib/python3.7/dist-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)
614 if not downloaded_from_gcs:
615 self._download_and_prepare(
--> 616 dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
617 )
618 # Sync info
/usr/local/lib/python3.7/dist-packages/datasets/builder.py in _download_and_prepare(self, dl_manager, verify_infos, **prepare_split_kwargs)
691 try:
692 # Prepare split will record examples associated to the split
--> 693 self._prepare_split(split_generator, **prepare_split_kwargs)
694 except OSError as e:
695 raise OSError(
/usr/local/lib/python3.7/dist-packages/datasets/builder.py in _prepare_split(self, split_generator)
1107 disable=bool(logging.get_verbosity() == logging.NOTSET),
1108 ):
-> 1109 example = self.info.features.encode_example(record)
1110 writer.write(example, key)
1111 finally:
/usr/local/lib/python3.7/dist-packages/datasets/features.py in encode_example(self, example)
1015 """
1016 example = cast_to_python_objects(example)
-> 1017 return encode_nested_example(self, example)
1018
1019 def encode_batch(self, batch):
/usr/local/lib/python3.7/dist-packages/datasets/features.py in encode_nested_example(schema, obj)
863 if isinstance(schema, dict):
864 return {
--> 865 k: encode_nested_example(sub_schema, sub_obj) for k, (sub_schema, sub_obj) in utils.zip_dict(schema, obj)
866 }
867 elif isinstance(schema, (list, tuple)):
/usr/local/lib/python3.7/dist-packages/datasets/features.py in <dictcomp>(.0)
863 if isinstance(schema, dict):
864 return {
--> 865 k: encode_nested_example(sub_schema, sub_obj) for k, (sub_schema, sub_obj) in utils.zip_dict(schema, obj)
866 }
867 elif isinstance(schema, (list, tuple)):
/usr/local/lib/python3.7/dist-packages/datasets/features.py in encode_nested_example(schema, obj)
890 # ClassLabel will convert from string to int, TranslationVariableLanguages does some checks
891 elif isinstance(schema, (ClassLabel, TranslationVariableLanguages, Value, _ArrayXD)):
--> 892 return schema.encode_example(obj)
893 # Other object should be directly convertible to a native Arrow type (like Translation and Translation)
894 return obj
/usr/local/lib/python3.7/dist-packages/datasets/features.py in encode_example(self, example_data)
665 # If a string is given, convert to associated integer
666 if isinstance(example_data, str):
--> 667 example_data = self.str2int(example_data)
668
669 # Allowing -1 to mean no label.
/usr/local/lib/python3.7/dist-packages/datasets/features.py in str2int(self, values)
623 if value not in self._str2int:
624 value = str(value).strip()
--> 625 output.append(self._str2int[str(value)])
626 else:
627 # No names provided, try to integerize
KeyError: ' '
``` | {
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} | https://api.github.com/repos/huggingface/datasets/issues/2826/timeline | null | completed | false |
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