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https://api.github.com/repos/huggingface/datasets/issues/2111 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2111/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2111/comments | https://api.github.com/repos/huggingface/datasets/issues/2111/events | https://github.com/huggingface/datasets/pull/2111 | 841,082,087 | MDExOlB1bGxSZXF1ZXN0NjAwODY4OTg5 | 2,111 | Compute WER metric iteratively | [] | closed | false | null | 7 | 2021-03-25T16:06:48Z | 2021-04-06T07:20:43Z | 2021-04-06T07:20:43Z | null | Compute WER metric iteratively to avoid MemoryError.
Fix #2078. | {
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"I discussed with Patrick and I think we could have a nice addition: have a parameter `concatenate_texts` that, if `True`, uses the old implementation.\r\n\r\nBy default `concatenate_texts` would be `False`, so that sentences are evaluated independently, and to save resources (the WER computation has a quadratic co... |
https://api.github.com/repos/huggingface/datasets/issues/1125 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1125/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1125/comments | https://api.github.com/repos/huggingface/datasets/issues/1125/events | https://github.com/huggingface/datasets/pull/1125 | 757,194,531 | MDExOlB1bGxSZXF1ZXN0NTMyNjExMDU5 | 1,125 | Add Urdu fake news dataset. | [] | closed | false | null | 3 | 2020-12-04T15:38:17Z | 2020-12-07T03:21:05Z | 2020-12-07T03:21:05Z | null | Added Urdu fake news dataset. More information about the dataset can be found <a href="https://github.com/MaazAmjad/Datasets-for-Urdu-news">here</a>. | {
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"@lhoestq looks like a lot of files were updated... shall I create a new PR?",
"Hi @chaitnayabasava ! you can try rebasing and see if that fixes the number of files changed, otherwise please do open a new PR with only the relevant files and close this one :) ",
"Created a new PR #1230.\r\nclosing this one :)"
] |
https://api.github.com/repos/huggingface/datasets/issues/3315 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3315/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3315/comments | https://api.github.com/repos/huggingface/datasets/issues/3315/events | https://github.com/huggingface/datasets/pull/3315 | 1,061,678,452 | PR_kwDODunzps4u7WpU | 3,315 | Removing query params for dynamic URL caching | [] | closed | false | null | 5 | 2021-11-23T20:24:12Z | 2021-11-25T14:44:32Z | 2021-11-25T14:44:31Z | null | The main use case for this is to make dynamically generated private URLs (like the ones returned by CommonVoice API) compatible with the datasets' caching logic.
Usage example:
```python
import datasets
class CommonVoice(datasets.GeneratorBasedBuilder):
def _info(self):
return datasets.DatasetInfo()
def _split_generators(self, dl_manager):
dl_manager.download_config.ignore_url_params = True
HUGE_URL = "https://mozilla-common-voice-datasets.s3.dualstack.us-west-2.amazonaws.com/cv-corpus-7.0-2021-07-21/cv-corpus-7.0-2021-07-21-ab.tar.gz?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=ASIAQ3GQRTO3IU5JYB5K%2F20211125%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20211125T131423Z&X-Amz-Expires=43200&X-Amz-Security-Token=FwoGZXIvYXdzEL7%2F%2F%2F%2F%2F%2F%2F%2F%2F%2FwEaDLsZw7Nj0d9h4rgheyKSBJJ6bxo1JdWLXAUhLMrUB8AXfhP8Ge4F8dtjwXmvGJgkIvdMT7P4YOEE1pS3mW8AyKsz7Z7IRVCIGQrOH1AbxGVVcDoCMMswXEOqL3nJFihKLf99%2F6l8iJVZdzftRUNgMhX5Hz0xSIL%2BzRDpH5nYa7C6YpEdOdW81CFVXybx7WUrX13wc8X4ZlUj7zrWcWf5p2VEIU5Utb7YHVi0Y5TQQiZSDoedQl0j4VmMuFkDzoobIO%2BvilgGeE2kIX0E62X423mEGNu4uQV5JsOuLAtv3GVlemsqEH3ZYrXDuxLmnvGj5HfMtySwI4vKv%2BlnnirD29o7hxvtidXiA8JMWhp93aP%2Fw7sod%2BPPbb5EqP%2B4Qb2GJ1myClOKcLEY0cqoy7XWm8NeVljLJojnFJVS5mNFBAzCCTJ%2FidxNsj8fflzkRoAzYaaPBuOTL1dgtZCdslK3FAuEvw0cik7P9A7IYiULV33otSHKMPcVfNHFsWQljs03gDztsIUWxaXvu6ck5vCcGULsHbfe6xoMPm2bR9jtKLONsslPcnzWIf7%2Fch2w%2F%2BjtTCd9IxaH4kytyJ6mIjpV%2FA%2F2h9qeDnDFsCphnMjAzPQn6tqCgTtPcyJ2b8c94ncgUnE4mepx%2FDa%2FanAEsrg9RPdmbdoPswzHn1IClh91IfSN74u95DZUxlPeZrHG5HxVCN3dKO6j%2Ft1xd20L0hEtazDdKOr8%2FYwGMirp8rp%2BII0pYOwQOrYHqH%2FREX2dRJctJtwE86Qj1eU8BAdXuFIkLC4NWXw%3D&X-Amz-Signature=1b8108d29b0e9c2bf6c7246e58ca8d5749a83de0704757ad8e8a44d78194691f&X-Amz-SignedHeaders=host"
dl_path = dl_manager.download_and_extract(HUGE_URL)
print(dl_path)
HUGE_URL += "&some_new_or_changed_param=12345"
dl_path = dl_manager.download_and_extract(HUGE_URL)
print(dl_path)
dl_manager = datasets.DownloadManager(dataset_name="common_voice")
CommonVoice()._split_generators(dl_manager)
```
Output:
```
/home/user/.cache/huggingface/datasets/downloads/6ef2a377398ff3309554be040caa78414e6562d623dbd0ce8fc262459a7f8ec6
/home/user/.cache/huggingface/datasets/downloads/6ef2a377398ff3309554be040caa78414e6562d623dbd0ce8fc262459a7f8ec6
``` | {
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"IMO it makes more sense to have `ignore_url_params` as an attribute of `DownloadConfig` to avoid defining a new argument in `DownloadManger`'s methods.",
"@mariosasko that would make sense to me too, but it seems like `DownloadConfig` wasn't intended to be modified from a dataset loading script. @lhoestq wdyt?",... |
https://api.github.com/repos/huggingface/datasets/issues/6075 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6075/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6075/comments | https://api.github.com/repos/huggingface/datasets/issues/6075/events | https://github.com/huggingface/datasets/issues/6075 | 1,822,341,398 | I_kwDODunzps5snrkW | 6,075 | Error loading music files using `load_dataset` | [] | closed | false | null | 2 | 2023-07-26T12:44:05Z | 2023-07-26T13:08:08Z | 2023-07-26T13:08:08Z | null | ### Describe the bug
I tried to load a music file using `datasets.load_dataset()` from the repository - https://huggingface.co/datasets/susnato/pop2piano_real_music_test
I got the following error -
```
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/susnato/anaconda3/envs/p2p/lib/python3.9/site-packages/datasets/arrow_dataset.py", line 2803, in __getitem__
return self._getitem(key)
File "/home/susnato/anaconda3/envs/p2p/lib/python3.9/site-packages/datasets/arrow_dataset.py", line 2788, in _getitem
formatted_output = format_table(
File "/home/susnato/anaconda3/envs/p2p/lib/python3.9/site-packages/datasets/formatting/formatting.py", line 629, in format_table
return formatter(pa_table, query_type=query_type)
File "/home/susnato/anaconda3/envs/p2p/lib/python3.9/site-packages/datasets/formatting/formatting.py", line 398, in __call__
return self.format_column(pa_table)
File "/home/susnato/anaconda3/envs/p2p/lib/python3.9/site-packages/datasets/formatting/formatting.py", line 442, in format_column
column = self.python_features_decoder.decode_column(column, pa_table.column_names[0])
File "/home/susnato/anaconda3/envs/p2p/lib/python3.9/site-packages/datasets/formatting/formatting.py", line 218, in decode_column
return self.features.decode_column(column, column_name) if self.features else column
File "/home/susnato/anaconda3/envs/p2p/lib/python3.9/site-packages/datasets/features/features.py", line 1924, in decode_column
[decode_nested_example(self[column_name], value) if value is not None else None for value in column]
File "/home/susnato/anaconda3/envs/p2p/lib/python3.9/site-packages/datasets/features/features.py", line 1924, in <listcomp>
[decode_nested_example(self[column_name], value) if value is not None else None for value in column]
File "/home/susnato/anaconda3/envs/p2p/lib/python3.9/site-packages/datasets/features/features.py", line 1325, in decode_nested_example
return schema.decode_example(obj, token_per_repo_id=token_per_repo_id)
File "/home/susnato/anaconda3/envs/p2p/lib/python3.9/site-packages/datasets/features/audio.py", line 184, in decode_example
array, sampling_rate = sf.read(f)
File "/home/susnato/anaconda3/envs/p2p/lib/python3.9/site-packages/soundfile.py", line 372, in read
with SoundFile(file, 'r', samplerate, channels,
File "/home/susnato/anaconda3/envs/p2p/lib/python3.9/site-packages/soundfile.py", line 740, in __init__
self._file = self._open(file, mode_int, closefd)
File "/home/susnato/anaconda3/envs/p2p/lib/python3.9/site-packages/soundfile.py", line 1264, in _open
_error_check(_snd.sf_error(file_ptr),
File "/home/susnato/anaconda3/envs/p2p/lib/python3.9/site-packages/soundfile.py", line 1455, in _error_check
raise RuntimeError(prefix + _ffi.string(err_str).decode('utf-8', 'replace'))
RuntimeError: Error opening <_io.BufferedReader name='/home/susnato/.cache/huggingface/datasets/downloads/d2b09cb974b967b13f91553297c40c0f02f3c0d4c8356350743598ff48d6f29e'>: Format not recognised.
```
### Steps to reproduce the bug
Code to reproduce the error -
```python
from datasets import load_dataset
ds = load_dataset("susnato/pop2piano_real_music_test", split="test")
print(ds[0])
```
### Expected behavior
I should be able to read the music file without any error.
### Environment info
- `datasets` version: 2.14.0
- Platform: Linux-5.19.0-50-generic-x86_64-with-glibc2.35
- Python version: 3.9.16
- Huggingface_hub version: 0.15.1
- PyArrow version: 11.0.0
- Pandas version: 1.5.3
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"This code behaves as expected on my local machine or in Colab. Which version of `soundfile` do you have installed? MP3 requires `soundfile>=0.12.1`.",
"I upgraded the `soundfile` and it's working now! \r\nThanks @mariosasko for the help!"
] |
https://api.github.com/repos/huggingface/datasets/issues/2628 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2628/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2628/comments | https://api.github.com/repos/huggingface/datasets/issues/2628/events | https://github.com/huggingface/datasets/pull/2628 | 941,676,404 | MDExOlB1bGxSZXF1ZXN0Njg3NTE0NzQz | 2,628 | Use ETag of remote data files | [] | closed | false | {
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} | 0 | 2021-07-12T05:10:10Z | 2021-07-12T14:08:34Z | 2021-07-12T08:40:07Z | null | Use ETag of remote data files to create config ID.
Related to #2616. | {
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https://api.github.com/repos/huggingface/datasets/issues/1334 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1334/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1334/comments | https://api.github.com/repos/huggingface/datasets/issues/1334/events | https://github.com/huggingface/datasets/pull/1334 | 759,699,993 | MDExOlB1bGxSZXF1ZXN0NTM0NjU5MDg2 | 1,334 | Add QED Amara Dataset | [] | closed | false | null | 0 | 2020-12-08T19:01:13Z | 2020-12-10T11:17:25Z | 2020-12-10T11:15:57Z | null | {
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https://api.github.com/repos/huggingface/datasets/issues/31 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/31/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/31/comments | https://api.github.com/repos/huggingface/datasets/issues/31/events | https://github.com/huggingface/datasets/pull/31 | 610,677,641 | MDExOlB1bGxSZXF1ZXN0NDEyMDczNDE4 | 31 | [Circle ci] Install a virtual env before running tests | [] | closed | false | null | 0 | 2020-05-01T10:11:17Z | 2020-05-01T22:06:16Z | 2020-05-01T22:06:15Z | null | Install a virtual env before running tests to not running into sudo issues when dynamically downloading files.
Same number of tests now pass / fail as on my local computer:
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https://api.github.com/repos/huggingface/datasets/issues/594 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/594/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/594/comments | https://api.github.com/repos/huggingface/datasets/issues/594/events | https://github.com/huggingface/datasets/pull/594 | 696,816,893 | MDExOlB1bGxSZXF1ZXN0NDgyODQ1OTc5 | 594 | Fix germeval url | [] | closed | false | null | 0 | 2020-09-09T13:29:35Z | 2020-09-09T13:34:35Z | 2020-09-09T13:34:34Z | null | Continuation of #593 but without the dummy data hack | {
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https://api.github.com/repos/huggingface/datasets/issues/5088 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5088/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5088/comments | https://api.github.com/repos/huggingface/datasets/issues/5088/events | https://github.com/huggingface/datasets/issues/5088 | 1,400,530,412 | I_kwDODunzps5TemXs | 5,088 | load_datasets("json", ...) don't read local .json.gz properly | [
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] | open | false | null | 2 | 2022-10-07T02:16:58Z | 2022-10-07T14:43:16Z | null | null | ## Describe the bug
I have a local file `*.json.gz` and it can be read by `pandas.read_json(lines=True)`, but cannot be read by `load_datasets("json")` (resulting in 0 lines)
## Steps to reproduce the bug
```python
fpath = '/data/junwang/.cache/general/57b6f2314cbe0bc45dda5b78f0871df2/test.json.gz'
ds_panda = DatasetDict(
test=Dataset.from_pandas(
pd.read_json(fpath, lines=True)
)
)
ds_direct = load_dataset(
'json', data_files={
'test': fpath
}, features=Features(
text_input=Value(dtype="string", id=None),
text_output=Value(dtype="string", id=None)
)
)
len(ds_panda['test']), len(ds_direct['test'])
```
## Expected results
Lines of `ds_panda['test']` and `ds_direct['test']` should match.
## Actual results
```
Using custom data configuration default-c0ef2598760968aa
Downloading and preparing dataset json/default to /data/junwang/.cache/huggingface/datasets/json/default-c0ef2598760968aa/0.0.0/e6070c77f18f01a5ad4551a8b7edfba20b8438b7cad4d94e6ad9378022ce4aab...
Dataset json downloaded and prepared to /data/junwang/.cache/huggingface/datasets/json/default-c0ef2598760968aa/0.0.0/e6070c77f18f01a5ad4551a8b7edfba20b8438b7cad4d94e6ad9378022ce4aab. Subsequent calls will reuse this data.
(62087, 0)
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version:
- Platform: Ubuntu 18.04.4 LTS
- Python version: 3.8.13
- PyArrow version: 9.0.0
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"Hi @junwang-wish, thanks for reporting.\r\n\r\nUnfortunately, I'm not able to reproduce the bug. Which version of `datasets` are you using? Does the problem persist if you update `datasets`?\r\n```shell\r\npip install -U datasets\r\n``` ",
"Thanks @albertvillanova I updated `datasets` from `2.5.1` to `2.5.2` and... |
https://api.github.com/repos/huggingface/datasets/issues/3841 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3841/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3841/comments | https://api.github.com/repos/huggingface/datasets/issues/3841/events | https://github.com/huggingface/datasets/issues/3841 | 1,161,203,842 | I_kwDODunzps5FNpCC | 3,841 | Pyright reportPrivateImportUsage when `from datasets import load_dataset` | [
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] | closed | false | null | 6 | 2022-03-07T10:24:04Z | 2023-02-18T19:14:03Z | 2023-02-13T13:48:41Z | null | ## Describe the bug
Pyright complains about module not exported.
## Steps to reproduce the bug
Use an editor/IDE with Pyright Language server with default configuration:
```python
from datasets import load_dataset
```
## Expected results
No complain from Pyright
## Actual results
Pyright complain below:
```
`load_dataset` is not exported from module "datasets"
Import from "datasets.load" instead [reportPrivateImportUsage]
```
Importing from `datasets.load` does indeed solves the problem but I believe importing directly from top level `datasets` is the intended usage per the documentation.
## Environment info
- `datasets` version: 1.18.3
- Platform: macOS-12.2.1-arm64-arm-64bit
- Python version: 3.9.10
- PyArrow version: 7.0.0
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"Hi! \r\n\r\nThis issue stems from `datasets` having `py.typed` defined (see https://github.com/microsoft/pyright/discussions/3764#discussioncomment-3282142) - to avoid it, we would either have to remove `py.typed` (added to be compliant with PEP-561) or export the names with `__all__`/`from .submodule import name ... |
https://api.github.com/repos/huggingface/datasets/issues/223 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/223/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/223/comments | https://api.github.com/repos/huggingface/datasets/issues/223/events | https://github.com/huggingface/datasets/issues/223 | 627,683,386 | MDU6SXNzdWU2Mjc2ODMzODY= | 223 | [Feature request] Add FLUE dataset | [
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] | closed | false | null | 3 | 2020-05-30T08:52:15Z | 2020-12-03T13:39:33Z | 2020-12-03T13:39:33Z | null | Hi,
I think it would be interesting to add the FLUE dataset for francophones or anyone wishing to work on French.
In other requests, I read that you are already working on some datasets, and I was wondering if FLUE was planned.
If it is not the case, I can provide each of the cleaned FLUE datasets (in the form of a directly exploitable dataset rather than in the original xml formats which require additional processing, with the French part for cases where the dataset is based on a multilingual dataframe, etc.). | {
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"Hi @lbourdois, yes please share it with us",
"@mariamabarham \r\nI put all the datasets on this drive: https://1drv.ms/u/s!Ao2Rcpiny7RFinDypq7w-LbXcsx9?e=iVsEDh\r\n\r\n\r\nSome information : \r\n• For FLUE, the quote used is\r\n\r\n> @misc{le2019flaubert,\r\n> title={FlauBERT: Unsupervised Language Model Pre... |
https://api.github.com/repos/huggingface/datasets/issues/1518 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1518/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1518/comments | https://api.github.com/repos/huggingface/datasets/issues/1518/events | https://github.com/huggingface/datasets/pull/1518 | 764,045,722 | MDExOlB1bGxSZXF1ZXN0NTM4MzAyNzYy | 1,518 | Add twi text | [] | closed | false | null | 2 | 2020-12-12T16:52:02Z | 2020-12-13T18:53:37Z | 2020-12-13T18:53:37Z | null | Add Twi texts | {
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"Hii please follow me",
"thank you"
] |
https://api.github.com/repos/huggingface/datasets/issues/4267 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4267/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4267/comments | https://api.github.com/repos/huggingface/datasets/issues/4267/events | https://github.com/huggingface/datasets/pull/4267 | 1,223,214,275 | PR_kwDODunzps43LzOR | 4,267 | Replace data URL in SAMSum dataset within the same repository | [] | closed | false | null | 1 | 2022-05-02T18:38:08Z | 2022-05-06T08:38:13Z | 2022-05-02T19:03:49Z | null | Replace data URL with one in the same repository. | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] |
https://api.github.com/repos/huggingface/datasets/issues/1418 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1418/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1418/comments | https://api.github.com/repos/huggingface/datasets/issues/1418/events | https://github.com/huggingface/datasets/pull/1418 | 760,672,320 | MDExOlB1bGxSZXF1ZXN0NTM1NDY0NzQ4 | 1,418 | Add arabic dialects | [] | closed | false | null | 1 | 2020-12-09T21:06:07Z | 2020-12-17T09:40:56Z | 2020-12-17T09:40:56Z | null | Data loading script and dataset card for Dialectal Arabic Resources dataset.
Fixed git issues from PR #976 | {
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"merging since the CI is fixed on master"
] |
https://api.github.com/repos/huggingface/datasets/issues/136 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/136/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/136/comments | https://api.github.com/repos/huggingface/datasets/issues/136/events | https://github.com/huggingface/datasets/pull/136 | 619,211,018 | MDExOlB1bGxSZXF1ZXN0NDE4NzgxNzI4 | 136 | Update README.md | [] | closed | false | null | 1 | 2020-05-15T20:01:07Z | 2020-05-17T12:17:28Z | 2020-05-17T12:17:28Z | null | small typo | {
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"Thanks, this was fixed with #135 :)"
] |
https://api.github.com/repos/huggingface/datasets/issues/2916 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2916/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2916/comments | https://api.github.com/repos/huggingface/datasets/issues/2916/events | https://github.com/huggingface/datasets/pull/2916 | 997,003,661 | PR_kwDODunzps4rx5ua | 2,916 | Add OpenAI's pass@k code evaluation metric | [] | closed | false | null | 4 | 2021-09-15T12:05:43Z | 2021-11-12T14:19:51Z | 2021-11-12T14:19:50Z | null | This PR introduces the `code_eval` metric which implements [OpenAI's code evaluation harness](https://github.com/openai/human-eval) introduced in the [Codex paper](https://arxiv.org/abs/2107.03374). It is heavily based on the original implementation and just adapts the interface to follow the `predictions`/`references` convention.
The addition of this metric should enable the evaluation against the code evaluation datasets added in #2897 and #2893.
A few open questions:
- The implementation makes heavy use of multiprocessing which this PR does not touch. Is this conflicting with multiprocessing natively integrated in `datasets`?
- This metric executes generated Python code and as such it poses dangers of executing malicious code. OpenAI addresses this issue by 1) commenting the `exec` call in the code so the user has to actively uncomment it and read the warning and 2) suggests using a sandbox environment (gVisor container). Should we add a similar safeguard? E.g. a prompt that needs to be answered when initialising the metric? Or at least a warning message?
- Naming: the implementation sticks to the `predictions`/`references` naming, however, the references are not reference solutions but unittest to test the solution. While reference solutions are also available they are not used. Should the naming be adapted? | {
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"> The implementation makes heavy use of multiprocessing which this PR does not touch. Is this conflicting with multiprocessing natively integrated in datasets?\r\n\r\nIt should work normally, but feel free to test it.\r\nThere is some documentation about using metrics in a distributed setup that uses multiprocessi... |
https://api.github.com/repos/huggingface/datasets/issues/1078 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1078/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1078/comments | https://api.github.com/repos/huggingface/datasets/issues/1078/events | https://github.com/huggingface/datasets/pull/1078 | 756,633,215 | MDExOlB1bGxSZXF1ZXN0NTMyMTUyMzgx | 1,078 | add AJGT dataset | [] | closed | false | null | 0 | 2020-12-03T22:16:31Z | 2020-12-04T09:55:15Z | 2020-12-04T09:55:15Z | null | Arabic Jordanian General Tweets. | {
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https://api.github.com/repos/huggingface/datasets/issues/5145 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5145/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5145/comments | https://api.github.com/repos/huggingface/datasets/issues/5145/events | https://github.com/huggingface/datasets/issues/5145 | 1,418,005,452 | I_kwDODunzps5UhQvM | 5,145 | Dataset order is not deterministic with ZIP archives and `iter_files` | [] | closed | false | null | 8 | 2022-10-21T09:00:03Z | 2022-10-27T09:51:49Z | 2022-10-27T09:51:10Z | null | ### Describe the bug
For the `beans` dataset (did not try on other), the order of samples is not the same on different machines. Tested on my local laptop, github actions machine, and ec2 instance. The three yield a different order.
### Steps to reproduce the bug
In a clean docker container or conda environment with datasets==2.6.1, run
```python
from datasets import load_dataset
from pprint import pprint
data = load_dataset("beans", split="validation")
pprint(data["image_file_path"])
```
### Expected behavior
The order of the images is the same on all machines.
### Environment info
On the EC2 instance:
```
- `datasets` version: 2.6.1
- Platform: Linux-4.14.291-218.527.amzn2.x86_64-x86_64-with-glibc2.2.5
- Python version: 3.7.10
- PyArrow version: 9.0.0
- Pandas version: 1.3.5
- Numpy version: not checked
```
On my local laptop:
```
- `datasets` version: 2.6.1
- Platform: Linux-5.15.0-50-generic-x86_64-with-glibc2.35
- Python version: 3.9.12
- PyArrow version: 7.0.0
- Pandas version: 1.3.5
- Numpy version: 1.23.1
```
On github actions:
```
- `datasets` version: 2.6.1
- Platform: Linux-5.15.0-1022-azure-x86_64-with-glibc2.2.5
- Python version: 3.8.14
- PyArrow version: 9.0.0
- Pandas version: 1.5.1
- Numpy version: 1.23.4
``` | {
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"Thanks for reporting ! The issue doesn't come from shuffling, but from `beans` row order not being deterministic:\r\n\r\nhttps://huggingface.co/datasets/beans/blob/main/beans.py uses `dl_manager.iter_files` on ZIP archives and the file order doesn't seen to be deterministic and changes across machines",
"Thank y... |
https://api.github.com/repos/huggingface/datasets/issues/2187 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2187/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2187/comments | https://api.github.com/repos/huggingface/datasets/issues/2187/events | https://github.com/huggingface/datasets/issues/2187 | 852,939,736 | MDU6SXNzdWU4NTI5Mzk3MzY= | 2,187 | Question (potential issue?) related to datasets caching | [
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] | open | false | null | 15 | 2021-04-08T00:16:28Z | 2023-01-03T18:30:38Z | null | null | I thought I had disabled datasets caching in my code, as follows:
```
from datasets import set_caching_enabled
...
def main():
# disable caching in datasets
set_caching_enabled(False)
```
However, in my log files I see messages like the following:
```
04/07/2021 18:34:42 - WARNING - datasets.builder - Using custom data configuration default-888a87931cbc5877
04/07/2021 18:34:42 - WARNING - datasets.builder - Reusing dataset csv (xxxx/cache-transformers/datasets/csv/default-888a87931cbc5877/0.0.0/965b6429be0fc05f975b608ce64e1fa941cc8fb4f30629b523d2390f3c0e1a93
```
Can you please let me know what this reusing dataset csv means? I wouldn't expect any reusing with the datasets caching disabled. Thank you! | {
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"An educated guess: does this refer to the fact that depending on the custom column names in the dataset files (csv in this case), there is a dataset loader being created? and this dataset loader - using the \"custom data configuration\" is used among all jobs running using this particular csv files? (thinking out ... |
https://api.github.com/repos/huggingface/datasets/issues/6003 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6003/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6003/comments | https://api.github.com/repos/huggingface/datasets/issues/6003/events | https://github.com/huggingface/datasets/issues/6003 | 1,786,554,110 | I_kwDODunzps5qfKb- | 6,003 | interleave_datasets & DataCollatorForLanguageModeling having a conflict ? | [] | open | false | null | 0 | 2023-07-03T17:15:31Z | 2023-07-03T17:15:31Z | null | null | ### Describe the bug
Hi everyone :)
I have two local & custom datasets (1 "sentence" per line) which I split along the 95/5 lines for pre-training a Bert model. I use a modified version of `run_mlm.py` in order to be able to make use of `interleave_dataset`:
- `tokenize()` runs fine
- `group_text()` runs fine
Everytime, on step 19, I get
```pytb
File "env/lib/python3.9/site-packages/transformers/data/data_collator.py", line 779, in torch_mask_tokens
inputs[indices_random] = random_words[indices_random]
RuntimeError: Index put requires the source and destination dtypes match, got Float for the destination and Long for the source.
```
I tried:
- training without interleave on dataset 1, it runs
- training without interleave on dataset 2, it runs
- training without `.to_iterable_dataset()`, it hangs then crash
- training without group_text() and padding to max_length seemed to fix the issue, but who knows if this was just because it was an issue that would come much later in terms of steps.
I might have coded something wrong, but I don't get what
### Steps to reproduce the bug
I have this function:
```py
def build_dataset(path: str, percent: str):
dataset = load_dataset(
"text",
data_files={"train": [path]},
split=f"train[{percent}]"
)
dataset = dataset.map(
lambda examples: tokenize(examples["text"]),
batched=True,
num_proc=num_proc,
)
dataset = dataset.map(
group_texts,
batched=True,
num_proc=num_proc,
desc=f"Grouping texts in chunks of {tokenizer.max_seq_length}",
remove_columns=["text"]
)
print(len(dataset))
return dataset.to_iterable_dataset()
```
I hardcoded group_text:
```py
def group_texts(examples):
# Concatenate all texts.
concatenated_examples = {k: list(chain(*examples[k])) for k in examples.keys()}
total_length = len(concatenated_examples[list(examples.keys())[0]])
# We drop the small remainder, and if the total_length < max_seq_length we exclude this batch and return an empty dict.
# We could add padding if the model supported it instead of this drop, you can customize this part to your needs.
total_length = (total_length // 512) * 512
# Split by chunks of max_len.
result = {
k: [t[i: i + 512] for i in range(0, total_length, 512)]
for k, t in concatenated_examples.items()
}
# result = {k: [el for el in elements if el] for k, elements in result.items()}
return result
```
And then I build datasets using the following code:
```py
train1 = build_dataset("d1.txt", ":95%")
train2 = build_dataset("d2.txt", ":95%")
dev1 = build_dataset("d1.txt", "95%:")
dev2 = build_dataset("d2.txt", "95%:")
```
and finally I run
```py
train_dataset = interleave_datasets(
[train1, train2],
probabilities=[0.8, 0.2],
seed=42
)
eval_dataset = interleave_datasets(
[dev1, dev2],
probabilities=[0.8, 0.2],
seed=42
)
```
Then I run the training part which remains mostly untouched:
> CUDA_VISIBLE_DEVICES=1 python custom_dataset.py --model_type bert --per_device_train_batch_size 32 --do_train --output_dir /var/mlm/training-bert/model --max_seq_length 512 --save_steps 10000 --save_total_limit 3 --auto_find_batch_size --logging_dir ./logs-bert --learning_rate 0.0001 --do_train --num_train_epochs 25 --warmup_steps 10000 --max_step 45000 --fp16
### Expected behavior
The model should then train normally, but fails every time at the same step (19).
printing the variables at `inputs[indices_random] = random_words[indices_random]` shows a magnificient empty tensor (, 32) [if I remember well]
### Environment info
transformers[torch] 4.30.2
Ubuntu
A100 0 CUDA 12
Driver Version: 525.116.04 | {
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https://api.github.com/repos/huggingface/datasets/issues/217 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/217/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/217/comments | https://api.github.com/repos/huggingface/datasets/issues/217/events | https://github.com/huggingface/datasets/issues/217 | 627,128,403 | MDU6SXNzdWU2MjcxMjg0MDM= | 217 | Multi-task dataset mixing | [
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"default": fals... | open | false | null | 26 | 2020-05-29T09:22:26Z | 2022-10-22T00:45:50Z | null | null | It seems like many of the best performing models on the GLUE benchmark make some use of multitask learning (simultaneous training on multiple tasks).
The [T5 paper](https://arxiv.org/pdf/1910.10683.pdf) highlights multiple ways of mixing the tasks together during finetuning:
- **Examples-proportional mixing** - sample from tasks proportionally to their dataset size
- **Equal mixing** - sample uniformly from each task
- **Temperature-scaled mixing** - The generalized approach used by multilingual BERT which uses a temperature T, where the mixing rate of each task is raised to the power 1/T and renormalized. When T=1 this is equivalent to equal mixing, and becomes closer to equal mixing with increasing T.
Following this discussion https://github.com/huggingface/transformers/issues/4340 in [transformers](https://github.com/huggingface/transformers), @enzoampil suggested that the `nlp` library might be a better place for this functionality.
Some method for combining datasets could be implemented ,e.g.
```
dataset = nlp.load_multitask(['squad','imdb','cnn_dm'], temperature=2.0, ...)
```
We would need a few additions:
- Method of identifying the tasks - how can we support adding a string to each task as an identifier: e.g. 'summarisation: '?
- Method of combining the metrics - a standard approach is to use the specific metric for each task and add them together for a combined score.
It would be great to support common use cases such as pretraining on the GLUE benchmark before fine-tuning on each GLUE task in turn.
I'm willing to write bits/most of this I just need some guidance on the interface and other library details so I can integrate it properly.
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"I like this feature! I think the first question we should decide on is how to convert all datasets into the same format. In T5, the authors decided to format every dataset into a text-to-text format. If the dataset had \"multiple\" inputs like MNLI, the inputs were concatenated. So in MNLI the input:\r\n\r\n> - **... |
https://api.github.com/repos/huggingface/datasets/issues/1579 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1579/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1579/comments | https://api.github.com/repos/huggingface/datasets/issues/1579/events | https://github.com/huggingface/datasets/pull/1579 | 767,808,465 | MDExOlB1bGxSZXF1ZXN0NTQwMzk5OTY5 | 1,579 | Adding CLIMATE-FEVER dataset | [] | closed | false | null | 5 | 2020-12-15T16:49:22Z | 2020-12-22T13:43:16Z | 2020-12-22T13:43:15Z | null | This PR request the addition of the CLIMATE-FEVER dataset:
A dataset adopting the FEVER methodology that consists of 1,535 real-world claims regarding climate-change collected on the internet. Each claim is accompanied by five manually annotated evidence sentences retrieved from the English Wikipedia that support, refute or do not give enough information to validate the claim totalling in 7,675 claim-evidence pairs. The dataset features challenging claims that relate multiple facets and disputed cases of claims where both supporting and refuting evidence are present.
More information can be found at:
- Homepage: <http://climatefever.ai>
- Paper: <https://arxiv.org/abs/2012.00614>
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"I `git rebase`ed my branch to `upstream/master` as suggested in point 7 of <https://huggingface.co/docs/datasets/share_dataset.html> and subsequently used `git pull` to be able to push to my remote branch. However, I think this messed up the history.\r\n\r\nPlease let me know if I should create a clean new PR with... |
https://api.github.com/repos/huggingface/datasets/issues/2543 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2543/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2543/comments | https://api.github.com/repos/huggingface/datasets/issues/2543/events | https://github.com/huggingface/datasets/issues/2543 | 928,571,915 | MDU6SXNzdWU5Mjg1NzE5MTU= | 2,543 | switching some low-level log.info's to log.debug? | [
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] | closed | false | null | 1 | 2021-06-23T19:26:55Z | 2021-06-25T13:40:19Z | 2021-06-25T13:40:19Z | null | In https://github.com/huggingface/transformers/pull/12276 we are now changing the examples to have `datasets` on the same log level as `transformers`, so that one setting can do a consistent logging across all involved components.
The trouble is that now we get a ton of these:
```
06/23/2021 12:15:31 - INFO - datasets.utils.filelock - Lock 139627640431136 acquired on /home/stas/.cache/huggingface/metrics/sacrebleu/default/default_experiment-1-0.arrow.lock
06/23/2021 12:15:31 - INFO - datasets.arrow_writer - Done writing 50 examples in 12280 bytes /home/stas/.cache/huggingface/metrics/sacrebleu/default/default_experiment-1-0.arrow.
06/23/2021 12:15:31 - INFO - datasets.arrow_dataset - Set __getitem__(key) output type to python objects for no columns (when key is int or slice) and don't output other (un-formatted) columns.
06/23/2021 12:15:31 - INFO - datasets.utils.filelock - Lock 139627640431136 released on /home/stas/.cache/huggingface/metrics/sacrebleu/default/default_experiment-1-0.arrow.lock
```
May I suggest that these can be `log.debug` as it's no informative to the user.
More examples: these are not informative - too much information:
```
06/23/2021 12:14:26 - INFO - datasets.load - Checking /home/stas/.cache/huggingface/datasets/downloads/459933f1fe47711fad2f6ff8110014ff189120b45ad159ef5b8e90ea43a174fa.e23e7d1259a8c6274a82a42a8936dd1b87225302c6dc9b7261beb3bc2daac640.py for additional imports.
06/23/2021 12:14:27 - INFO - datasets.builder - Constructing Dataset for split train, validation, test, from /home/stas/.cache/huggingface/datasets/wmt16/ro-en/1.0.0/0d9fb3e814712c785176ad8cdb9f465fbe6479000ee6546725db30ad8a8b5f8a
```
While these are:
```
06/23/2021 12:14:27 - INFO - datasets.info - Loading Dataset Infos from /home/stas/.cache/huggingface/modules/datasets_modules/datasets/wmt16/0d9fb3e814712c785176ad8cdb9f465fbe6479000ee6546725db30ad8a8b5f8a
06/23/2021 12:14:27 - WARNING - datasets.builder - Reusing dataset wmt16 (/home/stas/.cache/huggingface/datasets/wmt16/ro-en/1.0.0/0d9fb3e814712c785176ad8cdb9f465fbe6479000ee6546725db30ad8a8b5f8a)
```
I also realize that `transformers` examples don't have do use `info` for `datasets` to let the default `warning` keep logging to less noisy.
But I think currently the log levels are slightly misused and skewed by 1 level. Many `warnings` will better be `info`s and most `info`s be `debug`.
e.g.:
```
06/23/2021 12:14:27 - WARNING - datasets.builder - Reusing dataset wmt16 (/home/stas/.cache/huggingface/datasets/wmt16/ro-en/1.0.0/0d9fb3e814712c785176ad8cdb9f465fbe6479000ee6546725db30ad8a8b5f8a)
```
why is this a warning? it is informing me that the cache is used, there is nothing to be worried about. I'd have it as `info`.
Warnings are typically something that's bordering error or the first thing to check when things don't work as expected.
infrequent info is there to inform of the different stages or important events.
Everything else is debug.
At least the way I understand things.
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"Hi @stas00, thanks for pointing out this issue with logging.\r\n\r\nI agree that `datasets` can sometimes be too verbose... I can create a PR and we could discuss there the choice of the log levels for different parts of the code."
] |
https://api.github.com/repos/huggingface/datasets/issues/3306 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3306/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3306/comments | https://api.github.com/repos/huggingface/datasets/issues/3306/events | https://github.com/huggingface/datasets/issues/3306 | 1,059,185,860 | I_kwDODunzps4_IeTE | 3,306 | nested sequence feature won't encode example if the first item of the outside sequence is an empty list | [
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] | closed | false | null | 3 | 2021-11-20T16:57:54Z | 2021-12-08T13:02:15Z | 2021-12-08T13:02:15Z | null | ## Describe the bug
As the title, nested sequence feature won't encode example if the first item of the outside sequence is an empty list.
## Steps to reproduce the bug
```python
from datasets import Features, Sequence, ClassLabel
features = Features({
'x': Sequence(Sequence(ClassLabel(names=['a', 'b']))),
})
print(features.encode_batch({
'x': [
[['a'], ['b']],
[[], ['b']],
]
}))
```
## Expected results
print `{'x': [[[0], [1]], [[], ['1']]]}`
## Actual results
print `{'x': [[[0], [1]], [[], ['b']]]}`
## Environment info
- `datasets` version: 1.15.1
- Platform: Linux-5.13.0-21-generic-x86_64-with-glibc2.34
- Python version: 3.9.7
- PyArrow version: 6.0.0
## Additional information
I think the issue stems from [here](https://github.com/huggingface/datasets/blob/8555197a3fe826e98bd0206c2d031c4488c53c5c/src/datasets/features/features.py#L847-L848).
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"knock knock",
"Hi, thanks for reporting! I've linked a PR that should fix the issue.",
"I've checked the PR and it looks great, thanks a lot!"
] |
https://api.github.com/repos/huggingface/datasets/issues/2146 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2146/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2146/comments | https://api.github.com/repos/huggingface/datasets/issues/2146/events | https://github.com/huggingface/datasets/issues/2146 | 844,673,244 | MDU6SXNzdWU4NDQ2NzMyNDQ= | 2,146 | Dataset file size on disk is very large with 3D Array | [] | open | false | null | 6 | 2021-03-30T14:46:09Z | 2021-04-16T13:07:02Z | null | null | Hi,
I have created my own dataset using the provided dataset loading script. It is an image dataset where images are stored as 3D Array with dtype=uint8.
The actual size on disk is surprisingly large. It takes 520 MB. Here is some info from `dataset_info.json`.
`{
"description": "",
"citation": "",
"homepage": "",
"license": "",
"features": {
"image": {
"shape": [224, 224, 3],
"dtype": "uint8",
"id": null,
"_type": "Array3D",
}
},
"post_processed": null,
"supervised_keys": null,
"builder_name": "shot_type_image_dataset",
"config_name": "default",
"version": {
"version_str": "0.0.0",
"description": null,
"major": 0,
"minor": 0,
"patch": 0,
},
"splits": {
"train": {
"name": "train",
"num_bytes": 520803408,
"num_examples": 1479,
"dataset_name": "shot_type_image_dataset",
}
},
"download_checksums": {
"": {
"num_bytes": 16940447118,
"checksum": "5854035705efe08b0ed8f3cf3da7b4d29cba9055c2d2d702c79785350d72ee03",
}
},
"download_size": 16940447118,
"post_processing_size": null,
"dataset_size": 520803408,
"size_in_bytes": 17461250526,
}`
I have created the same dataset with tensorflow_dataset and it takes only 125MB on disk.
I am wondering, is it normal behavior ? I understand `Datasets` uses Arrow for serialization wheres tf uses TF Records.
This might be a problem for large dataset.
Thanks for your help.
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} | https://api.github.com/repos/huggingface/datasets/issues/2146/timeline | null | null | null | null | false | [
"Hi ! In the arrow file we store all the integers as uint8.\r\nSo your arrow file should weigh around `height x width x n_channels x n_images` bytes.\r\n\r\nWhat feature type do your TFDS dataset have ?\r\n\r\nIf it uses a `tfds.features.Image` type, then what is stored is the encoded data (as png or jpg for exampl... |
https://api.github.com/repos/huggingface/datasets/issues/674 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/674/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/674/comments | https://api.github.com/repos/huggingface/datasets/issues/674/events | https://github.com/huggingface/datasets/issues/674 | 709,661,006 | MDU6SXNzdWU3MDk2NjEwMDY= | 674 | load_dataset() won't download in Windows | [] | closed | false | null | 3 | 2020-09-27T03:56:25Z | 2020-10-05T08:28:18Z | 2020-10-05T08:28:18Z | null | I don't know if this is just me or Windows. Maybe other Windows users can chime in if they don't have this problem. I've been trying to get some of the tutorials working on Windows, but when I use the load_dataset() function, it just stalls and the script keeps running indefinitely without downloading anything. I've waited upwards of 18 hours to download the 'multi-news' dataset (which isn't very big), and still nothing. I've tried running it through different IDE's and the command line, but it had the same behavior. I've also tried it with all virus and malware protection turned off. I've made sure python and all IDE's are exceptions to the firewall and all the requisite permissions are enabled.
Additionally, I checked to see if other packages could download content such as an nltk corpus, and they could. I've also run the same script using Ubuntu and it downloaded fine (and quickly). When I copied the downloaded datasets from my Ubuntu drive to my Windows .cache folder it worked fine by reusing the already-downloaded dataset, but it's cumbersome to do that for every dataset I want to try in my Windows environment.
Could this be a bug, or is there something I'm doing wrong or not thinking of?
Thanks. | {
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"I have the same issue. Tried to download a few of them and not a single one is downloaded successfully.\r\n\r\nThis is the output:\r\n```\r\n>>> dataset = load_dataset('blended_skill_talk', split='train')\r\nUsing custom data configuration default <-- This step never ends\r\n```",
"This was fixed i... |
https://api.github.com/repos/huggingface/datasets/issues/3965 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3965/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3965/comments | https://api.github.com/repos/huggingface/datasets/issues/3965/events | https://github.com/huggingface/datasets/issues/3965 | 1,173,708,739 | I_kwDODunzps5F9V_D | 3,965 | TypeError: Couldn't cast array of type for JSONLines dataset | [
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] | closed | false | null | 1 | 2022-03-18T15:17:53Z | 2022-05-06T16:13:51Z | 2022-05-06T16:13:51Z | null | ## Describe the bug
One of the [course participants](https://discuss.huggingface.co/t/chapter-5-questions/11744/20?u=lewtun) is having trouble loading a JSONLines dataset that's composed of the GitHub issues from `spacy` (see stack trace below).
This reminds me a bit of #2799 where one can load the dataset in `pandas` but not in `datasets` and perhaps increasing the `block_size` is needed again.
## Steps to reproduce the bug
```python
from datasets import load_dataset
from huggingface_hub import hf_hub_url
import pandas as pd
# returns 'https://huggingface.co/datasets/Evan/spaCy-github-issues/resolve/main/spacy-issues.jsonl'
data_files = hf_hub_url(repo_id="Evan/spaCy-github-issues", filename="spacy-issues.jsonl", repo_type="dataset")
# throws TypeError: Couldn't cast array of type
dset = load_dataset("json", data_files=data_files, split="test")
# no problem with pandas - note this take a while as the file is >2GB
df = pd.read_json(data_files, orient="records", lines=True)
df.head()
```
## Expected results
I can load any line-separated JSON file, similar to pandas.
## Actual results
```
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/load.py", line 1702, in load_dataset
builder_instance.download_and_prepare(
File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/builder.py", line 594, in download_and_prepare
self._download_and_prepare(
File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/builder.py", line 683, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/builder.py", line 1136, in _prepare_split
writer.write_table(table)
File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/arrow_writer.py", line 511, in write_table
pa_table = table_cast(pa_table, self._schema)
File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/table.py", line 1121, in table_cast
return cast_table_to_features(table, Features.from_arrow_schema(schema))
File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/table.py", line 1102, in cast_table_to_features
arrays = [cast_array_to_feature(table[name], feature) for name, feature in features.items()]
File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/table.py", line 1102, in <listcomp>
arrays = [cast_array_to_feature(table[name], feature) for name, feature in features.items()]
File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/table.py", line 944, in wrapper
return func(array, *args, **kwargs)
File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/table.py", line 918, in wrapper
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/table.py", line 918, in <listcomp>
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/table.py", line 1086, in cast_array_to_feature
return array_cast(array, feature(), allow_number_to_str=allow_number_to_str)
File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/table.py", line 944, in wrapper
return func(array, *args, **kwargs)
File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/table.py", line 920, in wrapper
return func(array, *args, **kwargs)
File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/table.py", line 1019, in array_cast
raise TypeError(f"Couldn't cast array of type\n{array.type}\nto\n{pa_type}")
TypeError: Couldn't cast array of type
struct<url: string, html_url: string, labels_url: string, id: int64, node_id: string, number: int64, title: string, description: string, creator: struct<login: string, id: int64, node_id: string, avatar_url: string, gravatar_id: string, url: string, html_url: string, followers_url: string, following_url: string, gists_url: string, starred_url: string, subscriptions_url: string, organizations_url: string, repos_url: string, events_url: string, received_events_url: string, type: string, site_admin: bool>, open_issues: int64, closed_issues: int64, state: string, created_at: timestamp[s], updated_at: timestamp[s], due_on: null, closed_at: timestamp[s]>
to
null
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 2.0.0
- Platform: macOS-10.16-x86_64-i386-64bit
- Python version: 3.9.7
- PyArrow version: 7.0.0
- Pandas version: 1.4.1
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} | https://api.github.com/repos/huggingface/datasets/issues/3965/timeline | null | completed | null | null | false | [
"Hi @lewtun, thanks for reporting.\r\n\r\nIt seems that our library fails at inferring the dtype of the columns:\r\n- `milestone`\r\n- `performed_via_github_app` \r\n\r\n(and assigns them `null` dtype)."
] |
https://api.github.com/repos/huggingface/datasets/issues/2858 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2858/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2858/comments | https://api.github.com/repos/huggingface/datasets/issues/2858/events | https://github.com/huggingface/datasets/pull/2858 | 984,145,568 | MDExOlB1bGxSZXF1ZXN0NzIzNjEzNzQ0 | 2,858 | Fix s3fs version in CI | [] | closed | false | null | 0 | 2021-08-31T18:05:43Z | 2021-09-06T13:33:35Z | 2021-08-31T21:29:51Z | null | The latest s3fs version has new constrains on aiobotocore, and therefore on boto3 and botocore
This PR changes the constrains to avoid the new conflicts
In particular it pins the version of s3fs. | {
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https://api.github.com/repos/huggingface/datasets/issues/5569 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5569/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5569/comments | https://api.github.com/repos/huggingface/datasets/issues/5569/events | https://github.com/huggingface/datasets/pull/5569 | 1,597,132,383 | PR_kwDODunzps5KnwHD | 5,569 | pass the dataset features to the IterableDataset.from_generator function | [] | closed | false | null | 3 | 2023-02-23T16:06:04Z | 2023-02-24T14:06:37Z | 2023-02-23T18:15:16Z | null | [5558](https://github.com/huggingface/datasets/issues/5568) | {
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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... |
https://api.github.com/repos/huggingface/datasets/issues/2992 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2992/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2992/comments | https://api.github.com/repos/huggingface/datasets/issues/2992/events | https://github.com/huggingface/datasets/pull/2992 | 1,012,325,594 | PR_kwDODunzps4sg4ZP | 2,992 | Fix f1 metric with None average | [] | closed | false | null | 0 | 2021-09-30T15:31:57Z | 2021-10-01T14:17:39Z | 2021-10-01T14:17:38Z | null | Fix #2979. | {
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https://api.github.com/repos/huggingface/datasets/issues/5520 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5520/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5520/comments | https://api.github.com/repos/huggingface/datasets/issues/5520/events | https://github.com/huggingface/datasets/issues/5520 | 1,578,417,074 | I_kwDODunzps5eFLuy | 5,520 | ClassLabel.cast_storage raises TypeError when called on an empty IntegerArray | [] | closed | false | null | 0 | 2023-02-09T18:46:52Z | 2023-02-12T11:17:18Z | 2023-02-12T11:17:18Z | null | ### Describe the bug
`ClassLabel.cast_storage` raises `TypeError` when called on an empty `IntegerArray`.
### Steps to reproduce the bug
Minimal steps:
```python
import pyarrow as pa
from datasets import ClassLabel
ClassLabel(names=['foo', 'bar']).cast_storage(pa.array([], pa.int64()))
```
In practice, this bug arises in situations like the one below:
```python
from datasets import ClassLabel, Dataset, Features, Sequence
dataset = Dataset.from_dict({'labels': [[], []]}, features=Features({'labels': Sequence(ClassLabel(names=['foo', 'bar']))}))
# this raises TypeError
dataset.map(batched=True, batch_size=1)
```
### Expected behavior
`ClassLabel.cast_storage` should return an empty Int64Array.
### Environment info
- `datasets` version: 2.9.1.dev0
- Platform: Linux-4.15.0-1032-aws-x86_64-with-glibc2.27
- Python version: 3.10.6
- PyArrow version: 11.0.0
- Pandas version: 1.5.3 | {
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https://api.github.com/repos/huggingface/datasets/issues/195 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/195/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/195/comments | https://api.github.com/repos/huggingface/datasets/issues/195/events | https://github.com/huggingface/datasets/pull/195 | 624,858,686 | MDExOlB1bGxSZXF1ZXN0NDIzMTg1NTAy | 195 | [Dummy data command] add new case to command | [] | closed | false | null | 1 | 2020-05-26T12:50:47Z | 2020-05-26T14:38:28Z | 2020-05-26T14:38:27Z | null | Qanta: #194 introduces a case that was not noticed before. This change in code helps community users to have an easier time creating the dummy data. | {
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"@lhoestq - tiny change in the dummy data command, should be good to merge."
] |
https://api.github.com/repos/huggingface/datasets/issues/3297 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3297/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3297/comments | https://api.github.com/repos/huggingface/datasets/issues/3297/events | https://github.com/huggingface/datasets/issues/3297 | 1,058,263,859 | I_kwDODunzps4_E9Mz | 3,297 | .map() cache is wrongfully reused - only happens when the mapping function is imported | [
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"description": "Something isn't working",
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"name": "bug",
"node_id": "MDU6TGFiZWwxOTM1ODkyODU3",
"url": "https://api.github.com/repos/huggingface/datasets/labels/bug"
}
] | open | false | null | 3 | 2021-11-19T08:18:36Z | 2023-01-30T12:40:17Z | null | null | ## Describe the bug
When `.map` is used with a mapping function that is imported, the cache is reused even if the mapping function has been modified.
The reason for this is that `dill` that is used for creating the fingerprint [pickles imported functions by reference](https://stackoverflow.com/a/67851411).
I guess it is not a widespread case, but it can still lead to unwanted results unnoticeably.
## Steps to reproduce the bug
Create files `a.py` and `b.py`:
```python
# a.py
from datasets import load_dataset
def main():
squad = load_dataset("squad")
squad.map(mapping_func, batched=True)
def mapping_func(examples):
ID_LENGTH = 4
examples["id"] = [id_[:ID_LENGTH] for id_ in examples["id"]]
return examples
if __name__ == "__main__":
main()
```
```python
# b.py
from datasets import load_dataset
from a import mapping_func
def main():
squad = load_dataset("squad")
squad.map(mapping_func, batched=True)
if __name__ == "__main__":
main()
```
Run `python b.py` twice: In the first run you will see tqdm bars showing that the data is processed, and in the second run you will see "Loading cached processed dataset at...".
Now change `ID_LENGTH` to another number in order to change the mapping function, and run `python b.py` again. You'll see that `.map` loads from the cache the result of the previous mapping function.
## Expected results
Run `python a.py` twice: In the first run you will see tqdm bars showing that the data is processed, and in the second run you will see "Loading cached processed dataset at...".
Now change `ID_LENGTH` to another number in order to change the mapping function, and run `python a.py` again. You'll see that the dataset is being processed and that there's no reuse of the previous mapping function result.
## Workaround
Put the mapping function inside a dummy class as a static method:
```python
# a.py
class MappingFuncClass:
@staticmethod
def mapping_func(examples):
ID_LENGTH = 4
examples["id"] = [id_[:ID_LENGTH] for id_ in examples["id"]]
return examples
```
```python
# b.py
from datasets import load_dataset
from a import MappingFuncClass
def main():
squad = load_dataset("squad")
squad.map(MappingFuncClass.mapping_func, batched=True)
if __name__ == "__main__":
main()
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.15.1
- Platform: Linux-4.4.0-19041-Microsoft-x86_64-with-glibc2.17
- Python version: 3.8.10
- PyArrow version: 4.0.1
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} | https://api.github.com/repos/huggingface/datasets/issues/3297/timeline | null | null | null | null | false | [
"Hi ! Thanks for reporting. Indeed this is a current limitation of the usage we have of `dill` in `datasets`. I'd suggest you use your workaround for now until we find a way to fix this. Maybe functions that are not coming from a module not installed with pip should be dumped completely, rather than only taking the... |
https://api.github.com/repos/huggingface/datasets/issues/3391 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3391/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3391/comments | https://api.github.com/repos/huggingface/datasets/issues/3391/events | https://github.com/huggingface/datasets/issues/3391 | 1,072,849,055 | I_kwDODunzps4_8mCf | 3,391 | method to select columns | [
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] | closed | false | null | 1 | 2021-12-07T02:44:19Z | 2021-12-07T02:45:27Z | 2021-12-07T02:45:27Z | null | **Is your feature request related to a problem? Please describe.**
* There is currently no way to select some columns of a dataset. In pandas, one can use `df[['col1', 'col2']]` to select columns, but in `datasets`, it results in error.
**Describe the solution you'd like**
* A new method that can be used to create a new dataset with only a list of specified columns.
**Describe alternatives you've considered**
`.remove_columns(self, columns: Union[str, List[str]], inverse: bool = False)`
Or
`.select(self, indices: Iterable = None, columns: List[str] = None)`
| {
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"duplicate of #2655"
] |
https://api.github.com/repos/huggingface/datasets/issues/5087 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5087/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5087/comments | https://api.github.com/repos/huggingface/datasets/issues/5087/events | https://github.com/huggingface/datasets/pull/5087 | 1,400,487,967 | PR_kwDODunzps5AW-N9 | 5,087 | Fix filter with empty indices | [] | closed | false | null | 1 | 2022-10-07T01:07:00Z | 2022-10-07T18:43:03Z | 2022-10-07T18:40:26Z | null | Fix #5085 | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] |
https://api.github.com/repos/huggingface/datasets/issues/2906 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2906/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2906/comments | https://api.github.com/repos/huggingface/datasets/issues/2906/events | https://github.com/huggingface/datasets/pull/2906 | 995,962,905 | PR_kwDODunzps4rulH- | 2,906 | feat: 🎸 add a function to get a dataset config's split names | [] | closed | false | null | 1 | 2021-09-14T12:31:22Z | 2021-10-04T09:55:38Z | 2021-10-04T09:55:37Z | null | Also: pass additional arguments (use_auth_token) to get private configs + info of private datasets on the hub
Questions:
- [x] I'm not sure how the versions work: I changed 1.12.1.dev0 to 1.12.1.dev1, was it correct?
-> no: reverted
- [x] Should I add a section in https://github.com/huggingface/datasets/blob/master/docs/source/load_hub.rst? (there is no section for get_dataset_infos)
-> yes: added | {
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"> Should I add a section in https://github.com/huggingface/datasets/blob/master/docs/source/load_hub.rst? (there is no section for get_dataset_infos)\r\n\r\nYes totally :) This tutorial should indeed mention this, given how fundamental it is"
] |
https://api.github.com/repos/huggingface/datasets/issues/5363 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5363/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5363/comments | https://api.github.com/repos/huggingface/datasets/issues/5363/events | https://github.com/huggingface/datasets/issues/5363 | 1,498,171,317 | I_kwDODunzps5ZTEe1 | 5,363 | Dataset.from_generator() crashes on simple example | [] | closed | false | null | 0 | 2022-12-15T10:21:28Z | 2022-12-15T11:51:33Z | 2022-12-15T11:51:33Z | null | null | {
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https://api.github.com/repos/huggingface/datasets/issues/2618 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2618/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2618/comments | https://api.github.com/repos/huggingface/datasets/issues/2618/events | https://github.com/huggingface/datasets/issues/2618 | 940,852,640 | MDU6SXNzdWU5NDA4NTI2NDA= | 2,618 | `filelock.py` Error | [
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] | open | false | null | 1 | 2021-07-09T15:12:49Z | 2021-07-12T06:20:30Z | null | null | ## Describe the bug
It seems that the `filelock.py` went error.
```
>>> ds=load_dataset('xsum')
^CTraceback (most recent call last):
File "/user/HS502/yl02706/.conda/envs/lyc/lib/python3.6/site-packages/datasets/utils/filelock.py", line 402, in _acquire
fcntl.flock(fd, fcntl.LOCK_EX | fcntl.LOCK_NB)
OSError: [Errno 37] No locks available
```
According to error log, it is OSError, but there is an `except` in the `_acquire` function.
```
def _acquire(self):
open_mode = os.O_WRONLY | os.O_CREAT | os.O_EXCL | os.O_TRUNC
try:
fd = os.open(self._lock_file, open_mode)
except (IOError, OSError):
pass
else:
self._lock_file_fd = fd
return None
```
I don't know why it stucked rather than `pass` directly.
I am not quite familiar with filelock operation, so any help is highly appriciated.
## Steps to reproduce the bug
```python
ds = load_dataset('xsum')
```
## Expected results
A clear and concise description of the expected results.
## Actual results
```
>>> ds=load_dataset('xsum')
^CTraceback (most recent call last):
File "/user/HS502/yl02706/.conda/envs/lyc/lib/python3.6/site-packages/datasets/utils/filelock.py", line 402, in _acquire
fcntl.flock(fd, fcntl.LOCK_EX | fcntl.LOCK_NB)
OSError: [Errno 37] No locks available
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/user/HS502/yl02706/.conda/envs/lyc/lib/python3.6/site-packages/datasets/load.py", line 818, in load_dataset
use_auth_token=use_auth_token,
File "/user/HS502/yl02706/.conda/envs/lyc/lib/python3.6/site-packages/datasets/load.py", line 470, in prepare_module
with FileLock(lock_path):
File "/user/HS502/yl02706/.conda/envs/lyc/lib/python3.6/site-packages/datasets/utils/filelock.py", line 323, in __enter__
self.acquire()
File "/user/HS502/yl02706/.conda/envs/lyc/lib/python3.6/site-packages/datasets/utils/filelock.py", line 272, in acquire
self._acquire()
File "/user/HS502/yl02706/.conda/envs/lyc/lib/python3.6/site-packages/datasets/utils/filelock.py", line 402, in _acquire
fcntl.flock(fd, fcntl.LOCK_EX | fcntl.LOCK_NB)
KeyboardInterrupt
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.9.0
- Platform: Linux-4.15.0-135-generic-x86_64-with-debian-buster-sid
- Python version: 3.6.13
- PyArrow version: 4.0.1
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} | https://api.github.com/repos/huggingface/datasets/issues/2618/timeline | null | null | null | null | false | [
"Hi @liyucheng09, thanks for reporting.\r\n\r\nApparently this issue has to do with your environment setup. One question: is your data in an NFS share? Some people have reported this error when using `fcntl` to write to an NFS share... If this is the case, then it might be that your NFS just may not be set up to pr... |
https://api.github.com/repos/huggingface/datasets/issues/1288 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1288/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1288/comments | https://api.github.com/repos/huggingface/datasets/issues/1288/events | https://github.com/huggingface/datasets/pull/1288 | 759,309,457 | MDExOlB1bGxSZXF1ZXN0NTM0MzM2Mzgz | 1,288 | Add CodeSearchNet corpus dataset | [] | closed | false | null | 1 | 2020-12-08T10:07:50Z | 2020-12-09T17:05:28Z | 2020-12-09T17:05:28Z | null | This PR adds the CodeSearchNet corpus proxy dataset for semantic code search: https://github.com/github/CodeSearchNet
I have had a few issues, mentioned below. Would appreciate some help on how to solve them.
## Issues generating dataset card
Is there something wrong with my declaration of the dataset features ?
```
features=datasets.Features(
{
"repository_name": datasets.Value("string"),
"func_path_in_repository": datasets.Value("string"),
"func_name": datasets.Value("string"),
"whole_func_string": datasets.Value("string"),
"language": datasets.Value("string"),
"func_code_string": datasets.Value("string"),
"func_code_tokens": datasets.Sequence(datasets.Value("string")),
"func_documentation_string": datasets.Value("string"),
"func_documentation_tokens": datasets.Sequence(datasets.Value("string")),
"split_name": datasets.Value("string"),
"func_code_url": datasets.Value("string"),
# TODO - add licensing info in the examples
}
),
```
When running the streamlite app for tagging the dataset on my machine, I get the following error :
## Issues with dummy data
Due to the unusual structure of the data, I have been unable to generate dummy data automatically.
I tried to generate it manually, but pytests fail when using the manually-generated dummy data ! Pytests work fine when using the real data.
```
============================================================================================== test session starts ==============================================================================================
platform linux -- Python 3.7.9, pytest-6.1.2, py-1.9.0, pluggy-0.13.1
plugins: xdist-2.1.0, forked-1.3.0
collected 1 item
tests/test_dataset_common.py F [100%]
=================================================================================================== FAILURES ====================================================================================================
________________________________________________________________________ LocalDatasetTest.test_load_dataset_all_configs_code_search_net _________________________________________________________________________
self = <tests.test_dataset_common.LocalDatasetTest testMethod=test_load_dataset_all_configs_code_search_net>, dataset_name = 'code_search_net'
@slow
def test_load_dataset_all_configs(self, dataset_name):
configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)
> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True)
tests/test_dataset_common.py:237:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
tests/test_dataset_common.py:198: in check_load_dataset
self.parent.assertTrue(len(dataset[split]) > 0)
E AssertionError: False is not true
--------------------------------------------------------------------------------------------- Captured stdout call ----------------------------------------------------------------------------------------------
Downloading and preparing dataset code_search_net/all (download: 1.00 MiB, generated: 1.00 MiB, post-processed: Unknown size, total: 2.00 MiB) to /tmp/tmppx78sj24/code_search_net/all/1.0.0...
Dataset code_search_net downloaded and prepared to /tmp/tmppx78sj24/code_search_net/all/1.0.0. Subsequent calls will reuse this data.
--------------------------------------------------------------------------------------------- Captured stderr call ----------------------------------------------------------------------------------------------
... (irrelevant info - Deprecation warnings)
============================================================================================ short test summary info ============================================================================================
FAILED tests/test_dataset_common.py::LocalDatasetTest::test_load_dataset_all_configs_code_search_net - AssertionError: False is not true
========================================================================================= 1 failed, 4 warnings in 3.00s ========================================================================================
```
## Note : Data structure in S3
The data is stored on S3, and organized by programming languages.
It is stored in the following repository structure:
```
.
├── <language_name> # e.g. python
│ └── final
│ └── jsonl
│ ├── test
│ │ └── <language_name>_test_0.jsonl.gz
│ ├── train
│ │ ├── <language_name>_train_0.jsonl.gz
│ │ ├── <language_name>_train_1.jsonl.gz
│ │ ├── ...
│ │ └── <language_name>_train_n.jsonl.gz
│ └── valid
│ └── <language_name>_valid_0.jsonl.gz
├── <language_name>_dedupe_definitions_v2.pkl
└── <language_name>_licenses.pkl
``` | {
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"@lhoestq ready for a second review"
] |
https://api.github.com/repos/huggingface/datasets/issues/3056 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3056/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3056/comments | https://api.github.com/repos/huggingface/datasets/issues/3056/events | https://github.com/huggingface/datasets/pull/3056 | 1,022,345,564 | PR_kwDODunzps4tAB9h | 3,056 | Fix meteor metric for version >= 3.6.4 | [] | closed | false | null | 0 | 2021-10-11T07:11:44Z | 2021-10-11T07:29:20Z | 2021-10-11T07:29:19Z | null | After `nltk` update, the meteor metric expects pre-tokenized inputs (breaking change).
This PR fixes this issue, while maintaining compatibility with older versions. | {
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https://api.github.com/repos/huggingface/datasets/issues/2150 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2150/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2150/comments | https://api.github.com/repos/huggingface/datasets/issues/2150/events | https://github.com/huggingface/datasets/pull/2150 | 844,776,448 | MDExOlB1bGxSZXF1ZXN0NjAzOTg3OTcx | 2,150 | Allow pickling of big in-memory tables | [] | closed | false | null | 0 | 2021-03-30T15:51:56Z | 2021-03-31T10:37:15Z | 2021-03-31T10:37:14Z | null | This should fix issue #2134
Pickling is limited to <4GiB objects, it's not possible to pickle a big arrow table (for multiprocessing for example).
For big tables, we have to write them on disk and only pickle the path to the table. | {
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https://api.github.com/repos/huggingface/datasets/issues/2943 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2943/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2943/comments | https://api.github.com/repos/huggingface/datasets/issues/2943/events | https://github.com/huggingface/datasets/issues/2943 | 1,000,355,115 | I_kwDODunzps47oDUr | 2,943 | Backwards compatibility broken for cached datasets that use `.filter()` | [
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] | closed | false | null | 6 | 2021-09-19T16:16:37Z | 2021-09-20T16:25:43Z | 2021-09-20T16:25:42Z | null | ## Describe the bug
After upgrading to datasets `1.12.0`, some cached `.filter()` steps from `1.11.0` started failing with
`ValueError: Keys mismatch: between {'indices': Value(dtype='uint64', id=None)} and {'file': Value(dtype='string', id=None), 'text': Value(dtype='string', id=None), 'speaker_id': Value(dtype='int64', id=None), 'chapter_id': Value(dtype='int64', id=None), 'id': Value(dtype='string', id=None)}`
Related feature: https://github.com/huggingface/datasets/pull/2836
:question: This is probably a `wontfix` bug, since it can be solved by simply cleaning the related cache dirs, but the workaround could be useful for someone googling the error :)
## Workaround
Remove the cache for the given dataset, e.g. `rm -rf ~/.cache/huggingface/datasets/librispeech_asr`.
## Steps to reproduce the bug
1. Delete `~/.cache/huggingface/datasets/librispeech_asr` if it exists.
2. `pip install datasets==1.11.0` and run the following snippet:
```python
from datasets import load_dataset
ids = ["1272-141231-0000"]
ds = load_dataset("patrickvonplaten/librispeech_asr_dummy", "clean", split="validation")
ds = ds.filter(lambda x: x["id"] in ids)
```
3. `pip install datasets==1.12.1` and re-run the code again
## Expected results
Same result as with the previous `datasets` version.
## Actual results
```bash
Reusing dataset librispeech_asr (./.cache/huggingface/datasets/librispeech_asr/clean/2.1.0/468ec03677f46a8714ac6b5b64dba02d246a228d92cbbad7f3dc190fa039eab1)
Loading cached processed dataset at ./.cache/huggingface/datasets/librispeech_asr/clean/2.1.0/468ec03677f46a8714ac6b5b64dba02d246a228d92cbbad7f3dc190fa039eab1/cache-cd1c29844fdbc87a.arrow
Traceback (most recent call last):
File "./repos/transformers/src/transformers/models/wav2vec2/try_dataset.py", line 5, in <module>
ds = ds.filter(lambda x: x["id"] in ids)
File "./envs/transformers/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 185, in wrapper
out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
File "./envs/transformers/lib/python3.8/site-packages/datasets/fingerprint.py", line 398, in wrapper
out = func(self, *args, **kwargs)
File "./envs/transformers/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 2169, in filter
indices = self.map(
File "./envs/transformers/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 1686, in map
return self._map_single(
File "./envs/transformers/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 185, in wrapper
out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
File "./envs/transformers/lib/python3.8/site-packages/datasets/fingerprint.py", line 398, in wrapper
out = func(self, *args, **kwargs)
File "./envs/transformers/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 1896, in _map_single
return Dataset.from_file(cache_file_name, info=info, split=self.split)
File "./envs/transformers/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 343, in from_file
return cls(
File "./envs/transformers/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 282, in __init__
self.info.features = self.info.features.reorder_fields_as(inferred_features)
File "./envs/transformers/lib/python3.8/site-packages/datasets/features.py", line 1151, in reorder_fields_as
return Features(recursive_reorder(self, other))
File "./envs/transformers/lib/python3.8/site-packages/datasets/features.py", line 1140, in recursive_reorder
raise ValueError(f"Keys mismatch: between {source} and {target}" + stack_position)
ValueError: Keys mismatch: between {'indices': Value(dtype='uint64', id=None)} and {'file': Value(dtype='string', id=None), 'text': Value(dtype='string', id=None), 'speaker_id': Value(dtype='int64', id=None), 'chapter_id': Value(dtype='int64', id=None), 'id': Value(dtype='string', id=None)}
Process finished with exit code 1
```
## Environment info
- `datasets` version: 1.12.1
- Platform: Linux-5.11.0-34-generic-x86_64-with-glibc2.17
- Python version: 3.8.10
- PyArrow version: 5.0.0
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"Hi ! I guess the caching mechanism should have considered the new `filter` to be different from the old one, and don't use cached results from the old `filter`.\r\nTo avoid other users from having this issue we could make the caching differentiate the two, what do you think ?",
"If it's easy enough to implement,... |
https://api.github.com/repos/huggingface/datasets/issues/2145 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2145/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2145/comments | https://api.github.com/repos/huggingface/datasets/issues/2145/events | https://github.com/huggingface/datasets/pull/2145 | 844,603,518 | MDExOlB1bGxSZXF1ZXN0NjAzODMxOTE2 | 2,145 | Implement Dataset add_column | [
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} | 1 | 2021-03-30T14:02:14Z | 2021-04-29T14:50:44Z | 2021-04-29T14:50:43Z | null | Implement `Dataset.add_column`.
Close #1954. | {
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"#2274 has been merged. You can now merge master into this branch and use `assert_arrow_metadata_are_synced_with_dataset_features(dset)` to make sure that the metadata are good :)"
] |
https://api.github.com/repos/huggingface/datasets/issues/1645 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1645/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1645/comments | https://api.github.com/repos/huggingface/datasets/issues/1645/events | https://github.com/huggingface/datasets/pull/1645 | 775,473,106 | MDExOlB1bGxSZXF1ZXN0NTQ2MTQ4OTUx | 1,645 | Rename "part-of-speech-tagging" tag in some dataset cards | [] | closed | false | null | 0 | 2020-12-28T16:09:09Z | 2021-01-07T10:08:14Z | 2021-01-07T10:08:13Z | null | `part-of-speech-tagging` was not part of the tagging taxonomy under `structure-prediction` | {
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https://api.github.com/repos/huggingface/datasets/issues/879 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/879/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/879/comments | https://api.github.com/repos/huggingface/datasets/issues/879/events | https://github.com/huggingface/datasets/issues/879 | 748,848,847 | MDU6SXNzdWU3NDg4NDg4NDc= | 879 | boolq does not load | [
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] | closed | false | null | 3 | 2020-11-23T14:28:28Z | 2022-10-05T12:23:32Z | 2022-10-05T12:23:32Z | null | Hi
I am getting these errors trying to load boolq thanks
Traceback (most recent call last):
File "test.py", line 5, in <module>
data = AutoTask().get("boolq").get_dataset("train", n_obs=10)
File "/remote/idiap.svm/user.active/rkarimi/dev/internship/seq2seq/tasks/tasks.py", line 42, in get_dataset
dataset = self.load_dataset(split=split)
File "/remote/idiap.svm/user.active/rkarimi/dev/internship/seq2seq/tasks/tasks.py", line 38, in load_dataset
return datasets.load_dataset(self.task.name, split=split)
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/load.py", line 611, in load_dataset
ignore_verifications=ignore_verifications,
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/builder.py", line 476, in download_and_prepare
dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/builder.py", line 531, in _download_and_prepare
split_generators = self._split_generators(dl_manager, **split_generators_kwargs)
File " /idiap/home/rkarimi/.cache/huggingface/modules/datasets_modules/datasets/boolq/2987db1f15deaa19500ae24de560eabeaf1f8ef51df88c0470beeec72943bf11/boolq.py", line 74, in _split_generators
downloaded_files = dl_manager.download_custom(urls_to_download, tf.io.gfile.copy)
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/utils/download_manager.py", line 150, in download_custom
get_from_cache(url, cache_dir=cache_dir, local_files_only=True, use_etag=False)
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 472, in get_from_cache
f"Cannot find the requested files in the cached path at {cache_path} and outgoing traffic has been"
FileNotFoundError: Cannot find the requested files in the cached path at /idiap/home/rkarimi/.cache/huggingface/datasets/eaee069e38f6ceaa84de02ad088c34e63ec97671f2cd1910ddb16b10dc60808c and outgoing traffic has been disabled. To enable file online look-ups, set 'local_files_only' to False.
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} | https://api.github.com/repos/huggingface/datasets/issues/879/timeline | null | completed | null | null | false | [
"Hi ! It runs on my side without issues. I tried\r\n```python\r\nfrom datasets import load_dataset\r\nload_dataset(\"boolq\")\r\n```\r\n\r\nWhat version of datasets and tensorflow are your runnning ?\r\nAlso if you manage to get a minimal reproducible script (on google colab for example) that would be useful.",
"... |
https://api.github.com/repos/huggingface/datasets/issues/5299 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5299/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5299/comments | https://api.github.com/repos/huggingface/datasets/issues/5299/events | https://github.com/huggingface/datasets/pull/5299 | 1,464,695,091 | PR_kwDODunzps5Dt3Sk | 5,299 | Fix xopen for Windows pathnames | [] | closed | false | null | 1 | 2022-11-25T15:35:28Z | 2022-11-29T08:23:58Z | 2022-11-29T08:21:24Z | null | This PR fixes a bug in `xopen` function for Windows pathnames.
Fix #5298. | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] |
https://api.github.com/repos/huggingface/datasets/issues/3989 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3989/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3989/comments | https://api.github.com/repos/huggingface/datasets/issues/3989/events | https://github.com/huggingface/datasets/pull/3989 | 1,176,955,078 | PR_kwDODunzps400l1S | 3,989 | Remove old wikipedia leftovers | [] | closed | false | null | 3 | 2022-03-22T15:25:46Z | 2022-03-31T15:35:26Z | 2022-03-31T15:30:16Z | null | After updating Wikipedia dataset, remove old wikipedia leftovers from doc.
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"_The documentation is not available anymore as the PR was closed or merged._",
"> This makes me think we shouldn't advise the use of load_dataset in dataset scripts, since it doesn't guarantee that the cache will work as expected (the cache directory is not set correctly, and the required disk space for download... |
https://api.github.com/repos/huggingface/datasets/issues/3488 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3488/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3488/comments | https://api.github.com/repos/huggingface/datasets/issues/3488/events | https://github.com/huggingface/datasets/issues/3488 | 1,089,345,653 | I_kwDODunzps5A7hh1 | 3,488 | URL query parameters are set as path in the compression hop for fsspec | [
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] | open | false | null | 1 | 2021-12-27T16:29:00Z | 2022-01-05T15:15:25Z | null | null | ## Describe the bug
There is an ssue with `StreamingDownloadManager._extract`.
I don't know how the test `test_streaming_gg_drive_gzipped` passes:
For
```python
TEST_GG_DRIVE_GZIPPED_URL = "https://drive.google.com/uc?export=download&id=1Bt4Garpf0QLiwkJhHJzXaVa0I0H5Qhwz"
urlpath = StreamingDownloadManager().download_and_extract(TEST_GG_DRIVE_GZIPPED_URL)
```
gives `urlpath`:
```python
'gzip://uc?export=download&id=1Bt4Garpf0QLiwkJhHJzXaVa0I0H5Qhwz::https://drive.google.com/uc?export=download&id=1Bt4Garpf0QLiwkJhHJzXaVa0I0H5Qhwz'
```
The gzip path makes no sense: `gzip://uc?export=download&id=1Bt4Garpf0QLiwkJhHJzXaVa0I0H5Qhwz`
## Steps to reproduce the bug
```python
from datasets.utils.streaming_download_manager import StreamingDownloadManager
dl_manager = StreamingDownloadManager()
urlpath = dl_manager.extract("https://drive.google.com/uc?export=download&id=1Bt4Garpf0QLiwkJhHJzXaVa0I0H5Qhwz")
print(urlpath)
```
## Expected results
The query parameters should not be set as part of the path.
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"I think the test passes because it simply ignore what's after `gzip://`.\r\n\r\nThe returned urlpath is expected to look like `gzip://filename::url`, and the filename is currently considered to be what's after the final `/`, hence the result.\r\n\r\nWe can decide to change this and simply have `gzip://::url`, this... |
https://api.github.com/repos/huggingface/datasets/issues/5459 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5459/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5459/comments | https://api.github.com/repos/huggingface/datasets/issues/5459/events | https://github.com/huggingface/datasets/pull/5459 | 1,555,367,504 | PR_kwDODunzps5Icjwe | 5,459 | Disable aiohttp requoting of redirection URL | [] | closed | false | null | 7 | 2023-01-24T17:18:59Z | 2023-02-01T08:45:33Z | 2023-01-31T08:37:54Z | null | The library `aiohttp` performs a requoting of redirection URLs that unquotes the single quotation mark character: `%27` => `'`
This is a problem for our Hugging Face Hub, which requires exact URL from location header.
Specifically, in the query component of the URL (`https://netloc/path?query`), the value for `response-content-disposition` contains `%27`:
```
response-content-disposition=attachment%3B+filename*%3DUTF-8%27%27sample.jsonl.gz%3B+filename%3D%22sample.jsonl.gz%22%3B
```
and after the requoting, the `%27` characters get unquoted to `'`:
```
response-content-disposition=attachment%3B+filename*%3DUTF-8''sample.jsonl.gz%3B+filename%3D%22sample.jsonl.gz%22%3B
```
This PR disables the `aiohttp` requoting of redirection URLs. | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Comment by @lhoestq:\r\n> Do you think we need this in `datasets` if it's fixed on the moon landing side ? In the aiohttp doc they consider those symbols as \"non-safe\" ",
"The lib `requests` does not perform that requote on redir... |
https://api.github.com/repos/huggingface/datasets/issues/1011 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1011/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1011/comments | https://api.github.com/repos/huggingface/datasets/issues/1011/events | https://github.com/huggingface/datasets/pull/1011 | 755,463,726 | MDExOlB1bGxSZXF1ZXN0NTMxMTY5MjA3 | 1,011 | Add Bilingual Corpus of Arabic-English Parallel Tweets | [] | closed | false | null | 6 | 2020-12-02T17:20:02Z | 2020-12-04T14:45:10Z | 2020-12-04T14:44:33Z | null | Added Bilingual Corpus of Arabic-English Parallel Tweets. The link to the dataset can be found [here](https://alt.qcri.org/wp-content/uploads/2020/08/Bilingual-Corpus-of-Arabic-English-Parallel-Tweets.zip) and the paper can be found [here](https://www.aclweb.org/anthology/2020.bucc-1.3.pdf)
- [x] Followed the instructions in CONTRIBUTING.md
- [x] Ran the tests successfully
- [x] Created the dummy data | {
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"IMO, the problem with this dataset is that it is not really a text/nlp dataset. These are just collections of tweet ids. So, ultimately, one needs to crawl twitter to get the actual text.",
"That's true.\r\n\r\n",
"at least it's clear in the description that one needs to collect the tweets : \r\n```\r\nThis re... |
https://api.github.com/repos/huggingface/datasets/issues/5115 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5115/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5115/comments | https://api.github.com/repos/huggingface/datasets/issues/5115/events | https://github.com/huggingface/datasets/pull/5115 | 1,409,250,020 | PR_kwDODunzps5Az9Pm | 5,115 | Fix iter_batches | [] | closed | false | null | 3 | 2022-10-14T12:06:14Z | 2022-10-14T15:02:15Z | 2022-10-14T14:59:58Z | null | The `pa.Table.to_reader()` method available in `pyarrow>=8.0.0` may return chunks of size < `max_chunksize`, therefore `iter_batches` can return batches smaller than the `batch_size` specified by the user
Therefore batched `map` couldn't always use batches of the right size, e.g. this fails because it runs only on one batch of one element:
```python
from datasets import Dataset, concatenate_datasets
ds = concatenate_datasets([Dataset.from_dict({"a": [i]}) for i in range(10)])
ds2 = ds.map(lambda _: {}, batched=True)
assert list(ds2) == list(ds)
```
This was introduced in https://github.com/huggingface/datasets/pull/5030
Close https://github.com/huggingface/datasets/issues/5111
This will require a patch release along with https://github.com/huggingface/datasets/pull/5113
TODO:
- [x] fix tests
- [x] add more tests | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"I also ran the code in https://github.com/huggingface/datasets/issues/5111 and it works fine now :)",
"This is ready for review :)"
] |
https://api.github.com/repos/huggingface/datasets/issues/551 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/551/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/551/comments | https://api.github.com/repos/huggingface/datasets/issues/551/events | https://github.com/huggingface/datasets/pull/551 | 690,034,762 | MDExOlB1bGxSZXF1ZXN0NDc2OTkwNjAw | 551 | added HANS dataset | [] | closed | false | null | 0 | 2020-09-01T10:42:02Z | 2020-09-01T12:17:10Z | 2020-09-01T12:17:10Z | null | Adds the [HANS](https://github.com/tommccoy1/hans) dataset to evaluate NLI systems. | {
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https://api.github.com/repos/huggingface/datasets/issues/4840 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4840/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4840/comments | https://api.github.com/repos/huggingface/datasets/issues/4840/events | https://github.com/huggingface/datasets/issues/4840 | 1,337,342,672 | I_kwDODunzps5PtjrQ | 4,840 | Dataset Viewer issue for darragh/demo_data_raw3 | [] | open | false | null | 5 | 2022-08-12T15:22:58Z | 2022-09-08T07:55:44Z | null | null | ### Link
https://huggingface.co/datasets/darragh/demo_data_raw3
### Description
```
Exception: ValueError
Message: Arrow type extension<arrow.py_extension_type<pyarrow.lib.UnknownExtensionType>> does not have a datasets dtype equivalent.
```
reported by @NielsRogge
### Owner
No | {
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"do you have an idea of why it can occur @huggingface/datasets? The dataset consists of a single parquet file.",
"Thanks for reporting @severo.\r\n\r\nI'm not able to reproduce that error. I get instead:\r\n```\r\nFileNotFoundError: [Errno 2] No such file or directory: 'orix/data/ChiSig/唐合乐-9-3.jpg'\r\n```\r\n\r\... |
https://api.github.com/repos/huggingface/datasets/issues/5395 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5395/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5395/comments | https://api.github.com/repos/huggingface/datasets/issues/5395/events | https://github.com/huggingface/datasets/pull/5395 | 1,513,997,335 | PR_kwDODunzps5GXLUl | 5,395 | Temporarily pin pydantic test dependency | [] | closed | false | null | 3 | 2022-12-29T19:34:19Z | 2022-12-30T06:36:57Z | 2022-12-29T21:00:26Z | null | Temporarily pin `pydantic` until a permanent solution is found.
Fix #5394. | {
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https://api.github.com/repos/huggingface/datasets/issues/1494 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1494/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1494/comments | https://api.github.com/repos/huggingface/datasets/issues/1494/events | https://github.com/huggingface/datasets/pull/1494 | 762,992,601 | MDExOlB1bGxSZXF1ZXN0NTM3NDg2MzU4 | 1,494 | Added Opus Wikipedia | [] | closed | false | null | 1 | 2020-12-11T22:28:03Z | 2020-12-17T14:38:28Z | 2020-12-17T14:38:28Z | null | Dataset : http://opus.nlpl.eu/Wikipedia.php | {
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"merging since the CI is fixed on master"
] |
https://api.github.com/repos/huggingface/datasets/issues/4986 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4986/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4986/comments | https://api.github.com/repos/huggingface/datasets/issues/4986/events | https://github.com/huggingface/datasets/pull/4986 | 1,375,895,035 | PR_kwDODunzps4_GNSd | 4,986 | [doc] Fix broken snippet that had too many quotes | [] | closed | false | null | 2 | 2022-09-16T12:41:07Z | 2022-09-16T22:12:21Z | 2022-09-16T17:32:14Z | null | Hello!
### Pull request overview
* Fix broken snippet in https://huggingface.co/docs/datasets/main/en/process that has too many quotes
### Details
The snippet in question can be found here: https://huggingface.co/docs/datasets/main/en/process#map
This screenshot shows the issue, there is a quote too many, causing the snippet to be colored incorrectly:
The change speaks for itself.
Thank you for the detailed documentation, by the way.
- Tom Aarsen
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"_The documentation is not available anymore as the PR was closed or merged._",
"Spent the day familiarising myself with the huggingface line of products, and happened to run into some small issues here and there. Magically, I've found exactly one small issue in `transformers`, one in `accelerate` and now one in ... |
https://api.github.com/repos/huggingface/datasets/issues/5561 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5561/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5561/comments | https://api.github.com/repos/huggingface/datasets/issues/5561/events | https://github.com/huggingface/datasets/pull/5561 | 1,593,862,388 | PR_kwDODunzps5Kcxw_ | 5,561 | Add pre-commit config yaml file to enable automatic code formatting | [] | closed | false | null | 6 | 2023-02-21T17:35:07Z | 2023-02-28T15:37:22Z | 2023-02-23T18:23:29Z | null | @huggingface/datasets do you think it would be useful? Motivation - sometimes PRs are like 30% "fix: style" commits :)
If so - I need to double check the config but for me locally it works as expected. | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Better yet have someone enable pre-commit CI https://pre-commit.ci/ and it will apply the pre-commit fixes to the PR automatically as an additional commit.",
"@Skylion007 hi! I agree with @nateraw here, I'd better not force to use ... |
https://api.github.com/repos/huggingface/datasets/issues/673 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/673/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/673/comments | https://api.github.com/repos/huggingface/datasets/issues/673/events | https://github.com/huggingface/datasets/issues/673 | 709,603,989 | MDU6SXNzdWU3MDk2MDM5ODk= | 673 | blog_authorship_corpus crashed | [
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] | closed | false | null | 1 | 2020-09-26T20:15:28Z | 2022-02-15T10:47:58Z | 2022-02-15T10:47:58Z | null | This is just to report that When I pick blog_authorship_corpus in
https://huggingface.co/nlp/viewer/?dataset=blog_authorship_corpus
I get this:
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"Thanks for reporting !\r\nWe'll free some memory"
] |
https://api.github.com/repos/huggingface/datasets/issues/3771 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3771/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3771/comments | https://api.github.com/repos/huggingface/datasets/issues/3771/events | https://github.com/huggingface/datasets/pull/3771 | 1,146,561,140 | PR_kwDODunzps4zRHsd | 3,771 | Fix DuplicatedKeysError on msr_sqa dataset | [] | closed | false | null | 0 | 2022-02-22T07:44:24Z | 2022-02-22T08:12:40Z | 2022-02-22T08:12:39Z | null | Fix #3770. | {
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https://api.github.com/repos/huggingface/datasets/issues/5656 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5656/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5656/comments | https://api.github.com/repos/huggingface/datasets/issues/5656/events | https://github.com/huggingface/datasets/pull/5656 | 1,634,156,563 | PR_kwDODunzps5Mjxoo | 5,656 | Fix `fsspec.open` when using an HTTP proxy | [] | closed | false | null | 2 | 2023-03-21T15:23:29Z | 2023-03-23T14:14:50Z | 2023-03-23T13:15:46Z | null | Most HTTP(S) downloads from this library support proxy automatically by reading the `HTTP_PROXY` environment variable (et al.) because `requests` is widely used. However, in some parts of the code, `fsspec` is used, which in turn uses `aiohttp` for HTTP(S) requests (as opposed to `requests`), which in turn doesn't support reading proxy env variables by default. This PR enables reading them automatically.
Read [aiohttp docs on using proxies](https://docs.aiohttp.org/en/stable/client_advanced.html?highlight=trust_env#proxy-support).
For context, [the Python library requests](https://requests.readthedocs.io/en/latest/user/advanced/?highlight=http_proxy#proxies) and [the official Python library via `urllib.urlopen` support this automatically by default](https://docs.python.org/3/library/urllib.request.html#urllib.request.urlopen). Many (most common ones?) programs also do the same, including cURL, APT, Wget, and many others. | {
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https://api.github.com/repos/huggingface/datasets/issues/4346 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4346/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4346/comments | https://api.github.com/repos/huggingface/datasets/issues/4346/events | https://github.com/huggingface/datasets/issues/4346 | 1,235,067,062 | I_kwDODunzps5JnaC2 | 4,346 | GH Action to build documentation never ends | [
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] | closed | false | null | 0 | 2022-05-13T10:44:44Z | 2022-05-13T11:22:00Z | 2022-05-13T11:22:00Z | null | ## Describe the bug
See: https://github.com/huggingface/datasets/runs/6418035586?check_suite_focus=true
I finally forced the cancel of the workflow. | {
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https://api.github.com/repos/huggingface/datasets/issues/5950 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5950/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5950/comments | https://api.github.com/repos/huggingface/datasets/issues/5950/events | https://github.com/huggingface/datasets/issues/5950 | 1,755,197,946 | I_kwDODunzps5onjH6 | 5,950 | Support for data with instance-wise dictionary as features | [
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] | open | false | null | 1 | 2023-06-13T15:49:00Z | 2023-06-14T12:13:38Z | null | null | ### Feature request
I notice that when loading data instances with feature type of python dictionary, the dictionary keys would be broadcast so that every instance has the same set of keys. Please see an example in the Motivation section.
It is possible to avoid this behavior, i.e., load dictionary features as it is and do not broadcast the keys among instances? Please note that these dictionaries would have to be processed dynamically at each training iteration into strings (and tokenized).
### Motivation
I am trying to load a dataset from a json file. Each instance of the dataset has a feature that is a dictionary but its keys depend on the instance. Every two instances may have different keys. For example, imagine a dataset that contains a set of math expressions from a bunch of mutually redundant expressions:
```
{
"index": 0,
"feature": {
"2 * x + y >= 3": ["2 * x + y >= 3", "4 * x + 2 * y >= 6"],
...
}
},
...
{
"index": 9999,
"feature": {
"x >= 6": ["x >= 6", "x >= 0", "x >= -1"],
...
}
},
...
```
When directly loading the dataset using `data = load_dataset("json", data_files=file_paths, split='train')`, each instance would have all the keys from other instances and None as values. That is, instance of index 0 becomes:
```
{
"index": 0,
"feature": {
"2 * x + y >= 3": ["2 * x + y >= 3", "4 * x + 2 * y >= 6"],
...
"x >= 6": None, # keys from other instances
...
}
},
```
This is not desirable. Moreover, issue would be raised if I attempt to combine two such datasets using `data = concatenate_datasets(multi_datasets)`, perhaps because their dictionary features contain different keys.
A solution I can think of is to store the dictionary features as a long string, and evaluate it later. Please kindly suggest any other solution using existing methods of datasets.
### Your contribution
N/A | {
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"Hi ! We use the Arrow columnar format under the hood, which doesn't support such dictionaries: each field must have a fixed type and exist in each sample.\r\n\r\nInstead you can restructure your data like\r\n```\r\n{\r\n \"index\": 0,\r\n \"keys\": [\"2 * x + y >= 3\"],\r\n \"values\": [[\"2 * x + y >= 3\... |
https://api.github.com/repos/huggingface/datasets/issues/1116 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1116/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1116/comments | https://api.github.com/repos/huggingface/datasets/issues/1116/events | https://github.com/huggingface/datasets/pull/1116 | 757,133,502 | MDExOlB1bGxSZXF1ZXN0NTMyNTYwNDk4 | 1,116 | add dbpedia_14 dataset | [] | closed | false | null | 5 | 2020-12-04T14:13:59Z | 2020-12-07T10:06:54Z | 2020-12-05T15:36:23Z | null | This dataset corresponds to the DBpedia dataset requested in https://github.com/huggingface/datasets/issues/353. | {
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"Thanks for the review. \r\nCheers!",
"Hi @hfawaz, this week we are doing the 🤗 `datasets` sprint (see some details [here](https://discuss.huggingface.co/t/open-to-the-community-one-week-team-effort-to-reach-v2-0-of-hf-datasets-library/2176)).\r\n\r\nNothing more to do on your side but it means that if you regis... |
https://api.github.com/repos/huggingface/datasets/issues/1560 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1560/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1560/comments | https://api.github.com/repos/huggingface/datasets/issues/1560/events | https://github.com/huggingface/datasets/pull/1560 | 765,814,964 | MDExOlB1bGxSZXF1ZXN0NTM5MDkzMzky | 1,560 | Adding the BrWaC dataset | [] | closed | false | null | 0 | 2020-12-14T03:03:56Z | 2020-12-18T15:56:56Z | 2020-12-18T15:56:55Z | null | Adding the BrWaC dataset, a large corpus of Portuguese language texts | {
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https://api.github.com/repos/huggingface/datasets/issues/5213 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5213/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5213/comments | https://api.github.com/repos/huggingface/datasets/issues/5213/events | https://github.com/huggingface/datasets/pull/5213 | 1,440,037,534 | PR_kwDODunzps5CalQ_ | 5,213 | Add support for different configs with `push_to_hub` | [
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] | closed | false | null | 8 | 2022-11-08T11:45:47Z | 2022-12-02T16:48:23Z | 2022-12-02T16:44:07Z | null | will solve #5151
@lhoestq @albertvillanova @mariosasko
This is still a super draft so please ignore code issues but I want to discuss some conceptually important things.
I suggest a way to do `.push_to_hub("repo_id", "config_name")` with pushing parquet files to directories named as `config_name` (inside `data/` dir as it is now), for example:
```
data
|__config-v1
train-00000-00002-...-.parquet
train-00001-00002-...-.parquet
...
|__config-v2
....
```
When loading a dataset, I parse these configs from repository data files (only for `"data/{split}-[0-9][0-9][0-9][0-9][0-9]-of-[0-9][0-9][0-9][0-9][0-9]*.*"` pattern that is used for parquet datasets pushed with `.push_to_hub`).
Therefore,
- when user tries to load a dataset that has configs parsed from data files dir names without providing a config (like `load_dataset("repo")` instead of `load_dataset("repo", "config-v1")`) - raise error and asks for config - to be aligned with how it works in datasets with scripts.
- for backward compatibility: if user tries to `.push_to_hub(""repo", "config_name")` to an existing parquet repo with no configurations (all parquet files are directly in `data/` dir) - raise error. My initial idea was to raise a warning and move these files to another dir with name (config) like "default" or smth but in a PR and suggest user to merge it on the Hub. But there is no support for renaming (moving) files via `HfApi` yet so it would require deleting and pushing again if I understand it right.
This parsing approach can be extended to other Hub packaged modules, and to local packaged modules and other data files patterns
(except for cases when splits are in dir names `KEYWORDS_IN_DIR_NAME_BASE_PATTERNS` because we allow for arbitrary depth of directory hierarchy).
Do you think it's reasonable? Not sure how to provide flexibility (and backward compatibility) to not parsing configs and load all the data in a single config as it is now.
I also thought about getting information about configs from Readme.md `dataset_info` ([example](https://huggingface.co/datasets/polinaeterna/test_push_two_configs/blob/main/README.md)). But that way we
are dependent on if it exists. It is created automatically with `.push_to_hub` but what if it is
accidentally deleted or smth).
Also, what I don't like is that this parsing is a part of Module/DataFiles logic, not Builder's one, which is not aligned with datasets with custom scripts. But I don't know to implement the second approach in current library's logic.
What do you think about this all? Am I missing smth?
TODO:
- [ ] save cache in the same dir for configs of the same datasets
- [ ] fix verification errors
- [ ] correctly update `dataset_infos.json` too
- [ ] ...
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"_The documentation is not available anymore as the PR was closed or merged._",
"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5213). All of your documentation changes will be reflected on that endpoint.",
"The docs for this PR live [here](https://moon-ci-docs.huggingface... |
https://api.github.com/repos/huggingface/datasets/issues/2242 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2242/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2242/comments | https://api.github.com/repos/huggingface/datasets/issues/2242/events | https://github.com/huggingface/datasets/issues/2242 | 862,870,205 | MDU6SXNzdWU4NjI4NzAyMDU= | 2,242 | Link to datasets viwer on Quick Tour page returns "502 Bad Gateway" | [
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] | closed | false | null | 1 | 2021-04-20T14:19:51Z | 2021-04-20T15:02:45Z | 2021-04-20T15:02:45Z | null | Link to datasets viwer (https://huggingface.co/datasets/viewer/) on Quick Tour page (https://huggingface.co/docs/datasets/quicktour.html) returns "502 Bad Gateway"
The same error with https://huggingface.co/datasets/viewer/?dataset=glue&config=mrpc | {
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} | https://api.github.com/repos/huggingface/datasets/issues/2242/timeline | null | completed | null | null | false | [
"This should be fixed now!\r\n\r\ncc @srush "
] |
https://api.github.com/repos/huggingface/datasets/issues/5997 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5997/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5997/comments | https://api.github.com/repos/huggingface/datasets/issues/5997/events | https://github.com/huggingface/datasets/issues/5997 | 1,781,582,818 | I_kwDODunzps5qMMvi | 5,997 | extend the map function so it can wrap around long text that does not fit in the context window | [
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] | open | false | null | 2 | 2023-06-29T22:15:21Z | 2023-07-03T17:58:52Z | null | null | ### Feature request
I understand `dataset` provides a [`map`](https://github.com/huggingface/datasets/blob/main/src/datasets/arrow_dataset.py#L2849) function. This function in turn takes in a callable that is used to tokenize the text on which a model is trained. Frequently this text will not fit within a models's context window. In this case it would be useful to wrap around the text into multiple rows with each row fitting the model's context window. I tried to do it using this code as example which in turn I have borrowed from [here](https://stackoverflow.com/a/76343993/147530):
```
data = data.map(lambda samples: tokenizer(samples["text"], max_length=tokenizer.model_max_length, truncation=True, stride=4, return_overflowing_tokens=True), batched=True)
```
but running the code gives me this error:
```
File "/llm/fine-tune.py", line 117, in <module>
data = data.map(lambda samples: tokenizer(samples["text"], max_length=tokenizer.model_max_length, truncation=True, stride=4, return_overflowing_tokens=True), batched=True)
File "/llm/.env/lib/python3.9/site-packages/datasets/arrow_dataset.py", line 580, in wrapper
out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
File "/llm/.env/lib/python3.9/site-packages/datasets/arrow_dataset.py", line 545, in wrapper
out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
File "/llm/.env/lib/python3.9/site-packages/datasets/arrow_dataset.py", line 3087, in map
for rank, done, content in Dataset._map_single(**dataset_kwargs):
File "/llm/.env/lib/python3.9/site-packages/datasets/arrow_dataset.py", line 3480, in _map_single
writer.write_batch(batch)
File "/llm/.env/lib/python3.9/site-packages/datasets/arrow_writer.py", line 556, in write_batch
pa_table = pa.Table.from_arrays(arrays, schema=schema)
File "pyarrow/table.pxi", line 3798, in pyarrow.lib.Table.from_arrays
File "pyarrow/table.pxi", line 2962, in pyarrow.lib.Table.validate
File "pyarrow/error.pxi", line 100, in pyarrow.lib.check_status
pyarrow.lib.ArrowInvalid: Column 1 named input_ids expected length 394 but got length 447
```
The lambda function I have provided is correctly chopping up long text so it wraps around (and because of this 394 samples become 447 after wrap around) but the dataset `map` function does not like it.
### Motivation
please see above
### Your contribution
I'm afraid I don't have much knowledge to help | {
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"I just noticed the [docs](https://github.com/huggingface/datasets/blob/main/src/datasets/arrow_dataset.py#L2881C11-L2881C200) say:\r\n\r\n>If batched is `True` and `batch_size` is `n > 1`, then the function takes a batch of `n` examples as input and can return a batch with `n` examples, or with an arbitrary number... |
https://api.github.com/repos/huggingface/datasets/issues/3217 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3217/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3217/comments | https://api.github.com/repos/huggingface/datasets/issues/3217/events | https://github.com/huggingface/datasets/issues/3217 | 1,045,029,710 | I_kwDODunzps4-SeNO | 3,217 | Fix code quality bug in riddle_sense dataset | [
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] | closed | false | null | 1 | 2021-11-04T17:40:32Z | 2021-11-04T17:50:02Z | 2021-11-04T17:50:02Z | null | ## Describe the bug
```
datasets/riddle_sense/riddle_sense.py:36:21: W291 trailing whitespace
``` | {
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} | https://api.github.com/repos/huggingface/datasets/issues/3217/timeline | null | completed | null | null | false | [
"To give more context: https://github.com/psf/black/issues/318. `black` doesn't treat this as a bug, but `flake8` does. \r\n"
] |
https://api.github.com/repos/huggingface/datasets/issues/2802 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2802/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2802/comments | https://api.github.com/repos/huggingface/datasets/issues/2802/events | https://github.com/huggingface/datasets/pull/2802 | 970,848,302 | MDExOlB1bGxSZXF1ZXN0NzEyNzM0MTc3 | 2,802 | add openwebtext2 | [] | closed | false | null | 3 | 2021-08-14T07:09:03Z | 2021-08-23T14:06:14Z | 2021-08-23T14:06:14Z | null | openwebtext2 is part of EleutherAI/The Pile, but AFAIK, The Pile dataset blend all sub datasets together thus we are not able to use just one of its sub dataset from The Pile data. So I create an independent dataset using The Pile preliminary components.
When I was creating dataset card. I found there is room for creating / editing dataset card. I've made it an issue. #2797
Also I am wondering whether the import of The Pile dataset is actively undertaken (because I may need it recently)? #1675 | {
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"It seems we need to `pip install jsonlines` to pass the checks ?",
"Hi ! Do you really need `jsonlines` ? I think it simply uses `json.loads` under the hood.\r\n\r\nCurrently the test are failing because `jsonlines` is not part of the extra requirements `TESTS_REQUIRE` in setup.py\r\n\r\nSo either you can replac... |
https://api.github.com/repos/huggingface/datasets/issues/3949 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3949/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3949/comments | https://api.github.com/repos/huggingface/datasets/issues/3949/events | https://github.com/huggingface/datasets/pull/3949 | 1,171,467,981 | PR_kwDODunzps40jia- | 3,949 | Remove GLEU metric | [] | closed | false | null | 1 | 2022-03-16T19:35:31Z | 2022-04-12T20:43:26Z | 2022-04-12T20:37:09Z | null | Remove the GLEU metric as it is not actually implemented. | {
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] |
https://api.github.com/repos/huggingface/datasets/issues/3406 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3406/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3406/comments | https://api.github.com/repos/huggingface/datasets/issues/3406/events | https://github.com/huggingface/datasets/pull/3406 | 1,074,366,050 | PR_kwDODunzps4vjV21 | 3,406 | Fix module inference for archive with a directory | [] | closed | false | null | 0 | 2021-12-08T12:39:12Z | 2021-12-08T13:03:30Z | 2021-12-08T13:03:29Z | null | Fix module inference for an archive file that contains files within a directory.
Fix #3405. | {
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https://api.github.com/repos/huggingface/datasets/issues/4730 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4730/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4730/comments | https://api.github.com/repos/huggingface/datasets/issues/4730/events | https://github.com/huggingface/datasets/issues/4730 | 1,313,421,263 | I_kwDODunzps5OSTfP | 4,730 | Loading imagenet-1k validation split takes much more RAM than expected | [
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] | closed | false | null | 1 | 2022-07-21T15:14:06Z | 2022-07-21T16:41:04Z | 2022-07-21T16:41:04Z | null | ## Describe the bug
Loading into memory the validation split of imagenet-1k takes much more RAM than expected. Assuming ImageNet-1k is 150 GB, split is 50000 validation images and 1,281,167 train images, I would expect only about 6 GB loaded in RAM.
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset("imagenet-1k", split="validation")
print(dataset)
"""prints
Dataset({
features: ['image', 'label'],
num_rows: 50000
})
"""
pipe_inputs = dataset["image"]
# and wait :-)
```
## Expected results
Use only < 10 GB RAM when loading the images.
## Actual results
```
Using custom data configuration default
Reusing dataset imagenet-1k (/home/fxmarty/.cache/huggingface/datasets/imagenet-1k/default/1.0.0/a1e9bfc56c3a7350165007d1176b15e9128fcaf9ab972147840529aed3ae52bc)
Killed
```
## Environment info
- `datasets` version: 2.3.3.dev0
- Platform: Linux-5.15.0-41-generic-x86_64-with-glibc2.35
- Python version: 3.9.12
- PyArrow version: 7.0.0
- Pandas version: 1.3.5
- datasets commit: 4e4222f1b6362c2788aec0dd2cd8cede6dd17b80
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"My bad, `482 * 418 * 50000 * 3 / 1000000 = 30221 MB` ( https://stackoverflow.com/a/42979315 ).\r\n\r\nMeanwhile `256 * 256 * 50000 * 3 / 1000000 = 9830 MB`. We are loading the non-cropped images and that is why we take so much RAM."
] |
https://api.github.com/repos/huggingface/datasets/issues/5227 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5227/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5227/comments | https://api.github.com/repos/huggingface/datasets/issues/5227/events | https://github.com/huggingface/datasets/issues/5227 | 1,444,620,094 | I_kwDODunzps5WGyc- | 5,227 | datasets.data_files.EmptyDatasetError: The directory at wikisql doesn't contain any data files | [] | closed | false | null | 1 | 2022-11-10T21:57:06Z | 2022-11-10T22:05:43Z | 2022-11-10T22:05:43Z | null | ### Describe the bug
From these lines:
from datasets import list_datasets, load_dataset
dataset = load_dataset("wikisql","binary")
I get error message:
datasets.data_files.EmptyDatasetError: The directory at wikisql doesn't contain any data files
And yet the 'wikisql' is reported to exist via the list_datasets().
Any help appreciated.
### Steps to reproduce the bug
From these lines:
from datasets import list_datasets, load_dataset
dataset = load_dataset("wikisql","binary")
I get error message:
datasets.data_files.EmptyDatasetError: The directory at wikisql doesn't contain any data files
And yet the 'wikisql' is reported to exist via the list_datasets().
Any help appreciated.
### Expected behavior
Dataset should load. This same code used to work.
### Environment info
Mac OS | {
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] |
https://api.github.com/repos/huggingface/datasets/issues/3871 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3871/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3871/comments | https://api.github.com/repos/huggingface/datasets/issues/3871/events | https://github.com/huggingface/datasets/pull/3871 | 1,163,714,113 | PR_kwDODunzps40KRcM | 3,871 | add pandas to env command | [] | closed | false | null | 2 | 2022-03-09T09:48:51Z | 2022-03-09T11:21:38Z | 2022-03-09T11:21:37Z | null | Pandas is a required packages and used quite a bit. I don't see any downside with adding its version to the `datasets-cli env` command. | {
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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 :-)"
] |
https://api.github.com/repos/huggingface/datasets/issues/92 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/92/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/92/comments | https://api.github.com/repos/huggingface/datasets/issues/92/events | https://github.com/huggingface/datasets/pull/92 | 617,341,505 | MDExOlB1bGxSZXF1ZXN0NDE3Mjc1ODky | 92 | [WIP] add wmt14 | [] | closed | false | null | 0 | 2020-05-13T10:42:03Z | 2020-05-16T11:17:38Z | 2020-05-16T11:17:37Z | null | WMT14 takes forever to download :-/
- WMT is the first dataset that uses an abstract class IMO, so I had to modify the `load_dataset_module` a bit. | {
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https://api.github.com/repos/huggingface/datasets/issues/4197 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4197/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4197/comments | https://api.github.com/repos/huggingface/datasets/issues/4197/events | https://github.com/huggingface/datasets/pull/4197 | 1,211,342,558 | PR_kwDODunzps42kyXD | 4,197 | Add remove_columns=True | [] | closed | false | null | 4 | 2022-04-21T17:28:13Z | 2022-04-22T14:51:41Z | 2022-04-22T14:45:30Z | null | This should fix all the issue we have with in place operations in mapping functions. This is crucial as where we do some weird things like:
```
def apply(batch):
batch_size = len(batch["id"])
batch["text"] = ["potato" for _ range(batch_size)]
return {}
# Columns are: {"id": int}
dset.map(apply, batched=True, remove_columns="text") # crashes because `text` is not in the original columns
dset.map(apply, batched=True) # mapped datasets has `text` column
```
In this PR we suggest to have `remove_columns=True` so that we ignore the input completely, and just use the output to generate mapped dataset. This means that inplace operations won't have any effects anymore. | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Any reason why we can't just do `[inputs.copy()]` in this line for in-place operations to not have effects anymore:\r\nhttps://github.com/huggingface/datasets/blob/bf432011ff9155a5bc16c03956bc63e514baf80d/src/datasets/arrow_dataset.p... |
https://api.github.com/repos/huggingface/datasets/issues/3235 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3235/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3235/comments | https://api.github.com/repos/huggingface/datasets/issues/3235/events | https://github.com/huggingface/datasets/pull/3235 | 1,047,808,263 | PR_kwDODunzps4uPr9Z | 3,235 | Addd options to use updated bleurt checkpoints | [] | closed | false | null | 0 | 2021-11-08T18:53:54Z | 2021-11-12T14:05:28Z | 2021-11-12T14:05:28Z | null | Adds options to use newer recommended checkpoint (as of 2021/10/8) bleurt-20 and its distilled versions.
Updated checkpoints are described in https://github.com/google-research/bleurt/blob/master/checkpoints.md#the-recommended-checkpoint-bleurt-20
This change won't affect the default behavior of metrics/bleurt. It only adds option to load newer checkpoints as
`datasets.load_metric('bleurt', 'bleurt-20')`
`bluert-20` generates scores roughly between 0 and 1, which wasn't the case for the previous checkpoints. | {
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https://api.github.com/repos/huggingface/datasets/issues/1376 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1376/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1376/comments | https://api.github.com/repos/huggingface/datasets/issues/1376/events | https://github.com/huggingface/datasets/pull/1376 | 760,309,300 | MDExOlB1bGxSZXF1ZXN0NTM1MTYyODU4 | 1,376 | Add SETimes Dataset | [] | closed | false | null | 1 | 2020-12-09T13:01:08Z | 2020-12-10T16:11:57Z | 2020-12-10T16:11:56Z | null | {
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"merging since the CI is fixed on master"
] | |
https://api.github.com/repos/huggingface/datasets/issues/4927 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4927/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4927/comments | https://api.github.com/repos/huggingface/datasets/issues/4927/events | https://github.com/huggingface/datasets/pull/4927 | 1,360,428,139 | PR_kwDODunzps4-S0we | 4,927 | fix BLEU metric card | [] | closed | false | null | 0 | 2022-09-02T17:00:56Z | 2022-09-09T16:28:15Z | 2022-09-09T16:28:15Z | null | I've fixed some typos in BLEU metric card. | {
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https://api.github.com/repos/huggingface/datasets/issues/4002 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4002/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4002/comments | https://api.github.com/repos/huggingface/datasets/issues/4002/events | https://github.com/huggingface/datasets/pull/4002 | 1,179,263,787 | PR_kwDODunzps408Cfp | 4,002 | Support streaming conll2012_ontonotesv5 dataset | [] | closed | false | null | 1 | 2022-03-24T09:49:56Z | 2022-03-24T10:53:41Z | 2022-03-24T10:48:47Z | null | Use another URL whit a single ZIP file (instead of previous one with a ZIP file inside another ZIP file). | {
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https://api.github.com/repos/huggingface/datasets/issues/4950 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4950/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4950/comments | https://api.github.com/repos/huggingface/datasets/issues/4950/events | https://github.com/huggingface/datasets/pull/4950 | 1,365,458,633 | PR_kwDODunzps4-jWZ1 | 4,950 | Update Enwik8 broken link and information | [] | closed | false | null | 1 | 2022-09-08T03:15:00Z | 2022-09-24T22:14:35Z | 2022-09-08T14:51:00Z | null | The current enwik8 dataset link give a 502 bad gateway error which can be view on https://huggingface.co/datasets/enwik8 (click the dropdown to see the dataset preview, it will show the error). This corrects the links, and json metadata as well as adds a little bit more information about enwik8. | {
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https://api.github.com/repos/huggingface/datasets/issues/1046 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1046/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1046/comments | https://api.github.com/repos/huggingface/datasets/issues/1046/events | https://github.com/huggingface/datasets/issues/1046 | 756,122,709 | MDU6SXNzdWU3NTYxMjI3MDk= | 1,046 | Dataset.map() turns tensors into lists? | [] | closed | false | null | 2 | 2020-12-03T11:43:46Z | 2022-10-05T12:12:41Z | 2022-10-05T12:12:41Z | null | I apply `Dataset.map()` to a function that returns a dict of torch tensors (like a tokenizer from the repo transformers). However, in the mapped dataset, these tensors have turned to lists!
```import datasets
import torch
from datasets import load_dataset
print("version datasets", datasets.__version__)
dataset = load_dataset("snli", split='train[0:50]')
def tokenizer_fn(example):
# actually uses a tokenizer which does something like:
return {'input_ids': torch.tensor([[0, 1, 2]])}
print("First item in dataset:\n", dataset[0])
tokenized = tokenizer_fn(dataset[0])
print("Tokenized hyp:\n", tokenized)
dataset_tok = dataset.map(tokenizer_fn, batched=False,
remove_columns=['label', 'premise', 'hypothesis'])
print("Tokenized using map:\n", dataset_tok[0])
print(type(tokenized['input_ids']), type(dataset_tok[0]['input_ids']))
dataset_tok = dataset.map(tokenizer_fn, batched=False,
remove_columns=['label', 'premise', 'hypothesis'])
print("Tokenized using map:\n", dataset_tok[0])
print(type(tokenized['input_ids']), type(dataset_tok[0]['input_ids']))
```
The output is:
```
version datasets 1.1.3
Reusing dataset snli (/home/tom/.cache/huggingface/datasets/snli/plain_text/1.0.0/bb1102591c6230bd78813e229d5dd4c7fbf4fc478cec28f298761eb69e5b537c)
First item in dataset:
{'premise': 'A person on a horse jumps over a broken down airplane.', 'hypothesis': 'A person is training his horse for a competition.', 'label': 1}
Tokenized hyp:
{'input_ids': tensor([[0, 1, 2]])}
Loading cached processed dataset at /home/tom/.cache/huggingface/datasets/snli/plain_text/1.0.0/bb1102591c6230bd78813e229d5dd4c7fbf4fc478cec28f298761eb69e5b537c/cache-fe38f449fe9ac46f.arrow
Tokenized using map:
{'input_ids': [[0, 1, 2]]}
<class 'torch.Tensor'> <class 'list'>
```
Or am I doing something wrong?
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"A solution is to have the tokenizer return a list instead of a tensor, and then use `dataset_tok.set_format(type = 'torch')` to convert that list into a tensor. Still not sure if bug.",
"It is expected behavior, you should set the format to `\"torch\"` as you mentioned to get pytorch tensors back.\r\nBy default ... |
https://api.github.com/repos/huggingface/datasets/issues/1246 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1246/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1246/comments | https://api.github.com/repos/huggingface/datasets/issues/1246/events | https://github.com/huggingface/datasets/pull/1246 | 758,418,652 | MDExOlB1bGxSZXF1ZXN0NTMzNTk0NjIz | 1,246 | arXiv dataset added | [] | closed | false | null | 0 | 2020-12-07T11:20:23Z | 2020-12-07T14:22:58Z | 2020-12-07T14:22:58Z | null | {
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https://api.github.com/repos/huggingface/datasets/issues/5140 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5140/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5140/comments | https://api.github.com/repos/huggingface/datasets/issues/5140/events | https://github.com/huggingface/datasets/pull/5140 | 1,415,075,530 | PR_kwDODunzps5BHTNq | 5,140 | Make the KeyHasher FIPS compliant | [] | closed | false | null | 0 | 2022-10-19T14:25:52Z | 2022-11-07T16:20:43Z | 2022-11-07T16:20:43Z | null | MD5 is not FIPS compliant thus I am proposing this minimal change to make datasets package FIPS compliant | {
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https://api.github.com/repos/huggingface/datasets/issues/2586 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2586/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2586/comments | https://api.github.com/repos/huggingface/datasets/issues/2586/events | https://github.com/huggingface/datasets/pull/2586 | 936,747,588 | MDExOlB1bGxSZXF1ZXN0NjgzNDEwMDU3 | 2,586 | Fix misalignment in SQuAD | [] | closed | false | {
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} | 0 | 2021-07-05T06:42:20Z | 2021-07-12T14:11:10Z | 2021-07-07T13:18:51Z | null | Fix misalignment between:
- the answer text and
- the answer_start within the context
by keeping original leading blank spaces in the context.
Fix #2585. | {
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https://api.github.com/repos/huggingface/datasets/issues/4906 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4906/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4906/comments | https://api.github.com/repos/huggingface/datasets/issues/4906/events | https://github.com/huggingface/datasets/issues/4906 | 1,353,223,925 | I_kwDODunzps5QqI71 | 4,906 | Can't import datasets AttributeError: partially initialized module 'datasets' has no attribute 'utils' (most likely due to a circular import) | [
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] | closed | false | null | 5 | 2022-08-28T02:23:24Z | 2023-05-13T13:53:30Z | 2022-10-03T12:22:50Z | null | ## Describe the bug
A clear and concise description of what the bug is.
Not able to import datasets
## Steps to reproduce the bug
```python
# Sample code to reproduce the bug
import os
os.environ["WANDB_API_KEY"] = "0" ## to silence warning
import numpy as np
import random
import sklearn
import matplotlib.pyplot as plt
import pandas as pd
import sys
import tensorflow as tf
import plotly.express as px
import transformers
import tokenizers
import nlp as nlp
import utils
import datasets
```
## Expected results
A clear and concise description of the expected results.
import should work normal
## Actual results
Specify the actual results or traceback.
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-21-b3b5b0b62103> in <module>
13 import nlp as nlp
14 import utils
---> 15 import datasets
~\anaconda3\lib\site-packages\datasets\__init__.py in <module>
44 from .fingerprint import disable_caching, enable_caching, is_caching_enabled, set_caching_enabled
45 from .info import DatasetInfo, MetricInfo
---> 46 from .inspect import (
47 get_dataset_config_info,
48 get_dataset_config_names,
~\anaconda3\lib\site-packages\datasets\inspect.py in <module>
28 from .download.streaming_download_manager import StreamingDownloadManager
29 from .info import DatasetInfo
---> 30 from .load import dataset_module_factory, import_main_class, load_dataset_builder, metric_module_factory
31 from .utils.file_utils import relative_to_absolute_path
32 from .utils.logging import get_logger
~\anaconda3\lib\site-packages\datasets\load.py in <module>
53 from .iterable_dataset import IterableDataset
54 from .metric import Metric
---> 55 from .packaged_modules import (
56 _EXTENSION_TO_MODULE,
57 _MODULE_SUPPORTS_METADATA,
~\anaconda3\lib\site-packages\datasets\packaged_modules\__init__.py in <module>
4 from typing import List
5
----> 6 from .csv import csv
7 from .imagefolder import imagefolder
8 from .json import json
~\anaconda3\lib\site-packages\datasets\packaged_modules\csv\csv.py in <module>
13
14
---> 15 logger = datasets.utils.logging.get_logger(__name__)
16
17 _PANDAS_READ_CSV_NO_DEFAULT_PARAMETERS = ["names", "prefix"]
AttributeError: partially initialized module 'datasets' has no attribute 'utils' (most likely due to a circular import)
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
Copy-and-paste the text below in your GitHub issue.
- `datasets` version: 2.4.0
- Platform: Windows-10-10.0.22000-SP0
- Python version: 3.8.8
- PyArrow version: 9.0.0
- Pandas version: 1.2.4
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"Thanks for reporting, @OPterminator.\r\n\r\nHowever, we are not able to reproduce this issue.\r\n\r\nThere might be 2 reasons why you get this exception:\r\n- Either the name of your local Python file: if it is called `datasets.py` this could generate a circular import when trying to import the Hugging Face `data... |
https://api.github.com/repos/huggingface/datasets/issues/5521 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5521/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5521/comments | https://api.github.com/repos/huggingface/datasets/issues/5521/events | https://github.com/huggingface/datasets/pull/5521 | 1,578,418,289 | PR_kwDODunzps5JpWnp | 5,521 | Fix bug when casting empty array to class labels | [] | closed | false | null | 1 | 2023-02-09T18:47:59Z | 2023-02-13T20:40:48Z | 2023-02-12T11:17:17Z | null | Fix https://github.com/huggingface/datasets/issues/5520. | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] |
https://api.github.com/repos/huggingface/datasets/issues/4861 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4861/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4861/comments | https://api.github.com/repos/huggingface/datasets/issues/4861/events | https://github.com/huggingface/datasets/issues/4861 | 1,343,260,220 | I_kwDODunzps5QEIY8 | 4,861 | Using disk for memory with the method `from_dict` | [
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] | open | false | null | 1 | 2022-08-18T15:18:18Z | 2023-01-26T18:36:28Z | null | null | **Is your feature request related to a problem? Please describe.**
I start with an empty dataset. In a loop, at each iteration, I create a new dataset with the method `from_dict` (based on some data I load) and I concatenate this new dataset with the one at the previous iteration. After some iterations, I have an OOM error.
**Describe the solution you'd like**
The method `from_dict` loads the data in RAM. It could be good to add an option to use the disk instead.
**Describe alternatives you've considered**
To solve the problem, I have to do an intermediate step where I save the new datasets at each iteration with `save_to_disk`. Once it's done, I open them all and concatenate them.
| {
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} | https://api.github.com/repos/huggingface/datasets/issues/4861/timeline | null | null | null | null | false | [
"This issue was also causing an OOM in @nateraw 's workflow and shows again that behavior is confusing - we should definitely switch to using the disk IMO"
] |
https://api.github.com/repos/huggingface/datasets/issues/4103 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4103/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4103/comments | https://api.github.com/repos/huggingface/datasets/issues/4103/events | https://github.com/huggingface/datasets/pull/4103 | 1,193,987,104 | PR_kwDODunzps41s3T4 | 4,103 | Add the `GSM8K` dataset | [] | closed | false | null | 2 | 2022-04-06T04:07:52Z | 2022-04-12T15:38:28Z | 2022-04-12T10:21:16Z | null | null | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"The CI is failing because it's outdated, but the task tags are updated on `master`, merging :)"
] |
https://api.github.com/repos/huggingface/datasets/issues/4877 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4877/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4877/comments | https://api.github.com/repos/huggingface/datasets/issues/4877/events | https://github.com/huggingface/datasets/pull/4877 | 1,348,246,755 | PR_kwDODunzps49qF-w | 4,877 | Fix documentation card of covid_qa_castorini dataset | [] | closed | false | null | 1 | 2022-08-23T16:52:33Z | 2022-08-23T18:05:01Z | 2022-08-23T18:05:00Z | null | Fix documentation card of covid_qa_castorini dataset. | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_4877). All of your documentation changes will be reflected on that endpoint."
] |
https://api.github.com/repos/huggingface/datasets/issues/5878 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5878/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5878/comments | https://api.github.com/repos/huggingface/datasets/issues/5878/events | https://github.com/huggingface/datasets/issues/5878 | 1,718,203,843 | I_kwDODunzps5mabXD | 5,878 | Prefetching for IterableDataset | [
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] | open | false | null | 5 | 2023-05-20T15:25:40Z | 2023-06-01T17:40:00Z | null | null | ### Feature request
Add support for prefetching the next n batches through iterabledataset to reduce batch loading bottleneck in training loop.
### Motivation
The primary motivation behind this is to use hardware accelerators alongside a streaming dataset. This is required when you are in a low ram or low disk space setting as well as quick iteration where you're iterating though different accelerator environments (e.x changing ec2 instances quickly to figure out batch/sec for a particular architecture).
Currently, using the IterableDataset results in accelerators becoming basically useless due to the massive bottleneck induced by the dataset lazy loading/transform/mapping.
I've considered two alternatives:
PyTorch dataloader that handles this. However, I'm using jax, and I believe this is a piece of functionality that should live in the stream class.
Replicating the "num_workers" part of the PyTorch DataLoader to eagerly load batches and apply the transform so Arrow caching will automatically cache results and make them accessible.
### Your contribution
I may or may not have time to do this. Currently, I've written the basic multiprocessor approach to handle the eager DataLoader for my own use case with code that's not integrated to datasets. I'd definitely see this as being the default over the regular Dataset for most people given that they wouldn't have to wait on the datasets while also not worrying about performance. | {
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"Very cool! Do you have a link to the code that you're using to eagerly fetch the data? Would also be interested in hacking around something here for pre-fetching iterable datasets",
"I ended up just switching back to the pytorch dataloader and using it's multiprocessing functionality to handle this :(. I'm just ... |
https://api.github.com/repos/huggingface/datasets/issues/5268 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5268/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5268/comments | https://api.github.com/repos/huggingface/datasets/issues/5268/events | https://github.com/huggingface/datasets/pull/5268 | 1,455,633,978 | PR_kwDODunzps5DPIsp | 5,268 | Sharded save_to_disk + multiprocessing | [] | closed | false | null | 4 | 2022-11-18T18:50:01Z | 2022-12-14T18:25:52Z | 2022-12-14T18:22:58Z | null | Added `num_shards=` and `num_proc=` to `save_to_disk()`
EDIT: also added `max_shard_size=` to `save_to_disk()`, and also `num_shards=` to `push_to_hub`
I also:
- deprecated the fs parameter in favor of storage_options (for consistency with the rest of the lib) in save_to_disk and load_from_disk
- always embed the image/audio data in arrow when doing `save_to_disk`
- added a tqdm bar in `save_to_disk`
- Use the MockFileSystem in tests for `save_to_disk` and `load_from_disk`
- removed the unused integration tests with S3, since we can now test with `mockfs` instead of `s3fs`
TODO:
- [x] implem save_to_disk for dataset dict
- [x] save_to_disk for dataset dict tests
- [x] deprecate fs in dataset dict load_from_disk as well
- [x] update docs
Close #5263
Close https://github.com/huggingface/datasets/issues/4196
Close https://github.com/huggingface/datasets/issues/4351 | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Added both num_shards and max_shard_size in push_to_hub/save_to_disk. Will take care of updating the tests later",
"It's ready for a final review @mariosasko and @albertvillanova, let me know what you think :)",
"Took your commen... |
https://api.github.com/repos/huggingface/datasets/issues/5257 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5257/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5257/comments | https://api.github.com/repos/huggingface/datasets/issues/5257/events | https://github.com/huggingface/datasets/pull/5257 | 1,452,656,891 | PR_kwDODunzps5DFENm | 5,257 | remove an unused statement | [] | closed | false | null | 0 | 2022-11-17T04:00:50Z | 2022-11-18T11:04:08Z | 2022-11-18T11:04:08Z | null | remove the unused statement: `input_pairs = list(zip())` | {
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https://api.github.com/repos/huggingface/datasets/issues/4886 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4886/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4886/comments | https://api.github.com/repos/huggingface/datasets/issues/4886/events | https://github.com/huggingface/datasets/issues/4886 | 1,349,285,569 | I_kwDODunzps5QbHbB | 4,886 | Loading huggan/CelebA-HQ throws pyarrow.lib.ArrowInvalid | [
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] | open | false | null | 9 | 2022-08-24T11:24:21Z | 2023-02-02T02:40:53Z | null | null | ## Describe the bug
Loading huggan/CelebA-HQ throws pyarrow.lib.ArrowInvalid
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset('huggan/CelebA-HQ')
```
## Expected results
See https://colab.research.google.com/drive/141LJCcM2XyqprPY83nIQ-Zk3BbxWeahq?usp=sharing#scrollTo=N3ml_7f8kzDd
## Actual results
```
File "/home/jean/projects/cold_diffusion/celebA.py", line 4, in <module>
dataset = load_dataset('huggan/CelebA-HQ')
File "/home/jean/miniconda3/envs/seq/lib/python3.10/site-packages/datasets/load.py", line 1793, in load_dataset
builder_instance.download_and_prepare(
File "/home/jean/miniconda3/envs/seq/lib/python3.10/site-packages/datasets/builder.py", line 704, in download_and_prepare
self._download_and_prepare(
File "/home/jean/miniconda3/envs/seq/lib/python3.10/site-packages/datasets/builder.py", line 793, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/home/jean/miniconda3/envs/seq/lib/python3.10/site-packages/datasets/builder.py", line 1274, in _prepare_split
for key, table in logging.tqdm(
File "/home/jean/miniconda3/envs/seq/lib/python3.10/site-packages/tqdm/std.py", line 1195, in __iter__
for obj in iterable:
File "/home/jean/miniconda3/envs/seq/lib/python3.10/site-packages/datasets/packaged_modules/parquet/parquet.py", line 67, in _generate_tables
parquet_file = pq.ParquetFile(f)
File "/home/jean/miniconda3/envs/seq/lib/python3.10/site-packages/pyarrow/parquet/__init__.py", line 286, in __init__
self.reader.open(
File "pyarrow/_parquet.pyx", line 1227, in pyarrow._parquet.ParquetReader.open
File "pyarrow/error.pxi", line 100, in pyarrow.lib.check_status
pyarrow.lib.ArrowInvalid: Parquet magic bytes not found in footer. Either the file is corrupted or this is not a parquet file.
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: datasets-2.4.1.dev0
- Platform: Ubuntu 18.04
- Python version: 3.10
- PyArrow version: pyarrow 9.0.0
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} | https://api.github.com/repos/huggingface/datasets/issues/4886/timeline | null | null | null | null | false | [
"Hi! IIRC one of the files in this dataset is corrupted due to https://github.com/huggingface/datasets/pull/4081 (fixed now).\r\n\r\n@NielsRogge Could you please re-generate and re-push this dataset (or I can do it if you share the generation script)?",
"Could you put something in place to catch these problems? ... |
https://api.github.com/repos/huggingface/datasets/issues/2568 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2568/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2568/comments | https://api.github.com/repos/huggingface/datasets/issues/2568/events | https://github.com/huggingface/datasets/pull/2568 | 932,934,795 | MDExOlB1bGxSZXF1ZXN0NjgwMjE5MDU2 | 2,568 | Add interleave_datasets for map-style datasets | [] | closed | false | null | 0 | 2021-06-29T17:19:24Z | 2021-07-01T09:33:34Z | 2021-07-01T09:33:33Z | null | ### Add interleave_datasets for map-style datasets
Add support for map-style datasets (i.e. `Dataset` objects) in `interleave_datasets`.
It was only supporting iterable datasets (i.e. `IterableDataset` objects).
### Implementation details
It works by concatenating the datasets and then re-order the indices to make the new dataset.
### TODO
- [x] tests
- [x] docs
Close #2563 | {
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https://api.github.com/repos/huggingface/datasets/issues/5079 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5079/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5079/comments | https://api.github.com/repos/huggingface/datasets/issues/5079/events | https://github.com/huggingface/datasets/pull/5079 | 1,398,609,305 | PR_kwDODunzps5AQemi | 5,079 | refactor: replace AssertionError with more meaningful exceptions (#5074) | [] | closed | false | null | 1 | 2022-10-06T01:39:35Z | 2022-10-07T14:35:43Z | 2022-10-07T14:33:10Z | null | Closes #5074
Replaces `AssertionError` in the following files with more descriptive exceptions:
- `src/datasets/arrow_reader.py`
- `src/datasets/builder.py`
- `src/datasets/utils/version.py`
The issue listed more files that needed to be fixed, but the rest of them were contained in the top-level `datasets` directory, which was removed when #4974 was merged | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] |
https://api.github.com/repos/huggingface/datasets/issues/3 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3/comments | https://api.github.com/repos/huggingface/datasets/issues/3/events | https://github.com/huggingface/datasets/issues/3 | 600,180,050 | MDU6SXNzdWU2MDAxODAwNTA= | 3 | [Feature] More dataset outputs | [] | closed | false | null | 3 | 2020-04-15T10:08:14Z | 2020-05-04T06:12:27Z | 2020-05-04T06:12:27Z | null | Add the following dataset outputs:
- Spark
- Pandas | {
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"Yes!\r\n- pandas will be a one-liner in `arrow_dataset`: https://arrow.apache.org/docs/python/generated/pyarrow.Table.html#pyarrow.Table.to_pandas\r\n- for Spark I have no idea. let's investigate that at some point",
"For Spark it looks to be pretty straightforward as well https://spark.apache.org/docs/latest/sq... |
https://api.github.com/repos/huggingface/datasets/issues/17 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/17/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/17/comments | https://api.github.com/repos/huggingface/datasets/issues/17/events | https://github.com/huggingface/datasets/pull/17 | 605,753,027 | MDExOlB1bGxSZXF1ZXN0NDA4MDk3NjM0 | 17 | Add Pandas as format type | [] | closed | false | null | 0 | 2020-04-23T18:20:14Z | 2020-04-27T18:07:50Z | 2020-04-27T18:07:48Z | null | As detailed in the title ^^ | {
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https://api.github.com/repos/huggingface/datasets/issues/5574 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5574/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5574/comments | https://api.github.com/repos/huggingface/datasets/issues/5574/events | https://github.com/huggingface/datasets/issues/5574 | 1,598,104,691 | I_kwDODunzps5fQSRz | 5,574 | c4 dataset streaming fails with `FileNotFoundError` | [] | closed | false | null | 9 | 2023-02-24T07:57:32Z | 2023-03-06T13:14:11Z | 2023-02-27T04:03:38Z | null | ### Describe the bug
Loading the `c4` dataset in streaming mode with `load_dataset("c4", "en", split="validation", streaming=True)` and then using it fails with a `FileNotFoundException`.
### Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset("c4", "en", split="train", streaming=True)
next(iter(dataset))
```
causes a
```
FileNotFoundError: https://huggingface.co/datasets/allenai/c4/resolve/1ddc917116b730e1859edef32896ec5c16be51d0/en/c4-train.00000-of-01024.json.gz
```
I can download this file manually though e.g. by entering this URL in a browser.
There is an underlying HTTP 403 status code:
```
aiohttp.client_exceptions.ClientResponseError: 403, message='Forbidden', url=URL('https://cdn-lfs.huggingface.co/datasets/allenai/c4/8ef8d75b0e045dec4aa5123a671b4564466b0707086a7ed1ba8721626dfffbc9?response-content-disposition=attachment%3B+filename*%3DUTF-8''c4-train.00000-of-01024.json.gz%3B+filename%3D%22c4-train.00000-of-01024.json.gz%22%3B&response-content-type=application/gzip&Expires=1677483770&Policy=eyJTdGF0ZW1lbnQiOlt7IlJlc291cmNlIjoiaHR0cHM6Ly9jZG4tbGZzLmh1Z2dpbmdmYWNlLmNvL2RhdGFzZXRzL2FsbGVuYWkvYzQvOGVmOGQ3NWIwZTA0NWRlYzRhYTUxMjNhNjcxYjQ1NjQ0NjZiMDcwNzA4NmE3ZWQxYmE4NzIxNjI2ZGZmZmJjOT9yZXNwb25zZS1jb250ZW50LWRpc3Bvc2l0aW9uPSomcmVzcG9uc2UtY29udGVudC10eXBlPWFwcGxpY2F0aW9uJTJGZ3ppcCIsIkNvbmRpdGlvbiI6eyJEYXRlTGVzc1RoYW4iOnsiQVdTOkVwb2NoVGltZSI6MTY3NzQ4Mzc3MH19fV19&Signature=yjL3UeY72cf2xpnvPvD68eAYOEe2qtaUJV55sB-jnPskBJEMwpMJcBZvg2~GqXZdM3O-GWV-Z3CI~d4u5VCb4YZ-HlmOjr3VBYkvox2EKiXnBIhjMecf2UVUPtxhTa9kBVlWjqu4qKzB9gKXZF2Cwpp5ctLzapEaT2nnqF84RAL-rsqMA3I~M8vWWfivQsbBK63hMfgZqqKMgdWM0iKMaItveDl0ufQ29azMFmsR7qd8V7sU2Z-F1fAeohS8HpN9OOnClW34yi~YJ2AbgZJJBXA~qsylfVA0Qp7Q~yX~q4P8JF1vmJ2BjkiSbGrj3bAXOGugpOVU5msI52DT88yMdA__&Key-Pair-Id=KVTP0A1DKRTAX')
```
### Expected behavior
This should retrieve the first example from the C4 validation set. This worked a few days ago but stopped working now.
### Environment info
- `datasets` version: 2.9.0
- Platform: Linux-5.15.0-60-generic-x86_64-with-glibc2.31
- Python version: 3.9.16
- PyArrow version: 11.0.0
- Pandas version: 1.5.3
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} | https://api.github.com/repos/huggingface/datasets/issues/5574/timeline | null | completed | null | null | false | [
"Also encountering this issue for every dataset I try to stream! Installed datasets from main:\r\n```\r\n- `datasets` version: 2.10.1.dev0\r\n- Platform: macOS-13.1-arm64-arm-64bit\r\n- Python version: 3.9.13\r\n- PyArrow version: 10.0.1\r\n- Pandas version: 1.5.2\r\n```\r\n\r\nRepro:\r\n```python\r\nfrom datasets ... |
https://api.github.com/repos/huggingface/datasets/issues/1177 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1177/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1177/comments | https://api.github.com/repos/huggingface/datasets/issues/1177/events | https://github.com/huggingface/datasets/pull/1177 | 757,778,684 | MDExOlB1bGxSZXF1ZXN0NTMzMDkxMTQ3 | 1,177 | Add Korean NER dataset | [] | closed | false | null | 1 | 2020-12-05T20:56:00Z | 2020-12-06T20:19:48Z | 2020-12-06T20:19:48Z | null | This PR adds the [Korean named entity recognition dataset](https://github.com/kmounlp/NER). This dataset has been used in many downstream tasks, such as training [KoBERT](https://github.com/SKTBrain/KoBERT) for NER, as seen in this [KoBERT-CRF implementation](https://github.com/eagle705/pytorch-bert-crf-ner). | {
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} | true | [
"Closed via #1219 "
] |
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