id int64 599M 3.48B | number int64 1 7.8k | title stringlengths 1 290 | state stringclasses 2
values | comments listlengths 0 30 | created_at timestamp[s]date 2020-04-14 10:18:02 2025-10-05 06:37:50 | updated_at timestamp[s]date 2020-04-27 16:04:17 2025-10-05 10:32:43 | closed_at timestamp[s]date 2020-04-14 12:01:40 2025-10-01 13:56:03 ⌀ | body stringlengths 0 228k ⌀ | user stringlengths 3 26 | html_url stringlengths 46 51 | pull_request dict | is_pull_request bool 2
classes |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
1,086,945,384 | 3,474 | Decode images when iterating | closed | [] | 2021-12-22T15:34:49 | 2023-09-24T09:54:04 | 2021-12-28T16:08:10 | If I iterate over a vision dataset, the images are not decoded, and the dictionary with the bytes is returned.
This PR enables image decoding in `Dataset.__iter__`
Close https://github.com/huggingface/datasets/issues/3473 | lhoestq | https://github.com/huggingface/datasets/pull/3474 | {
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"patch_url": "https://github.com/huggingface/datasets/pull/3474.patch",
"merged_at": null
} | true |
1,086,937,610 | 3,473 | Iterating over a vision dataset doesn't decode the images | closed | [
"As discussed, I remember I set `decoded=False` here to avoid decoding just by iterating over examples of dataset. We wanted to decode only if the \"audio\" field (for Audio feature) was accessed.",
"> I set decoded=False here to avoid decoding just by iterating over examples of dataset. We wanted to decode only ... | 2021-12-22T15:26:32 | 2021-12-27T14:13:21 | 2021-12-23T15:21:57 | ## Describe the bug
If I load `mnist` and I iterate over the dataset, the images are not decoded, and the dictionary with the bytes is returned.
## Steps to reproduce the bug
```python
from datasets import load_dataset
import PIL
mnist = load_dataset("mnist", split="train")
first_image = mnist[0]["image"]
assert isinstance(first_image, PIL.PngImagePlugin.PngImageFile) # passes
first_image = next(iter(mnist))["image"]
assert isinstance(first_image, PIL.PngImagePlugin.PngImageFile) # fails
```
## Expected results
The image should be decoded, as a PIL Image
## Actual results
We get a dictionary
```
{'bytes': b'\x89PNG\r\n\x1a\n\x00..., 'path': None}
```
## Environment info
- `datasets` version: 1.17.1.dev0
- Platform: Darwin-20.6.0-x86_64-i386-64bit
- Python version: 3.7.2
- PyArrow version: 6.0.0
The bug also exists in 1.17.0
## Investigation
I think the issue is that decoding is disabled in `__iter__`:
https://github.com/huggingface/datasets/blob/dfe5b73387c5e27de6a16b0caeb39d3b9ded66d6/src/datasets/arrow_dataset.py#L1651-L1661
Do you remember why it was disabled in the first place @albertvillanova ?
Also cc @mariosasko @NielsRogge
| lhoestq | https://github.com/huggingface/datasets/issues/3473 | null | false |
1,086,908,508 | 3,472 | Fix `str(Path(...))` conversion in streaming on Linux | closed | [] | 2021-12-22T15:06:03 | 2021-12-22T16:52:53 | 2021-12-22T16:52:52 | Fix `str(Path(...))` conversion in streaming on Linux. This should fix the streaming of the `beans` and `cats_vs_dogs` datasets. | mariosasko | https://github.com/huggingface/datasets/pull/3472 | {
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"patch_url": "https://github.com/huggingface/datasets/pull/3472.patch",
"merged_at": "2021-12-22T16:52:52"
} | true |
1,086,588,074 | 3,471 | Fix Tashkeela dataset to yield stripped text | closed | [] | 2021-12-22T08:41:30 | 2021-12-22T10:12:08 | 2021-12-22T10:12:07 | This PR:
- Yields stripped text
- Fix path for Windows
- Adds license
- Adds more info in dataset card
Close bigscience-workshop/data_tooling#279 | albertvillanova | https://github.com/huggingface/datasets/pull/3471 | {
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"merged_at": "2021-12-22T10:12:07"
} | true |
1,086,049,888 | 3,470 | Fix rendering of docs | closed | [] | 2021-12-21T17:17:01 | 2021-12-22T09:23:47 | 2021-12-22T09:23:47 | Minor fix in docs.
Currently, `ClassLabel` docstring rendering is not right. | albertvillanova | https://github.com/huggingface/datasets/pull/3470 | {
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"patch_url": "https://github.com/huggingface/datasets/pull/3470.patch",
"merged_at": "2021-12-22T09:23:47"
} | true |
1,085,882,664 | 3,469 | Fix METEOR missing NLTK's omw-1.4 | closed | [
"I also modified the doctest call to raise the exception that doctest may catch, instead of `doctest.UnexpectedException`.\r\nThis will make debugging easier if it happens again"
] | 2021-12-21T14:19:11 | 2021-12-21T14:52:28 | 2021-12-21T14:49:28 | NLTK 3.6.6 now requires `omw-1.4` to be downloaded for METEOR to work.
This should fix the CI on master | lhoestq | https://github.com/huggingface/datasets/pull/3469 | {
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"merged_at": "2021-12-21T14:49:28"
} | true |
1,085,871,301 | 3,468 | Add COCO dataset | closed | [
"The CI failures other than a missing dummy data file and missing fields in the card are unrelated to this PR. ",
"Thanks a lot for this great work and fixing TFDS based script @mariosasko 🤗 will generate the dummy dataset and write the model card tomorrow!",
"@mariosasko I added the dataset card, I'm on the d... | 2021-12-21T14:07:50 | 2023-09-24T09:33:31 | 2022-10-03T09:36:08 | This PR adds the MS COCO dataset. Compared to the [TFDS](https://github.com/tensorflow/datasets/blob/master/tensorflow_datasets/object_detection/coco.py) script, this implementation adds 8 additional configs to cover the tasks other than object detection.
Some notes:
* the data exposed by TFDS is contained in the `2014`, `2015`, `2017` and `2017_panoptic_segmentation` configs here
* I've updated `encode_nested_example` for easier handling of missing values (cc @lhoestq @albertvillanova; will add tests if you are OK with the changes in `features.py`)
* this implementation should fix https://github.com/huggingface/datasets/pull/3377#issuecomment-985559427
TODOs:
- [x] dataset card
- [ ] dummy data
cc @merveenoyan
Closes #2526 | mariosasko | https://github.com/huggingface/datasets/pull/3468 | {
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"patch_url": "https://github.com/huggingface/datasets/pull/3468.patch",
"merged_at": null
} | true |
1,085,870,665 | 3,467 | Push dataset infos.json to Hub | closed | [
"The change from `___` to `--` was allowed by https://github.com/huggingface/moon-landing/pull/1657"
] | 2021-12-21T14:07:13 | 2021-12-21T17:00:10 | 2021-12-21T17:00:09 | When doing `push_to_hub`, the feature types are lost (see issue https://github.com/huggingface/datasets/issues/3394).
This PR fixes this by also pushing a `dataset_infos.json` file to the Hub, that stores the feature types.
Other minor changes:
- renamed the `___` separator to `--`, since `--` is now disallowed in a name in the back-end.
I tested this feature with datasets like conll2003 that has feature types like `ClassLabel` that were previously lost.
Close https://github.com/huggingface/datasets/issues/3394
I would like to include this in today's release (though not mandatory), so feel free to comment/suggest changes | lhoestq | https://github.com/huggingface/datasets/pull/3467 | {
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"patch_url": "https://github.com/huggingface/datasets/pull/3467.patch",
"merged_at": "2021-12-21T17:00:09"
} | true |
1,085,722,837 | 3,466 | Add CRASS dataset | closed | [
"Hi Albert,\r\nThank you for your comments.\r\nI hope I have uploaded my local git repo to include the dummy files and style reworkings.\r\nAdded YAML in Readme as well.\r\n\r\nPlease check again.\r\n\r\nHope it works now :)",
"Thanks for your contribution, @apergo-ai. \r\n\r\nWe are removing the dataset scripts ... | 2021-12-21T11:17:22 | 2022-10-03T09:37:06 | 2022-10-03T09:37:06 | Added crass dataset | apergo-ai | https://github.com/huggingface/datasets/pull/3466 | {
"url": "https://api.github.com/repos/huggingface/datasets/pulls/3466",
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"patch_url": "https://github.com/huggingface/datasets/pull/3466.patch",
"merged_at": null
} | true |
1,085,400,432 | 3,465 | Unable to load 'cnn_dailymail' dataset | closed | [
"Hi @talha1503, thanks for reporting.\r\n\r\nIt seems there is an issue with one of the data files hosted at Google Drive:\r\n```\r\nGoogle Drive - Quota exceeded\r\n\r\nSorry, you can't view or download this file at this time.\r\n\r\nToo many users have viewed or downloaded this file recently. Please try accessing... | 2021-12-21T03:32:21 | 2024-06-12T14:41:17 | 2022-02-17T14:13:57 | ## Describe the bug
I wanted to load cnn_dailymail dataset from huggingface datasets on Google Colab, but I am getting an error while loading it.
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset('cnn_dailymail', '3.0.0', ignore_verifications = True)
```
## Expected results
Expecting to load 'cnn_dailymail' dataset.
## Actual results
`NotADirectoryError: [Errno 20] Not a directory: '/root/.cache/huggingface/datasets/downloads/1bc05d24fa6dda2468e83a73cf6dc207226e01e3c48a507ea716dc0421da583b/cnn/stories'`
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.16.1
- Platform: Linux-5.4.104+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.12
- PyArrow version: 3.0.0
| talha1503 | https://github.com/huggingface/datasets/issues/3465 | null | false |
1,085,399,097 | 3,464 | struct.error: 'i' format requires -2147483648 <= number <= 2147483647 | open | [
"Hi ! Can you try setting `datasets.config.MAX_TABLE_NBYTES_FOR_PICKLING` to a smaller value than `4 << 30` (4GiB), for example `500 << 20` (500MiB) ? It should reduce the maximum size of the arrow table being pickled during multiprocessing.\r\n\r\nIf it fixes the issue, we can consider lowering the default value f... | 2021-12-21T03:29:01 | 2022-11-21T19:55:11 | null | ## Describe the bug
A clear and concise description of what the bug is.
using latest datasets=datasets-1.16.1-py3-none-any.whl
process my own multilingual dataset by following codes, and the number of rows in all dataset is 306000, the max_length of each sentence is 256:
then I get this error:
I have seen the issue in #2134 and #2150, so I don't understand why latest repo still can't deal with big dataset.
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version:
- Platform: linux docker
- Python version: 3.6
| koukoulala | https://github.com/huggingface/datasets/issues/3464 | null | false |
1,085,078,795 | 3,463 | Update swahili_news dataset | closed | [] | 2021-12-20T18:20:20 | 2021-12-21T06:24:03 | 2021-12-21T06:24:02 | Update dataset with latest verion data files.
Fix #3462.
Close bigscience-workshop/data_tooling#107 | albertvillanova | https://github.com/huggingface/datasets/pull/3463 | {
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"patch_url": "https://github.com/huggingface/datasets/pull/3463.patch",
"merged_at": "2021-12-21T06:24:01"
} | true |
1,085,049,661 | 3,462 | Update swahili_news dataset | closed | [] | 2021-12-20T17:44:01 | 2021-12-21T06:24:02 | 2021-12-21T06:24:01 | Please note also: the HuggingFace version at https://huggingface.co/datasets/swahili_news is outdated. An updated version, with deduplicated text and official splits, can be found at https://zenodo.org/record/5514203.
## Adding a Dataset
- **Name:** swahili_news
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
Related to:
- bigscience-workshop/data_tooling#107
| albertvillanova | https://github.com/huggingface/datasets/issues/3462 | null | false |
1,085,007,346 | 3,461 | Fix links in metrics description | closed | [] | 2021-12-20T16:56:19 | 2021-12-20T17:14:52 | 2021-12-20T17:14:51 | Remove Markdown syntax for links in metrics description, as it is not properly rendered.
Related to #3437. | albertvillanova | https://github.com/huggingface/datasets/pull/3461 | {
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"patch_url": "https://github.com/huggingface/datasets/pull/3461.patch",
"merged_at": "2021-12-20T17:14:51"
} | true |
1,085,002,469 | 3,460 | Don't encode lists as strings when using `Value("string")` | closed | [
"Should we close this PR?",
"since the original issue has to do with metrics that have been moved to `evaludate` I think we can close this one",
"_The documentation is not available anymore as the PR was closed or merged._"
] | 2021-12-20T16:50:49 | 2023-09-25T10:28:30 | 2023-09-25T09:20:28 | Following https://github.com/huggingface/datasets/pull/3456#event-5792250497 it looks like `datasets` can silently convert lists to strings using `str()`, instead of raising an error.
This PR fixes this and should fix the issue with WER showing low values if the input format is not right. | lhoestq | https://github.com/huggingface/datasets/pull/3460 | {
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"patch_url": "https://github.com/huggingface/datasets/pull/3460.patch",
"merged_at": null
} | true |
1,084,969,672 | 3,459 | dataset.filter overwriting previously set dataset._indices values, resulting in the wrong elements being selected. | closed | [
"I think this is a duplicate of [#3190](https://github.com/huggingface/datasets/issues/3190)?",
"Upgrading the datasets version as per #3190 fixes this bug. \r\nI'm Marking as closed."
] | 2021-12-20T16:16:49 | 2021-12-20T16:34:57 | 2021-12-20T16:34:57 | ## Describe the bug
When using dataset.select to select a subset of a dataset, dataset._indices are set to indicate which elements are now considered in the dataset.
The same thing happens when you shuffle the dataset; dataset._indices are set to indicate what the new order of the data is.
However, if you then use a dataset.filter, that filter interacts with those dataset._indices values in a non-intuitive manner.
https://huggingface.co/docs/datasets/_modules/datasets/arrow_dataset.html#Dataset.filter
Effectively, it looks like the original set of _indices were discared and overwritten by the set created during the filter operation.
I think this is actually an issue with how the map function handles dataset._indices. Ideally it should use the _indices it gets passed, and then return an updated _indices which reflect the map transformation applied to the starting _indices.
## Steps to reproduce the bug
```python
dataset = load_dataset('imdb', split='train', keep_in_memory=True)
dataset = dataset.shuffle(keep_in_memory=True)
dataset = dataset.select(range(0, 10), keep_in_memory=True)
print("initial 10 elements")
print(dataset['label']) # -> [1, 1, 0, 1, 0, 0, 0, 1, 0, 0]
dataset = dataset.filter(lambda x: x['label'] == 0, keep_in_memory=True)
print("filtered 10 elements looking for label 0")
print(dataset['label']) # -> [1, 1, 1, 1, 1, 1]
```
## Actual results
```
$ python indices_bug.py
initial 10 elements
[1, 1, 0, 1, 0, 0, 0, 1, 0, 0]
filtered 10 elements looking for label 0
[1, 1, 1, 1, 1, 1]
```
This code block first shuffles the dataset (to get a mix of label 0 and label 1).
Then it selects just the first 10 elements (the number of elements does not matter, 10 is just easy to visualize). The important part is that you select some subset of the dataset.
Finally, a filter is applied to pull out just the elements with `label == 0`.
The bug is that you cannot combine any dataset operation which sets the dataset._indices with filter.
In this case I have 2, shuffle and subset.
If you just use a single dataset._indices operation (in this case shuffle) the bug still shows up.
The shuffle sets the dataset._indices and then filter uses those indices in the map, then overwrites dataset._indices with the filter results.
```python
dataset = load_dataset('imdb', split='train', keep_in_memory=True)
dataset = dataset.shuffle(keep_in_memory=True)
dataset = dataset.filter(lambda x: x['label'] == 0, keep_in_memory=True)
dataset = dataset.select(range(0, 10), keep_in_memory=True)
print(dataset['label']) # -> [1, 1, 1, 1, 1, 1, 1, 1, 1, 1]
```
## Expected results
In an ideal world, the dataset filter would respect any dataset._indices values which had previously been set.
If you use dataset.filter with the base dataset (where dataset._indices has not been set) then the filter command works as expected.
## Environment info
Here are the commands required to rebuild the conda environment from scratch.
```
# create a virtual environment
conda create -n dataset_indices python=3.8 -y
# activate the virtual environment
conda activate dataset_indices
# install huggingface datasets
conda install datasets
```
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.12.1
- Platform: Linux-5.11.0-41-generic-x86_64-with-glibc2.17
- Python version: 3.8.12
- PyArrow version: 3.0.0
### Full Conda Environment
```
$ conda env export
name: dasaset_indices
channels:
- defaults
dependencies:
- _libgcc_mutex=0.1=main
- _openmp_mutex=4.5=1_gnu
- abseil-cpp=20210324.2=h2531618_0
- aiohttp=3.8.1=py38h7f8727e_0
- aiosignal=1.2.0=pyhd3eb1b0_0
- arrow-cpp=3.0.0=py38h6b21186_4
- attrs=21.2.0=pyhd3eb1b0_0
- aws-c-common=0.4.57=he6710b0_1
- aws-c-event-stream=0.1.6=h2531618_5
- aws-checksums=0.1.9=he6710b0_0
- aws-sdk-cpp=1.8.185=hce553d0_0
- bcj-cffi=0.5.1=py38h295c915_0
- blas=1.0=mkl
- boost-cpp=1.73.0=h27cfd23_11
- bottleneck=1.3.2=py38heb32a55_1
- brotli=1.0.9=he6710b0_2
- brotli-python=1.0.9=py38heb0550a_2
- brotlicffi=1.0.9.2=py38h295c915_0
- brotlipy=0.7.0=py38h27cfd23_1003
- bzip2=1.0.8=h7b6447c_0
- c-ares=1.17.1=h27cfd23_0
- ca-certificates=2021.10.26=h06a4308_2
- certifi=2021.10.8=py38h06a4308_0
- cffi=1.14.6=py38h400218f_0
- conllu=4.4.1=pyhd3eb1b0_0
- cryptography=36.0.0=py38h9ce1e76_0
- dataclasses=0.8=pyh6d0b6a4_7
- dill=0.3.4=pyhd3eb1b0_0
- double-conversion=3.1.5=he6710b0_1
- et_xmlfile=1.1.0=py38h06a4308_0
- filelock=3.4.0=pyhd3eb1b0_0
- frozenlist=1.2.0=py38h7f8727e_0
- gflags=2.2.2=he6710b0_0
- glog=0.5.0=h2531618_0
- gmp=6.2.1=h2531618_2
- grpc-cpp=1.39.0=hae934f6_5
- huggingface_hub=0.0.17=pyhd3eb1b0_0
- icu=58.2=he6710b0_3
- idna=3.3=pyhd3eb1b0_0
- importlib-metadata=4.8.2=py38h06a4308_0
- importlib_metadata=4.8.2=hd3eb1b0_0
- intel-openmp=2021.4.0=h06a4308_3561
- krb5=1.19.2=hac12032_0
- ld_impl_linux-64=2.35.1=h7274673_9
- libboost=1.73.0=h3ff78a5_11
- libcurl=7.80.0=h0b77cf5_0
- libedit=3.1.20210910=h7f8727e_0
- libev=4.33=h7f8727e_1
- libevent=2.1.8=h1ba5d50_1
- libffi=3.3=he6710b0_2
- libgcc-ng=9.3.0=h5101ec6_17
- libgomp=9.3.0=h5101ec6_17
- libnghttp2=1.46.0=hce63b2e_0
- libprotobuf=3.17.2=h4ff587b_1
- libssh2=1.9.0=h1ba5d50_1
- libstdcxx-ng=9.3.0=hd4cf53a_17
- libthrift=0.14.2=hcc01f38_0
- libxml2=2.9.12=h03d6c58_0
- libxslt=1.1.34=hc22bd24_0
- lxml=4.6.3=py38h9120a33_0
- lz4-c=1.9.3=h295c915_1
- mkl=2021.4.0=h06a4308_640
- mkl-service=2.4.0=py38h7f8727e_0
- mkl_fft=1.3.1=py38hd3c417c_0
- mkl_random=1.2.2=py38h51133e4_0
- multiprocess=0.70.12.2=py38h7f8727e_0
- multivolumefile=0.2.3=pyhd3eb1b0_0
- ncurses=6.3=h7f8727e_2
- numexpr=2.7.3=py38h22e1b3c_1
- numpy=1.21.2=py38h20f2e39_0
- numpy-base=1.21.2=py38h79a1101_0
- openpyxl=3.0.9=pyhd3eb1b0_0
- openssl=1.1.1l=h7f8727e_0
- orc=1.6.9=ha97a36c_3
- packaging=21.3=pyhd3eb1b0_0
- pip=21.2.4=py38h06a4308_0
- py7zr=0.16.1=pyhd3eb1b0_1
- pycparser=2.21=pyhd3eb1b0_0
- pycryptodomex=3.10.1=py38h27cfd23_1
- pyopenssl=21.0.0=pyhd3eb1b0_1
- pyparsing=3.0.4=pyhd3eb1b0_0
- pyppmd=0.16.1=py38h295c915_0
- pysocks=1.7.1=py38h06a4308_0
- python=3.8.12=h12debd9_0
- python-dateutil=2.8.2=pyhd3eb1b0_0
- python-xxhash=2.0.2=py38h7f8727e_0
- pyzstd=0.14.4=py38h7f8727e_3
- re2=2020.11.01=h2531618_1
- readline=8.1=h27cfd23_0
- requests=2.26.0=pyhd3eb1b0_0
- setuptools=58.0.4=py38h06a4308_0
- six=1.16.0=pyhd3eb1b0_0
- snappy=1.1.8=he6710b0_0
- sqlite=3.36.0=hc218d9a_0
- texttable=1.6.4=pyhd3eb1b0_0
- tk=8.6.11=h1ccaba5_0
- typing_extensions=3.10.0.2=pyh06a4308_0
- uriparser=0.9.3=he6710b0_1
- utf8proc=2.6.1=h27cfd23_0
- wheel=0.37.0=pyhd3eb1b0_1
- xxhash=0.8.0=h7f8727e_3
- xz=5.2.5=h7b6447c_0
- zipp=3.6.0=pyhd3eb1b0_0
- zlib=1.2.11=h7f8727e_4
- zstd=1.4.9=haebb681_0
- pip:
- async-timeout==4.0.2
- charset-normalizer==2.0.9
- datasets==1.16.1
- fsspec==2021.11.1
- huggingface-hub==0.2.1
- multidict==5.2.0
- pandas==1.3.5
- pyarrow==6.0.1
- pytz==2021.3
- pyyaml==6.0
- tqdm==4.62.3
- typing-extensions==4.0.1
- urllib3==1.26.7
- yarl==1.7.2
```
| mmajurski | https://github.com/huggingface/datasets/issues/3459 | null | false |
1,084,926,025 | 3,458 | Fix duplicated tag in wikicorpus dataset card | closed | [
"CI is failing just because of empty sections - merging"
] | 2021-12-20T15:34:16 | 2021-12-20T16:03:25 | 2021-12-20T16:03:24 | null | lhoestq | https://github.com/huggingface/datasets/pull/3458 | {
"url": "https://api.github.com/repos/huggingface/datasets/pulls/3458",
"html_url": "https://github.com/huggingface/datasets/pull/3458",
"diff_url": "https://github.com/huggingface/datasets/pull/3458.diff",
"patch_url": "https://github.com/huggingface/datasets/pull/3458.patch",
"merged_at": "2021-12-20T16:03:24"
} | true |
1,084,862,121 | 3,457 | Add CMU Graphics Lab Motion Capture dataset | open | [
"This dataset has files in ASF/AMC format. [ The skeleton file is the ASF file (Acclaim Skeleton File). The motion file is the AMC file (Acclaim Motion Capture data). ] \r\n\r\nSome questions : \r\n1. How do we go about representing these features using datasets.Features and generate examples ?\r\n2. The dataset d... | 2021-12-20T14:34:39 | 2022-03-16T16:53:09 | null | ## Adding a Dataset
- **Name:** CMU Graphics Lab Motion Capture database
- **Description:** The database contains free motions which you can download and use.
- **Data:** http://mocap.cs.cmu.edu/
- **Motivation:** Nice motion capture dataset
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md). | osanseviero | https://github.com/huggingface/datasets/issues/3457 | null | false |
1,084,687,973 | 3,456 | [WER] Better error message for wer | closed | [
"Hi ! I don't think this would solve this issue.\r\nCurrently it looks like there's a bug that converts the list `[\"hello it's nice\"]` to a string `'[\"hello it's nice\"]'` since this is what the metric expects as input. The conversion is done before the data are passed to `_compute()`.\r\n\r\nThis is `Value(\"st... | 2021-12-20T11:38:40 | 2021-12-20T16:53:37 | 2021-12-20T16:53:36 | Currently we have the following problem when using the WER. When the input format to the WER metric is wrong, instead of throwing an error message a word-error-rate is computed which is incorrect. E.g. when doing the following:
```python
from datasets import load_metric
wer = load_metric("wer")
target_str = ["hello this is nice", "hello the weather is bloomy"]
pred_str = [["hello it's nice"], ["hello it's the weather"]]
print("Wrong:", wer.compute(predictions=pred_str, references=target_str))
print("Correct", wer.compute(predictions=[x[0] for x in pred_str], references=target_str))
```
We get:
```
Wrong: 1.0
Correct 0.5555555555555556
```
meaning that we get a word-error rate for incorrectly passed input formats. We should raise an error here instead so that people don't spent hours fixing a model while it's their incorrect evaluation metric is the problem for a low WER. | patrickvonplaten | https://github.com/huggingface/datasets/pull/3456 | {
"url": "https://api.github.com/repos/huggingface/datasets/pulls/3456",
"html_url": "https://github.com/huggingface/datasets/pull/3456",
"diff_url": "https://github.com/huggingface/datasets/pull/3456.diff",
"patch_url": "https://github.com/huggingface/datasets/pull/3456.patch",
"merged_at": null
} | true |
1,084,599,650 | 3,455 | Easier information editing | closed | [
"Hi ! I guess you are talking about the dataset cards that are in this repository on github ?\r\n\r\nI think github allows to submit a PR even for 1 line though the `Edit file` button on the page of the dataset card.\r\n\r\nMaybe let's mention this in `CONTRIBUTING.md` ?",
"We now host all the datasets on the HF ... | 2021-12-20T10:10:43 | 2023-07-25T15:36:14 | 2023-07-25T15:36:14 | **Is your feature request related to a problem? Please describe.**
It requires a lot of effort to improve a datasheet.
**Describe the solution you'd like**
UI or at least a link to the place where the code that needs to be edited is (and an easy way to edit this code directly from the site, without cloning, branching, makefile etc.)
**Describe alternatives you've considered**
The current Ux is to have the 8 steps for contribution while One just wishes to change a line a type etc.
| borgr | https://github.com/huggingface/datasets/issues/3455 | null | false |
1,084,519,107 | 3,454 | Fix iter_archive generator | closed | [] | 2021-12-20T08:50:15 | 2021-12-20T10:05:00 | 2021-12-20T10:04:59 | This PR:
- Adds tests to DownloadManager and StreamingDownloadManager `iter_archive` for both path and file inputs
- Fixes bugs in `iter_archive` introduced in:
- #3443
Fix #3453. | albertvillanova | https://github.com/huggingface/datasets/pull/3454 | {
"url": "https://api.github.com/repos/huggingface/datasets/pulls/3454",
"html_url": "https://github.com/huggingface/datasets/pull/3454",
"diff_url": "https://github.com/huggingface/datasets/pull/3454.diff",
"patch_url": "https://github.com/huggingface/datasets/pull/3454.patch",
"merged_at": "2021-12-20T10:04:59"
} | true |
1,084,515,911 | 3,453 | ValueError while iter_archive | closed | [] | 2021-12-20T08:46:18 | 2021-12-20T10:04:59 | 2021-12-20T10:04:59 | ## Describe the bug
After the merge of:
- #3443
the method `iter_archive` throws a ValueError:
```
ValueError: read of closed file
```
## Steps to reproduce the bug
```python
for path, file in dl_manager.iter_archive(archive_path):
pass
```
| albertvillanova | https://github.com/huggingface/datasets/issues/3453 | null | false |
1,083,803,178 | 3,452 | why the stratify option is omitted from test_train_split function? | closed | [
"Hi ! It's simply not added yet :)\r\n\r\nIf someone wants to contribute to add the `stratify` parameter I'd be happy to give some pointers.\r\n\r\nIn the meantime, I guess you can use `sklearn` or other tools to do a stratified train/test split over the **indices** of your dataset and then do\r\n```\r\ntrain_datas... | 2021-12-18T10:37:47 | 2022-05-25T20:43:51 | 2022-05-25T20:43:51 | why the stratify option is omitted from test_train_split function?
is there any other way implement the stratify option while splitting the dataset? as it is important point to be considered while splitting the dataset. | j-sieger | https://github.com/huggingface/datasets/issues/3452 | null | false |
1,083,459,137 | 3,451 | [Staging] Update dataset repos automatically on the Hub | closed | [
"do keep us updated on how it's going in staging! cc @SBrandeis ",
"Sure ! For now it works smoothly. We'll also do a new release today.\r\n\r\nI can send you some repos to explore on staging, in case you want to see how they look like after being updated.\r\nFor example [swahili_news](https://moon-staging.huggin... | 2021-12-17T17:12:11 | 2021-12-21T10:25:46 | 2021-12-20T14:09:51 | Let's have a script that updates the dataset repositories on staging for now. This way we can make sure it works fine before going in prod.
Related to https://github.com/huggingface/datasets/issues/3341
The script runs on each commit on `master`. It checks the datasets that were changed, and it pushes the changes to the corresponding repositories on the Hub.
If there's a new dataset, then a new repository is created.
If the commit is a new release of `datasets`, it also pushes the tag to all the repositories. | lhoestq | https://github.com/huggingface/datasets/pull/3451 | {
"url": "https://api.github.com/repos/huggingface/datasets/pulls/3451",
"html_url": "https://github.com/huggingface/datasets/pull/3451",
"diff_url": "https://github.com/huggingface/datasets/pull/3451.diff",
"patch_url": "https://github.com/huggingface/datasets/pull/3451.patch",
"merged_at": "2021-12-20T14:09:51"
} | true |
1,083,450,158 | 3,450 | Unexpected behavior doing Split + Filter | closed | [
"Hi ! This is an issue with `datasets` 1.12. Sorry for the inconvenience. Can you update to `>=1.13` ?\r\nsee https://github.com/huggingface/datasets/issues/3190\r\n\r\nMaybe we should also backport the bug fix to `1.12` (in a new version `1.12.2`)"
] | 2021-12-17T17:00:39 | 2023-07-25T15:38:47 | 2023-07-25T15:38:47 | ## Describe the bug
I observed unexpected behavior when applying 'train_test_split' followed by 'filter' on dataset. Elements of the training dataset eventually end up in the test dataset (after applying the 'filter')
## Steps to reproduce the bug
```
from datasets import Dataset
import pandas as pd
dic = {'x': [1,2,3,4,5,6,7,8,9], 'y':['q','w','e','r','t','y','u','i','o']}
df = pd.DataFrame.from_dict(dic)
dataset = Dataset.from_pandas(df)
split_dataset = dataset.train_test_split(test_size=0.5, shuffle=False, seed=42)
train_dataset = split_dataset["train"]
eval_dataset = split_dataset["test"]
eval_dataset_2 = eval_dataset.filter(lambda example: example['x'] % 2 == 0)
print( eval_dataset['x'])
print(eval_dataset_2['x'])
```
One observes that elements in eval_dataset2 are actually coming from the training dataset...
## Expected results
The expected results would be that the filtered eval dataset would only contain elements from the original eval dataset.
## Actual results
Specify the actual results or traceback.
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.12.1
- Platform: Windows 10
- Python version: 3.7
- PyArrow version: 5.0.0
| jbrachat | https://github.com/huggingface/datasets/issues/3450 | null | false |
1,083,373,018 | 3,449 | Add `__add__()`, `__iadd__()` and similar to `Dataset` class | closed | [
"I was going through the codebase, and I believe the implementation of __add__() and __iadd__() will be similar to concatenate_datasets() after the elimination of code for arguments other than the list of datasets (info, split, axis). \r\n(Assuming elimination of axis means concatenating over axis 1.)",
"Most dat... | 2021-12-17T15:29:11 | 2024-02-29T16:47:56 | 2023-07-25T15:33:56 | **Is your feature request related to a problem? Please describe.**
No.
**Describe the solution you'd like**
I would like to be able to concatenate datasets as follows:
```python
>>> dataset["train"] += dataset["validation"]
```
... instead of using `concatenate_datasets()`:
```python
>>> raw_datasets["train"] = concatenate_datasets([raw_datasets["train"], raw_datasets["validation"]])
>>> del raw_datasets["validation"]
```
**Describe alternatives you've considered**
Well, I have considered `concatenate_datasets()` 😀
**Additional context**
N.a.
| sgraaf | https://github.com/huggingface/datasets/issues/3449 | null | false |
1,083,231,080 | 3,448 | JSONDecodeError with HuggingFace dataset viewer | closed | [
"Hi ! I think the issue comes from the dataset_infos.json file: it has the \"flat\" field twice.\r\n\r\nCan you try deleting this file and regenerating it please ?",
"Thanks! That fixed that, but now I am getting:\r\nServer Error\r\nStatus code: 400\r\nException: KeyError\r\nMessage: 'feature'\r\n\r\n... | 2021-12-17T12:52:41 | 2022-02-24T09:10:26 | 2022-02-24T09:10:26 | ## Dataset viewer issue for 'pubmed_neg'
**Link:** https://huggingface.co/datasets/IGESML/pubmed_neg
I am getting the error:
Status code: 400
Exception: JSONDecodeError
Message: Expecting property name enclosed in double quotes: line 61 column 2 (char 1202)
I have checked all files - I am not using single quotes anywhere. Not sure what is causing this issue.
Am I the one who added this dataset ? Yes
| kathrynchapman | https://github.com/huggingface/datasets/issues/3448 | null | false |
1,082,539,790 | 3,447 | HF_DATASETS_OFFLINE=1 didn't stop datasets.builder from downloading | closed | [
"Hi ! Indeed it says \"downloading and preparing\" but in your case it didn't need to download anything since you used local files (it would have thrown an error otherwise). I think we can improve the logging to make it clearer in this case",
"@lhoestq Thank you for explaining. I am sorry but I was not clear abou... | 2021-12-16T18:51:13 | 2022-02-17T14:16:27 | 2022-02-17T14:16:27 | ## Describe the bug
According to https://huggingface.co/docs/datasets/loading_datasets.html#loading-a-dataset-builder, setting HF_DATASETS_OFFLINE to 1 should make datasets to "run in full offline mode". It didn't work for me. At the very beginning, datasets still tried to download "custom data configuration" for JSON, despite I have run the program once and cached all data into the same --cache_dir.
"Downloading" is not an issue when running with local disk, but crashes often with cloud storage because (1) multiply GPU processes try to access the same file, AND (2) FileLocker fails to synchronize all processes, due to storage throttling. 99% of times, when the main process releases FileLocker, the file is not actually ready for access in cloud storage and thus triggers "FileNotFound" errors for all other processes. Well, another way to resolve the problem is to investigate super reliable cloud storage, but that's out of scope here.
## Steps to reproduce the bug
```
export HF_DATASETS_OFFLINE=1
python run_clm.py --model_name_or_path=models/gpt-j-6B --train_file=trainpy.v2.train.json --validation_file=trainpy.v2.eval.json --cache_dir=datacache/trainpy.v2
```
## Expected results
datasets should stop all "downloading" behavior but reuse the cached JSON configuration. I think the problem here is part of the cache directory path, "default-471372bed4b51b53", is randomly generated, and it could change if some parameters changed. And I didn't find a way to use a fixed path to ensure datasets to reuse cached data every time.
## Actual results
The logging shows datasets are still downloading into "datacache/trainpy.v2/json/default-471372bed4b51b53/0.0.0/c2d554c3377ea79c7664b93dc65d0803b45e3279000f993c7bfd18937fd7f426".
```
12/16/2021 10:25:59 - WARNING - datasets.builder - Using custom data configuration default-471372bed4b51b53
12/16/2021 10:25:59 - INFO - datasets.builder - Generating dataset json (datacache/trainpy.v2/json/default-471372bed4b51b53/0.0.0/c2d554c3377ea79c7664b93dc65d0803b45e3279000f993c7bfd18937fd7f426)
Downloading and preparing dataset json/default to datacache/trainpy.v2/json/default-471372bed4b51b53/0.0.0/c2d554c3377ea79c7664b93dc65d0803b45e3279000f993c7bfd18937fd7f426...
100%|██████████████████████████████████████████████████████████████████████████████████| 2/2 [00:00<00:00, 17623.13it/s]
12/16/2021 10:25:59 - INFO - datasets.utils.download_manager - Downloading took 0.0 min
12/16/2021 10:26:00 - INFO - datasets.utils.download_manager - Checksum Computation took 0.0 min
100%|███████████████████████████████████████████████████████████████████████████████████| 2/2 [00:00<00:00, 1206.99it/s]
12/16/2021 10:26:00 - INFO - datasets.utils.info_utils - Unable to verify checksums.
12/16/2021 10:26:00 - INFO - datasets.builder - Generating split train
12/16/2021 10:26:01 - INFO - datasets.builder - Generating split validation
12/16/2021 10:26:02 - INFO - datasets.utils.info_utils - Unable to verify splits sizes.
Dataset json downloaded and prepared to datacache/trainpy.v2/json/default-471372bed4b51b53/0.0.0/c2d554c3377ea79c7664b93dc65d0803b45e3279000f993c7bfd18937fd7f426. Subsequent calls will reuse this data.
100%|█████████████████████████████████████████████████████████████████████████████████████| 2/2 [00:00<00:00, 53.54it/s]
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.16.1
- Platform: Linux
- Python version: 3.8.10
- PyArrow version: 6.0.1
| dunalduck0 | https://github.com/huggingface/datasets/issues/3447 | null | false |
1,082,414,229 | 3,446 | Remove redundant local path information in audio/image datasets | closed | [
"Cool, I'm in favor of this PR. Our official examples in speech already make use of `\"audio\"` so no need to change anything there. It would be great if we could prominently feature how one can get the audio path without decoding in the docs.",
"@patrickvonplaten Yes, I agree.\r\n\r\ncc @stevhliu we should add a... | 2021-12-16T16:35:15 | 2023-09-24T10:09:30 | 2023-09-24T10:09:27 | Remove the redundant path information in the audio/image dataset as discussed in https://github.com/huggingface/datasets/pull/3430#issuecomment-994734828
TODOs:
* [ ] merge https://github.com/huggingface/datasets/pull/3430
* [ ] merge https://github.com/huggingface/datasets/pull/3364
* [ ] re-generate the info files of the updated audio datasets
cc: @patrickvonplaten @anton-l @nateraw (I expect this to break the audio/vision examples in Transformers; after this change you'll be able to access underlying paths as follows `dset = dset.cast_column("audio", Audio(..., decode=False)); path = dset[0]["audio"]`)
| mariosasko | https://github.com/huggingface/datasets/pull/3446 | {
"url": "https://api.github.com/repos/huggingface/datasets/pulls/3446",
"html_url": "https://github.com/huggingface/datasets/pull/3446",
"diff_url": "https://github.com/huggingface/datasets/pull/3446.diff",
"patch_url": "https://github.com/huggingface/datasets/pull/3446.patch",
"merged_at": null
} | true |
1,082,370,968 | 3,445 | question | closed | [
"Hi ! What's your question ?"
] | 2021-12-16T15:57:00 | 2022-01-03T10:09:00 | 2022-01-03T10:09:00 | ## Dataset viewer issue for '*name of the dataset*'
**Link:** *link to the dataset viewer page*
*short description of the issue*
Am I the one who added this dataset ? Yes-No
| BAKAYOKO0232 | https://github.com/huggingface/datasets/issues/3445 | null | false |
1,082,078,961 | 3,444 | Align the Dataset and IterableDataset processing API | open | [
"Yes I agree, these should be as aligned as possible. Maybe we can also check the feedback in the survey at http://hf.co/oss-survey and see if people mentioned related things on the API (in particular if we go the breaking change way, it would be good to be sure we are taking the right direction for the community).... | 2021-12-16T11:26:11 | 2025-01-31T11:07:07 | null | ## Intro
items marked like <s>this</s> are done already :)
Currently the two classes have two distinct API for processing:
### The `.map()` method
Both have those parameters in common: function, batched, batch_size
- IterableDataset is missing those parameters:
<s>with_indices</s>, with_rank, <s>input_columns</s>, <s>drop_last_batch</s>, <s>remove_columns</s>, features, disable_nullable, fn_kwargs, num_proc
- Dataset also has additional parameters that are exclusive, due to caching:
keep_in_memory, load_from_cache_file, cache_file_name, writer_batch_size, suffix_template, new_fingerprint
- <s>There is also an important difference in terms of behavior:
**Dataset.map adds new columns** (with dict.update)
BUT
**IterableDataset discards previous columns** (it overwrites the dict)
IMO the two methods should have the same behavior. This would be an important breaking change though.</s>
- Dataset.map is eager while IterableDataset.map is lazy
### The `.shuffle()` method
- <s>Both have an optional seed parameter, but IterableDataset requires a mandatory parameter buffer_size to control the size of the local buffer used for approximate shuffling.</s>
- <s>IterableDataset is missing the parameter generator</s>
- Also Dataset has exclusive parameters due to caching: keep_in_memory, load_from_cache_file, indices_cache_file_name, writer_batch_size, new_fingerprint
### The `.with_format()` method
- <s>IterableDataset only supports "torch" (it misses tf, jax, pandas, arrow)</s> and is missing the parameters: columns, output_all_columns and format_kwargs
- other methods like `set_format`, `reset_format` or `formatted_as` are also missing
### Other methods
- Both have the same `remove_columns` method
- IterableDataset is missing: <s>cast</s>, <s>cast_column</s>, <s>filter</s>, <s>rename_column</s>, <s>rename_columns</s>, class_encode_column, flatten, train_test_split, <s>shard</s>
- Some other methods are missing but we can discuss them: set_transform, formatted_as, with_transform
- And others don't really make sense for an iterable dataset: select, sort, <s>add_column</s>, add_item
- Dataset is missing skip and take, that IterableDataset implements.
## Questions
I think it would be nice to be able to switch between streaming and regular dataset easily, without changing the processing code significantly.
1. What should be aligned and what shouldn't between those two APIs ?
IMO the minimum is to align the main processing methods.
It would mean aligning breaking the current `Iterable.map` to have the same behavior as `Dataset.map` (add columns with dict.update), and add multiprocessing as well as the missing parameters. DONE ✅
It would also mean implementing the missing methods: cast, cast_column, filter, rename_column, rename_columns, class_encode_column, flatten, prepare_for_task, train_test_split, shard. WIP 🟠
2. What are the breaking changes for IterableDataset ?
The main breaking change would be the change of behavior of `IterableDataset.map`, because currently it discards all the previous columns instead of keeping them. DONE ✅
3. Shall we also do some changes for regular datasets ?
I agree the simplest would be to have the exact same methods for both Dataset and IterableDataset. However this is probably not a good idea because it would prevent users from using the best benefits of them. That's why we can keep some aspects of regular datasets as they are:
- keep the eager Dataset.map with caching
- keep the with_transform method for lazy processing
- keep Dataset.select (it could also be added to IterableDataset even though it's not recommended)
We could have a completely aligned `map` method if both methods were lazy by default, but this is a very big breaking change so I'm not sure we can consider doing that.
For information, TFDS does lazy map by default, and has an additional `.cache()` method.
## Opinions ?
I'd love to gather some opinions about this here. If the two APIs are more aligned it would be awesome for the examples in `transformers`, and it would create a satisfactory experience for users that want to switch from one mode to the other.
cc @mariosasko @albertvillanova @thomwolf @patrickvonplaten @sgugger | lhoestq | https://github.com/huggingface/datasets/issues/3444 | null | false |
1,082,052,833 | 3,443 | Extend iter_archive to support file object input | closed | [] | 2021-12-16T10:59:14 | 2021-12-17T17:53:03 | 2021-12-17T17:53:02 | This PR adds support to passing a file object to `[Streaming]DownloadManager.iter_archive`.
With this feature, we can iterate over a tar file inside another tar file. | albertvillanova | https://github.com/huggingface/datasets/pull/3443 | {
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"patch_url": "https://github.com/huggingface/datasets/pull/3443.patch",
"merged_at": "2021-12-17T17:53:02"
} | true |
1,081,862,747 | 3,442 | Extend text to support yielding lines, paragraphs or documents | closed | [
"The parameter can also be named `split_by` with values \"line\", \"paragraph\" or \"document\" (no 's' at the end)",
"> The parameter can also be named `split_by` with values \"line\", \"paragraph\" or \"document\" (no 's' at the end)\r\n\r\n@lhoestq @mariosasko I would avoid the term `split` in this context and... | 2021-12-16T07:33:17 | 2021-12-20T16:59:10 | 2021-12-20T16:39:18 | Add `config.row` option to `text` module to allow yielding lines (default, current case), paragraphs or documents.
Feel free to comment on the name of the config parameter `row`:
- Currently, the docs state datasets are made of rows and columns
- Other names I considered: `example`, `item` | albertvillanova | https://github.com/huggingface/datasets/pull/3442 | {
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"merged_at": "2021-12-20T16:39:18"
} | true |
1,081,571,784 | 3,441 | Add QuALITY dataset | open | [
"I'll take this one if no one hasn't yet!"
] | 2021-12-15T22:26:19 | 2021-12-28T15:17:05 | null | ## Adding a Dataset
- **Name:** QuALITY
- **Description:** A challenging question answering with very long contexts (Twitter [thread](https://twitter.com/sleepinyourhat/status/1471225421794529281?s=20))
- **Paper:** No ArXiv link yet, but draft is [here](https://github.com/nyu-mll/quality/blob/main/quality_preprint.pdf)
- **Data:** GitHub repo [here](https://github.com/nyu-mll/quality)
- **Motivation:** This dataset would serve as a nice way to benchmark long-range Transformer models like BigBird, Longformer and their descendants. In particular, it would be very interesting to see how the S4 model fares on this given it's impressive performance on the Long Range Arena
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
| lewtun | https://github.com/huggingface/datasets/issues/3441 | null | false |
1,081,528,426 | 3,440 | datasets keeps reading from cached files, although I disabled it | closed | [
"Hi ! What version of `datasets` are you using ? Can you also provide the logs you get before it raises the error ?"
] | 2021-12-15T21:26:22 | 2022-02-24T09:12:22 | 2022-02-24T09:12:22 | ## Describe the bug
Hi,
I am trying to avoid dataset library using cached files, I get the following bug when this tried to read the cached files. I tried to do the followings:
```
from datasets import set_caching_enabled
set_caching_enabled(False)
```
also force redownlaod:
```
download_mode='force_redownload'
```
but none worked so far, this is on a cluster and on some of the machines this reads from the cached files, I really appreciate any idea on how to fully remove caching @lhoestq
many thanks
```
File "run_clm.py", line 496, in <module>
main()
File "run_clm.py", line 419, in main
train_result = trainer.train(resume_from_checkpoint=checkpoint)
File "/users/dara/codes/fewshot/debug/fewshot/third_party/trainers/trainer.py", line 943, in train
self._maybe_log_save_evaluate(tr_loss, model, trial, epoch, ignore_keys_for_eval)
File "/users/dara/conda/envs/multisuccess/lib/python3.8/site-packages/transformers/trainer.py", line 1445, in _maybe_log_save_evaluate
metrics = self.evaluate(ignore_keys=ignore_keys_for_eval)
File "/users/dara/codes/fewshot/debug/fewshot/third_party/trainers/trainer.py", line 172, in evaluate
output = self.eval_loop(
File "/users/dara/codes/fewshot/debug/fewshot/third_party/trainers/trainer.py", line 241, in eval_loop
metrics = self.compute_pet_metrics(eval_datasets, model, self.extra_info[metric_key_prefix], task=task)
File "/users/dara/codes/fewshot/debug/fewshot/third_party/trainers/trainer.py", line 268, in compute_pet_metrics
centroids = self._compute_per_token_train_centroids(model, task=task)
File "/users/dara/codes/fewshot/debug/fewshot/third_party/trainers/trainer.py", line 353, in _compute_per_token_train_centroids
data = get_label_samples(self.get_per_task_train_dataset(task), label)
File "/users/dara/codes/fewshot/debug/fewshot/third_party/trainers/trainer.py", line 350, in get_label_samples
return dataset.filter(lambda example: int(example['labels']) == label)
File "/users/dara/conda/envs/multisuccess/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 470, in wrapper
out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
File "/users/dara/conda/envs/multisuccess/lib/python3.8/site-packages/datasets/fingerprint.py", line 406, in wrapper
out = func(self, *args, **kwargs)
File "/users/dara/conda/envs/multisuccess/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 2519, in filter
indices = self.map(
File "/users/dara/conda/envs/multisuccess/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 2036, in map
return self._map_single(
File "/users/dara/conda/envs/multisuccess/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 503, in wrapper
out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
File "/users/dara/conda/envs/multisuccess/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 470, in wrapper
out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
File "/users/dara/conda/envs/multisuccess/lib/python3.8/site-packages/datasets/fingerprint.py", line 406, in wrapper
out = func(self, *args, **kwargs)
File "/users/dara/conda/envs/multisuccess/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 2248, in _map_single
return Dataset.from_file(cache_file_name, info=info, split=self.split)
File "/users/dara/conda/envs/multisuccess/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 654, in from_file
return cls(
File "/users/dara/conda/envs/multisuccess/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 593, in __init__
self.info.features = self.info.features.reorder_fields_as(inferred_features)
File "/users/dara/conda/envs/multisuccess/lib/python3.8/site-packages/datasets/features/features.py", line 1092, in reorder_fields_as
return Features(recursive_reorder(self, other))
File "/users/dara/conda/envs/multisuccess/lib/python3.8/site-packages/datasets/features/features.py", line 1081, 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 {'candidates_ids': Sequence(feature=Value(dtype='null', id=None), length=-1, id=None), 'labels': Value(dtype='int64', id=None), 'attention_mask': Sequence(feature=Value(dtype='int8', id=None), length=-1, id=None), 'input_ids': Sequence(feature=Value(dtype='int32', id=None), length=-1, id=None), 'extra_fields': {}, 'task': Value(dtype='string', id=None)}
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version:
- Platform: linux
- Python version: 3.8.12
- PyArrow version: 6.0.1
| dorost1234 | https://github.com/huggingface/datasets/issues/3440 | null | false |
1,081,389,723 | 3,439 | Add `cast_column` to `IterableDataset` | closed | [
"Awesome thanks a lot @mariosasko "
] | 2021-12-15T19:00:45 | 2021-12-16T15:55:20 | 2021-12-16T15:55:19 | Closes #3369.
cc: @patrickvonplaten | mariosasko | https://github.com/huggingface/datasets/pull/3439 | {
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"patch_url": "https://github.com/huggingface/datasets/pull/3439.patch",
"merged_at": "2021-12-16T15:55:19"
} | true |
1,081,302,203 | 3,438 | Update supported versions of Python in setup.py | closed | [] | 2021-12-15T17:30:12 | 2021-12-20T14:22:13 | 2021-12-20T14:22:12 | Update the list of supported versions of Python in `setup.py` to keep the PyPI project description updated. | mariosasko | https://github.com/huggingface/datasets/pull/3438 | {
"url": "https://api.github.com/repos/huggingface/datasets/pulls/3438",
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"diff_url": "https://github.com/huggingface/datasets/pull/3438.diff",
"patch_url": "https://github.com/huggingface/datasets/pull/3438.patch",
"merged_at": "2021-12-20T14:22:12"
} | true |
1,081,247,889 | 3,437 | Update BLEURT hyperlink | closed | [
"seems like a very very low-prio improvement :)",
"@albertvillanova thanks for the feedback! I removed the formatting altogether since I think this is a bit simpler tor read than non-rendered Markdown"
] | 2021-12-15T16:34:47 | 2021-12-17T13:28:26 | 2021-12-17T13:28:25 | The description of BLEURT on the hf.co website has a strange use of URL hyperlinking. This PR attempts to fix this, although I am not 100% sure Markdown syntax is allowed on the frontend or not.
| lewtun | https://github.com/huggingface/datasets/pull/3437 | {
"url": "https://api.github.com/repos/huggingface/datasets/pulls/3437",
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"patch_url": "https://github.com/huggingface/datasets/pull/3437.patch",
"merged_at": "2021-12-17T13:28:25"
} | true |
1,081,068,139 | 3,436 | Add the OneStopQa dataset | closed | [] | 2021-12-15T13:53:31 | 2021-12-17T14:32:00 | 2021-12-17T13:25:29 | Adding OneStopQA, a multiple choice reading comprehension dataset annotated according to the STARC (Structured Annotations for Reading Comprehension) scheme. | OmerShubi | https://github.com/huggingface/datasets/pull/3436 | {
"url": "https://api.github.com/repos/huggingface/datasets/pulls/3436",
"html_url": "https://github.com/huggingface/datasets/pull/3436",
"diff_url": "https://github.com/huggingface/datasets/pull/3436.diff",
"patch_url": "https://github.com/huggingface/datasets/pull/3436.patch",
"merged_at": "2021-12-17T13:25:29"
} | true |
1,081,043,756 | 3,435 | Improve Wikipedia Loading Script | closed | [
"I wanted to flag a change from since we discussed this: I initially wrote a function for using the Wikimedia APIs to collect namespace aliases, but decided that adding in more http requests to the script wasn't a great idea so instead used that code to build a static list that I just added directly to the code.\r\... | 2021-12-15T13:30:06 | 2022-03-04T08:16:00 | 2022-03-04T08:16:00 | * More structured approach to detecting redirects
* Remove redundant template filter code (covered by strip_code)
* Add language-specific lists of additional media namespace aliases for filtering
* Add language-specific lists of category namespace aliases for new link text cleaning step
* Remove magic words (parser directions like __TOC__ that occasionally occur in text)
Fix #3400
With support from @albertvillanova
CC @yjernite | geohci | https://github.com/huggingface/datasets/pull/3435 | {
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"patch_url": "https://github.com/huggingface/datasets/pull/3435.patch",
"merged_at": "2022-03-04T08:16:00"
} | true |
1,080,917,446 | 3,434 | Add The People's Speech | closed | [
"This dataset is now available on the Hub here: https://huggingface.co/datasets/MLCommons/peoples_speech"
] | 2021-12-15T11:21:21 | 2023-02-28T16:22:29 | 2023-02-28T16:22:28 | ## Adding a Dataset
- **Name:** The People's Speech
- **Description:** a massive English-language dataset of audio transcriptions of full sentences.
- **Paper:** https://openreview.net/pdf?id=R8CwidgJ0yT
- **Data:** https://mlcommons.org/en/peoples-speech/
- **Motivation:** With over 30,000 hours of speech, this dataset is the largest and most diverse freely available English speech recognition corpus today.
[The article](https://thegradient.pub/new-datasets-to-democratize-speech-recognition-technology-2/) which may be useful when working on the dataset.
cc: @anton-l
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
| mariosasko | https://github.com/huggingface/datasets/issues/3434 | null | false |
1,080,910,724 | 3,433 | Add Multilingual Spoken Words dataset | closed | [] | 2021-12-15T11:14:44 | 2022-02-22T10:03:53 | 2022-02-22T10:03:53 | ## Adding a Dataset
- **Name:** Multilingual Spoken Words
- **Description:** Multilingual Spoken Words Corpus is a large and growing audio dataset of spoken words in 50 languages for academic research and commercial applications in keyword spotting and spoken term search, licensed under CC-BY 4.0. The dataset contains more than 340,000 keywords, totaling 23.4 million 1-second spoken examples (over 6,000 hours).
Read more: https://mlcommons.org/en/news/spoken-words-blog/
- **Paper:** https://datasets-benchmarks-proceedings.neurips.cc/paper/2021/file/fe131d7f5a6b38b23cc967316c13dae2-Paper-round2.pdf
- **Data:** https://mlcommons.org/en/multilingual-spoken-words/
- **Motivation:**
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
| albertvillanova | https://github.com/huggingface/datasets/issues/3433 | null | false |
1,079,910,769 | 3,432 | Correctly indent builder config in dataset script docs | closed | [] | 2021-12-14T15:39:47 | 2021-12-14T17:35:17 | 2021-12-14T17:35:17 | null | mariosasko | https://github.com/huggingface/datasets/pull/3432 | {
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"patch_url": "https://github.com/huggingface/datasets/pull/3432.patch",
"merged_at": "2021-12-14T17:35:17"
} | true |
1,079,866,083 | 3,431 | Unable to resolve any data file after loading once | closed | [
"Hi ! `load_dataset` accepts as input either a local dataset directory or a dataset name from the Hugging Face Hub.\r\n\r\nSo here you are getting this error the second time because it tries to load the local `wiki_dpr` directory, instead of `wiki_dpr` from the Hub. It doesn't work since it's a **cache** directory,... | 2021-12-14T15:02:15 | 2022-12-11T10:53:04 | 2022-02-24T09:13:52 | when I rerun my program, it occurs this error
" Unable to resolve any data file that matches '['**train*']' at /data2/whr/lzy/open_domain_data/retrieval/wiki_dpr with any supported extension ['csv', 'tsv', 'json', 'jsonl', 'parquet', 'txt', 'zip']", so how could i deal with this problem?
thx.
And below is my code .
| LzyFischer | https://github.com/huggingface/datasets/issues/3431 | null | false |
1,079,811,124 | 3,430 | Make decoding of Audio and Image feature optional | closed | [
"Closing this PR for now due to https://github.com/huggingface/datasets/issues/3145#issuecomment-993664104.",
"Okay, after some more thinking, I'm re-opening this PR for three reasons:\r\n* This feature will allow us to remove the `image_file_path`/`audio_file_path` columns in our vision/audio datasets. Currently... | 2021-12-14T14:15:08 | 2022-01-25T18:57:52 | 2022-01-25T18:57:52 | Add the `decode` argument (`True` by default) to the `Audio` and the `Image` feature to make it possible to toggle on/off decoding of these features.
Even though we've discussed that on Slack, I'm not removing the `_storage_dtype` argument of the Audio feature in this PR to avoid breaking the Audio feature tests. | mariosasko | https://github.com/huggingface/datasets/pull/3430 | {
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"patch_url": "https://github.com/huggingface/datasets/pull/3430.patch",
"merged_at": "2022-01-25T18:57:52"
} | true |
1,078,902,390 | 3,429 | Make cast cacheable (again) on Windows | closed | [] | 2021-12-13T19:32:02 | 2021-12-14T14:39:51 | 2021-12-14T14:39:50 | `cast` currently emits the following warning when called on Windows:
```
Parameter 'function'=<function Dataset.cast.<locals>.<lambda> at 0x000001C930571EA0> of the transform datasets.arrow_dataset.Dataset._map_single couldn't be hashed properly, a random hash was used instead. Make sure your transforms and parameters are serializable with pickle or dill for the dataset fingerprinting
and caching to work. If you reuse this transform, the caching mechanism will consider it to be different
from the previous calls and recompute everything. This warning is only showed once. Subsequent hashing failures won't be showed.
```
It seems like the issue stems from the `config.PYARROW_VERSION` object not being serializable on Windows (tested with `dumps(lambda: config.PYARROW_VERSION)`), so I'm fixing this by capturing `config.PYARROW_VERSION.major` before the lambda definition. | mariosasko | https://github.com/huggingface/datasets/pull/3429 | {
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"merged_at": "2021-12-14T14:39:50"
} | true |
1,078,863,468 | 3,428 | Clean squad dummy data | closed | [] | 2021-12-13T18:46:29 | 2021-12-13T18:57:50 | 2021-12-13T18:57:50 | Some unused files were remaining, this PR removes them. We just need to keep the dummy_data.zip file | lhoestq | https://github.com/huggingface/datasets/pull/3428 | {
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"merged_at": "2021-12-13T18:57:50"
} | true |
1,078,782,159 | 3,427 | Add The Pile Enron Emails subset | closed | [] | 2021-12-13T17:14:16 | 2021-12-14T17:30:59 | 2021-12-14T17:30:57 | Add:
- Enron Emails subset of The Pile: "enron_emails" config
Close bigscience-workshop/data_tooling#310.
CC: @StellaAthena | albertvillanova | https://github.com/huggingface/datasets/pull/3427 | {
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"merged_at": "2021-12-14T17:30:55"
} | true |
1,078,670,031 | 3,426 | Update disaster_response_messages download urls (+ add validation split) | closed | [] | 2021-12-13T15:30:12 | 2021-12-14T14:38:30 | 2021-12-14T14:38:29 | Fixes #3240, fixes #3416 | mariosasko | https://github.com/huggingface/datasets/pull/3426 | {
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"merged_at": "2021-12-14T14:38:29"
} | true |
1,078,598,140 | 3,425 | Getting configs names takes too long | open | [
"maybe related to https://github.com/huggingface/datasets/issues/2859\r\n",
"It looks like it's currently calling `HfFileSystem.ls()` ~8 times at the root and for each subdirectory:\r\n- \"\"\r\n- \"en.noblocklist\"\r\n- \"en.noclean\"\r\n- \"en\"\r\n- \"multilingual\"\r\n- \"realnewslike\"\r\n\r\nCurrently `ls` ... | 2021-12-13T14:27:57 | 2021-12-13T14:53:33 | null |
## Steps to reproduce the bug
```python
from datasets import get_dataset_config_names
get_dataset_config_names("allenai/c4")
```
## Expected results
I would expect to get the answer quickly, at least in less than 10s
## Actual results
It takes about 45s on my environment
## Environment info
- `datasets` version: 1.16.1
- Platform: Linux-5.11.0-1022-aws-x86_64-with-glibc2.31
- Python version: 3.9.6
- PyArrow version: 4.0.1 | severo | https://github.com/huggingface/datasets/issues/3425 | null | false |
1,078,543,625 | 3,424 | Add RedCaps dataset | closed | [
"Cool ! If you want you can include `dataset_infos.json` but only for the main configurations. That's what we do for example for translation datasets when there are too many configs",
"@lhoestq I've added an example that uses `map` to download the images."
] | 2021-12-13T13:38:13 | 2022-01-12T14:13:16 | 2022-01-12T14:13:15 | Add the RedCaps dataset. I'm not adding the generated `dataset_infos.json` file for now due to its size (11 MB).
TODOs:
- [x] dummy data
- [x] dataset card
Close #3316 | mariosasko | https://github.com/huggingface/datasets/pull/3424 | {
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"merged_at": "2022-01-12T14:13:15"
} | true |
1,078,049,638 | 3,423 | data duplicate when setting num_works > 1 with streaming data | closed | [
"Hi ! Thanks for reporting :)\r\n\r\nWhen using a PyTorch's data loader with `num_workers>1` and an iterable dataset, each worker streams the exact same data by default, resulting in duplicate data when iterating using the data loader.\r\n\r\nWe can probably fix this in `datasets` by checking `torch.utils.data.get_... | 2021-12-13T03:43:17 | 2022-12-14T16:04:22 | 2022-12-14T16:04:22 | ## Describe the bug
The data is repeated num_works times when we load_dataset with streaming and set num_works > 1 when construct dataloader
## Steps to reproduce the bug
```python
# Sample code to reproduce the bug
import pandas as pd
import numpy as np
import os
from datasets import load_dataset
from torch.utils.data import DataLoader
from tqdm import tqdm
import shutil
NUM_OF_USER = 1000000
NUM_OF_ACTION = 50000
NUM_OF_SEQUENCE = 10000
NUM_OF_FILES = 32
NUM_OF_WORKERS = 16
if __name__ == "__main__":
shutil.rmtree("./dataset")
for i in range(NUM_OF_FILES):
sequence_data = pd.DataFrame(
{
"imei": np.random.randint(1, NUM_OF_USER, size=NUM_OF_SEQUENCE),
"sequence": np.random.randint(1, NUM_OF_ACTION, size=NUM_OF_SEQUENCE)
}
)
if not os.path.exists("./dataset"):
os.makedirs("./dataset")
sequence_data.to_csv(f"./dataset/sequence_data_{i}.csv",
index=False)
dataset = load_dataset("csv",
data_files=[os.path.join("./dataset",file) for file in os.listdir("./dataset") if file.endswith(".csv")],
split="train",
streaming=True).with_format("torch")
data_loader = DataLoader(dataset,
batch_size=1024,
num_workers=NUM_OF_WORKERS)
result = pd.DataFrame()
for i, batch in tqdm(enumerate(data_loader)):
result = pd.concat([result,
pd.DataFrame(batch)],
axis=0)
result.to_csv(f"num_work_{NUM_OF_WORKERS}.csv", index=False)
```
## Expected results
data do not duplicate
## Actual results
data duplicate NUM_OF_WORKERS = 16
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version:datasets==1.14.0
- Platform:transformers==4.11.3
- Python version:3.8
- PyArrow version:
| cloudyuyuyu | https://github.com/huggingface/datasets/issues/3423 | null | false |
1,078,022,619 | 3,422 | Error about load_metric | closed | [
"Hi ! I wasn't able to reproduce your error.\r\n\r\nCan you try to clear your cache at `~/.cache/huggingface/modules` and try again ?"
] | 2021-12-13T02:49:51 | 2022-01-07T14:06:47 | 2022-01-07T14:06:47 | ## Describe the bug
File "/opt/conda/lib/python3.8/site-packages/datasets/load.py", line 1371, in load_metric
metric = metric_cls(
TypeError: 'NoneType' object is not callable
## Steps to reproduce the bug
```python
metric = load_metric("glue", "sst2")
```
## Environment info
- `datasets` version: 1.16.1
- Platform: Linux-4.15.0-161-generic-x86_64-with-glibc2.10
- Python version: 3.8.3
- PyArrow version: 6.0.1
| jiacheng-ye | https://github.com/huggingface/datasets/issues/3422 | null | false |
1,077,966,571 | 3,421 | Adding mMARCO dataset | closed | [
"Hi @albertvillanova we've made a major overhaul of the loading script including all configurations we're making available. Could you please review it again?",
"@albertvillanova :ping_pong: ",
"Thanks @lhbonifacio for adding this dataset.\r\nHi there, i got an error about mmarco:\r\nConnectionError: Couldn't re... | 2021-12-13T00:56:43 | 2022-10-03T09:37:15 | 2022-10-03T09:37:15 | Adding mMARCO (v1.1) to HF datasets. | lhbonifacio | https://github.com/huggingface/datasets/pull/3421 | {
"url": "https://api.github.com/repos/huggingface/datasets/pulls/3421",
"html_url": "https://github.com/huggingface/datasets/pull/3421",
"diff_url": "https://github.com/huggingface/datasets/pull/3421.diff",
"patch_url": "https://github.com/huggingface/datasets/pull/3421.patch",
"merged_at": null
} | true |
1,077,913,468 | 3,420 | Add eli5_category dataset | closed | [
"> Thanks a lot for adding this dataset ! Good job with the dataset card and the dataset scripts - they're really good :)\r\n> \r\n> I just added minor changes\r\n\r\nThanks for fixing typos!"
] | 2021-12-12T21:30:45 | 2021-12-14T17:53:03 | 2021-12-14T17:53:02 | This pull request adds a categorized Long-form question answering dataset `ELI5_Category`. It's a new variant of the [ELI5](https://huggingface.co/datasets/eli5) dataset that uses the Reddit tags to alleviate the training/validation overlapping in the origin ELI5 dataset.
A [report](https://celeritasml.netlify.app/posts/2021-12-01-eli5c/)(Section 2) on this dataset. | jingshenSN2 | https://github.com/huggingface/datasets/pull/3420 | {
"url": "https://api.github.com/repos/huggingface/datasets/pulls/3420",
"html_url": "https://github.com/huggingface/datasets/pull/3420",
"diff_url": "https://github.com/huggingface/datasets/pull/3420.diff",
"patch_url": "https://github.com/huggingface/datasets/pull/3420.patch",
"merged_at": "2021-12-14T17:53:02"
} | true |
1,077,350,974 | 3,419 | `.to_json` is extremely slow after `.select` | open | [
"Hi ! It's slower indeed because a datasets on which `select`/`shard`/`train_test_split`/`shuffle` has been called has to do additional steps to retrieve the data of the dataset table in the right order.\r\n\r\nIndeed, if you call `dataset.select([0, 5, 10])`, the underlying table of the dataset is not altered to k... | 2021-12-11T01:36:31 | 2021-12-21T15:49:07 | null | ## Describe the bug
Saving a dataset to JSON with `to_json` is extremely slow after using `.select` on the original dataset.
## Steps to reproduce the bug
```python
from datasets import load_dataset
original = load_dataset("squad", split="train")
original.to_json("from_original.json") # Takes 0 seconds
selected_subset1 = original.select([i for i in range(len(original))])
selected_subset1.to_json("from_select1.json") # Takes 212 seconds
selected_subset2 = original.select([i for i in range(int(len(original) / 2))])
selected_subset2.to_json("from_select2.json") # Takes 90 seconds
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: master (https://github.com/huggingface/datasets/commit/6090f3cfb5c819f441dd4a4bb635e037c875b044)
- Platform: Linux-4.4.0-19041-Microsoft-x86_64-with-glibc2.27
- Python version: 3.9.7
- PyArrow version: 6.0.0
| eladsegal | https://github.com/huggingface/datasets/issues/3419 | null | false |
1,077,053,296 | 3,418 | Add Wikisource dataset | closed | [
"As we are removing the dataset scripts from GitHub and moving them to the Hugging Face Hub, I am going to transfer this script to the repo: https://huggingface.co/datasets/wikimedia/wikisource"
] | 2021-12-10T17:04:44 | 2022-10-04T09:35:56 | 2022-10-03T09:37:20 | Add loading script for Wikisource dataset.
Fix #3399.
CC: @geohci, @yjernite | albertvillanova | https://github.com/huggingface/datasets/pull/3418 | {
"url": "https://api.github.com/repos/huggingface/datasets/pulls/3418",
"html_url": "https://github.com/huggingface/datasets/pull/3418",
"diff_url": "https://github.com/huggingface/datasets/pull/3418.diff",
"patch_url": "https://github.com/huggingface/datasets/pull/3418.patch",
"merged_at": null
} | true |
1,076,943,343 | 3,417 | Fix type of bridge field in QED | closed | [] | 2021-12-10T15:07:21 | 2021-12-14T14:39:06 | 2021-12-14T14:39:05 | Use `Value("string")` instead of `Value("bool")` for the feature type of the `"bridge"` field in the QED dataset. If the value is `False`, set to `None`.
The following paragraph in the QED repo explains the purpose of this field:
>Each annotation in referential_equalities is a pair of spans, the question_reference and the sentence_reference, corresponding to an entity mention in the question and the selected_sentence respectively. As described in the paper, sentence_references can be "bridged in", in which case they do not correspond with any actual span in the selected_sentence. Hence, sentence_reference spans contain an additional field, bridge, which is a prepositional phrase when a reference is bridged, and is False otherwise. Prepositional phrases serve to link bridged references to an anchoring phrase in the selected_sentence. In the case a sentence_reference is bridged, the start and end, as well as the span string, map to such an anchoring phrase in the selected_sentence.
Fix #3346
cc @VictorSanh | mariosasko | https://github.com/huggingface/datasets/pull/3417 | {
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"patch_url": "https://github.com/huggingface/datasets/pull/3417.patch",
"merged_at": "2021-12-14T14:39:05"
} | true |
1,076,868,771 | 3,416 | disaster_response_messages unavailable | closed | [
"Hi, thanks for reporting! This is a duplicate of https://github.com/huggingface/datasets/issues/3240. We are working on a fix.\r\n\r\n"
] | 2021-12-10T13:49:17 | 2021-12-14T14:38:29 | 2021-12-14T14:38:29 | ## Dataset viewer issue for '* disaster_response_messages*'
**Link:** https://huggingface.co/datasets/disaster_response_messages
Dataset unavailable. Link dead: https://datasets.appen.com/appen_datasets/disaster_response_data/disaster_response_messages_training.csv
Am I the one who added this dataset ?No
| sacdallago | https://github.com/huggingface/datasets/issues/3416 | null | false |
1,076,472,534 | 3,415 | Non-deterministic tests: CI tests randomly fail | closed | [
"I think it might come from two different issues:\r\n1. Google Drive is an unreliable host, mainly because of quota limitations\r\n2. the staging environment can sometimes raise some errors\r\n\r\nFor Google Drive tests we could set up some retries with backup URLs if necessary I guess.\r\nFor staging on the other ... | 2021-12-10T06:08:59 | 2022-03-31T16:38:51 | 2022-03-31T16:38:51 | ## Describe the bug
Some CI tests fail randomly.
1. In https://github.com/huggingface/datasets/pull/3375/commits/c10275fe36085601cb7bdb9daee9a8f1fc734f48, there were 3 failing tests, only on Linux:
```
=========================== short test summary info ============================
FAILED tests/test_streaming_download_manager.py::test_streaming_dl_manager_get_extraction_protocol[https://drive.google.com/uc?export=download&id=1k92sUfpHxKq8PXWRr7Y5aNHXwOCNUmqh-zip]
FAILED tests/test_streaming_download_manager.py::test_streaming_gg_drive - Fi...
FAILED tests/test_streaming_download_manager.py::test_streaming_gg_drive_zipped
= 3 failed, 3553 passed, 2950 skipped, 2 xfailed, 1 xpassed, 125 warnings in 192.79s (0:03:12) =
```
2. After re-running the CI (without any change in the code) in https://github.com/huggingface/datasets/pull/3375/commits/57bfe1f342cd3c59d2510b992d5f06a0761eb147, there was only 1 failing test (one on Linux and a different one on Windows):
- On Linux:
```
=========================== short test summary info ============================
FAILED tests/test_streaming_download_manager.py::test_streaming_gg_drive_zipped
= 1 failed, 3555 passed, 2950 skipped, 2 xfailed, 1 xpassed, 125 warnings in 199.76s (0:03:19) =
```
- On Windows:
```
=========================== short test summary info ===========================
FAILED tests/test_load.py::test_load_dataset_builder_for_community_dataset_without_script
= 1 failed, 3551 passed, 2954 skipped, 2 xfailed, 1 xpassed, 121 warnings in 478.58s (0:07:58) =
```
The test `tests/test_streaming_download_manager.py::test_streaming_gg_drive_zipped` passes locally.
3. After re-running again the CI (without any change in the code) in https://github.com/huggingface/datasets/pull/3375/commits/39f32f2119cf91b86867216bb5c356c586503c6a, ALL the tests passed.
| albertvillanova | https://github.com/huggingface/datasets/issues/3415 | null | false |
1,076,028,998 | 3,414 | Skip None encoding (line deleted by accident in #3195) | closed | [] | 2021-12-09T21:17:33 | 2021-12-10T11:00:03 | 2021-12-10T11:00:02 | Return the line deleted by accident in #3195 while [resolving merge conflicts](https://github.com/huggingface/datasets/pull/3195/commits/8b0ed15be08559056b817836a07d47acda0c4510).
Fix #3181 (finally :))
| mariosasko | https://github.com/huggingface/datasets/pull/3414 | {
"url": "https://api.github.com/repos/huggingface/datasets/pulls/3414",
"html_url": "https://github.com/huggingface/datasets/pull/3414",
"diff_url": "https://github.com/huggingface/datasets/pull/3414.diff",
"patch_url": "https://github.com/huggingface/datasets/pull/3414.patch",
"merged_at": "2021-12-10T11:00:02"
} | true |
1,075,854,325 | 3,413 | Add WIDER FACE dataset | closed | [] | 2021-12-09T18:03:38 | 2022-01-12T14:13:47 | 2022-01-12T14:13:47 | Adds the WIDER FACE face detection benchmark.
TODOs:
* [x] dataset card
* [x] dummy data | mariosasko | https://github.com/huggingface/datasets/pull/3413 | {
"url": "https://api.github.com/repos/huggingface/datasets/pulls/3413",
"html_url": "https://github.com/huggingface/datasets/pull/3413",
"diff_url": "https://github.com/huggingface/datasets/pull/3413.diff",
"patch_url": "https://github.com/huggingface/datasets/pull/3413.patch",
"merged_at": "2022-01-12T14:13:47"
} | true |
1,075,846,368 | 3,412 | Fix flaky test again for s3 serialization | closed | [] | 2021-12-09T17:54:41 | 2021-12-09T18:00:52 | 2021-12-09T18:00:52 | Following https://github.com/huggingface/datasets/pull/3388 that wasn't enough (see CI error [here](https://app.circleci.com/pipelines/github/huggingface/datasets/9080/workflows/b971fb27-ff20-4220-9416-c19acdfdf6f4/jobs/55985)) | lhoestq | https://github.com/huggingface/datasets/pull/3412 | {
"url": "https://api.github.com/repos/huggingface/datasets/pulls/3412",
"html_url": "https://github.com/huggingface/datasets/pull/3412",
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"patch_url": "https://github.com/huggingface/datasets/pull/3412.patch",
"merged_at": "2021-12-09T18:00:52"
} | true |
1,075,846,272 | 3,411 | [chinese wwm] load_datasets behavior not as expected when using run_mlm_wwm.py script | open | [
"@LysandreJik not so sure who to @\r\nCould you help?",
"Hi @hyusterr, I believe it is @wlhgtc from https://github.com/huggingface/transformers/pull/9887"
] | 2021-12-09T17:54:35 | 2021-12-22T11:21:33 | null | ## Describe the bug
Model I am using (Bert, XLNet ...): bert-base-chinese
The problem arises when using:
* [https://github.com/huggingface/transformers/blob/master/examples/research_projects/mlm_wwm/run_mlm_wwm.py] the official example scripts: `rum_mlm_wwm.py`
The tasks I am working on is: pretraining whole word masking with my own dataset and ref.json file
I tried follow the run_mlm_wwm.py procedure to do whole word masking on pretraining task. my file is in .txt form, where one line represents one sample, with `9,264,784` chinese lines in total. the ref.json file is also contains 9,264,784 lines of whole word masking reference data for my chinese corpus. but when I try to adapt the run_mlm_wwm.py script, it shows that somehow after
`datasets["train"] = load_dataset(...`
`len(datasets["train"])` returns `9,265,365`
then, after `tokenized_datasets = datasets.map(...`
`len(tokenized_datasets["train"])` returns `9,265,279`
I'm really confused and tried to trace code by myself but can't know what happened after a week trial.
I want to know what happened in the `load_dataset()` function and `datasets.map` here and how did I get more lines of data than I input. so I'm here to ask.
## To reproduce
Sorry that I can't provide my data here since it did not belong to me. but I'm sure I remove the blank lines.
## Expected behavior
I expect the code run as it should. but the AssertionError in line 167 keeps raise as the line of reference json and datasets['train'] differs.
Thanks for your patient reading!
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.8.0
- Platform: Linux-5.4.0-91-generic-x86_64-with-glibc2.29
- Python version: 3.8.10
- PyArrow version: 3.0.0
| hyusterr | https://github.com/huggingface/datasets/issues/3411 | null | false |
1,075,815,415 | 3,410 | Fix dependencies conflicts in Windows CI after conda update to 4.11 | closed | [] | 2021-12-09T17:19:11 | 2021-12-09T17:36:20 | 2021-12-09T17:36:19 | For some reason the CI wasn't using python 3.6 but python 3.7 after the update to conda 4.11 | lhoestq | https://github.com/huggingface/datasets/pull/3410 | {
"url": "https://api.github.com/repos/huggingface/datasets/pulls/3410",
"html_url": "https://github.com/huggingface/datasets/pull/3410",
"diff_url": "https://github.com/huggingface/datasets/pull/3410.diff",
"patch_url": "https://github.com/huggingface/datasets/pull/3410.patch",
"merged_at": "2021-12-09T17:36:19"
} | true |
1,075,684,593 | 3,409 | Pass new_fingerprint in multiprocessing | closed | [
"@lhoestq Hi~, does this support that `datasets.map(func, batched=True, batch_size, num_proc>1, new_fingerprint=\"func_v1\")` even if `func` can't pickle. I also notice that you said \"Unfortunately you need picklable mapping functions to make multiprocessing work :confused: Also feel free to open an issue or send ... | 2021-12-09T15:12:00 | 2022-08-19T10:41:04 | 2021-12-09T17:38:43 | Following https://github.com/huggingface/datasets/pull/3045
Currently one can pass `new_fingerprint` to `.map()` to use a custom fingerprint instead of the one computed by hashing the map transform. However it's ignored if `num_proc>1`.
In this PR I fixed that by passing `new_fingerprint` to `._map_single()` when `num_proc>1`.
More specifically, `new_fingerprint` with a suffix based on the process `rank` is passed, so that each process has a different `new_fingerprint`
cc @TevenLeScao @vlievin | lhoestq | https://github.com/huggingface/datasets/pull/3409 | {
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"patch_url": "https://github.com/huggingface/datasets/pull/3409.patch",
"merged_at": "2021-12-09T17:38:43"
} | true |
1,075,642,915 | 3,408 | Typo in Dataset viewer error message | closed | [
"Fixed, thanks\r\n<img width=\"661\" alt=\"Capture d’écran 2021-12-22 à 12 02 30\" src=\"https://user-images.githubusercontent.com/1676121/147082881-cf700e8d-0511-4431-b214-d6cf8137db10.png\">\r\n"
] | 2021-12-09T14:34:02 | 2021-12-22T11:02:53 | 2021-12-22T11:02:53 | ## Dataset viewer issue for '*name of the dataset*'
**Link:** *link to the dataset viewer page*
*short description of the issue*
When creating an empty dataset repo, the Dataset Preview provides a helpful message that no files were found. There is a tiny typo in that message: "ressource" should be "resource"
Am I the one who added this dataset ?
N/A
| lewtun | https://github.com/huggingface/datasets/issues/3408 | null | false |
1,074,502,225 | 3,407 | Use max number of data files to infer module | closed | [
"Cool thanks :) Feel free to merge if it's all good for you"
] | 2021-12-08T14:58:43 | 2021-12-14T17:08:42 | 2021-12-14T17:08:42 | When inferring the module for datasets without script, set a maximum number of iterations over data files.
This PR fixes the issue of taking too long when hundred of data files present.
Please, feel free to agree on both numbers:
```
# Datasets without script
DATA_FILES_MAX_NUMBER = 10
ARCHIVED_DATA_FILES_MAX_NUMBER = 5
```
Fix #3404. | albertvillanova | https://github.com/huggingface/datasets/pull/3407 | {
"url": "https://api.github.com/repos/huggingface/datasets/pulls/3407",
"html_url": "https://github.com/huggingface/datasets/pull/3407",
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"patch_url": "https://github.com/huggingface/datasets/pull/3407.patch",
"merged_at": "2021-12-14T17:08:41"
} | true |
1,074,366,050 | 3,406 | Fix module inference for archive with a directory | closed | [] | 2021-12-08T12:39:12 | 2021-12-08T13:03:30 | 2021-12-08T13:03:29 | Fix module inference for an archive file that contains files within a directory.
Fix #3405. | albertvillanova | https://github.com/huggingface/datasets/pull/3406 | {
"url": "https://api.github.com/repos/huggingface/datasets/pulls/3406",
"html_url": "https://github.com/huggingface/datasets/pull/3406",
"diff_url": "https://github.com/huggingface/datasets/pull/3406.diff",
"patch_url": "https://github.com/huggingface/datasets/pull/3406.patch",
"merged_at": "2021-12-08T13:03:28"
} | true |
1,074,360,362 | 3,405 | ZIP format inference does not work when files located in a dir inside the archive | closed | [] | 2021-12-08T12:32:15 | 2021-12-08T13:03:29 | 2021-12-08T13:03:29 | ## Describe the bug
When a zipped file contains archived files within a directory, the function `infer_module_for_data_files_in_archives` does not work.
It only works for files located in the root directory of the ZIP file.
## Steps to reproduce the bug
```python
infer_module_for_data_files_in_archives(["path/to/zip/file.zip"], False)
``` | albertvillanova | https://github.com/huggingface/datasets/issues/3405 | null | false |
1,073,657,561 | 3,404 | Optimize ZIP format inference | closed | [] | 2021-12-07T18:44:49 | 2021-12-14T17:08:41 | 2021-12-14T17:08:41 | **Is your feature request related to a problem? Please describe.**
When hundreds of ZIP files are present in a dataset, format inference takes too long.
See: https://github.com/bigscience-workshop/data_tooling/issues/232#issuecomment-986685497
**Describe the solution you'd like**
Iterate over a maximum number of files.
CC: @lhoestq
| albertvillanova | https://github.com/huggingface/datasets/issues/3404 | null | false |
1,073,622,120 | 3,403 | Cannot import name 'maybe_sync' | closed | [
"Hi ! Can you try updating `fsspec` ? The minimum version is `2021.05.0`",
"hey @lhoestq. I'm using `fsspec-2021.11.1` but still getting that error.",
"Maybe this discussion can help:\r\n\r\nhttps://github.com/fsspec/filesystem_spec/issues/597#issuecomment-958646964",
"Thanks @lhoestq. Downgrading `fsspec and... | 2021-12-07T17:57:59 | 2021-12-17T07:00:35 | 2021-12-17T07:00:35 | ## Describe the bug
Cannot seem to import datasets when running run_summarizer.py script on a VM set up on ovhcloud
## Steps to reproduce the bug
```python
from datasets import load_dataset
```
## Expected results
No error
## Actual results
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/opt/conda/lib/python3.7/site-packages/datasets/__init__.py", line 34, in <module>
from .arrow_dataset import Dataset, concatenate_datasets
File "/opt/conda/lib/python3.7/site-packages/datasets/arrow_dataset.py", line 48, in <module>
from .arrow_writer import ArrowWriter, OptimizedTypedSequence
File "/opt/conda/lib/python3.7/site-packages/datasets/arrow_writer.py", line 27, in <module>
from .features import (
File "/opt/conda/lib/python3.7/site-packages/datasets/features/__init__.py", line 2, in <module>
from .audio import Audio
File "/opt/conda/lib/python3.7/site-packages/datasets/features/audio.py", line 8, in <module>
from ..utils.streaming_download_manager import xopen
File "/opt/conda/lib/python3.7/site-packages/datasets/utils/streaming_download_manager.py", line 16, in <module>
from ..filesystems import COMPRESSION_FILESYSTEMS
File "/opt/conda/lib/python3.7/site-packages/datasets/filesystems/__init__.py", line 13, in <module>
from .s3filesystem import S3FileSystem # noqa: F401
File "/opt/conda/lib/python3.7/site-packages/datasets/filesystems/s3filesystem.py", line 1, in <module>
import s3fs
File "/opt/conda/lib/python3.7/site-packages/s3fs/__init__.py", line 1, in <module>
from .core import S3FileSystem, S3File
File "/opt/conda/lib/python3.7/site-packages/s3fs/core.py", line 11, in <module>
from fsspec.asyn import AsyncFileSystem, sync, sync_wrapper, maybe_sync
ImportError: cannot import name 'maybe_sync' from 'fsspec.asyn' (/opt/conda/lib/python3.7/site-packages/fsspec/asyn.py)
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.16.0
- Platform: OVH Cloud Tesla V100 Machine
- Python version: 3.7.9
- PyArrow version: 6.0.1
| KMFODA | https://github.com/huggingface/datasets/issues/3403 | null | false |
1,073,614,815 | 3,402 | More robust first elem check in encode/cast example | closed | [] | 2021-12-07T17:48:16 | 2021-12-08T13:02:16 | 2021-12-08T13:02:15 | Fix #3306 | mariosasko | https://github.com/huggingface/datasets/pull/3402 | {
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"diff_url": "https://github.com/huggingface/datasets/pull/3402.diff",
"patch_url": "https://github.com/huggingface/datasets/pull/3402.patch",
"merged_at": "2021-12-08T13:02:15"
} | true |
1,073,603,508 | 3,401 | Add Wikimedia pre-processed datasets | closed | [
"As we are planning to stop using Apache Beam (our `datasets.BeamBasedBuilder`) for the generation of some datasets (including [Wikipedia](https://huggingface.co/datasets/wikipedia/blob/main/wikipedia.py)), I have been working on [wikimedia/wikipedia](https://huggingface.co/datasets/wikimedia/wikipedia) to:\r\n- Po... | 2021-12-07T17:33:19 | 2024-10-09T16:10:47 | 2024-10-09T16:10:47 | ## Adding a Dataset
- **Name:** Add pre-processed data to:
- *wikimedia/wikipedia*: https://huggingface.co/datasets/wikimedia/wikipedia
- *wikimedia/wikisource*: https://huggingface.co/datasets/wikimedia/wikisource
- **Description:** Add pre-processed data to the Hub for all languages
- **Paper:** *link to the dataset paper if available*
- **Data:** *link to the Github repository or current dataset location*
- **Motivation:** This will be very useful for the NLP community, as the pre-processing has a high cost for lot of researchers (both in computation and in knowledge)
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
CC: @geohci, @yjernite | albertvillanova | https://github.com/huggingface/datasets/issues/3401 | null | false |
1,073,600,382 | 3,400 | Improve Wikipedia loading script | closed | [
"Thanks! See https://public.paws.wmcloud.org/User:Isaac_(WMF)/HuggingFace%20Wikipedia%20Processing.ipynb for more implementation details / some data around the overhead induced by adding the extra preprocessing steps (stripping link prefixes and magic words)",
"Closed by:\r\n- #3435"
] | 2021-12-07T17:29:25 | 2022-03-22T16:52:28 | 2022-03-22T16:52:28 | As reported by @geohci, the "wikipedia" processing/loading script could be improved by some additional small suggested processing functions:
- _extract_content(filepath):
- Replace .startswith("#redirect") with more structured approach: if elem.find(f"./{namespace}redirect") is None: continue
- _parse_and_clean_wikicode(raw_content, parser):
- Remove rm_template from cleaning -- this is redundant with .strip_code() from mwparserformhell
- Build a language-specific list of namespace prefixes to filter out per below get_namespace_prefixes
- Optional: strip prefixes like categories -- e.g., Category:Towns in Tianjin becomes Towns in Tianjin
- Optional: strip magic words
| albertvillanova | https://github.com/huggingface/datasets/issues/3400 | null | false |
1,073,593,861 | 3,399 | Add Wikisource dataset | closed | [
"See notebook by @geohci: https://public.paws.wmcloud.org/User:Isaac_(WMF)/HuggingFace%20Wikisource%20Processing.ipynb",
"See: https://huggingface.co/datasets/wikimedia/wikisource"
] | 2021-12-07T17:21:31 | 2024-10-09T16:11:27 | 2024-10-09T16:11:26 | ## Adding a Dataset
- **Name:** *wikisource*
- **Description:** *short description of the dataset (or link to social media or blog post)*
- **Paper:** *link to the dataset paper if available*
- **Data:** *link to the Github repository or current dataset location*
- **Motivation:** Additional high quality textual data, besides Wikipedia.
Add loading script as "canonical" dataset (as it is the case for ""wikipedia").
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
CC: @geohci, @yjernite | albertvillanova | https://github.com/huggingface/datasets/issues/3399 | null | false |
1,073,590,384 | 3,398 | Add URL field to Wikimedia dataset instances: wikipedia,... | closed | [
"@geohci, I think the field \"url\" does not appear in the Wikimedia dumps. Therefore I guess we should generate it, using the \"title\" field and making some transformation of it (replacing spaces with underscores) and prepending the domain (created using the language)?",
"Indeed:\r\n\r\n> To re-distribute text ... | 2021-12-07T17:17:27 | 2022-03-22T16:53:27 | 2022-03-22T16:53:27 | As reported by @geohci, in order to host pre-processed data in the Hub, we should add the full URL to data instances (new field "url"), so that we conform to proper attribution from license requirement. See, e.g.: https://fair-trec.github.io/docs/Fair_Ranking_2021_Participant_Instructions.pdf#subsection.3.2
This should be done for all pre-processed datasets under "wikimedia" org in the Hub: https://huggingface.co/wikimedia
| albertvillanova | https://github.com/huggingface/datasets/issues/3398 | null | false |
1,073,502,444 | 3,397 | add BNL newspapers | closed | [
"\r\n> Also, maybe calling the dataset as \"bnl_historical_newspapers\" and setting \"processed\" as one configuration name?\r\n\r\nThis sounds like a good idea but my only question around this is how easy it would be to use the same approach for processing the other newspaper collections [https://data.bnl.lu/data/... | 2021-12-07T15:43:21 | 2022-01-17T18:35:34 | 2022-01-17T18:35:34 | This pull request adds the BNL's [processed newspaper collections](https://data.bnl.lu/data/historical-newspapers/) as a dataset. This is partly done to support BigScience see: https://github.com/bigscience-workshop/data_tooling/issues/192.
The Datacard is more sparse than I would like but I plan to make a separate pull request to try and make this more complete at a later date.
I had to manually add the `dummy_data` but I believe I've done this correctly (the tests pass locally).
| davanstrien | https://github.com/huggingface/datasets/pull/3397 | {
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"patch_url": "https://github.com/huggingface/datasets/pull/3397.patch",
"merged_at": "2022-01-17T18:35:34"
} | true |
1,073,467,183 | 3,396 | Install Audio dependencies to support audio decoding | closed | [
"https://huggingface.co/datasets/projecte-aina/parlament_parla -> works (but we still have to show an audio player)\r\n\r\nhttps://huggingface.co/datasets/openslr -> another issue: `Message: [Errno 2] No such file or directory: '/home/hf/datasets-preview-backend/zip:/asr_javanese/data/00/00004fe6aa.flac'`",
... | 2021-12-07T15:11:36 | 2022-04-25T16:12:22 | 2022-04-25T16:12:01 | ## Dataset viewer issue for '*openslr*', '*projecte-aina/parlament_parla*'
**Link:** *https://huggingface.co/datasets/openslr*
**Link:** *https://huggingface.co/datasets/projecte-aina/parlament_parla*
Error:
```
Status code: 400
Exception: ImportError
Message: To support decoding audio files, please install 'librosa'.
```
Am I the one who added this dataset ? Yes-No
- openslr: No
- projecte-aina/parlament_parla: Yes
| albertvillanova | https://github.com/huggingface/datasets/issues/3396 | null | false |
1,073,432,650 | 3,395 | Fix formatting in IterableDataset.map docs | closed | [] | 2021-12-07T14:41:01 | 2021-12-08T10:11:33 | 2021-12-08T10:11:33 | Fix formatting in the recently added `Map` section of the streaming docs. | mariosasko | https://github.com/huggingface/datasets/pull/3395 | {
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"patch_url": "https://github.com/huggingface/datasets/pull/3395.patch",
"merged_at": "2021-12-08T10:11:32"
} | true |
1,073,396,308 | 3,394 | Preserve all feature types when saving a dataset on the Hub with `push_to_hub` | closed | [
"According to this [comment in the forum](https://discuss.huggingface.co/t/save-datasetdict-to-huggingface-hub/12075/8?u=lhoestq), using `push_to_hub` on a dataset with `ClassLabel` can also make the feature simply disappear when it's reloaded !",
"Maybe we can also fix https://github.com/huggingface/datasets/iss... | 2021-12-07T14:08:30 | 2021-12-21T17:00:09 | 2021-12-21T17:00:09 | Currently, if one of the dataset features is of type `ClassLabel`, saving the dataset with `push_to_hub` and reloading the dataset with `load_dataset` will return the feature of type `Value`. To fix this, we should do something similar to `save_to_disk` (which correctly preserves the types) and not only push the parquet files in `push_to_hub`, but also the dataset `info` (stored in a JSON file). | mariosasko | https://github.com/huggingface/datasets/issues/3394 | null | false |
1,073,189,777 | 3,393 | Common Voice Belarusian Dataset | open | [] | 2021-12-07T10:37:02 | 2021-12-09T15:56:03 | null | ## Adding a Dataset
- **Name:** *Common Voice Belarusian Dataset*
- **Description:** *[commonvoice.mozilla.org/be](https://commonvoice.mozilla.org/be)*
- **Data:** *[commonvoice.mozilla.org/be/datasets](https://commonvoice.mozilla.org/be/datasets)*
- **Motivation:** *It has more than 7GB of data, so it will be great to have it in this package so anyone can try to train something for Belarusian language.*
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
| wiedymi | https://github.com/huggingface/datasets/issues/3393 | null | false |
1,073,073,408 | 3,392 | Dataset viewer issue for `dansbecker/hackernews_hiring_posts` | closed | [
"This issue was fixed by me calling `all_datasets.push_to_hub(\"hackernews_hiring_posts\")`.\r\n\r\nThe previous problems were from calling `all_datasets.save_to_disk` and then pushing with `my_repo.git_add` and `my_repo.push_to_hub`.\r\n"
] | 2021-12-07T08:41:01 | 2021-12-07T14:04:28 | 2021-12-07T14:04:28 | ## Dataset viewer issue for `dansbecker/hackernews_hiring_posts`
**Link:** https://huggingface.co/datasets/dansbecker/hackernews_hiring_posts
*short description of the issue*
Dataset preview not showing for uploaded DatasetDict. See https://discuss.huggingface.co/t/dataset-preview-not-showing-for-uploaded-datasetdict/12603
Am I the one who added this dataset ?
No -> @dansbecker | severo | https://github.com/huggingface/datasets/issues/3392 | null | false |
1,072,849,055 | 3,391 | method to select columns | closed | [
"duplicate of #2655"
] | 2021-12-07T02:44:19 | 2021-12-07T02:45:27 | 2021-12-07T02:45:27 | **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)`
| changjonathanc | https://github.com/huggingface/datasets/issues/3391 | null | false |
1,072,462,456 | 3,390 | Loading dataset throws "KeyError: 'Field "builder_name" does not exist in table schema'" | closed | [
"Got solved it with push_to_hub, closing"
] | 2021-12-06T18:22:49 | 2021-12-06T20:22:05 | 2021-12-06T20:22:05 | ## Describe the bug
I have prepared dataset to datasets and now I am trying to load it back Finnish-NLP/voxpopuli_fi
I get "KeyError: 'Field "builder_name" does not exist in table schema'"
My dataset folder and files should be like @patrickvonplaten has here https://huggingface.co/datasets/flax-community/german-common-voice-processed
How my voxpopuli dataset looks like:
Part of the processing (path column is the absolute path to audio files)
```
def add_audio_column(example):
example['audio'] = example['path']
return example
voxpopuli = voxpopuli.map(add_audio_column)
voxpopuli.cast_column("audio", Audio())
voxpopuli["audio"] <-- to my knowledge this does load the local files and prepares those arrays
voxpopuli = voxpopuli.cast_column("audio", Audio(sampling_rate=16_000)) resampling 16kHz
```
I have then saved it to disk_
`voxpopuli.save_to_disk('/asr_disk/datasets_processed_new/voxpopuli')`
and made folder structure same as @patrickvonplaten
I also get same error while trying to load_dataset from his repo:
## Steps to reproduce the bug
```python
dataset = load_dataset("Finnish-NLP/voxpopuli_fi")
```
## Expected results
Dataset is loaded correctly and looks like in the first picture
## Actual results
Loading throws keyError:
KeyError: 'Field "builder_name" does not exist in table schema'
Resources I have been trying to follow:
https://huggingface.co/docs/datasets/audio_process.html
https://huggingface.co/docs/datasets/share_dataset.html
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.16.2.dev0
- Platform: Ubuntu 20.04.2 LTS
- Python version: 3.8.12
- PyArrow version: 6.0.1
| R4ZZ3 | https://github.com/huggingface/datasets/issues/3390 | null | false |
1,072,191,865 | 3,389 | Add EDGAR | open | [
"cc @juliensimon ",
"Datasets are not tracked in this repository anymore. But you can make your own dataset in the huggingface hub"
] | 2021-12-06T14:06:11 | 2022-10-05T10:40:22 | null | ## Adding a Dataset
- **Name:** EDGAR Database
- **Description:** https://www.sec.gov/edgar/about EDGAR, the Electronic Data Gathering, Analysis, and Retrieval system, is the primary system for companies and others submitting documents under the Securities Act of 1933, the Securities Exchange Act of 1934, the Trust Indenture Act of 1939, and the Investment Company Act of 1940. Containing millions of company and individual filings, EDGAR benefits investors, corporations, and the U.S. economy overall by increasing the efficiency, transparency, and fairness of the securities markets. The system processes about 3,000 filings per day, serves up 3,000 terabytes of data to the public annually, and accommodates 40,000 new filers per year on average. EDGAR® and EDGARLink® are registered trademarks of the SEC.
- **Data:** https://www.sec.gov/os/accessing-edgar-data
- **Motivation:** Enabling and improving FSI (Financial Services Industry) datasets to increase ease of use
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
| philschmid | https://github.com/huggingface/datasets/issues/3389 | null | false |
1,072,022,021 | 3,388 | Fix flaky test of the temporary directory used by load_from_disk | closed | [
"CI failed because of a server error - merging"
] | 2021-12-06T11:09:31 | 2021-12-06T11:25:03 | 2021-12-06T11:24:49 | The test is flaky, here is an example of random CI failure:
https://github.com/huggingface/datasets/commit/73ed6615b4b3eb74d5311684f7b9e05cdb76c989
I fixed that by not checking the content of the random part of the temporary directory name | lhoestq | https://github.com/huggingface/datasets/pull/3388 | {
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"patch_url": "https://github.com/huggingface/datasets/pull/3388.patch",
"merged_at": "2021-12-06T11:24:49"
} | true |
1,071,836,456 | 3,387 | Create Language Modeling task | closed | [] | 2021-12-06T07:56:07 | 2021-12-17T17:18:28 | 2021-12-17T17:18:27 | Create Language Modeling task to be able to specify the input "text" column in a dataset.
This can be useful for datasets which are not exclusively used for language modeling and have more than one column:
- for text classification datasets (with columns "review" and "rating", for example), the Language Modeling task can be used to specify the "text" column ("review" in this case).
TODO:
- [ ] Add the LanguageModeling task to all dataset scripts which can be used for language modeling | albertvillanova | https://github.com/huggingface/datasets/pull/3387 | {
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"patch_url": "https://github.com/huggingface/datasets/pull/3387.patch",
"merged_at": "2021-12-17T17:18:27"
} | true |
1,071,813,141 | 3,386 | Fix typos in dataset cards | closed | [] | 2021-12-06T07:20:40 | 2021-12-06T09:30:55 | 2021-12-06T09:30:54 | This PR:
- Fix typos in dataset cards
- Fix Papers With Code ID for:
- Bilingual Corpus of Arabic-English Parallel Tweets
- Tweets Hate Speech Detection
- Add pretty name tags | albertvillanova | https://github.com/huggingface/datasets/pull/3386 | {
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"patch_url": "https://github.com/huggingface/datasets/pull/3386.patch",
"merged_at": "2021-12-06T09:30:54"
} | true |
1,071,742,310 | 3,385 | None batched `with_transform`, `set_transform` | open | [
"Hi ! Thanks for the suggestion :)\r\nIt makes sense to me, and it can surely be implemented by wrapping the user's function to make it a batched function. However I'm not a big fan of the inconsistency it would create with `map`: `with_transform` is batched by default while `map` isn't.\r\n\r\nIs there something y... | 2021-12-06T05:20:54 | 2022-01-17T15:25:01 | null | **Is your feature request related to a problem? Please describe.**
A `torch.utils.data.Dataset.__getitem__` operates on a single example.
But 🤗 `Datasets.with_transform` doesn't seem to allow non-batched transform.
**Describe the solution you'd like**
Have a `batched=True` argument in `Datasets.with_transform`
**Describe alternatives you've considered**
* Convert a non-batched transform function to batched one myself.
* Wrap a 🤗 Dataset with torch Dataset, and add a `__getitem__`. 🙄
* Have `lazy=False` in `Dataset.map`, and returns a `LazyDataset` if `lazy=True`. This way the same `map` interface can be used, and existing code can be updated with one argument change. | changjonathanc | https://github.com/huggingface/datasets/issues/3385 | null | false |
1,071,594,165 | 3,384 | Adding mMARCO dataset | closed | [] | 2021-12-05T23:59:11 | 2021-12-12T15:27:36 | 2021-12-12T15:27:36 | We are adding mMARCO dataset to HuggingFace datasets repo.
This way, all the languages covered in the translation are available in a easy way. | lhbonifacio | https://github.com/huggingface/datasets/pull/3384 | {
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"patch_url": "https://github.com/huggingface/datasets/pull/3384.patch",
"merged_at": null
} | true |
1,071,551,884 | 3,383 | add Georgian data in cc100. | closed | [] | 2021-12-05T20:38:09 | 2021-12-14T14:37:23 | 2021-12-14T14:37:22 | update cc100 dataset to support loading Georgian (ka) data which is originally available in CC100 dataset source.
All tests are passed.
Dummy data generated.
metadata generated. | AnzorGozalishvili | https://github.com/huggingface/datasets/pull/3383 | {
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"merged_at": "2021-12-14T14:37:22"
} | true |
1,071,293,299 | 3,382 | #3337 Add typing overloads to Dataset.__getitem__ for mypy | closed | [
"Locally the `make quality` passes with the same dependencies. I would suggest upgrading flake8. (I can take care of it in another PR)\r\ncc @lhoestq ",
"Thank you for fixing flake8! I think we are ready to merge then. "
] | 2021-12-04T20:54:49 | 2021-12-14T10:28:55 | 2021-12-14T10:28:55 | Add typing overloads to Dataset.__getitem__ for mypy
Fixes #3337
**Iterable**
Iterable from `collections` cannot have a type, so you can't do `Iterable[int]` for example. `typing` has a Generic version that builds upon the one from `collections`.
**Flake8**
I had to add `# noqa: F811`, this is a bug from Flake8.
datasets uses flake8==3.7.9 which released in October 2019 if I update flake8 (4.0.1), I no longer get these errors, but I did not want to make the update without your approval. (It also triggers other errors like no args in f-strings.) | Dref360 | https://github.com/huggingface/datasets/pull/3382 | {
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"merged_at": "2021-12-14T10:28:54"
} | true |
1,071,283,879 | 3,381 | Unable to load audio_features from common_voice dataset | closed | [
"Hi ! Feel free to access `batch[\"audio\"][\"array\"]` and `batch[\"audio\"][\"sampling_rate\"]` instead\r\n\r\n`datasets` 1.16 introduced some changes in `common_voice` and now the `path` field is no longer a path to a local file (but rather the path to the file in the archive it's extracted from)",
"Thanks for... | 2021-12-04T19:59:11 | 2021-12-06T17:52:42 | 2021-12-06T17:52:42 | ## Describe the bug
I am not able to load audio features from common_voice dataset
## Steps to reproduce the bug
```
from datasets import load_dataset
import torchaudio
test_dataset = load_dataset("common_voice", "hi", split="test[:2%]")
resampler = torchaudio.transforms.Resample(48_000, 16_000)
def speech_file_to_array_fn(batch):
speech_array, sampling_rate = torchaudio.load(batch["path"])
batch["speech"] = resampler(speech_array).squeeze().numpy()
return batch
test_dataset = test_dataset.map(speech_file_to_array_fn)
```
## Expected results
This piece of code should return test_dataset after loading audio features.
## Actual results
Reusing dataset common_voice (/home/jovyan/.cache/huggingface/datasets/common_voice/hi/6.1.0/b879a355caa529b11f2249400b61cadd0d9433f334d5c60f8c7216ccedfecfe1)
/opt/conda/lib/python3.7/site-packages/transformers/configuration_utils.py:341: UserWarning: Passing `gradient_checkpointing` to a config initialization is deprecated and will be removed in v5 Transformers. Using `model.gradient_checkpointing_enable()` instead, or if you are using the `Trainer` API, pass `gradient_checkpointing=True` in your `TrainingArguments`.
"Passing `gradient_checkpointing` to a config initialization is deprecated and will be removed in v5 "
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
0%| | 0/3 [00:00<?, ?ex/s]formats: can't open input file `common_voice_hi_23795358.mp3': No such file or directory
0%| | 0/3 [00:00<?, ?ex/s]
Traceback (most recent call last):
File "demo_file.py", line 23, in <module>
test_dataset = test_dataset.map(speech_file_to_array_fn)
File "/opt/conda/lib/python3.7/site-packages/datasets/arrow_dataset.py", line 2036, in map
desc=desc,
File "/opt/conda/lib/python3.7/site-packages/datasets/arrow_dataset.py", line 518, in wrapper
out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
File "/opt/conda/lib/python3.7/site-packages/datasets/arrow_dataset.py", line 485, in wrapper
out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
File "/opt/conda/lib/python3.7/site-packages/datasets/fingerprint.py", line 411, in wrapper
out = func(self, *args, **kwargs)
File "/opt/conda/lib/python3.7/site-packages/datasets/arrow_dataset.py", line 2368, in _map_single
example = apply_function_on_filtered_inputs(example, i, offset=offset)
File "/opt/conda/lib/python3.7/site-packages/datasets/arrow_dataset.py", line 2277, in apply_function_on_filtered_inputs
processed_inputs = function(*fn_args, *additional_args, **fn_kwargs)
File "/opt/conda/lib/python3.7/site-packages/datasets/arrow_dataset.py", line 1978, in decorated
result = f(decorated_item, *args, **kwargs)
File "demo_file.py", line 19, in speech_file_to_array_fn
speech_array, sampling_rate = torchaudio.load(batch["path"])
File "/opt/conda/lib/python3.7/site-packages/torchaudio/backend/sox_io_backend.py", line 154, in load
filepath, frame_offset, num_frames, normalize, channels_first, format)
RuntimeError: Error loading audio file: failed to open file common_voice_hi_23795358.mp3
## Environment info
- `datasets` version: 1.16.1
- Platform: Linux-4.14.243 with-debian-bullseye-sid
- Python version: 3.7.9
- PyArrow version: 6.0.1
| ashu5644 | https://github.com/huggingface/datasets/issues/3381 | null | false |
1,071,166,270 | 3,380 | [Quick poll] Give your opinion on the future of the Hugging Face Open Source ecosystem! | closed | [] | 2021-12-04T09:18:33 | 2022-01-11T12:29:53 | 2022-01-11T12:29:53 | Thanks to all of you, `datasets` will pass 11.5k stars :star2: this week!
If you have a couple of minutes and want to participate in shaping the future of the ecosystem, please share your thoughts:
[**hf.co/oss-survey**](https://hf.co/oss-survey)
(please reply in the above feedback form rather than to this thread)
Thank you all on behalf of the HuggingFace team! 🤗 | LysandreJik | https://github.com/huggingface/datasets/issues/3380 | null | false |
1,071,079,146 | 3,379 | iter_archive on zipfiles with better compression type check | closed | [
"Hello @lhoestq, thank you for your answer.\r\n\r\nI don't use pytest a lot so I think I might need some help on it :) but I tried some tests for `streaming_download_manager.py` only. I don't know how to test `download_manager.py` since we need to use local files.\r\n\r\n# Comments : \r\n* In **download_manager.py*... | 2021-12-04T01:04:48 | 2023-01-24T13:00:19 | 2023-01-24T12:53:08 | Hello @lhoestq , thank you for your detailed answer on previous PR !
I made this new PR because I misused git on the previous one #3347.
Related issue #3272.
# Comments :
* For extension check I used the `_get_extraction_protocol` function in **download_manager.py** with a slight change and called it `_get_extraction_protocol_local`:
**I removed this part :**
```python
elif path.endswith(".tar.gz") or path.endswith(".tgz"):
raise NotImplementedError(
f"Extraction protocol for TAR archives like '{urlpath}' is not implemented in streaming mode. Please use `dl_manager.iter_archive` instead."
)
```
**And also changed :**
```diff
- extension = path.split(".")[-1]
+ extension = "tar" if path.endswith(".tar.gz") else path.split(".")[-1]
```
The reason for this is a compression like **.tar.gz** will be considered a **.gz** which is handled with **zipfile**, though **tar.gz** can only be opened using **tarfile**.
Please tell me if there's anything to change.
# Tasks :
- [x] download_manager.py
- [x] streaming_download_manager.py | Mehdi2402 | https://github.com/huggingface/datasets/pull/3379 | {
"url": "https://api.github.com/repos/huggingface/datasets/pulls/3379",
"html_url": "https://github.com/huggingface/datasets/pull/3379",
"diff_url": "https://github.com/huggingface/datasets/pull/3379.diff",
"patch_url": "https://github.com/huggingface/datasets/pull/3379.patch",
"merged_at": "2023-01-24T12:53:08"
} | true |
1,070,580,126 | 3,378 | Add The Pile subsets | closed | [] | 2021-12-03T13:14:54 | 2021-12-09T18:11:25 | 2021-12-09T18:11:23 | Add The Pile subsets:
- pubmed
- ubuntu_irc
- europarl
- hacker_news
- nih_exporter
Close bigscience-workshop/data_tooling#301.
CC: @StellaAthena | albertvillanova | https://github.com/huggingface/datasets/pull/3378 | {
"url": "https://api.github.com/repos/huggingface/datasets/pulls/3378",
"html_url": "https://github.com/huggingface/datasets/pull/3378",
"diff_url": "https://github.com/huggingface/datasets/pull/3378.diff",
"patch_url": "https://github.com/huggingface/datasets/pull/3378.patch",
"merged_at": "2021-12-09T18:11:23"
} | true |
1,070,562,907 | 3,377 | COCO 🥥 on the 🤗 Hub? | closed | [
"@mariosasko I fixed couple of bugs",
"TO-DO: \r\n- [x] Add unlabeled 2017 splits, train and validation splits of 2015\r\n- [x] Add Class Labels as list instead",
"@mariosasko added fine & coarse grained labels, will fix the bugs (currently getting set up with VM, my internet is too slow to run the tests and do... | 2021-12-03T12:55:27 | 2021-12-20T14:14:01 | 2021-12-20T14:14:00 | This is a draft PR since I ran into few small problems.
I referred to this TFDS code: https://github.com/tensorflow/datasets/blob/2538a08c184d53b37bfcf52cc21dd382572a88f4/tensorflow_datasets/object_detection/coco.py
cc: @mariosasko | merveenoyan | https://github.com/huggingface/datasets/pull/3377 | {
"url": "https://api.github.com/repos/huggingface/datasets/pulls/3377",
"html_url": "https://github.com/huggingface/datasets/pull/3377",
"diff_url": "https://github.com/huggingface/datasets/pull/3377.diff",
"patch_url": "https://github.com/huggingface/datasets/pull/3377.patch",
"merged_at": null
} | true |
1,070,522,979 | 3,376 | Update clue benchmark | closed | [
"The CI error is due to missing tags in the CLUE dataset card - merging !"
] | 2021-12-03T12:06:01 | 2021-12-08T14:14:42 | 2021-12-08T14:14:41 | Fix #3374 | mariosasko | https://github.com/huggingface/datasets/pull/3376 | {
"url": "https://api.github.com/repos/huggingface/datasets/pulls/3376",
"html_url": "https://github.com/huggingface/datasets/pull/3376",
"diff_url": "https://github.com/huggingface/datasets/pull/3376.diff",
"patch_url": "https://github.com/huggingface/datasets/pull/3376.patch",
"merged_at": "2021-12-08T14:14:41"
} | true |
1,070,454,913 | 3,375 | Support streaming zipped dataset repo by passing only repo name | closed | [
"I just tested and I think this only opens one file ? If there are several files in the ZIP, only the first one is opened. To open several files from a ZIP, one has to call `open` several times.\r\n\r\nWhat about updating the CSV loader to make it `download_and_extract` zip files, and open each extracted file ?",
... | 2021-12-03T10:43:05 | 2021-12-16T18:03:32 | 2021-12-16T18:03:31 | Proposed solution:
- I have added the method `iter_files` to DownloadManager and StreamingDownloadManager
- I use this in modules: "csv", "json", "text"
- I test for CSV/JSONL/TXT zipped (and non-zipped) files, both in streaming and non-streaming modes
Fix #3373. | albertvillanova | https://github.com/huggingface/datasets/pull/3375 | {
"url": "https://api.github.com/repos/huggingface/datasets/pulls/3375",
"html_url": "https://github.com/huggingface/datasets/pull/3375",
"diff_url": "https://github.com/huggingface/datasets/pull/3375.diff",
"patch_url": "https://github.com/huggingface/datasets/pull/3375.patch",
"merged_at": "2021-12-16T18:03:31"
} | true |
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