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https://api.github.com/repos/huggingface/datasets/issues/1338 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1338/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1338/comments | https://api.github.com/repos/huggingface/datasets/issues/1338/events | https://github.com/huggingface/datasets/pull/1338 | 759,725,770 | MDExOlB1bGxSZXF1ZXN0NTM0Njc5ODcz | 1,338 | Add GigaFren Dataset | {
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"@lhoestq fixed"
] | 2020-12-08T19:42:04Z | 2020-12-14T10:03:47Z | 2020-12-14T10:03:46Z | MEMBER | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/1470 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1470/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1470/comments | https://api.github.com/repos/huggingface/datasets/issues/1470/events | https://github.com/huggingface/datasets/pull/1470 | 761,791,065 | MDExOlB1bGxSZXF1ZXN0NTM2NDA2MjQx | 1,470 | Add wiki lingua dataset | {
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"it’s failing because of `RemoteDatasetTest.test_load_dataset_orange_sum`\r\nwhich i think is not the dataset you are doing a PR for. Try rebasing with:\r\n```\r\ngit fetch upstream\r\ngit rebase upstream/master\r\ngit push -u -f origin your_branch\r\n```",
"> it’s failing because of `RemoteDatasetTest.test_load_... | 2020-12-11T02:04:18Z | 2020-12-16T15:27:13Z | 2020-12-16T15:27:13Z | CONTRIBUTOR | null | 0 | {
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} | Hello @lhoestq ,
I am opening a fresh pull request as advised in my original PR https://github.com/huggingface/datasets/pull/1308
Thanks | {
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https://api.github.com/repos/huggingface/datasets/issues/1916 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1916/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1916/comments | https://api.github.com/repos/huggingface/datasets/issues/1916/events | https://github.com/huggingface/datasets/pull/1916 | 812,291,984 | MDExOlB1bGxSZXF1ZXN0NTc2NjgwNjY5 | 1,916 | Remove unused py_utils objects | {
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"Hmmm this one broke master. I'm fixing it.\r\n\r\nMaybe because your branch was outdated ?",
"Sorry @lhoestq, I forgot to update the imports... :/",
"It's fine, the CI should have caught this tbh. Not sure why it did't fail"
] | 2021-02-19T19:51:25Z | 2021-02-22T14:56:56Z | 2021-02-22T13:32:49Z | MEMBER | null | 0 | {
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"_The documentation is not available anymore as the PR was closed or merged._"
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"The CI error is unrelated to the change."
] | 2021-11-12T18:02:37Z | 2021-11-16T18:18:17Z | 2021-11-16T17:55:22Z | CONTRIBUTOR | null | 0 | {
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* allows 403 status code in HEAD requests to S3 buckets to fix the connection error in the Scielo dataset (instead of `url`, uses `response.url` to check the URL of the final endpoint)
* makes the Scielo dataset streamable
Fixes #3255. | {
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"Thanks for reporting, @sauravtii.\r\n\r\nUnfortunately, I'm not able to reproduce the issue:\r\n```python\r\nIn [1]: from datasets import load_dataset\r\n\r\nIn [2]: ds = load_dataset(\"josianem/imdb\")\r\n\r\nIn [2]: ds\r\nOut[2]: \r\nDatasetDict({\r\n train: Dataset({\r\n features: ['text', 'label'],\r... | 2023-04-17T09:08:18Z | 2023-04-18T07:18:20Z | 2023-04-18T07:18:20Z | NONE | null | null | null | ### Describe the bug
I want to use this (https://huggingface.co/datasets/josianem/imdb) dataset therefore I am trying to load it using the following code:
```
dataset = load_dataset("josianem/imdb")
```
The dataset is not getting loaded and gives the error message as the following:
```
Traceback (most recent call last):
File "sample.py", line 3, in <module>
dataset = load_dataset("josianem/imdb")
File "/home/saurav/.local/lib/python3.8/site-packages/datasets/load.py", line 1112, in load_dataset
builder_instance.download_and_prepare(
File "/home/saurav/.local/lib/python3.8/site-packages/datasets/builder.py", line 636, in download_and_prepare
self._download_and_prepare(
File "/home/saurav/.local/lib/python3.8/site-packages/datasets/builder.py", line 704, in _download_and_prepare
split_generators = self._split_generators(dl_manager, **split_generators_kwargs)
File "/home/saurav/.cache/huggingface/modules/datasets_modules/datasets/imdb/cc6ab4acab2799be15d5d217c24548b856156dafdc850165fdc4f2031f27ff2f/imdb.py", line 79, in _split_generators
archive = dl_manager.download(_DOWNLOAD_URL)
File "/home/saurav/.local/lib/python3.8/site-packages/datasets/utils/download_manager.py", line 196, in download
downloaded_path_or_paths = map_nested(
File "/home/saurav/.local/lib/python3.8/site-packages/datasets/utils/py_utils.py", line 197, in map_nested
return function(data_struct)
File "/home/saurav/.local/lib/python3.8/site-packages/datasets/utils/download_manager.py", line 217, in _download
return cached_path(url_or_filename, download_config=download_config)
File "/home/saurav/.local/lib/python3.8/site-packages/datasets/utils/file_utils.py", line 289, in cached_path
output_path = get_from_cache(
File "/home/saurav/.local/lib/python3.8/site-packages/datasets/utils/file_utils.py", line 606, in get_from_cache
raise ConnectionError("Couldn't reach {}".format(url))
ConnectionError: Couldn't reach https://www.dropbox.com/s/zts98j4vkqtsns6/aclImdb_v2.tar?dl=1
```
### Steps to reproduce the bug
You can reproduce the error by using the following code:
```
from datasets import load_dataset, load_metric
dataset = load_dataset("josianem/imdb")
```
### Expected behavior
The dataset should get loaded (I am using this dataset for the first time so not much aware of the exact behavior).
### Environment info
- `datasets` version: 1.12.1
- Platform: Linux-5.4.0-58-generic-x86_64-with-glibc2.29
- Python version: 3.8.10
- PyArrow version: 11.0.0 | {
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"Hi! Thanks for the detailed analysis of adding IIIF support. I like the idea of \"using IIIF through datasets scripts\" due to its ease of use. Another approach that I like is yielding image ids and using the `piffle` library (which offers a bit more flexibility) + `map` to download + cache images. We can handle b... | 2022-03-28T15:19:25Z | 2022-04-05T18:20:53Z | null | MEMBER | null | null | null | This is a feature request for support for IIIF in `datasets`. Apologies for the long issue. I have also used a different format to the usual feature request since I think that makes more sense but happy to use the standard template if preferred.
## What is [IIIF](https://iiif.io/)?
IIIF (International Image Interoperability Framework)
> is a set of open standards for delivering high-quality, attributed digital objects online at scale. It’s also an international community developing and implementing the IIIF APIs. IIIF is backed by a consortium of leading cultural institutions.
The tl;dr is that IIIF provides various specifications for implementing useful functionality for:
- Institutions to make available images for various use cases
- Users to have a consistent way of interacting/requesting these images
- For developers to have a common standard for developing tools for working with IIIF images that will work across all institutions that implement a particular IIIF standard (for example the image viewer for the BNF can also work for the Library of Congress if they both use IIIF).
Some institutions that various levels of support IIF include: The British Library, Internet Archive, Library of Congress, Wikidata. There are also many smaller institutions that have IIIF support. An incomplete list can be found here: https://iiif.io/guides/finding_resources/
## IIIF APIs
IIIF consists of a number of APIs which could be integrated with datasets. I think the most obvious candidate for inclusion would be the [Image API](https://iiif.io/api/image/3.0/)
### IIIF Image API
The Image API https://iiif.io/api/image/3.0/ is likely the most suitable first candidate for integration with datasets. The Image API offers a consistent protocol for requesting images via a URL:
```{scheme}://{server}{/prefix}/{identifier}/{region}/{size}/{rotation}/{quality}.{format}```
A concrete example of this:
```https://stacks.stanford.edu/image/iiif/hg676jb4964%2F0380_796-44/full/full/0/default.jpg```
As you can see the scheme offers a number of options that can be specified in the URL, for example, size. Using the example URL we return:
We can change the size to request a size of 250 by 250, this is done by changing the size from `full` to `250,250` i.e. switching the URL to `https://stacks.stanford.edu/image/iiif/hg676jb4964%2F0380_796-44/full/250,250/0/default.jpg`
We can also request the image with max width 250, max height 250 whilst maintaining the aspect ratio using `!w,h`. i.e. change the url to `https://stacks.stanford.edu/image/iiif/hg676jb4964%2F0380_796-44/full/!250,250/0/default.jpg`
A full overview of the options for size can be found here: https://iiif.io/api/image/3.0/#42-size
## Why would/could this be useful for datasets?
There are a few reasons why support for the IIIF Image API could be useful. Broadly the ability to have more control over how an image is returned from a server is useful for many ML workflows:
- images can be requested in the right size, this prevents having to download/stream large images when the actual desired size is much smaller
- can select a subset of an image: it is possible to select a sub-region of an image, this could be useful for example when you already have a bounding box for a subset of an image and then want to use this subset of an image for another task. For example, https://github.com/Living-with-machines/nnanno uses IIIF to request parts of a newspaper image that have been detected as 'photograph', 'illustration' etc for downstream use.
- options for quality, rotation, the format can all be encoded in the URL request.
These may become particularly useful when pre-training models on large image datasets where the cost of downloading images with 1600 pixel width when you actually want 240 has a larger impact.
## What could this look like in datasets?
I think there are various ways in which support for IIIF could potentially be included in `datasets`. These suggestions aren't fully fleshed out but hopefully, give a sense of possible approaches that match existing `datasets` methods in their approach.
### Use through datasets scripts
Loading images via URL is already supported. There are a few possible 'extras' that could be included when using IIIF. One option is to leverage the IIIF protocol in datasets scripts, i.e. the dataset script can expose the IIIF options via the dataset script:
```python
ds = load_dataset("iiif_dataset", image_size="250,250", fmt="jpg")
```
This is already possible. The approach to parsing the IIIF URLs would be left to the person creating the dataset script.
### Support through dataset scripts (with some datasets support)
This is similar to the above but `datasets` would offer some way of saying this is a iiif URL and then expose the options associated with IIIF images automatically. i.e. if you did something like:
```python
features = {"label": ClassLabel(names=['dog','cat']),
"url": datasets.IIIFURL()}
```
inside your loading script, you would automatically have exposed `size`, `fmt` etc. options when loading the dataset.
### Other possible integrations
Some other possible pseudocode ways that a user could interact with IIIF URLs:
The ability to cast to an `IIIFImage` feature type:
```
ds.cast_column('url', IIIFImage, download=False)
```
The ability to specify some options associated with IIIF urls.
```
ds = ds.set_iiif_options(column='url', size="250,250")
```
I think all of these would rely on having an `IIIFImage` feature type - this would be a little bit of a Frankenstein between a `string` and `datasets.Image`. I think most of the actual image behaviour would be exactly the same as `datasets.Image`, the difference would be that the underlying URL could be modified in various ways.
## prerequisite requirements
There are a few pre-requisites that I can anticipate. This doesn't cover a full implementation of IIIF support which would have different requirements depending on the approach taken to implementing IIIF. Some of these features would be useful independently of adding IIIF support:
### support for handling failed images loaded via a URL (or a specific IIIFImage feature).
Working with images via web requests will inevitably return the odd failed request. If these images are then requests and don't return it would be useful to have a `None` returned instead of an error. For example, when using `push_to_hub` `datasets` will try and include the image but currently fails with bad URLs.
```python
from datasets import Dataset
import datasets
urls = ['https://stacks.stanford.edu/image/iiif/hg676jb4964%2F0380_796-44/full/!250,250/0/default.jpg']*3
urls.append("badurl.com/image.jpg")
data = {"url":urls}
ds = Dataset.from_dict(data)
ds = ds.cast_column('url', datasets.Image())
ds[3]['url']
```
returns a `FileNotFoundError`, for streaming large datasets of images using their URLs it could be useful to have `None` returned instead. This has implications for the actual training loop i.e. you now need to somehow skip those examples because of this it might not be desirable to support this.
### Caching support
Since IIIF requests images via a URL it would be great to have a way of not requesting the images multiple times. This is tracked in https://github.com/huggingface/datasets/issues/3142 and I think this would also be very desirable to have here particularly as one of the primary use cases of IIIF may be to do unsupervised pre-training on large datasets of IIIF URLs.
### Support for Parsing IIIF URLs
This gets closer to the actual implementation. Here the requirement would be some way for `datasets` to parse a URL that the users specify is an IIIF URL. An example of a Python library that does this: https://github.com/Princeton-CDH/piffle. I also have a rough version that uses `dataclasses` which I can share.
## Why it might not be worthwhile/suitable for datasets
There are some reasons that this might not be worth implementing:
- currently, IIIF is mainly used by cultural heritage organizations (museums, archives etc.) The adoption of IIIF in this sector has been growing but it's possible that adoption won't be extended to other industries which may also be a source of image data for training ML models.
- It may end up being better to leave this to the user. It would for example be possible for someone to write map functions to change an IIIF URL to the correct size etc. Adding direct support for IIIF in datasets may potentially not be worth the trouble.
- The impact of different approaches to doing image scaling can impact the downstream model's performance, see: https://twitter.com/wightmanr/status/1479528581466243073?s=20. Since different IIIF image servers may implement different approaches to resizing images this could have a downstream impact on model performance. think this is something that could be flagged to the end-user in the documentation. This probably also falls into general "gotchas" that probably aren't the `datasets` libraries' role to protect users from.
Some of the requirements outlined above would be useful for images anyway. These could be implemented prior to a final decision about whether IIIF support could/should be added to datasets.
## Suggested next steps:
I realise this is a long and slightly open-ended issue. I am happy to clarify/answer questions on IIIF and possible integrations. If the prerequisite requirements seem worth exploring/are better explored in their own issues let me know and I can open new issues for those.
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https://api.github.com/repos/huggingface/datasets/issues/4631 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4631/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4631/comments | https://api.github.com/repos/huggingface/datasets/issues/4631/events | https://github.com/huggingface/datasets/pull/4631 | 1,293,545,900 | PR_kwDODunzps460Vy0 | 4,631 | Update WinoBias README | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-07-04T20:24:40Z | 2022-07-07T13:23:32Z | 2022-07-07T13:11:47Z | NONE | null | 0 | {
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} | I'm adding some information about Winobias that I got from the paper :smile:
I think this makes it a bit clearer! | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-07-15T17:47:48Z | 2022-07-18T08:46:56Z | 2022-07-18T08:34:49Z | MEMBER | null | 0 | {
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} | This PR:
- Refactors base extractors as subclasses of `BaseExtractor`:
- this is an abstract class defining the interface with:
- `is_extractable`: abstract class method
- `extract`: abstract static method
- Implements abstract `MagicNumberBaseExtractor` (as subclass of `BaseExtractor`):
- this has a default implementation of `is_extractable`
- this improves performance (reducing the number of file reads) by allowing passing already read `magic_number`
- Refactors `Extractor`:
- reads magic number from file only once
This PR deprecates:
```python
is_extractable, extractor = self.extractor.is_extractable(input_path, return_extractor=True)
self.extractor.extract(input_path, output_path, extractor=extractor)
```
and uses more Pythonic instead:
```python
extractor_format = self.extractor.infer_extractor_format(input_path)
self.extractor.extract(input_path, output_path, extractor_format)
``` | {
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"Are there any `task_categories:automatic-speech-recognition` dataset for which we should update the tags ?",
"> Are there any `task_categories:automatic-speech-recognition` dataset for which we should update the tags ?\r\n\r\nYes there's a few - I'll fix them tomorrow :)"
] | 2021-07-09T16:07:29Z | 2021-07-12T18:32:59Z | 2021-07-12T17:32:02Z | MEMBER | null | 0 | {
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} | This PR replaces the `automatic-speech-recognition` task category with a broader `speech-processing` category.
The tasks associated with this category are derived from the [SUPERB benchmark](https://arxiv.org/abs/2105.01051), and ASR is included in this set. | {
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https://api.github.com/repos/huggingface/datasets/issues/4431 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4431/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4431/comments | https://api.github.com/repos/huggingface/datasets/issues/4431/events | https://github.com/huggingface/datasets/pull/4431 | 1,254,618,948 | PR_kwDODunzps44x5aG | 4,431 | Add personaldialog datasets | {
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"These test errors are related to issue #4428 \r\n",
"_The documentation is not available anymore as the PR was closed or merged._",
"I only made a trivial modification in my commit https://github.com/huggingface/datasets/pull/4431/commits/402c893d35224d7828176717233909ac5f1e7b3e\r\n\r\nI have submitted a PR #4... | 2022-06-01T01:20:40Z | 2022-06-11T12:40:23Z | 2022-06-11T12:31:16Z | CONTRIBUTOR | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/6304 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6304/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6304/comments | https://api.github.com/repos/huggingface/datasets/issues/6304/events | https://github.com/huggingface/datasets/pull/6304 | 1,945,913,521 | PR_kwDODunzps5c7-4q | 6,304 | Update README.md | {
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"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_a... | 2023-10-16T19:10:39Z | 2023-10-17T15:13:37Z | 2023-10-17T15:04:52Z | CONTRIBUTOR | null | 0 | {
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} | Fixed typos in ReadMe and added punctuation marks
Tensorflow --> TensorFlow
| {
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https://api.github.com/repos/huggingface/datasets/issues/4544 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4544/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4544/comments | https://api.github.com/repos/huggingface/datasets/issues/4544/events | https://github.com/huggingface/datasets/issues/4544 | 1,280,500,340 | I_kwDODunzps5MUuJ0 | 4,544 | [CI] seqeval installation fails sometimes on python 3.6 | {
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"gists... | null | [] | 2022-06-22T16:35:23Z | 2022-06-23T10:13:44Z | 2022-06-23T10:13:44Z | MEMBER | null | null | null | The CI sometimes fails to install seqeval, which cause the `seqeval` metric tests to fail.
The installation fails because of this error:
```
Collecting seqeval
Downloading seqeval-1.2.2.tar.gz (43 kB)
|███████▌ | 10 kB 42.1 MB/s eta 0:00:01
|███████████████ | 20 kB 53.3 MB/s eta 0:00:01
|██████████████████████▌ | 30 kB 67.2 MB/s eta 0:00:01
|██████████████████████████████ | 40 kB 76.1 MB/s eta 0:00:01
|████████████████████████████████| 43 kB 10.0 MB/s
Preparing metadata (setup.py) ... - error
ERROR: Command errored out with exit status 1:
command: /home/circleci/.pyenv/versions/3.6.15/bin/python3.6 -c 'import io, os, sys, setuptools, tokenize; sys.argv[0] = '"'"'/tmp/pip-install-1l96tbyj/seqeval_b31086f711d84743abe6905d2aa9dade/setup.py'"'"'; __file__='"'"'/tmp/pip-install-1l96tbyj/seqeval_b31086f711d84743abe6905d2aa9dade/setup.py'"'"';f = getattr(tokenize, '"'"'open'"'"', open)(__file__) if os.path.exists(__file__) else io.StringIO('"'"'from setuptools import setup; setup()'"'"');code = f.read().replace('"'"'\r\n'"'"', '"'"'\n'"'"');f.close();exec(compile(code, __file__, '"'"'exec'"'"'))' egg_info --egg-base /tmp/pip-pip-egg-info-pf54_vqy
cwd: /tmp/pip-install-1l96tbyj/seqeval_b31086f711d84743abe6905d2aa9dade/
Complete output (22 lines):
Traceback (most recent call last):
File "<string>", line 1, in <module>
File "/tmp/pip-install-1l96tbyj/seqeval_b31086f711d84743abe6905d2aa9dade/setup.py", line 56, in <module>
'Programming Language :: Python :: Implementation :: PyPy'
File "/home/circleci/.pyenv/versions/3.6.15/lib/python3.6/site-packages/setuptools/__init__.py", line 143, in setup
return distutils.core.setup(**attrs)
File "/home/circleci/.pyenv/versions/3.6.15/lib/python3.6/distutils/core.py", line 108, in setup
_setup_distribution = dist = klass(attrs)
File "/home/circleci/.pyenv/versions/3.6.15/lib/python3.6/site-packages/setuptools/dist.py", line 442, in __init__
k: v for k, v in attrs.items()
File "/home/circleci/.pyenv/versions/3.6.15/lib/python3.6/distutils/dist.py", line 281, in __init__
self.finalize_options()
File "/home/circleci/.pyenv/versions/3.6.15/lib/python3.6/site-packages/setuptools/dist.py", line 601, in finalize_options
ep.load()(self, ep.name, value)
File "/home/circleci/.pyenv/versions/3.6.15/lib/python3.6/site-packages/pkg_resources/__init__.py", line 2346, in load
return self.resolve()
File "/home/circleci/.pyenv/versions/3.6.15/lib/python3.6/site-packages/pkg_resources/__init__.py", line 2352, in resolve
module = __import__(self.module_name, fromlist=['__name__'], level=0)
File "/tmp/pip-install-1l96tbyj/seqeval_b31086f711d84743abe6905d2aa9dade/.eggs/setuptools_scm-7.0.2-py3.6.egg/setuptools_scm/__init__.py", line 5
from __future__ import annotations
^
SyntaxError: future feature annotations is not defined
----------------------------------------
WARNING: Discarding https://files.pythonhosted.org/packages/9d/2d/233c79d5b4e5ab1dbf111242299153f3caddddbb691219f363ad55ce783d/seqeval-1.2.2.tar.gz#sha256=f28e97c3ab96d6fcd32b648f6438ff2e09cfba87f05939da9b3970713ec56e6f (from https://pypi.org/simple/seqeval/). Command errored out with exit status 1: python setup.py egg_info Check the logs for full command output.
```
for example in https://app.circleci.com/pipelines/github/huggingface/datasets/12665/workflows/93878eb9-a923-4b35-b2e7-c5e9b22f10ad/jobs/75300
Here is a diff of the pip install logs until the error is reached: https://www.diffchecker.com/VkQDLeQT
This could be caused by the latest updates of setuptools-scm | {
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https://api.github.com/repos/huggingface/datasets/issues/4865 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4865/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4865/comments | https://api.github.com/repos/huggingface/datasets/issues/4865/events | https://github.com/huggingface/datasets/issues/4865 | 1,344,552,626 | I_kwDODunzps5QJD6y | 4,865 | Dataset Viewer issue for MoritzLaurer/multilingual_nli | {
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"Thanks for reporting @MoritzLaurer.\r\n\r\nCurrently, the dataset preview is working properly: https://huggingface.co/datasets/MoritzLaurer/multilingual_nli\r\n\r\nPlease note that when a dataset is modified, it might take some time until the preview is completely updated.\r\n\r\n@severo might it be worth adding ... | 2022-08-19T14:55:20Z | 2022-08-22T14:47:14Z | 2022-08-22T06:13:20Z | NONE | null | null | null | ### Link
_No response_
### Description
I've just uploaded a new dataset to the hub and the viewer does not work for some reason, see here: https://huggingface.co/datasets/MoritzLaurer/multilingual_nli
It displays the error:
```
Status code: 400
Exception: Status400Error
Message: The dataset does not exist.
```
Weirdly enough the dataviewer works for an earlier version of the same dataset. The only difference is that it is smaller, but I'm not aware of other changes I have made: https://huggingface.co/datasets/MoritzLaurer/multilingual_nli_test
Do you know why the dataviewer is not working?
### Owner
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https://api.github.com/repos/huggingface/datasets/issues/1495 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1495/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1495/comments | https://api.github.com/repos/huggingface/datasets/issues/1495/events | https://github.com/huggingface/datasets/pull/1495 | 763,025,562 | MDExOlB1bGxSZXF1ZXN0NTM3NTE2ODE4 | 1,495 | Opus DGT added | {
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"merging since the CI is fixed on master"
] | 2020-12-11T23:05:09Z | 2020-12-17T14:38:41Z | 2020-12-17T14:38:41Z | CONTRIBUTOR | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/5604 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5604/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5604/comments | https://api.github.com/repos/huggingface/datasets/issues/5604/events | https://github.com/huggingface/datasets/issues/5604 | 1,608,304,775 | I_kwDODunzps5f3MiH | 5,604 | Problems with downloading The Pile | {
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"Hi! \r\n\r\n\r\nYou can specify `download_config=DownloadConfig(resume_download=True))` in `load_dataset` to resume the download when re-running the code after the timeout error:\r\n```python\r\nfrom datasets import load_dataset, DownloadConfig\r\ndataset = load_dataset('the_pile', split='train', cache_dir='F:\\da... | 2023-03-03T09:52:08Z | 2023-10-14T02:15:52Z | 2023-03-24T12:44:25Z | NONE | null | null | null | ### Describe the bug
The downloads in the screenshot seem to be interrupted after some time and the last download throws a "Read timed out" error.
Here are the downloaded files:
They should be all 14GB like here (https://the-eye.eu/public/AI/pile/train/).
Alternatively, can I somehow download the files by myself and use the datasets preparing script?
### Steps to reproduce the bug
dataset = load_dataset('the_pile', split='train', cache_dir='F:\datasets')
### Expected behavior
The files should be downloaded correctly.
### Environment info
- `datasets` version: 2.10.1
- Platform: Windows-10-10.0.22623-SP0
- Python version: 3.10.5
- PyArrow version: 9.0.0
- Pandas version: 1.4.2 | {
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https://api.github.com/repos/huggingface/datasets/issues/5049 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5049/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5049/comments | https://api.github.com/repos/huggingface/datasets/issues/5049/events | https://github.com/huggingface/datasets/pull/5049 | 1,392,361,381 | PR_kwDODunzps4_7zOY | 5,049 | Add `kwargs` to `Dataset.from_generator` | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-09-30T12:24:27Z | 2022-10-03T11:00:11Z | 2022-10-03T10:58:15Z | CONTRIBUTOR | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/4814 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4814/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4814/comments | https://api.github.com/repos/huggingface/datasets/issues/4814/events | https://github.com/huggingface/datasets/issues/4814 | 1,333,356,230 | I_kwDODunzps5PeWbG | 4,814 | Support CSV as metadata file format in AudioFolder/ImageFolder | {
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... | null | [] | 2022-08-09T14:36:49Z | 2022-08-31T11:59:08Z | 2022-08-31T11:59:08Z | CONTRIBUTOR | null | null | null | Requested here: https://discuss.huggingface.co/t/how-to-structure-an-image-dataset-repo-using-the-image-folder-approach/21004. CSV is also used in AutoTrain for specifying metadata in image datasets. | {
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https://api.github.com/repos/huggingface/datasets/issues/2014 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2014/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2014/comments | https://api.github.com/repos/huggingface/datasets/issues/2014/events | https://github.com/huggingface/datasets/pull/2014 | 825,916,531 | MDExOlB1bGxSZXF1ZXN0NTg3OTY1NDg3 | 2,014 | more explicit method parameters | {
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} | re: #2009
not super convinced this is better, and while I usually fight against kwargs here it seems to me that it better conveys the relationship to the `_split_generator` method. | {
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https://api.github.com/repos/huggingface/datasets/issues/4226 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4226/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4226/comments | https://api.github.com/repos/huggingface/datasets/issues/4226/events | https://github.com/huggingface/datasets/pull/4226 | 1,216,331,073 | PR_kwDODunzps420kAv | 4,226 | Add pearsonr mc, update functionality to match the original docs | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"thank you @lhoestq!! :hugs: "
] | 2022-04-26T18:30:46Z | 2022-05-03T17:09:24Z | 2022-05-03T17:02:28Z | CONTRIBUTOR | null | 0 | {
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} | - adds pearsonr metric card
- adds ability to return p-value
- p-value was mentioned in the original docs as a return value, but there was no option to return it. I updated the _compute function slightly to have an option to return the p-value. | {
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https://api.github.com/repos/huggingface/datasets/issues/2611 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2611/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2611/comments | https://api.github.com/repos/huggingface/datasets/issues/2611/events | https://github.com/huggingface/datasets/pull/2611 | 940,307,053 | MDExOlB1bGxSZXF1ZXN0Njg2Mzk5MjU3 | 2,611 | More consistent naming | {
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} | As per @stas00's suggestion in #2500, this PR inserts a space between the logo and the lib name (`🤗Datasets` -> `🤗 Datasets`) for consistency with the Transformers lib. Additionally, more consistent names are used for Datasets Hub, etc. | {
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https://api.github.com/repos/huggingface/datasets/issues/1895 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1895/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1895/comments | https://api.github.com/repos/huggingface/datasets/issues/1895/events | https://github.com/huggingface/datasets/issues/1895 | 809,630,271 | MDU6SXNzdWU4MDk2MzAyNzE= | 1,895 | Bug Report: timestamp[ns] not recognized | {
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"Thanks for reporting !\r\n\r\nYou're right, `string_to_arrow` should be able to take `\"timestamp[ns]\"` as input and return the right pyarrow timestamp type.\r\nFeel free to suggest a fix for `string_to_arrow` and open a PR if you want to contribute ! This would be very appreciated :)\r\n\r\nTo give you more cont... | 2021-02-16T20:38:04Z | 2021-02-19T18:27:11Z | 2021-02-19T18:27:11Z | CONTRIBUTOR | null | null | null | Repro:
```
from datasets import Dataset
import pandas as pd
import pyarrow
df = pd.DataFrame(pd.date_range("2018-01-01", periods=3, freq="H"))
pyarrow.Table.from_pandas(df)
Dataset.from_pandas(df)
# Throws ValueError: Neither timestamp[ns] nor timestamp[ns]_ seems to be a pyarrow data type.
```
The factory function seems to be just "timestamp": https://arrow.apache.org/docs/python/generated/pyarrow.timestamp.html#pyarrow.timestamp
It seems like https://github.com/huggingface/datasets/blob/master/src/datasets/features.py#L36-L43 could have a little bit of additional structure for handling these cases? I'd be happy to take a shot at opening a PR if I could receive some guidance on whether parsing something like `timestamp[ns]` and resolving it to timestamp('ns') is the goal of this method.
Alternatively, if I'm using this incorrectly (e.g. is the expectation that we always provide a schema when timestamps are involved?), that would be very helpful to know as well!
```
$ pip list # only the relevant libraries/versions
datasets 1.2.1
pandas 1.0.3
pyarrow 3.0.0
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/2685 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2685/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2685/comments | https://api.github.com/repos/huggingface/datasets/issues/2685/events | https://github.com/huggingface/datasets/pull/2685 | 948,791,572 | MDExOlB1bGxSZXF1ZXN0NjkzNTgxNTk2 | 2,685 | Fix Blog Authorship Corpus dataset | {
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"Normally, I'm expecting errors from the validation of the README file... 😅 ",
"That is:\r\n```\r\n=========================== short test summary info ============================\r\nFAILED tests/test_dataset_cards.py::test_changed_dataset_card[blog_authorship_corpus]\r\n==== 1 failed, 3182 passed, 2763 skipped,... | 2021-07-20T15:44:50Z | 2021-07-21T13:11:58Z | 2021-07-21T13:11:58Z | MEMBER | null | 0 | {
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} | This PR:
- Update the JSON metadata file, which previously was raising a `NonMatchingSplitsSizesError`
- Fix the codec of the data files (`latin_1` instead of `utf-8`), which previously was raising ` UnicodeDecodeError` for some files
Close #2679. | {
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https://api.github.com/repos/huggingface/datasets/issues/5847 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5847/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5847/comments | https://api.github.com/repos/huggingface/datasets/issues/5847/events | https://github.com/huggingface/datasets/issues/5847 | 1,706,616,634 | I_kwDODunzps5luOc6 | 5,847 | Streaming IterableDataset not working with translation pipeline | {
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"I wasn't sure to file this against transformers or datasets.",
"[`KeyDataset`](https://github.com/huggingface/transformers/blob/7f8b909189547944617741d8d3c6c84504701693/src/transformers/pipelines/pt_utils.py#L296) doesn't support iterable datasets, so you either need to implement a version that does (and also in... | 2023-05-11T21:52:38Z | 2023-05-16T15:59:55Z | null | NONE | null | null | null | ### Describe the bug
I'm trying to use a streaming dataset for translation inference to avoid downloading the training data.
I'm using a pipeline and a dataset, and following the guidance in the tutorial.
Instead I get an exception that IterableDataset has no len().
### Steps to reproduce the bug
CODE:
```
from transformers import pipeline
from transformers.pipelines.pt_utils import KeyDataset
from datasets import load_dataset
ds = load_dataset(path="wmt14", name="fr-en", split="test", streaming=True)
bs=1
mt = pipeline("translation_en_to_fr", model="t5-base", batch_size=bs)
#print(mt("hello")) THIS WORKS
ks = KeyDataset(ds, "translation")
print(f"{ks}")
xx= mt(ks)
for x in xx:
print(x)
```
RUN:
```
(watnlp) [jlquinn@bertdev01 hf]$ python ende.t5.pipe.py
2023-05-11 16:48:08.817572: I tensorflow/core/util/util.cc:169] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2023-05-11 16:48:08.821388: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory
2023-05-11 16:48:08.821407: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
<transformers.pipelines.pt_utils.KeyDataset object at 0x7f61ed5da9d0>
Traceback (most recent call last):
File "/home/jlquinn/models/hf/ende.t5.pipe.py", line 11, in <module>
for x in xx:
File "/home/jlquinn/miniconda3/envs/watnlp/lib/python3.9/site-packages/transformers/pipelines/pt_utils.py", line 111, in __next__
item = next(self.iterator)
File "/home/jlquinn/miniconda3/envs/watnlp/lib/python3.9/site-packages/transformers/pipelines/pt_utils.py", line 111, in __next__
item = next(self.iterator)
File "/home/jlquinn/miniconda3/envs/watnlp/lib/python3.9/site-packages/torch/utils/data/dataloader.py", line 681, in __next__
data = self._next_data()
File "/home/jlquinn/miniconda3/envs/watnlp/lib/python3.9/site-packages/torch/utils/data/dataloader.py", line 720, in _next_data
index = self._next_index() # may raise StopIteration
File "/home/jlquinn/miniconda3/envs/watnlp/lib/python3.9/site-packages/torch/utils/data/dataloader.py", line 671, in _next_index
return next(self._sampler_iter) # may raise StopIteration
File "/home/jlquinn/miniconda3/envs/watnlp/lib/python3.9/site-packages/torch/utils/data/sampler.py", line 247, in __iter__
for idx in self.sampler:
File "/home/jlquinn/miniconda3/envs/watnlp/lib/python3.9/site-packages/torch/utils/data/sampler.py", line 76, in __iter__
return iter(range(len(self.data_source)))
File "/home/jlquinn/miniconda3/envs/watnlp/lib/python3.9/site-packages/transformers/pipelines/pt_utils.py", line 13, in __len__
return len(self.dataset)
File "/home/jlquinn/miniconda3/envs/watnlp/lib/python3.9/site-packages/transformers/pipelines/pt_utils.py", line 289, in __len__
return len(self.dataset)
TypeError: object of type 'IterableDataset' has no len()
```
### Expected behavior
I'm expecting french translations of the english test set to be printed.
### Environment info
Run on CPU with no GPU.
RHEL 8.7 x86_64
python 3.9.0
transformers 4.17.0
datasets 2.0.0
tokenizers 0.12.1
```
(watnlp) [jlquinn@bertdev01 hf]$ datasets-cli env
Copy-and-paste the text below in your GitHub issue.
- `datasets` version: 2.0.0
- Platform: Linux-4.18.0-372.19.1.el8_6.x86_64-x86_64-with-glibc2.28
- Python version: 3.9.0
- PyArrow version: 8.0.0
- Pandas version: 1.4.4
```
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https://api.github.com/repos/huggingface/datasets/issues/4445 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4445/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4445/comments | https://api.github.com/repos/huggingface/datasets/issues/4445/events | https://github.com/huggingface/datasets/pull/4445 | 1,259,947,568 | PR_kwDODunzps45EjtA | 4,445 | Fix missing args in docstring of load_dataset_builder | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-06-03T13:55:50Z | 2022-06-03T14:35:32Z | 2022-06-03T14:27:09Z | MEMBER | null | 0 | {
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} | Currently, the docstring of `load_dataset_builder` only contains the first parameter `path` (no other):
- https://huggingface.co/docs/datasets/v2.2.1/en/package_reference/loading_methods#datasets.load_dataset_builder.path | {
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https://api.github.com/repos/huggingface/datasets/issues/5636 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5636/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5636/comments | https://api.github.com/repos/huggingface/datasets/issues/5636/events | https://github.com/huggingface/datasets/pull/5636 | 1,623,721,577 | PR_kwDODunzps5MAunR | 5,636 | Fix CI: ignore C901 ("some_func" is to complex) in `ruff` | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2023-03-14T15:29:11Z | 2023-03-14T16:37:06Z | 2023-03-14T16:29:52Z | CONTRIBUTOR | null | 0 | {
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} | idk if I should have added this ignore to `ruff` too, but I added :) | {
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https://api.github.com/repos/huggingface/datasets/issues/2319 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2319/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2319/comments | https://api.github.com/repos/huggingface/datasets/issues/2319/events | https://github.com/huggingface/datasets/issues/2319 | 876,251,376 | MDU6SXNzdWU4NzYyNTEzNzY= | 2,319 | UnicodeDecodeError for OSCAR (Afrikaans) | {
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"Thanks for reporting, @sgraaf.\r\n\r\nI am going to have a look at it. \r\n\r\nI guess the expected codec is \"UTF-8\". Normally, when no explicitly codec is passed, Python uses one which is platform-dependent. For Linux machines, the default codec is `utf_8`, which is OK. However for Windows machine, the default ... | 2021-05-05T09:22:52Z | 2021-05-05T10:57:31Z | 2021-05-05T10:50:55Z | NONE | null | null | null | ## Describe the bug
When loading the [OSCAR dataset](https://huggingface.co/datasets/oscar) (specifically `unshuffled_deduplicated_af`), I encounter a `UnicodeDecodeError`.
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset("oscar", "unshuffled_deduplicated_af")
```
## Expected results
Anything but an error, really.
## Actual results
```python
>>> from datasets import load_dataset
>>> dataset = load_dataset("oscar", "unshuffled_deduplicated_af")
Downloading: 14.7kB [00:00, 4.91MB/s]
Downloading: 3.07MB [00:00, 32.6MB/s]
Downloading and preparing dataset oscar/unshuffled_deduplicated_af (download: 62.93 MiB, generated: 163.38 MiB, post-processed: Unknown size, total: 226.32 MiB) to C:\Users\sgraaf\.cache\huggingface\datasets\oscar\unshuffled_deduplicated_af\1.0.0\bd4f96df5b4512007ef9fd17bbc1ecde459fa53d2fc0049cf99392ba2efcc464...
Downloading: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 81.0/81.0 [00:00<00:00, 40.5kB/s]
Downloading: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 66.0M/66.0M [00:18<00:00, 3.50MB/s]
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "C:\Users\sgraaf\AppData\Local\Programs\Python\Python39\lib\site-packages\datasets\load.py", line 745, in load_dataset
builder_instance.download_and_prepare(
File "C:\Users\sgraaf\AppData\Local\Programs\Python\Python39\lib\site-packages\datasets\builder.py", line 574, in download_and_prepare
self._download_and_prepare(
File "C:\Users\sgraaf\AppData\Local\Programs\Python\Python39\lib\site-packages\datasets\builder.py", line 652, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "C:\Users\sgraaf\AppData\Local\Programs\Python\Python39\lib\site-packages\datasets\builder.py", line 979, in _prepare_split
for key, record in utils.tqdm(
File "C:\Users\sgraaf\AppData\Local\Programs\Python\Python39\lib\site-packages\tqdm\std.py", line 1133, in __iter__
for obj in iterable:
File "C:\Users\sgraaf\.cache\huggingface\modules\datasets_modules\datasets\oscar\bd4f96df5b4512007ef9fd17bbc1ecde459fa53d2fc0049cf99392ba2efcc464\oscar.py", line 359, in _generate_examples
for line in f:
File "C:\Users\sgraaf\AppData\Local\Programs\Python\Python39\lib\encodings\cp1252.py", line 23, in decode
return codecs.charmap_decode(input,self.errors,decoding_table)[0]
UnicodeDecodeError: 'charmap' codec can't decode byte 0x9d in position 7454: character maps to <undefined>
```
## Versions
Paste the output of the following code:
```python
import datasets
import sys
import platform
print(f"""
- Datasets: {datasets.__version__}
- Python: {sys.version}
- Platform: {platform.platform()}
""")
```
- Datasets: 1.6.2
- Python: 3.9.4 (tags/v3.9.4:1f2e308, Apr 6 2021, 13:40:21) [MSC v.1928 64 bit (AMD64)]
- Platform: Windows-10-10.0.19041-SP0 | {
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https://api.github.com/repos/huggingface/datasets/issues/3936 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3936/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3936/comments | https://api.github.com/repos/huggingface/datasets/issues/3936/events | https://github.com/huggingface/datasets/pull/3936 | 1,170,713,473 | PR_kwDODunzps40hE-P | 3,936 | Fix Wikipedia version and re-add tests | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3936). All of your documentation changes will be reflected on that endpoint."
] | 2022-03-16T08:48:04Z | 2022-03-16T17:04:07Z | 2022-03-16T17:04:05Z | MEMBER | null | 0 | {
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} | To keep backward compatibility when loading using "wikipedia" dataset ID (https://huggingface.co/datasets/wikipedia), we have created the pre-processed data for the same languages we were offering before, but with updated date "20220301":
- de
- en
- fr
- frr
- it
- simple
These pre-processed data can be accessed, e.g.:
```python
ds = load_dataset("wikipedia", "20220301.frr", split="train")
```
The next step will be to offer the pre-processed data for many other languages, but when loading using "wikimedia/wikipedia": https://huggingface.co/datasets/wikimedia/wikipedia | {
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https://api.github.com/repos/huggingface/datasets/issues/3485 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3485/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3485/comments | https://api.github.com/repos/huggingface/datasets/issues/3485/events | https://github.com/huggingface/datasets/issues/3485 | 1,089,027,581 | I_kwDODunzps5A6T39 | 3,485 | skip columns which cannot set to specific format when set_format | {
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"You can add columns that you wish to set into `torch` format using `dataset.set_format(\"torch\", ['id', 'abc'])` so that input batch of the transform only contains those columns",
"Sorry, I miss `output_all_columns` args and thought after `dataset.set_format(\"torch\", columns=columns)` I can only get specific ... | 2021-12-27T07:19:55Z | 2021-12-27T09:07:07Z | 2021-12-27T09:07:07Z | NONE | null | null | null | **Is your feature request related to a problem? Please describe.**
When using `dataset.set_format("torch")`, I must make sure every columns in datasets can convert to `torch`, however, sometimes I want to keep some string columns.
**Describe the solution you'd like**
skip columns which cannot set to specific format when set_format instead of raise an error.
| {
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https://api.github.com/repos/huggingface/datasets/issues/4394 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4394/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4394/comments | https://api.github.com/repos/huggingface/datasets/issues/4394/events | https://github.com/huggingface/datasets/issues/4394 | 1,245,221,657 | I_kwDODunzps5KOJMZ | 4,394 | trainer became extremely slow after reload dataset by `load_from_disk` | {
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"I tried to make the dataset much more smaller (100000 rows) , then the speed became `33.88it/s` from`8.62s/it`. It's nearly 200 times... Do you have any idea? Thank you!",
"Similar issue: https://github.com/huggingface/transformers/issues/8818\r\n\r\nI changed `RandomSampler` to `SequentialSampler` in the `tra... | 2022-05-23T14:04:37Z | 2022-06-06T16:08:01Z | null | NONE | null | null | null | ## Describe the bug
Due to memory problem, I need to save my tokenized datasets locally by CPU and reload it by multi GPU for running training script. However, after I reload it by `load_from_disk` and start training, the speed is extremely slow. It says I need about 1500 hours with 8 A100 cards. Before this, I can run the whole script in one day with a single A100 card.
Since I am try to pre-train a BERT, **my dataset is very large(29058165 rows)**
## Steps to reproduce the bug
```python
tokenized_datasets.save_to_disk(
"/pathto/dataset"
)
tokenized_datasets = load_from_disk(
"/pathto/dataset"
)
trainer = Trainer(
model=model,
args=training_args,
train_dataset=tokenized_datasets["train"] if training_args.do_train else None,
eval_dataset=tokenized_datasets["validation"]
if training_args.do_eval
else None,
tokenizer=tokenizer,
data_collator=data_collator,
)
train_result = trainer.train(resume_from_checkpoint=checkpoint)
```
## Expected results
Without the save and reload process, I only need about one day to run the whole script with one A100 card.
## Actual results
```
[INFO|trainer.py:1290] 2022-05-23 22:49:46,266 >> ***** Running training *****
[INFO|trainer.py:1291] 2022-05-23 22:49:46,266 >> Num examples = 29058165
[INFO|trainer.py:1292] 2022-05-23 22:49:46,266 >> Num Epochs = 5
[INFO|trainer.py:1293] 2022-05-23 22:49:46,266 >> Instantaneous batch size per device = 16
[INFO|trainer.py:1294] 2022-05-23 22:49:46,266 >> Total train batch size (w. parallel, distributed & accumulation) = 256
[INFO|trainer.py:1295] 2022-05-23 22:49:46,266 >> Gradient Accumulation steps = 2
[INFO|trainer.py:1296] 2022-05-23 22:49:46,266 >> Total optimization steps = 567540
0%| | 1/567540 [00:09<1544:49:04, 9.80s/it]
0%| | 2/567540 [00:17<1320:00:17, 8.37s/it]
0%| | 3/567540 [00:26<1393:10:17, 8.84s/it]
0%| | 4/567540 [00:34<1344:56:33, 8.53s/it]
0%| | 5/567540 [00:43<1359:36:12, 8.62s/it]
```
## Environment info
```
torch 1.11.0+cu113
torchaudio 0.11.0+cu113
torchvision 0.12.0+cu113
transformers 4.18.0
datasets 2.2.2
``` | {
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```python
from datasets.download.streaming_download_manager import xjoin
path = xjoin("C:\\Users\\USERNAME", "filename.txt")
```
Join path should be:
```python
"C:\\Users\\USERNAME\\filename.txt"
```
However it is:
```python
"C:/Users/USERNAME/filename.txt"
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/4893 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4893/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4893/comments | https://api.github.com/repos/huggingface/datasets/issues/4893/events | https://github.com/huggingface/datasets/issues/4893 | 1,350,655,674 | I_kwDODunzps5QgV66 | 4,893 | Oversampling strategy for iterable datasets in `interleave_datasets` | {
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"Hi @lhoestq,\r\nI plunged into the code and it should be manageable for me to work on it!\r\n#take\r\n\r\nAlso, setting `d1`, `d2` and `d3` as you did raised a `SyntaxError: 'yield' inside list comprehension` for me, on Python 3.8.10.\r\nThe following snippet works for me though:\r\n```\r\nd1 = IterableDataset(Exa... | 2022-08-25T10:06:55Z | 2022-10-03T12:37:46Z | 2022-10-03T12:37:46Z | MEMBER | null | null | null | In https://github.com/huggingface/datasets/pull/4831 @ylacombe added an oversampling strategy for `interleave_datasets`. However right now it doesn't work for datasets loaded using `load_dataset(..., streaming=True)`, which are `IterableDataset` objects.
It would be nice to expand `interleave_datasets` for iterable datasets as well to support this oversampling strategy
```python
>>> from datasets.iterable_dataset import IterableDataset, ExamplesIterable
>>> d1 = IterableDataset(ExamplesIterable(lambda: [(yield i, {"a": i}) for i in [0, 1, 2]], {}))
>>> d2 = IterableDataset(ExamplesIterable(lambda: [(yield i, {"a": i}) for i in [10, 11, 12, 13]], {}))
>>> d3 = IterableDataset(ExamplesIterable(lambda: [(yield i, {"a": i}) for i in [20, 21, 22, 23, 24]], {}))
>>> dataset = interleave_datasets([d1, d2, d3]) # is supported
>>> [x["a"] for x in dataset]
[0, 10, 20, 1, 11, 21, 2, 12, 22]
>>> dataset = interleave_datasets([d1, d2, d3], stopping_strategy="all_exhausted") # is not supported yet
>>> [x["a"] for x in dataset]
[0, 10, 20, 1, 11, 21, 2, 12, 22, 0, 13, 23, 1, 0, 24]
```
This can be implemented by adding the strategy to both `CyclingMultiSourcesExamplesIterable` and `RandomlyCyclingMultiSourcesExamplesIterable` used in `_interleave_iterable_datasets` in `iterable_dataset.py`
I would be happy to share some guidance if anyone would like to give it a shot :) | {
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"Cool thanks :) Feel free to merge if it's all good for you"
] | 2021-12-08T14:58:43Z | 2021-12-14T17:08:42Z | 2021-12-14T17:08:42Z | MEMBER | null | 0 | {
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} | 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. | {
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https://api.github.com/repos/huggingface/datasets/issues/2161 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2161/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2161/comments | https://api.github.com/repos/huggingface/datasets/issues/2161/events | https://github.com/huggingface/datasets/issues/2161 | 849,127,041 | MDU6SXNzdWU4NDkxMjcwNDE= | 2,161 | any possibility to download part of large datasets only? | {
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"Not yet but it’s on the short/mid-term roadmap (requested by many indeed).",
"oh, great, really awesome feature to have, thank you very much for the great, fabulous work",
"We'll work on dataset streaming soon. This should allow you to only load the examples you need ;)",
"thanks a lot Quentin, this would be... | 2021-04-02T10:06:46Z | 2022-10-05T13:26:51Z | 2022-10-05T13:26:51Z | NONE | null | null | null | Hi
Some of the datasets I need like cc100 are very large, and then I wonder if I can download first X samples of the shuffled/unshuffled data without going through first downloading the whole data then sampling? thanks | {
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https://api.github.com/repos/huggingface/datasets/issues/3092 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3092/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3092/comments | https://api.github.com/repos/huggingface/datasets/issues/3092/events | https://github.com/huggingface/datasets/pull/3092 | 1,027,260,383 | PR_kwDODunzps4tPj6e | 3,092 | Fix JNLBA dataset | {
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"Fix #3089.",
"@albertvillanova all tests are passing now. Either you or @lhoestq can review it!"
] | 2021-10-15T09:31:14Z | 2022-07-10T14:36:49Z | 2021-10-22T08:23:57Z | CONTRIBUTOR | null | 0 | {
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} | As mentioned in #3089, I've added more tags and also updated the link for dataset which was earlier using a Google Drive link.
I'm having problem with generating dummy data as `datasets-cli dummy_data ./datasets/jnlpba --auto_generate --match_text_files "*.iob2"` is giving `datasets.keyhash.DuplicatedKeysError: FAILURE TO GENERATE DATASET !
` error. I'll try to add dummy data manually. | {
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https://api.github.com/repos/huggingface/datasets/issues/5495 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5495/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5495/comments | https://api.github.com/repos/huggingface/datasets/issues/5495/events | https://github.com/huggingface/datasets/issues/5495 | 1,566,803,452 | I_kwDODunzps5dY4X8 | 5,495 | to_tf_dataset fails with datetime UTC columns even if not included in columns argument | {
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"descript... | closed | false | null | [] | null | [
"Hi! This is indeed a bug in our zero-copy logic.\r\n\r\nTo fix it, instead of the line:\r\nhttps://github.com/huggingface/datasets/blob/7cfac43b980ab9e4a69c2328f085770996323005/src/datasets/features/features.py#L702\r\n\r\nwe should have:\r\n```python\r\nreturn pa.types.is_primitive(pa_type) and not (pa.types.is_b... | 2023-02-01T20:47:33Z | 2023-02-08T14:33:19Z | 2023-02-08T14:33:19Z | CONTRIBUTOR | null | null | null | ### Describe the bug
There appears to be some eager behavior in `to_tf_dataset` that runs against every column in a dataset even if they aren't included in the columns argument. This is problematic with datetime UTC columns due to them not working with zero copy. If I don't have UTC information in my datetime column, then everything works as expected.
### Steps to reproduce the bug
```python
import numpy as np
import pandas as pd
from datasets import Dataset
df = pd.DataFrame(np.random.rand(2, 1), columns=["x"])
# df["dt"] = pd.to_datetime(["2023-01-01", "2023-01-01"]) # works fine
df["dt"] = pd.to_datetime(["2023-01-01 00:00:00.00000+00:00", "2023-01-01 00:00:00.00000+00:00"])
df.to_parquet("test.pq")
ds = Dataset.from_parquet("test.pq")
tf_ds = ds.to_tf_dataset(columns=["x"], batch_size=2, shuffle=True)
```
```
ArrowInvalid Traceback (most recent call last)
Cell In[1], line 12
8 df.to_parquet("test.pq")
11 ds = Dataset.from_parquet("test.pq")
---> 12 tf_ds = ds.to_tf_dataset(columns=["r"], batch_size=2, shuffle=True)
File ~/venv/lib/python3.8/site-packages/datasets/arrow_dataset.py:411, in TensorflowDatasetMixin.to_tf_dataset(self, batch_size, columns, shuffle, collate_fn, drop_remainder, collate_fn_args, label_cols, prefetch, num_workers)
407 dataset = self
409 # TODO(Matt, QL): deprecate the retention of label_ids and label
--> 411 output_signature, columns_to_np_types = dataset._get_output_signature(
412 dataset,
413 collate_fn=collate_fn,
414 collate_fn_args=collate_fn_args,
415 cols_to_retain=cols_to_retain,
416 batch_size=batch_size if drop_remainder else None,
417 )
419 if "labels" in output_signature:
420 if ("label_ids" in columns or "label" in columns) and "labels" not in columns:
File ~/venv/lib/python3.8/site-packages/datasets/arrow_dataset.py:254, in TensorflowDatasetMixin._get_output_signature(dataset, collate_fn, collate_fn_args, cols_to_retain, batch_size, num_test_batches)
252 for _ in range(num_test_batches):
253 indices = sample(range(len(dataset)), test_batch_size)
--> 254 test_batch = dataset[indices]
255 if cols_to_retain is not None:
256 test_batch = {key: value for key, value in test_batch.items() if key in cols_to_retain}
File ~/venv/lib/python3.8/site-packages/datasets/arrow_dataset.py:2590, in Dataset.__getitem__(self, key)
2588 def __getitem__(self, key): # noqa: F811
2589 """Can be used to index columns (by string names) or rows (by integer index or iterable of indices or bools)."""
-> 2590 return self._getitem(
2591 key,
2592 )
File ~/venv/lib/python3.8/site-packages/datasets/arrow_dataset.py:2575, in Dataset._getitem(self, key, **kwargs)
2573 formatter = get_formatter(format_type, features=self.features, **format_kwargs)
2574 pa_subtable = query_table(self._data, key, indices=self._indices if self._indices is not None else None)
-> 2575 formatted_output = format_table(
2576 pa_subtable, key, formatter=formatter, format_columns=format_columns, output_all_columns=output_all_columns
2577 )
2578 return formatted_output
File ~/venv/lib/python3.8/site-packages/datasets/formatting/formatting.py:634, in format_table(table, key, formatter, format_columns, output_all_columns)
632 python_formatter = PythonFormatter(features=None)
633 if format_columns is None:
--> 634 return formatter(pa_table, query_type=query_type)
635 elif query_type == "column":
636 if key in format_columns:
File ~/venv/lib/python3.8/site-packages/datasets/formatting/formatting.py:410, in Formatter.__call__(self, pa_table, query_type)
408 return self.format_column(pa_table)
409 elif query_type == "batch":
--> 410 return self.format_batch(pa_table)
File ~/venv/lib/python3.8/site-packages/datasets/formatting/np_formatter.py:78, in NumpyFormatter.format_batch(self, pa_table)
77 def format_batch(self, pa_table: pa.Table) -> Mapping:
---> 78 batch = self.numpy_arrow_extractor().extract_batch(pa_table)
79 batch = self.python_features_decoder.decode_batch(batch)
80 batch = self.recursive_tensorize(batch)
File ~/venv/lib/python3.8/site-packages/datasets/formatting/formatting.py:164, in NumpyArrowExtractor.extract_batch(self, pa_table)
163 def extract_batch(self, pa_table: pa.Table) -> dict:
--> 164 return {col: self._arrow_array_to_numpy(pa_table[col]) for col in pa_table.column_names}
File ~/venv/lib/python3.8/site-packages/datasets/formatting/formatting.py:164, in <dictcomp>(.0)
163 def extract_batch(self, pa_table: pa.Table) -> dict:
--> 164 return {col: self._arrow_array_to_numpy(pa_table[col]) for col in pa_table.column_names}
File ~/venv/lib/python3.8/site-packages/datasets/formatting/formatting.py:185, in NumpyArrowExtractor._arrow_array_to_numpy(self, pa_array)
181 else:
182 zero_copy_only = _is_zero_copy_only(pa_array.type) and all(
183 not _is_array_with_nulls(chunk) for chunk in pa_array.chunks
184 )
--> 185 array: List = [
186 row for chunk in pa_array.chunks for row in chunk.to_numpy(zero_copy_only=zero_copy_only)
187 ]
188 else:
189 if isinstance(pa_array.type, _ArrayXDExtensionType):
190 # don't call to_pylist() to preserve dtype of the fixed-size array
File ~/venv/lib/python3.8/site-packages/datasets/formatting/formatting.py:186, in <listcomp>(.0)
181 else:
182 zero_copy_only = _is_zero_copy_only(pa_array.type) and all(
183 not _is_array_with_nulls(chunk) for chunk in pa_array.chunks
184 )
185 array: List = [
--> 186 row for chunk in pa_array.chunks for row in chunk.to_numpy(zero_copy_only=zero_copy_only)
187 ]
188 else:
189 if isinstance(pa_array.type, _ArrayXDExtensionType):
190 # don't call to_pylist() to preserve dtype of the fixed-size array
File ~/venv/lib/python3.8/site-packages/pyarrow/array.pxi:1475, in pyarrow.lib.Array.to_numpy()
File ~/venv/lib/python3.8/site-packages/pyarrow/error.pxi:100, in pyarrow.lib.check_status()
ArrowInvalid: Needed to copy 1 chunks with 0 nulls, but zero_copy_only was True
```
### Expected behavior
I think there are two potential issues/fixes
1. Proper handling of datetime UTC columns (perhaps there is something incorrect with zero copy handling here)
2. Not eagerly running against every column in a dataset when the columns argument of `to_tf_dataset` specifies a subset of columns (although I'm not sure if this is unavoidable)
### Environment info
- `datasets` version: 2.9.0
- Platform: macOS-13.2-x86_64-i386-64bit
- Python version: 3.8.12
- PyArrow version: 11.0.0
- Pandas version: 1.5.3
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https://api.github.com/repos/huggingface/datasets/issues/3961 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3961/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3961/comments | https://api.github.com/repos/huggingface/datasets/issues/3961/events | https://github.com/huggingface/datasets/issues/3961 | 1,173,223,086 | I_kwDODunzps5F7fau | 3,961 | Scores from Index at extra positions are not filtered out | {
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"Hi! Yes, that makes sense! Would you like to submit a PR to fix this?",
"Created PR https://github.com/huggingface/datasets/pull/3971"
] | 2022-03-18T06:13:23Z | 2022-04-12T14:41:58Z | 2022-04-12T14:41:58Z | CONTRIBUTOR | null | null | null | If a FAISS index has fewer records than the requested number of top results (k), then it returns -1 in indices for the additional positions. The get_nearest_examples method only filters out the extra results from the dataset samples. It would be better to filter out extra scores too.
Reference: https://github.com/huggingface/datasets/blob/2.0.0/src/datasets/search.py#L693
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https://api.github.com/repos/huggingface/datasets/issues/3995 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3995/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3995/comments | https://api.github.com/repos/huggingface/datasets/issues/3995/events | https://github.com/huggingface/datasets/pull/3995 | 1,178,232,623 | PR_kwDODunzps404054 | 3,995 | Close `PIL.Image` file handler in `Image.decode_example` | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-03-23T14:51:48Z | 2022-03-23T18:24:52Z | 2022-03-23T18:19:27Z | CONTRIBUTOR | null | 0 | {
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} | Closes the file handler of the PIL image object in `Image.decode_example` to avoid the `Too many open files` error.
To pass [the image equality checks](https://app.circleci.com/pipelines/github/huggingface/datasets/10774/workflows/d56670e6-16bb-4c64-b601-a152c5acf5ed/jobs/65825) in CI, `Image.decode_example` calls `image.load()` regardless of how the image object is created (not only for the `PIL.Image.open(local_path)` case). This is needed because `load()` sets the `readonly` attribute of a `PIL.Image` object to 0 (it's 1 after `PIL.Image.open(file_like)`), and in the older PIL versions (only fixed on main), that attribute is considered in `PIL.Image.__eq__`. More info can be found here: https://github.com/python-pillow/Pillow/issues/5926.
Fix #3985
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https://api.github.com/repos/huggingface/datasets/issues/4921 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4921/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4921/comments | https://api.github.com/repos/huggingface/datasets/issues/4921/events | https://github.com/huggingface/datasets/pull/4921 | 1,357,609,003 | PR_kwDODunzps4-JVFV | 4,921 | Fix missing tags in dataset cards | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-08-31T16:52:27Z | 2022-09-22T14:34:11Z | 2022-09-01T05:04:53Z | MEMBER | null | 0 | {
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} | Fix missing tags in dataset cards:
- eraser_multi_rc
- hotpot_qa
- metooma
- movie_rationales
- qanta
- quora
- quoref
- race
- ted_hrlr
- ted_talks_iwslt
This PR partially fixes the missing tags in dataset cards. Subsequent PRs will follow to complete this task.
Related to:
- #4833
- #4891
- #4896
- #4908 | {
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https://api.github.com/repos/huggingface/datasets/issues/5254 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5254/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5254/comments | https://api.github.com/repos/huggingface/datasets/issues/5254/events | https://github.com/huggingface/datasets/pull/5254 | 1,452,600,088 | PR_kwDODunzps5DE47u | 5,254 | typo | {
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https://api.github.com/repos/huggingface/datasets/issues/4662 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4662/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4662/comments | https://api.github.com/repos/huggingface/datasets/issues/4662/events | https://github.com/huggingface/datasets/pull/4662 | 1,298,845,369 | PR_kwDODunzps47GTEc | 4,662 | Fix: conll2003 - fix empty example | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-07-08T10:49:13Z | 2022-07-08T14:14:53Z | 2022-07-08T14:02:42Z | MEMBER | null | 0 | {
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} | As reported in https://huggingface.co/datasets/conll2003/discussions/2#62c45a14f93fc97e8260532f, there was an extra empty example at the end of the dataset | {
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https://api.github.com/repos/huggingface/datasets/issues/2136 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2136/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2136/comments | https://api.github.com/repos/huggingface/datasets/issues/2136/events | https://github.com/huggingface/datasets/pull/2136 | 843,492,015 | MDExOlB1bGxSZXF1ZXN0NjAyODY0ODY5 | 2,136 | fix dialogue action slot name and value | {
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https://api.github.com/repos/huggingface/datasets/issues/1587 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1587/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1587/comments | https://api.github.com/repos/huggingface/datasets/issues/1587/events | https://github.com/huggingface/datasets/pull/1587 | 768,929,877 | MDExOlB1bGxSZXF1ZXN0NTQxMjAwMDk3 | 1,587 | Add nq_open question answering dataset | {
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"@SBrandeis all checks passing"
] | 2020-12-16T14:22:08Z | 2020-12-17T16:07:10Z | 2020-12-17T16:07:10Z | CONTRIBUTOR | null | 0 | {
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} | this is pr is a copy of #1506 due to messed up git history in that pr. | {
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https://api.github.com/repos/huggingface/datasets/issues/1798 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1798/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1798/comments | https://api.github.com/repos/huggingface/datasets/issues/1798/events | https://github.com/huggingface/datasets/pull/1798 | 797,766,818 | MDExOlB1bGxSZXF1ZXN0NTY0Njk2NjE1 | 1,798 | Add Arabic sarcasm dataset | {
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"@lhoestq thanks for the comments - I believe these are now addressed. I re-generated the datasets_info.json and dummy data"
] | 2021-01-31T17:38:55Z | 2021-02-10T20:39:13Z | 2021-02-03T10:35:54Z | CONTRIBUTOR | null | 0 | {
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} | This MIT license dataset: https://github.com/iabufarha/ArSarcasm
Via https://sites.google.com/view/ar-sarcasm-sentiment-detection/ | {
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https://api.github.com/repos/huggingface/datasets/issues/4721 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4721/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4721/comments | https://api.github.com/repos/huggingface/datasets/issues/4721/events | https://github.com/huggingface/datasets/issues/4721 | 1,310,253,552 | I_kwDODunzps5OGOHw | 4,721 | PyArrow Dataset error when calling `load_dataset` | {
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"Hi ! It looks like a bug in `pyarrow`. If you manage to end up with only one chunk per parquet file it should workaround this issue.\r\n\r\nTo achieve that you can try to lower the value of `max_shard_size` and also don't use `map` before `push_to_hub`.\r\n\r\nDo you have a minimum reproducible example that we can... | 2022-07-20T01:16:03Z | 2022-07-22T14:11:47Z | null | NONE | null | null | null | ## Describe the bug
I am fine tuning a wav2vec2 model following the script here using my own dataset: https://github.com/huggingface/transformers/blob/main/examples/pytorch/speech-recognition/run_speech_recognition_ctc.py
Loading my Audio dataset from the hub which was originally generated from disk results in the following PyArrow error:
```sh
File "/home/ubuntu/w2v2/run_speech_recognition_ctc.py", line 227, in main
raw_datasets = load_dataset(
File "/home/ubuntu/.virtualenvs/meval/lib/python3.8/site-packages/datasets/load.py", line 1679, in load_dataset
builder_instance.download_and_prepare(
File "/home/ubuntu/.virtualenvs/meval/lib/python3.8/site-packages/datasets/builder.py", line 704, in download_and_prepare
self._download_and_prepare(
File "/home/ubuntu/.virtualenvs/meval/lib/python3.8/site-packages/datasets/builder.py", line 793, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/home/ubuntu/.virtualenvs/meval/lib/python3.8/site-packages/datasets/builder.py", line 1268, in _prepare_split
for key, table in logging.tqdm(
File "/home/ubuntu/.virtualenvs/meval/lib/python3.8/site-packages/tqdm/std.py", line 1195, in __iter__
for obj in iterable:
File "/home/ubuntu/.virtualenvs/meval/lib/python3.8/site-packages/datasets/packaged_modules/parquet/parquet.py", line 68, in _generate_tables
for batch_idx, record_batch in enumerate(
File "pyarrow/_parquet.pyx", line 1309, in iter_batches
File "pyarrow/error.pxi", line 121, in pyarrow.lib.check_status
pyarrow.lib.ArrowNotImplementedError: Nested data conversions not implemented for chunked array outputs
```
## Steps to reproduce the bug
I created a dataset from a JSON lines manifest of `audio_filepath`, `text`, and `duration`.
When creating the dataset, I do something like this:
```python
import json
from datasets import Dataset, Audio
# manifest_lines is a list of dicts w/ "audio_filepath", "duration", and "text
for line in manifest_lines:
line = line.strip()
if line:
line_dict = json.loads(line)
manifest_dict["audio"].append(f"{root_path}/{line_dict['audio_filepath']}")
manifest_dict["duration"].append(line_dict["duration"])
manifest_dict["transcription"].append(line_dict["text"])
# Create a HF dataset
dataset = Dataset.from_dict(manifest_dict).cast_column(
"audio", Audio(sampling_rate=16_000),
)
# From the docs for saving to disk
# https://huggingface.co/docs/datasets/v2.3.2/en/package_reference/main_classes#datasets.Dataset.save_to_disk
def read_audio_file(example):
with open(example["audio"]["path"], "rb") as f:
return {"audio": {"bytes": f.read()}}
dataset = dataset.map(read_audio_file, num_proc=70)
dataset.save_to_disk(f"/audio-data/hf/{artifact_name}")
dataset.push_to_hub(f"{org-name}/{artifact_name}", max_shard_size="5GB", private=True)
```
Then when I call `load_dataset()` in my training script, with the same dataset I generated above, and download from the huggingface hub I get the above stack trace.
I am able to load the dataset fine if I use `load_from_disk()`.
## Expected results
`load_dataset()` should behave just like `load_from_disk()` and not cause any errors.
## Actual results
See above
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
I am using the `huggingface/transformers-pytorch-gpu:latest` image
- `datasets` version: 2.3.0
- Platform: Docker/Ubuntu 20.04
- Python version: 3.8
- PyArrow version: 8.0.0
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https://api.github.com/repos/huggingface/datasets/issues/1973 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1973/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1973/comments | https://api.github.com/repos/huggingface/datasets/issues/1973/events | https://github.com/huggingface/datasets/issues/1973 | 820,077,312 | MDU6SXNzdWU4MjAwNzczMTI= | 1,973 | Question: what gets stored in the datasets cache and why is it so huge? | {
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"Echo'ing this observation: I have a few datasets in the neighborhood of 2GB CSVs uncompressed, and when I use something like `Dataset.save_to_disk()` it's ~18GB on disk.\r\n\r\nIf this is unexpected behavior, would be happy to help run debugging as needed.",
"Thanks @ioana-blue for pointing out this problem (and... | 2021-03-02T14:35:53Z | 2021-03-30T14:03:59Z | 2021-03-16T09:44:00Z | NONE | null | null | null | I'm running several training jobs (around 10) with a relatively large dataset (3M samples). The datasets cache reached 178G and it seems really large. What is it stored in there and why is it so large? I don't think I noticed this problem before and seems to be related to the new version of the datasets library. Any insight? Thank you! | {
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https://api.github.com/repos/huggingface/datasets/issues/5978 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5978/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5978/comments | https://api.github.com/repos/huggingface/datasets/issues/5978/events | https://github.com/huggingface/datasets/pull/5978 | 1,770,187,053 | PR_kwDODunzps5Tru2_ | 5,978 | Release: 2.13.1 | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | rea... | 2023-06-22T18:23:11Z | 2023-06-22T18:40:24Z | 2023-06-22T18:30:16Z | MEMBER | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/3928 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3928/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3928/comments | https://api.github.com/repos/huggingface/datasets/issues/3928/events | https://github.com/huggingface/datasets/issues/3928 | 1,170,017,132 | I_kwDODunzps5FvQts | 3,928 | Frugal score deprecations | {
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"Hi @Ierezell, thanks for reporting.\r\n\r\nI'm making a PR to suppress those logs from the terminal. "
] | 2022-03-15T18:10:42Z | 2022-03-17T08:37:24Z | 2022-03-17T08:37:24Z | NONE | null | null | null | ## Describe the bug
The frugal score returns a really verbose output with warnings that can be easily changed.
## Steps to reproduce the bug
```python
# Sample code to reproduce the bug
from datasets.load import load_metric
frugal = load_metric("frugalscore")
frugal.compute(predictions=["Do you like spinachis"], references=["Do you like spinach"])
```
## Expected results
A clear and concise description of the expected results.
```
{'scores': [0.9946]}
```
## Actual results
Specify the actual results or traceback.
```
PyTorch: setting up devices
The default value for the training argument `--report_to` will change in v5 (from all installed integrations to none). In v5, you will need to use `--report_to all` to get the same behavior as now. You should start updating your code and make this info disappear :-).
100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 864.09ba/s]
Using amp half precision backend
The following columns in the test set don't have a corresponding argument in `BertForSequenceClassification.forward` and have been ignored: sentence2, sentence1. If sentence2, sentence1 are not expected by `BertForSequenceClassification.forward`, you can safely ignore this message.
***** Running Prediction *****
Num examples = 1
Batch size = 64
100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 4644.85it/s]
{'scores': [0.9946]}
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.17.0
- Platform: Linux-5.13.0-30-generic-x86_64-with-glibc2.29
- Python version: 3.8.10
- PyArrow version: 7.0.0
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https://api.github.com/repos/huggingface/datasets/issues/3039 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3039/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3039/comments | https://api.github.com/repos/huggingface/datasets/issues/3039/events | https://github.com/huggingface/datasets/pull/3039 | 1,018,219,800 | PR_kwDODunzps4sy_J- | 3,039 | Add sberquad dataset | {
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https://api.github.com/repos/huggingface/datasets/issues/5856 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5856/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5856/comments | https://api.github.com/repos/huggingface/datasets/issues/5856/events | https://github.com/huggingface/datasets/issues/5856 | 1,709,218,242 | I_kwDODunzps5l4JnC | 5,856 | Error loading natural_questions | {
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"Hi! You can avoid this error by using the preprocessed version:\r\n```python\r\nimport datasets\r\nds = datasets.load_dataset('natural_questions')\r\n```\r\n\r\nPS: Once we finish https://github.com/huggingface/datasets/pull/5364, this error will no longer be a problem.",
"> Hi! You can avoid this error by using... | 2023-05-15T02:46:04Z | 2023-06-05T09:11:19Z | 2023-06-05T09:11:18Z | NONE | null | null | null | ### Describe the bug
When try to load natural_questions through datasets == 2.12.0 with python == 3.8.9:
```python
import datasets
datasets.load_dataset('natural_questions',beam_runner='DirectRunner')
```
It failed with following info:
`pyarrow.lib.ArrowNotImplementedError: Nested data conversions not implemented for chunked array outputs`
### Steps to reproduce the bug
In python console:
```python
import datasets
datasets.load_dataset('natural_questions',beam_runner='DirectRunner')
```
Then the trace is:
```
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/nlp/.cache/pypoetry/virtualenvs/drg-W3LF4Ol9-py3.8/lib/python3.8/site-packages/datasets/load.py", line 1797, in load_dataset
builder_instance.download_and_prepare(
File "/home/nlp/.cache/pypoetry/virtualenvs/drg-W3LF4Ol9-py3.8/lib/python3.8/site-packages/datasets/builder.py", line 890, in download_and_prepare
self._download_and_prepare(
File "/home/nlp/.cache/pypoetry/virtualenvs/drg-W3LF4Ol9-py3.8/lib/python3.8/site-packages/datasets/builder.py", line 2019, in _download_and_prepare
num_examples, num_bytes = beam_writer.finalize(metrics.query(m_filter))
File "/home/nlp/.cache/pypoetry/virtualenvs/drg-W3LF4Ol9-py3.8/lib/python3.8/site-packages/datasets/arrow_writer.py", line 694, in finalize
shard_num_bytes, _ = parquet_to_arrow(source, destination)
File "/home/nlp/.cache/pypoetry/virtualenvs/drg-W3LF4Ol9-py3.8/lib/python3.8/site-packages/datasets/arrow_writer.py", line 737, in parquet_to_arrow
for record_batch in parquet_file.iter_batches():
File "pyarrow/_parquet.pyx", line 1323, in iter_batches
File "pyarrow/error.pxi", line 121, in pyarrow.lib.check_status
pyarrow.lib.ArrowNotImplementedError: Nested data conversions not implemented for chunked array outputs
```
### Expected behavior
load natural_question questions
### Environment info
```
- `datasets` version: 2.12.0
- Platform: Linux-3.10.0-1160.42.2.el7.x86_64-x86_64-with-glibc2.2.5
- Python version: 3.8.9
- Huggingface_hub version: 0.14.1
- PyArrow version: 11.0.0
- Pandas version: 2.0.1
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/6055 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6055/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6055/comments | https://api.github.com/repos/huggingface/datasets/issues/6055/events | https://github.com/huggingface/datasets/issues/6055 | 1,813,524,145 | I_kwDODunzps5sGC6x | 6,055 | Fix host URL in The Pile datasets | {
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} | [] | open | false | null | [] | null | [] | 2023-07-20T09:08:52Z | 2023-07-20T09:09:37Z | null | NONE | null | null | null | ### Describe the bug
In #3627 and #5543, you tried to fix the host URL in The Pile datasets. But both URLs are not working now:
`HTTPError: 404 Client Error: Not Found for URL: https://the-eye.eu/public/AI/pile_preliminary_components/PUBMED_title_abstracts_2019_baseline.jsonl.zst`
And
`ConnectTimeout: HTTPSConnectionPool(host='mystic.the-eye.eu', port=443): Max retries exceeded with url: /public/AI/pile_preliminary_components/PUBMED_title_abstracts_2019_baseline.jsonl.zst (Caused by ConnectTimeoutError(, 'Connection to mystic.the-eye.eu timed out. (connect timeout=10.0)'))`
### Steps to reproduce the bug
```
from datasets import load_dataset
# This takes a few minutes to run, so go grab a tea or coffee while you wait :)
data_files = "https://mystic.the-eye.eu/public/AI/pile_preliminary_components/PUBMED_title_abstracts_2019_baseline.jsonl.zst"
pubmed_dataset = load_dataset("json", data_files=data_files, split="train")
pubmed_dataset
```
Result:
`ConnectTimeout: HTTPSConnectionPool(host='mystic.the-eye.eu', port=443): Max retries exceeded with url: /public/AI/pile_preliminary_components/PUBMED_title_abstracts_2019_baseline.jsonl.zst (Caused by ConnectTimeoutError(, 'Connection to mystic.the-eye.eu timed out. (connect timeout=10.0)'))`
And
```
from datasets import load_dataset
# This takes a few minutes to run, so go grab a tea or coffee while you wait :)
data_files = "https://the-eye.eu/public/AI/pile_preliminary_components/PUBMED_title_abstracts_2019_baseline.jsonl.zst"
pubmed_dataset = load_dataset("json", data_files=data_files, split="train")
pubmed_dataset
```
Result:
`HTTPError: 404 Client Error: Not Found for URL: https://the-eye.eu/public/AI/pile_preliminary_components/PUBMED_title_abstracts_2019_baseline.jsonl.zst`
### Expected behavior
Downloading as normal.
### Environment info
Environment info
`datasets` version: 2.9.0
Platform: Windows
Python version: 3.9.13
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https://api.github.com/repos/huggingface/datasets/issues/4105 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4105/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4105/comments | https://api.github.com/repos/huggingface/datasets/issues/4105/events | https://github.com/huggingface/datasets/issues/4105 | 1,194,297,119 | I_kwDODunzps5HL4cf | 4,105 | push to hub fails with huggingface-hub 0.5.0 | {
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] | closed | false | null | [] | null | [
"Hi ! Indeed there was a breaking change in `huggingface_hub` 0.5.0 in `HfApi.create_repo`, which is called here in `datasets` by passing the org name in both the `repo_id` and the `organization` arguments:\r\n\r\nhttps://github.com/huggingface/datasets/blob/2230f7f7d7fbaf102cff356f5a8f3bd1561bea43/src/datasets/arr... | 2022-04-06T08:59:57Z | 2022-04-13T14:30:47Z | 2022-04-13T14:30:47Z | NONE | null | null | null | ## Describe the bug
`ds.push_to_hub` is failing when updating a dataset in the form "org_id/repo_id"
## Steps to reproduce the bug
```python
from datasets import load_dataset
ds = load_dataset("rubrix/news_test")
ds.push_to_hub("<your-user>/news_test", token="<your-token>")
```
## Expected results
The dataset is successfully uploaded
## Actual results
An error validation is raised:
```bash
if repo_id and (name or organization):
> raise ValueError(
"Only pass `repo_id` and leave deprecated `name` and "
"`organization` to be None."
E ValueError: Only pass `repo_id` and leave deprecated `name` and `organization` to be None.
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.18.1
- `huggingface-hub`: 0.5
- Platform: macOS
- Python version: 3.8.12
- PyArrow version: 6.0.0
cc @adrinjalali
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https://api.github.com/repos/huggingface/datasets/issues/1844 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1844/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1844/comments | https://api.github.com/repos/huggingface/datasets/issues/1844/events | https://github.com/huggingface/datasets/issues/1844 | 803,588,125 | MDU6SXNzdWU4MDM1ODgxMjU= | 1,844 | Update Open Subtitles corpus with original sentence IDs | {
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"Hi ! You're right this can can useful.\r\nThis should be easy to add, so feel free to give it a try if you want to contribute :)\r\nI think we just need to add it to the _generate_examples method of the OpenSubtitles dataset builder [here](https://github.com/huggingface/datasets/blob/master/datasets/open_subtitles... | 2021-02-08T13:55:13Z | 2021-02-12T17:38:58Z | 2021-02-12T17:38:58Z | CONTRIBUTOR | null | null | null | Hi! It would be great if you could add the original sentence ids to [Open Subtitles](https://huggingface.co/datasets/open_subtitles).
I can think of two reasons: first, it's possible to gather sentences for an entire document (the original ids contain media id, subtitle file id and sentence id), therefore somewhat allowing for document-level machine translation (and other document-level stuff which could be cool to have); second, it's possible to have parallel sentences in multiple languages, as they share the same ids across bitexts.
I think I should tag @abhishekkrthakur as he's the one who added it in the first place.
Thanks! | {
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https://api.github.com/repos/huggingface/datasets/issues/3705 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3705/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3705/comments | https://api.github.com/repos/huggingface/datasets/issues/3705/events | https://github.com/huggingface/datasets/pull/3705 | 1,132,053,226 | PR_kwDODunzps4yfhyj | 3,705 | Raise informative error when loading a save_to_disk dataset | {
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} | [] | closed | false | null | [] | null | [] | 2022-02-11T08:21:03Z | 2022-02-11T22:56:40Z | 2022-02-11T22:56:39Z | MEMBER | null | 0 | {
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} | People recurrently report error when trying to load a dataset (using `load_dataset`) that was previously saved using `save_to_disk`.
This PR raises an informative error message telling them they should use `load_from_disk` instead.
Close #3700. | {
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https://api.github.com/repos/huggingface/datasets/issues/2367 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2367/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2367/comments | https://api.github.com/repos/huggingface/datasets/issues/2367/events | https://github.com/huggingface/datasets/pull/2367 | 893,317,427 | MDExOlB1bGxSZXF1ZXN0NjQ1ODUxNTE0 | 2,367 | Remove getchildren from hyperpartisan news detection | {
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} | `Element.getchildren()` is now deprecated in the ElementTree library (I think in python 3.9, so it still passes the automated tests which are using 3.6. But for those of us on bleeding-edge distros it now fails).
https://bugs.python.org/issue29209 | {
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https://api.github.com/repos/huggingface/datasets/issues/3899 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3899/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3899/comments | https://api.github.com/repos/huggingface/datasets/issues/3899/events | https://github.com/huggingface/datasets/pull/3899 | 1,166,931,812 | PR_kwDODunzps40UzR3 | 3,899 | Add exact match metric | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-03-11T22:21:40Z | 2022-03-21T16:10:03Z | 2022-03-21T16:05:35Z | CONTRIBUTOR | null | 0 | {
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Note: Some of the tests have failed, but I wanted to make a PR anyway so that the rest of the code can be reviewed if anyone has time. I'll look into + work on fixing the failed tests when I'm back online after the weekend | {
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https://api.github.com/repos/huggingface/datasets/issues/3618 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3618/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3618/comments | https://api.github.com/repos/huggingface/datasets/issues/3618/events | https://github.com/huggingface/datasets/issues/3618 | 1,112,123,365 | I_kwDODunzps5CSafl | 3,618 | TIMIT Dataset not working with GPU | {
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"Hi ! I think you should avoid calling `timit_train['audio']`. Indeed by doing so you're **loading all the audio column in memory**. This is problematic in your case because the TIMIT dataset is huge.\r\n\r\nIf you want to access the audio data of some samples, you should do this instead `timit_train[:10][\"train\"... | 2022-01-24T03:26:03Z | 2023-07-25T15:20:20Z | 2023-07-25T15:20:20Z | NONE | null | null | null | ## Describe the bug
I am working trying to use the TIMIT dataset in order to fine-tune Wav2Vec2 model and I am unable to load the "audio" column from the dataset when working with a GPU.
I am working on Amazon Sagemaker Studio, on the Python 3 (PyTorch 1.8 Python 3.6 GPU Optimized) environment, with a single ml.g4dn.xlarge instance (corresponds to a Tesla T4 GPU).
I don't know if the issue is GPU related or Python environment related because everything works when I work off of the CPU Optimized environment with a non-GPU instance. My code also works on Google Colab with a GPU instance.
This issue is blocking because I cannot get the 'audio' column in any way due to this error, which means that I can't pass it to any functions. I later use the dataset.map function and that is where I originally noticed this error.
## Steps to reproduce the bug
```python
from datasets import load_dataset
timit_train = load_dataset('timit_asr', split='train')
print(timit_train['audio'])
```
## Expected results
Expected to see inside the 'audio' column, which contains an 'array' nested field with the array data I actually need.
## Actual results
Traceback
```
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-6-ceeac555e921> in <module>
----> 1 timit_train['audio']
/opt/conda/lib/python3.6/site-packages/datasets/arrow_dataset.py in __getitem__(self, key)
1917 """Can be used to index columns (by string names) or rows (by integer index or iterable of indices or bools)."""
1918 return self._getitem(
-> 1919 key,
1920 )
1921
/opt/conda/lib/python3.6/site-packages/datasets/arrow_dataset.py in _getitem(self, key, decoded, **kwargs)
1902 pa_subtable = query_table(self._data, key, indices=self._indices if self._indices is not None else None)
1903 formatted_output = format_table(
-> 1904 pa_subtable, key, formatter=formatter, format_columns=format_columns, output_all_columns=output_all_columns
1905 )
1906 return formatted_output
/opt/conda/lib/python3.6/site-packages/datasets/formatting/formatting.py in format_table(table, key, formatter, format_columns, output_all_columns)
529 python_formatter = PythonFormatter(features=None)
530 if format_columns is None:
--> 531 return formatter(pa_table, query_type=query_type)
532 elif query_type == "column":
533 if key in format_columns:
/opt/conda/lib/python3.6/site-packages/datasets/formatting/formatting.py in __call__(self, pa_table, query_type)
280 return self.format_row(pa_table)
281 elif query_type == "column":
--> 282 return self.format_column(pa_table)
283 elif query_type == "batch":
284 return self.format_batch(pa_table)
/opt/conda/lib/python3.6/site-packages/datasets/formatting/formatting.py in format_column(self, pa_table)
315 column = self.python_arrow_extractor().extract_column(pa_table)
316 if self.decoded:
--> 317 column = self.python_features_decoder.decode_column(column, pa_table.column_names[0])
318 return column
319
/opt/conda/lib/python3.6/site-packages/datasets/formatting/formatting.py in decode_column(self, column, column_name)
221
222 def decode_column(self, column: list, column_name: str) -> list:
--> 223 return self.features.decode_column(column, column_name) if self.features else column
224
225 def decode_batch(self, batch: dict) -> dict:
/opt/conda/lib/python3.6/site-packages/datasets/features/features.py in decode_column(self, column, column_name)
1337 return (
1338 [self[column_name].decode_example(value) if value is not None else None for value in column]
-> 1339 if self._column_requires_decoding[column_name]
1340 else column
1341 )
/opt/conda/lib/python3.6/site-packages/datasets/features/features.py in <listcomp>(.0)
1336 """
1337 return (
-> 1338 [self[column_name].decode_example(value) if value is not None else None for value in column]
1339 if self._column_requires_decoding[column_name]
1340 else column
/opt/conda/lib/python3.6/site-packages/datasets/features/audio.py in decode_example(self, value)
85 dict
86 """
---> 87 path, file = (value["path"], BytesIO(value["bytes"])) if value["bytes"] is not None else (value["path"], None)
88 if path is None and file is None:
89 raise ValueError(f"An audio sample should have one of 'path' or 'bytes' but both are None in {value}.")
TypeError: string indices must be integers
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.18.0
- Platform: Linux-4.14.256-197.484.amzn2.x86_64-x86_64-with-debian-buster-sid
- Python version: 3.6.13
- PyArrow version: 6.0.1
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https://api.github.com/repos/huggingface/datasets/issues/5151 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5151/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5151/comments | https://api.github.com/repos/huggingface/datasets/issues/5151/events | https://github.com/huggingface/datasets/issues/5151 | 1,420,791,163 | I_kwDODunzps5Ur417 | 5,151 | Add support to create different configs with `push_to_hub` (+ inferring configs from directories with package managers?) | {
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"also asked in https://discuss.huggingface.co/t/create-multiple-dataset-configs-with-push-to-hub-method/25480"
] | 2022-10-24T12:59:18Z | 2022-11-04T14:55:20Z | null | CONTRIBUTOR | null | null | null | Now one can push only different splits within one default config of a dataset.
Would be nice to allow something like:
```
ds.push_to_hub(repo_name, config=config_name)
```
I'm not sure, but this will probably require changes in `data_files.py` patterns. If so, it would also allow to create different configs for packaged modules datasets.
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"What's the issue exactly ?\r\n\r\nGiven an `upstream` remote repository with url `https://github.com/huggingface/datasets.git`, you can totally rebase from `upstream/master`.\r\n\r\nIt's mentioned at the beginning how to add the `upstream` remote repository\r\n\r\nhttps://github.com/huggingface/datasets/blob/987df... | 2021-03-09T09:48:55Z | 2021-03-09T11:33:31Z | 2021-03-09T11:33:31Z | CONTRIBUTOR | null | null | null | Feels like the documentation on adding a new dataset is outdated?
https://github.com/huggingface/datasets/blob/987df6b4e9e20fc0c92bc9df48137d170756fd7b/ADD_NEW_DATASET.md#L49-L54
There is no upstream branch on remote. | {
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https://api.github.com/repos/huggingface/datasets/issues/3673 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3673/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3673/comments | https://api.github.com/repos/huggingface/datasets/issues/3673/events | https://github.com/huggingface/datasets/issues/3673 | 1,123,010,520 | I_kwDODunzps5C78fY | 3,673 | `load_dataset("snli")` is different from dataset viewer | {
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"Yes, we decided to replace the encoded label with the corresponding label when possible in the dataset viewer. But\r\n1. maybe it's the wrong default\r\n2. we could find a way to show both (with a switch, or showing both ie. `0 (neutral)`).\r\n",
"Hi @severo,\r\n\r\nThanks for clarifying. \r\n\r\nI think this de... | 2022-02-03T12:10:43Z | 2022-02-16T11:22:31Z | 2022-02-11T17:01:21Z | NONE | null | null | null | ## Describe the bug
The dataset that is downloaded from the Hub via `load_dataset("snli")` is different from what is available in the dataset viewer. In the viewer the labels are not encoded (i.e., "neutral", "entailment", "contradiction"), while the downloaded dataset shows the encoded labels (i.e., 0, 1, 2).
Is this expected?
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version:
- Platform: Ubuntu 20.4
- Python version: 3.7
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https://api.github.com/repos/huggingface/datasets/issues/1817 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1817/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1817/comments | https://api.github.com/repos/huggingface/datasets/issues/1817/events | https://github.com/huggingface/datasets/issues/1817 | 800,870,652 | MDU6SXNzdWU4MDA4NzA2NTI= | 1,817 | pyarrow.lib.ArrowInvalid: Column 1 named input_ids expected length 599 but got length 1500 | {
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"Hi !\r\nThe error you have is due to the `input_ids` column not having the same number of examples as the other columns.\r\nIndeed you're concatenating the `input_ids` at this line:\r\n\r\nhttps://github.com/LuCeHe/GenericTools/blob/431835d8e13ec24dceb5ee4dc4ae58f0e873b091/KerasTools/lm_preprocessing.py#L134\r\n\r... | 2021-02-04T02:30:23Z | 2022-10-05T12:42:57Z | 2022-10-05T12:42:57Z | NONE | null | null | null | I am trying to preprocess any dataset in this package with GPT-2 tokenizer, so I need to structure the datasets as long sequences of text without padding. I've been following a couple of your tutorials and here you can find the script that is failing right at the end
https://github.com/LuCeHe/GenericTools/blob/master/KerasTools/lm_preprocessing.py
In the last iteration of the last dset.map, it gives the error that I copied in the title. Another issue that I have, if I leave the batch_size set as 1000 in the last .map, I'm afraid it's going to lose most text, so I'm considering setting both writer_batch_size and batch_size to 300 K, but I'm not sure it's the best way to go.
Can you help me?
Thanks! | {
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} | Updating license with appropriate capitalization & a link.
Updating Personal and Sensitive Information to address PII concern. | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5364). All of your documentation changes will be reflected on that endpoint.",
"Deleting `BeamPipeline` and `upload_local_to_remote` would break the existing Beam scripts, so I reverted this change.\r\n\r\nFrom what I understan... | 2022-12-15T12:38:05Z | 2023-01-25T15:49:25Z | null | CONTRIBUTOR | null | 1 | {
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https://api.github.com/repos/huggingface/datasets/issues/3931 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3931/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3931/comments | https://api.github.com/repos/huggingface/datasets/issues/3931/events | https://github.com/huggingface/datasets/pull/3931 | 1,170,097,208 | PR_kwDODunzps40fBjx | 3,931 | Add align_labels_with_mapping docs | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-03-15T19:24:57Z | 2022-03-18T16:28:31Z | 2022-03-18T16:24:33Z | MEMBER | null | 0 | {
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} | This PR documents the `align_labels_with_mapping` function to ensure predicted labels are aligned with the dataset, or to assign a different mapping of labels to ids (requested by @mariosasko 🎉 ).
For this specific code sample, the current dataset has a `mixed` label that the original [dataset](https://huggingface.co/datasets/poem_sentiment#data-fields) didn't. Is there a way to remove this label so it is completely aligned with the original dataset mappings? Otherwise, I'll just leave it as it is. | {
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https://api.github.com/repos/huggingface/datasets/issues/1650 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1650/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1650/comments | https://api.github.com/repos/huggingface/datasets/issues/1650/events | https://github.com/huggingface/datasets/pull/1650 | 775,545,912 | MDExOlB1bGxSZXF1ZXN0NTQ2MjA0MzYy | 1,650 | Update README.md | {
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https://api.github.com/repos/huggingface/datasets/issues/5196 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5196/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5196/comments | https://api.github.com/repos/huggingface/datasets/issues/5196/events | https://github.com/huggingface/datasets/pull/5196 | 1,434,401,646 | PR_kwDODunzps5CH439 | 5,196 | Use hfh hf_hub_url function | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5196). All of your documentation changes will be reflected on that endpoint.",
"@lhoestq I think we should first agree if `datasets` can introduce the breaking change of ignoring `config.HUB_DATASETS_URL`: some users may have o... | 2022-11-03T10:08:09Z | 2022-12-06T11:38:17Z | 2022-11-09T07:15:12Z | MEMBER | null | 0 | {
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} | Small refactoring to use `hf_hub_url` function from `huggingface_hub`.
This PR also creates the `hub` module that will contain all `huggingface_hub` functionalities relevant to `datasets`.
This is a necessary stage before implementing the use of the `hfh` caching system (which uses its `hf_hub_url` under the hood).
EDIT:
~~Finally, we use our `config.HUB_DATASETS_URL` when using `hfh.hf_hub_url`~~
There is a breaking change: the `hfh` `hf_hub_url` function uses
- `hfh` `HUGGINGFACE_CO_URL_TEMPLATE` URL template, different from the `datasets` `config.HUB_DATASETS_URL`
- also, `hfh` `DEFAULT_REVISION`, instead of `datasets` `config.HUB_DEFAULT_VERSION` | {
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https://api.github.com/repos/huggingface/datasets/issues/4057 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4057/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4057/comments | https://api.github.com/repos/huggingface/datasets/issues/4057/events | https://github.com/huggingface/datasets/issues/4057 | 1,185,442,001 | I_kwDODunzps5GqGjR | 4,057 | `load_dataset` consumes too much memory for audio + tar archives | {
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"Hi ! Could it be because you need to free the memory used by `tarfile` by emptying the tar `members` by any chance ?\r\n```python\r\n yield key, {\"audio\": {\"path\": audio_name, \"bytes\": audio_file_obj.read()}}\r\n audio_tarfile.members = [] # free memory\r\n key += 1\r\n```\r\n\r\nand th... | 2022-03-29T21:38:55Z | 2022-08-16T10:22:55Z | 2022-08-16T10:22:55Z | NONE | null | null | null |
## Description
`load_dataset` consumes more and more memory until it's killed, even though it's made with a generator. I'm adding a loading script for a new dataset, made up of ~15s audio coming from a tar file. Tried setting `DEFAULT_WRITER_BATCH_SIZE = 1` as per the discussion in #741 but the problem persists.
## Steps to reproduce the bug
Here's my implementation of `_generate_examples`:
```python
class MyDatasetBuilder(datasets.GeneratorBasedBuilder):
DEFAULT_WRITER_BATCH_SIZE = 1
...
def _split_generators(self, dl_manager):
archive_path = dl_manager.download(_DL_URLS[self.config.name])
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"audio_tarfile_path": archive_path["audio_tarfile"]
},
),
]
def _generate_examples(self, audio_tarfile_path):
key = 0
with tarfile.open(audio_tarfile_path, mode="r|") as audio_tarfile:
for audio_tarinfo in audio_tarfile:
audio_name = audio_tarinfo.name
audio_file_obj = audio_tarfile.extractfile(audio_tarinfo)
yield key, {"audio": {"path": audio_name, "bytes": audio_file_obj.read()}}
key += 1
```
I then try to load via `ds = load_dataset('./datasets/my_new_dataset', writer_batch_size=1)`, and memory usage grows until all 8GB of my machine are taken and process is killed (`Killed`). Also tried an untarred version of this using `os.walk` but the same happened.
I created a script to confirm that one can safely go through such a generator, which runs just fine with memory <500MB at all times.
```python
import tarfile
def generate_examples():
audio_tarfile = tarfile.open("audios.tar", mode="r|")
key = 0
for audio_tarinfo in audio_tarfile:
audio_name = audio_tarinfo.name
audio_file_obj = audio_tarfile.extractfile(audio_tarinfo)
yield key, {"audio": {"path": audio_name, "bytes": audio_file_obj.read()}}
key += 1
if __name__ == "__main__":
examples = generate_examples()
for example in examples:
pass
```
## Expected results
Memory consumption should be similar to the non-huggingface script.
## Actual results
Process is killed after consuming too much memory.
## Environment info
- `datasets` version: 2.0.1.dev0
- Platform: Linux-4.19.0-20-cloud-amd64-x86_64-with-debian-10.12
- Python version: 3.7.12
- PyArrow version: 6.0.1
- Pandas version: 1.3.5 | {
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https://api.github.com/repos/huggingface/datasets/issues/2927 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2927/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2927/comments | https://api.github.com/repos/huggingface/datasets/issues/2927/events | https://github.com/huggingface/datasets/issues/2927 | 997,654,680 | I_kwDODunzps47dwCY | 2,927 | Datasets 1.12 dataset.filter TypeError: get_indices_from_mask_function() got an unexpected keyword argument | {
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"gists... | null | [
"Thanks for reporting, I'm looking into it :)",
"Fixed by #2950."
] | 2021-09-16T01:14:02Z | 2021-09-20T16:23:22Z | 2021-09-20T16:23:21Z | NONE | null | null | null | ## Describe the bug
Upgrading to 1.12 caused `dataset.filter` call to fail with
> get_indices_from_mask_function() got an unexpected keyword argument valid_rel_labels
## Steps to reproduce the bug
```pythondef
filter_good_rows(
ex: Dict,
valid_rel_labels: Set[str],
valid_ner_labels: Set[str],
tokenizer: PreTrainedTokenizerFast,
) -> bool:
"""Get the good rows"""
encoding = get_encoding_for_text(text=ex["text"], tokenizer=tokenizer)
ex["encoding"] = encoding
for relation in ex["relations"]:
if not is_valid_relation(relation, valid_rel_labels):
return False
for span in ex["spans"]:
if not is_valid_span(span, valid_ner_labels, encoding):
return False
return True
def get_dataset():
loader_path = str(Path(__file__).parent / "prodigy_dataset_builder.py")
ds = load_dataset(
loader_path,
name="prodigy-dataset",
data_files=sorted(file_paths),
cache_dir=cache_dir,
)["train"]
valid_ner_labels = set(vocab.ner_category)
valid_relations = set(vocab.relation_types.keys())
ds = ds.filter(
filter_good_rows,
fn_kwargs=dict(
valid_rel_labels=valid_relations,
valid_ner_labels=valid_ner_labels,
tokenizer=vocab.tokenizer,
),
keep_in_memory=True,
num_proc=num_proc,
)
```
`ds` is a `DatasetDict` produced by a jsonl dataset.
This runs fine on 1.11 but fails on 1.12
**Stack Trace**
## Expected results
I expect 1.12 datasets filter to filter the dataset without raising as it does on 1.11
## Actual results
```
tf_ner_rel_lib/dataset.py:695: in load_prodigy_arrow_datasets_from_jsonl
ds = ds.filter(
../../../../.pyenv/versions/tf_ner_rel_lib/lib/python3.8/site-packages/datasets/arrow_dataset.py:185: in wrapper
out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
../../../../.pyenv/versions/tf_ner_rel_lib/lib/python3.8/site-packages/datasets/fingerprint.py:398: in wrapper
out = func(self, *args, **kwargs)
../../../../.pyenv/versions/tf_ner_rel_lib/lib/python3.8/site-packages/datasets/arrow_dataset.py:2169: in filter
indices = self.map(
../../../../.pyenv/versions/tf_ner_rel_lib/lib/python3.8/site-packages/datasets/arrow_dataset.py:1686: in map
return self._map_single(
../../../../.pyenv/versions/tf_ner_rel_lib/lib/python3.8/site-packages/datasets/arrow_dataset.py:185: in wrapper
out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
../../../../.pyenv/versions/tf_ner_rel_lib/lib/python3.8/site-packages/datasets/fingerprint.py:398: in wrapper
out = func(self, *args, **kwargs)
../../../../.pyenv/versions/tf_ner_rel_lib/lib/python3.8/site-packages/datasets/arrow_dataset.py:2048: in _map_single
batch = apply_function_on_filtered_inputs(
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
inputs = {'_input_hash': [2108817714, 1477695082, -1021597032, 2130671338, -1260483858, -1203431639, ...], '_task_hash': [18070...ons', 'relations', 'relations', ...], 'answer': ['accept', 'accept', 'accept', 'accept', 'accept', 'accept', ...], ...}
indices = [0, 1, 2, 3, 4, 5, ...], check_same_num_examples = False, offset = 0
def apply_function_on_filtered_inputs(inputs, indices, check_same_num_examples=False, offset=0):
"""Utility to apply the function on a selection of columns."""
nonlocal update_data
fn_args = [inputs] if input_columns is None else [inputs[col] for col in input_columns]
if offset == 0:
effective_indices = indices
else:
effective_indices = [i + offset for i in indices] if isinstance(indices, list) else indices + offset
processed_inputs = (
> function(*fn_args, effective_indices, **fn_kwargs) if with_indices else function(*fn_args, **fn_kwargs)
)
E TypeError: get_indices_from_mask_function() got an unexpected keyword argument 'valid_rel_labels'
../../../../.pyenv/versions/tf_ner_rel_lib/lib/python3.8/site-packages/datasets/arrow_dataset.py:1939: TypeError
```
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.12.1
- Platform: Mac
- Python version: 3.8.9
- PyArrow version: pyarrow==5.0.0
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https://api.github.com/repos/huggingface/datasets/issues/5815 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5815/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5815/comments | https://api.github.com/repos/huggingface/datasets/issues/5815/events | https://github.com/huggingface/datasets/issues/5815 | 1,693,701,743 | I_kwDODunzps5k89Zv | 5,815 | Easy way to create a Kaggle dataset from a Huggingface dataset? | {
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"Hi @hrbigelow , I'm no expert for such a question so I'll ping @lhoestq from the `datasets` library (also this issue could be moved there if someone with permission can do it :) )",
"Hi ! Many datasets are made of several files, and how they are parsed often requires a python script. Because of that, datasets li... | 2023-05-02T21:43:33Z | 2023-07-26T16:13:31Z | null | NONE | null | null | null | I'm not sure whether this is more appropriately addressed with HuggingFace or Kaggle. I would like to somehow directly create a Kaggle dataset from a HuggingFace Dataset.
While Kaggle does provide the option to create a dataset from a URI, that URI must point to a single file. For example:
Is there some mechanism from huggingface to represent a dataset (such as that from `load_dataset('wmt14', 'de-en', split='train')` as a single file? Or, some other way to get that into a Kaggle dataset so that I can use the huggingface `datasets` module to process and consume it inside of a Kaggle notebook?
Thanks in advance!
| {
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https://api.github.com/repos/huggingface/datasets/issues/4670 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4670/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4670/comments | https://api.github.com/repos/huggingface/datasets/issues/4670/events | https://github.com/huggingface/datasets/issues/4670 | 1,299,984,246 | I_kwDODunzps5NfC92 | 4,670 | Can't extract files from `.7z` zipfile using `download_and_extract` | {
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"color": "d73a4a",
"default": true,
"description": "Something isn't working",
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"name": "bug",
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"Hi @bhavitvyamalik, thanks for reporting.\r\n\r\nYes, currently we do not support 7zip archive compression: I think we should.\r\n\r\nAs a workaround, you could uncompress it explicitly, like done in e.g. `samsum` dataset: \r\n\r\nhttps://github.com/huggingface/datasets/blob/fedf891a08bfc77041d575fad6c26091bc0fce5... | 2022-07-10T18:16:49Z | 2022-07-15T13:02:07Z | 2022-07-15T13:02:07Z | CONTRIBUTOR | null | null | null | ## Describe the bug
I'm adding a new dataset which is a `.7z` zip file in Google drive and contains 3 json files inside. I'm able to download the data files using `download_and_extract` but after downloading it throws this error:
```
>>> dataset = load_dataset("./datasets/mantis/")
Using custom data configuration default
Downloading and preparing dataset mantis/default to /Users/bhavitvyamalik/.cache/huggingface/datasets/mantis/default/1.1.0/611affa804ec53e2055a335cc1b8b213bb5a0b5142d919967729d5ee23c6bab4...
Downloading data: 100%|█████████████████████████████████████████████████████████| 77.2M/77.2M [00:23<00:00, 3.28MB/s]
/Users/bhavitvyamalik/.cache/huggingface/datasets/downloads/fc3d70123c9de8407587a59aa426c37819cf2bf016795d33270e8a1d558a34e6
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/Users/bhavitvyamalik/Desktop/work/hf/datasets/src/datasets/load.py", line 1745, in load_dataset
use_auth_token=use_auth_token,
File "/Users/bhavitvyamalik/Desktop/work/hf/datasets/src/datasets/builder.py", line 595, in download_and_prepare
dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
File "/Users/bhavitvyamalik/Desktop/work/hf/datasets/src/datasets/builder.py", line 690, in _download_and_prepare
) from None
OSError: Cannot find data file.
Original error:
[Errno 20] Not a directory: '/Users/bhavitvyamalik/.cache/huggingface/datasets/downloads/fc3d70123c9de8407587a59aa426c37819cf2bf016795d33270e8a1d558a34e6/merged_train.json'
```
just before generating the splits. I checked `fc3d70123c9de8407587a59aa426c37819cf2bf016795d33270e8a1d558a34e6` file and it's `7z` zip file (similar to downloaded Google drive file) which means it didn't get unzip. Do I need to unzip it separately and then pass the paths for train,dev,test files in `SplitGenerator`?
## Environment info
- `datasets` version: 1.18.4.dev0
- Platform: Darwin-19.6.0-x86_64-i386-64bit
- Python version: 3.7.8
- PyArrow version: 5.0.0 | {
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https://api.github.com/repos/huggingface/datasets/issues/4151 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4151/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4151/comments | https://api.github.com/repos/huggingface/datasets/issues/4151/events | https://github.com/huggingface/datasets/pull/4151 | 1,201,837,999 | PR_kwDODunzps42GgLu | 4,151 | Add missing label for emotion description | {
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https://api.github.com/repos/huggingface/datasets/issues/4194 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4194/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4194/comments | https://api.github.com/repos/huggingface/datasets/issues/4194/events | https://github.com/huggingface/datasets/pull/4194 | 1,210,958,602 | PR_kwDODunzps42jjD3 | 4,194 | Support lists of multi-dimensional numpy arrays | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-04-21T12:22:26Z | 2022-05-12T15:16:34Z | 2022-05-12T15:08:40Z | MEMBER | null | 0 | {
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} | Fix #4191.
CC: @SaulLu | {
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https://api.github.com/repos/huggingface/datasets/issues/6191 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6191/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6191/comments | https://api.github.com/repos/huggingface/datasets/issues/6191/events | https://github.com/huggingface/datasets/pull/6191 | 1,871,634,840 | PR_kwDODunzps5ZCKmv | 6,191 | Add missing `revision` argument | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"I have found the same issue. Good fix. Should be merged as soon as possible.",
"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_a... | 2023-08-29T13:05:04Z | 2023-09-04T06:38:17Z | 2023-08-31T13:50:00Z | CONTRIBUTOR | null | 0 | {
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} | I've noticed that when you're not working on the main branch, there are sometimes errors in the files returned. After some investigation, I realized that the revision was not properly passed everywhere. This PR proposes a fix. | {
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https://api.github.com/repos/huggingface/datasets/issues/1801 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1801/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1801/comments | https://api.github.com/repos/huggingface/datasets/issues/1801/events | https://github.com/huggingface/datasets/pull/1801 | 797,814,275 | MDExOlB1bGxSZXF1ZXN0NTY0NzMwODYw | 1,801 | [GEM] Updated the source link of the data to update correct tokenized version. | {
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"@mounicam we'll keep the original version in the Turk dataset proper, and use the updated file in the GEM aggregated dataset which I'll add later today\r\n\r\n@lhoestq do not merge, I'll close when I've submitted the GEM dataset PR :) ",
"Closed by https://github.com/huggingface/datasets/pull/1807"
] | 2021-01-31T21:17:19Z | 2021-02-02T13:17:38Z | 2021-02-02T13:17:28Z | CONTRIBUTOR | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/2459 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2459/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2459/comments | https://api.github.com/repos/huggingface/datasets/issues/2459/events | https://github.com/huggingface/datasets/issues/2459 | 915,222,015 | MDU6SXNzdWU5MTUyMjIwMTU= | 2,459 | `Proto_qa` hosting seems to be broken | {
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] | closed | false | null | [] | null | [
"@VictorSanh , I think @mariosasko is already working on it. "
] | 2021-06-08T16:16:32Z | 2021-06-10T08:31:09Z | 2021-06-10T08:31:09Z | MEMBER | null | null | null | ## Describe the bug
The hosting (on Github) of the `proto_qa` dataset seems broken. I haven't investigated more yet, just flagging it for now.
@zaidalyafeai if you want to dive into it, I think it's just a matter of changing the links in `proto_qa.py`
## Steps to reproduce the bug
```python
from datasets import load_dataset
dataset = load_dataset("proto_qa")
```
## Actual results
```
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/hf/dev/promptsource/.venv/lib/python3.7/site-packages/datasets/load.py", line 751, in load_dataset
use_auth_token=use_auth_token,
File "/home/hf/dev/promptsource/.venv/lib/python3.7/site-packages/datasets/builder.py", line 575, in download_and_prepare
dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
File "/home/hf/dev/promptsource/.venv/lib/python3.7/site-packages/datasets/builder.py", line 630, in _download_and_prepare
split_generators = self._split_generators(dl_manager, **split_generators_kwargs)
File "/home/hf/.cache/huggingface/modules/datasets_modules/datasets/proto_qa/445346efaad5c5f200ecda4aa7f0fb50ff1b55edde3003be424a2112c3e8102e/proto_qa.py", line 131, in _split_generators
train_fpath = dl_manager.download(_URLs[self.config.name]["train"])
File "/home/hf/dev/promptsource/.venv/lib/python3.7/site-packages/datasets/utils/download_manager.py", line 199, in download
num_proc=download_config.num_proc,
File "/home/hf/dev/promptsource/.venv/lib/python3.7/site-packages/datasets/utils/py_utils.py", line 195, in map_nested
return function(data_struct)
File "/home/hf/dev/promptsource/.venv/lib/python3.7/site-packages/datasets/utils/download_manager.py", line 218, in _download
return cached_path(url_or_filename, download_config=download_config)
File "/home/hf/dev/promptsource/.venv/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 291, in cached_path
use_auth_token=download_config.use_auth_token,
File "/home/hf/dev/promptsource/.venv/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 621, in get_from_cache
raise FileNotFoundError("Couldn't find file at {}".format(url))
FileNotFoundError: Couldn't find file at https://raw.githubusercontent.com/iesl/protoqa-data/master/data/train/protoqa_train.jsonl
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/4505 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4505/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4505/comments | https://api.github.com/repos/huggingface/datasets/issues/4505/events | https://github.com/huggingface/datasets/pull/4505 | 1,272,477,226 | PR_kwDODunzps45uH-o | 4,505 | Fix double dots in data files | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"The CI fails are unrelated to this PR (apparently something related to `seqeval` on windows) - merging :)"
] | 2022-06-15T16:31:04Z | 2022-06-15T17:15:58Z | 2022-06-15T17:05:53Z | MEMBER | null | 0 | {
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} | As mentioned in https://github.com/huggingface/transformers/pull/17715 `data_files` can't find a file if the path contains double dots `/../`. This has been introduced in https://github.com/huggingface/datasets/pull/4412, by trying to ignore hidden files and directories (i.e. if they start with a dot)
I fixed this and added a test
cc @sgugger @ydshieh | {
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https://api.github.com/repos/huggingface/datasets/issues/6182 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6182/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6182/comments | https://api.github.com/repos/huggingface/datasets/issues/6182/events | https://github.com/huggingface/datasets/issues/6182 | 1,867,203,131 | I_kwDODunzps5vS0I7 | 6,182 | Loading Meteor metric in HF evaluate module crashes due to datasets import issue | {
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"Our minimal Python version requirement is 3.8, so we dropped `importlib_metadata`. \r\n\r\nFeel free to open a PR in the `evaluate` repo to replace the problematic import with\r\n```python\r\nif PY_VERSION < version.parse(\"3.8\"):\r\n import importlib_metadata\r\nelse:\r\n import importlib.metadata as impor... | 2023-08-25T14:54:06Z | 2023-09-04T16:41:11Z | 2023-08-31T14:38:23Z | NONE | null | null | null | ### Describe the bug
When using python3.9 and ```evaluate``` module loading Meteor metric crashes at a non-existent import from ```datasets.config``` in ```datasets v2.14```
### Steps to reproduce the bug
```
from evaluate import load
meteor = load("meteor")
```
produces the following error:
```
from datasets.config import importlib_metadata, version
ImportError: cannot import name 'importlib_metadata' from 'datasets.config' (<path_to_project>/venv/lib/python3.9/site-packages/datasets/config.py)
```
### Expected behavior
```datasets``` of v2.10 has the following workaround in ```config.py```:
```
if PY_VERSION < version.parse("3.8"):
import importlib_metadata
else:
import importlib.metadata as importlib_metadata
```
However, it's absent in v2.14 which might be the cause of the issue.
### Environment info
- `datasets` version: 2.14.4
- Platform: macOS-13.5-arm64-arm-64bit
- Python version: 3.9.6
- Huggingface_hub version: 0.16.4
- PyArrow version: 12.0.1
- Pandas version: 2.0.3
- Evaluate version: 0.4.0 | {
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https://api.github.com/repos/huggingface/datasets/issues/3957 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3957/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3957/comments | https://api.github.com/repos/huggingface/datasets/issues/3957/events | https://github.com/huggingface/datasets/pull/3957 | 1,172,401,455 | PR_kwDODunzps40magW | 3,957 | Fix xtreme s metrics | {
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"Sorry for the commit history mess, but will be squashed anyways so should be fine",
"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-03-17T13:39:04Z | 2022-03-18T13:46:19Z | 2022-03-18T13:42:16Z | MEMBER | null | 0 | {
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} | We in fact do need BABEL in xtreme-s | {
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https://api.github.com/repos/huggingface/datasets/issues/3677 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3677/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3677/comments | https://api.github.com/repos/huggingface/datasets/issues/3677/events | https://github.com/huggingface/datasets/issues/3677 | 1,123,192,866 | I_kwDODunzps5C8pAi | 3,677 | Discovery cannot be streamed anymore | {
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"Seems like a regression from https://github.com/huggingface/datasets/pull/2843\r\n\r\nOr maybe it's an issue with the hosting. I don't think so, though, because https://www.dropbox.com/s/aox84z90nyyuikz/discovery.zip seems to work as expected\r\n\r\n",
"Hi @severo, thanks for reporting.\r\n\r\nSome servers do no... | 2022-02-03T15:02:03Z | 2022-02-10T16:51:24Z | 2022-02-10T16:51:24Z | CONTRIBUTOR | null | null | null | ## Describe the bug
A clear and concise description of what the bug is.
## Steps to reproduce the bug
```python
from datasets import load_dataset
iterable_dataset = load_dataset("discovery", name="discovery", split="train", streaming=True)
list(iterable_dataset.take(1))
```
## Expected results
The first row of the train split.
## Actual results
```
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 365, in __iter__
for key, example in self._iter():
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 362, in _iter
yield from ex_iterable
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 272, in __iter__
yield from islice(self.ex_iterable, self.n)
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 79, in __iter__
yield from self.generate_examples_fn(**self.kwargs)
File "/home/slesage/.cache/huggingface/modules/datasets_modules/datasets/discovery/542fab7a9ddc1d9726160355f7baa06a1ccc44c40bc8e12c09e9bc743aca43a2/discovery.py", line 333, in _generate_examples
with open(data_file, encoding="utf8") as f:
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/datasets/streaming.py", line 64, in wrapper
return function(*args, use_auth_token=use_auth_token, **kwargs)
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/datasets/utils/streaming_download_manager.py", line 369, in xopen
file_obj = fsspec.open(file, mode=mode, *args, **kwargs).open()
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/fsspec/core.py", line 456, in open
return open_files(
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/fsspec/core.py", line 288, in open_files
fs, fs_token, paths = get_fs_token_paths(
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/fsspec/core.py", line 611, in get_fs_token_paths
fs = filesystem(protocol, **inkwargs)
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/fsspec/registry.py", line 253, in filesystem
return cls(**storage_options)
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/fsspec/spec.py", line 68, in __call__
obj = super().__call__(*args, **kwargs)
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/fsspec/implementations/zip.py", line 57, in __init__
self.zip = zipfile.ZipFile(self.fo)
File "/home/slesage/.pyenv/versions/3.9.6/lib/python3.9/zipfile.py", line 1257, in __init__
self._RealGetContents()
File "/home/slesage/.pyenv/versions/3.9.6/lib/python3.9/zipfile.py", line 1320, in _RealGetContents
endrec = _EndRecData(fp)
File "/home/slesage/.pyenv/versions/3.9.6/lib/python3.9/zipfile.py", line 263, in _EndRecData
fpin.seek(0, 2)
File "/home/slesage/hf/datasets-preview-backend/.venv/lib/python3.9/site-packages/fsspec/implementations/http.py", line 676, in seek
raise ValueError("Cannot seek streaming HTTP file")
ValueError: Cannot seek streaming HTTP file
```
## Environment info
- `datasets` version: 1.18.3
- Platform: Linux-5.11.0-1027-aws-x86_64-with-glibc2.31
- Python version: 3.9.6
- PyArrow version: 6.0.1
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https://api.github.com/repos/huggingface/datasets/issues/4904 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4904/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4904/comments | https://api.github.com/repos/huggingface/datasets/issues/4904/events | https://github.com/huggingface/datasets/pull/4904 | 1,353,002,837 | PR_kwDODunzps4959Ad | 4,904 | [LibriSpeech] Fix dev split local_extracted_archive for 'all' config | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"This PR fixes a bug introduced in:\r\n- #4184"
] | 2022-08-27T10:04:57Z | 2022-08-30T10:06:21Z | 2022-08-30T10:03:25Z | CONTRIBUTOR | null | 0 | {
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} | We define the keys for the `_DL_URLS` of the dev split as `dev.clean` and `dev.other`:
https://github.com/huggingface/datasets/blob/2e7142a3c6500b560da45e8d5128e320a09fcbd4/datasets/librispeech_asr/librispeech_asr.py#L60-L61
These keys get forwarded to the `dl_manager` and thus the `local_extracted_archive`.
However, when calling `SplitGenerator` for the dev sets, we query the `local_extracted_archive` keys `validation.clean` and `validation.other`:
https://github.com/huggingface/datasets/blob/2e7142a3c6500b560da45e8d5128e320a09fcbd4/datasets/librispeech_asr/librispeech_asr.py#L212
https://github.com/huggingface/datasets/blob/2e7142a3c6500b560da45e8d5128e320a09fcbd4/datasets/librispeech_asr/librispeech_asr.py#L219
The consequence of this is that the `local_extracted_archive` arg passed to `_generate_examples` is always `None`, as the keys `validation.clean` and `validation.other` do not exists in the `local_extracted_archive`.
When defining the `audio_file` in `_generate_examples`, since `local_extracted_archive` is always `None`, we always omit the `local_extracted_archive` path from the `audio_file` path, **even** if in non-streaming mode:
https://github.com/huggingface/datasets/blob/2e7142a3c6500b560da45e8d5128e320a09fcbd4/datasets/librispeech_asr/librispeech_asr.py#L259-L263
Thus, `audio_file` will only ever be the streaming path (`audio_file`, not `os.path.join(local_extracted_archive, audio_file)`).
This PR fixes the `.get()` keys for the `local_extracted_archive` for the dev splits.
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https://api.github.com/repos/huggingface/datasets/issues/3938 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3938/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3938/comments | https://api.github.com/repos/huggingface/datasets/issues/3938/events | https://github.com/huggingface/datasets/pull/3938 | 1,170,875,417 | PR_kwDODunzps40hnjM | 3,938 | Avoid info log messages from transformers in FrugalScore metric | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_3938). All of your documentation changes will be reflected on that endpoint."
] | 2022-03-16T11:11:29Z | 2022-03-17T08:37:25Z | 2022-03-17T08:37:24Z | MEMBER | null | 0 | {
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} | Fix #3928. | {
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https://api.github.com/repos/huggingface/datasets/issues/1840 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1840/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1840/comments | https://api.github.com/repos/huggingface/datasets/issues/1840/events | https://github.com/huggingface/datasets/issues/1840 | 803,560,039 | MDU6SXNzdWU4MDM1NjAwMzk= | 1,840 | Add common voice | {
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"color": "d93f0b",... | closed | false | null | [] | null | [
"I have started working on adding this dataset.",
"Hey @BirgerMoell - awesome that you started working on Common Voice. Common Voice is a bit special since, there is no direct download link to download the data. In these cases we usually consider two options:\r\n\r\n1) Find a hacky solution to extract the downloa... | 2021-02-08T13:21:05Z | 2022-03-20T15:23:40Z | 2021-03-15T05:56:21Z | MEMBER | null | null | null | ## Adding a Dataset
- **Name:** *common voice*
- **Description:** *Mozilla Common Voice Dataset*
- **Paper:** Homepage: https://voice.mozilla.org/en/datasets
- **Data:** https://voice.mozilla.org/en/datasets
- **Motivation:** Important speech dataset
- **TFDatasets Implementation**: https://www.tensorflow.org/datasets/catalog/common_voice
If interested in tackling this issue, feel free to tag @patrickvonplaten
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
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https://api.github.com/repos/huggingface/datasets/issues/5405 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5405/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5405/comments | https://api.github.com/repos/huggingface/datasets/issues/5405/events | https://github.com/huggingface/datasets/issues/5405 | 1,517,879,386 | I_kwDODunzps5aeQBa | 5,405 | size_in_bytes the same for all splits | {
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"Hi @Breakend,\r\n\r\nIndeed, the attribute `size_in_bytes` refers to the size of the entire dataset configuration, for all splits (size of downloaded files + Arrow files), not the specific split.\r\nThis is also the case for `download_size` (downloaded files) and `dataset_size` (Arrow files).\r\n\r\nThe size of th... | 2023-01-03T20:25:48Z | 2023-01-04T09:22:59Z | null | NONE | null | null | null | ### Describe the bug
Hi, it looks like whenever you pull a dataset and get size_in_bytes, it returns the same size for all splits (and that size is the combined size of all splits). It seems like this shouldn't be the intended behavior since it is misleading. Here's an example:
```
>>> from datasets import load_dataset
>>> x = load_dataset("glue", "wnli")
Found cached dataset glue (/Users/breakend/.cache/huggingface/datasets/glue/wnli/1.0.0/dacbe3125aa31d7f70367a07a8a9e72a5a0bfeb5fc42e75c9db75b96da6053ad)
100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<00:00, 1097.70it/s]
>>> x["train"].size_in_bytes
186159
>>> x["validation"].size_in_bytes
186159
>>> x["test"].size_in_bytes
186159
>>>
```
### Steps to reproduce the bug
```
>>> from datasets import load_dataset
>>> x = load_dataset("glue", "wnli")
>>> x["train"].size_in_bytes
186159
>>> x["validation"].size_in_bytes
186159
>>> x["test"].size_in_bytes
186159
```
### Expected behavior
The expected behavior is that it should return the separate sizes for all splits.
### Environment info
- `datasets` version: 2.7.1
- Platform: macOS-12.5-arm64-arm-64bit
- Python version: 3.10.8
- PyArrow version: 10.0.1
- Pandas version: 1.5.2 | {
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https://api.github.com/repos/huggingface/datasets/issues/2815 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2815/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2815/comments | https://api.github.com/repos/huggingface/datasets/issues/2815/events | https://github.com/huggingface/datasets/pull/2815 | 973,862,024 | MDExOlB1bGxSZXF1ZXN0NzE1MjUxNDQ5 | 2,815 | Tiny typo fixes of "fo" -> "of" | {
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} | Noticed a few of these when reading docs- feel free to ignore the PR and just fix on some main contributor branch if more helpful. Thanks for the great library! :) | {
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https://api.github.com/repos/huggingface/datasets/issues/2746 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2746/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2746/comments | https://api.github.com/repos/huggingface/datasets/issues/2746/events | https://github.com/huggingface/datasets/issues/2746 | 958,551,619 | MDU6SXNzdWU5NTg1NTE2MTk= | 2,746 | Cannot load `few-nerd` dataset | {
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"Hi @Mehrad0711,\r\n\r\nI'm afraid there is no \"canonical\" Hugging Face dataset named \"few-nerd\".\r\n\r\nThere are 2 kinds of datasets hosted at the Hugging Face Hub:\r\n- canonical datasets (their identifier contains no slash \"/\"): we, the Hugging Face team, supervise their implementation and we make sure th... | 2021-08-02T22:18:57Z | 2021-11-16T08:51:34Z | 2021-08-03T19:45:43Z | NONE | null | null | null | ## Describe the bug
Cannot load `few-nerd` dataset.
## Steps to reproduce the bug
```python
from datasets import load_dataset
load_dataset('few-nerd', 'supervised')
```
## Actual results
Executing above code will give the following error:
```
Using the latest cached version of the module from /Users/Mehrad/.cache/huggingface/modules/datasets_modules/datasets/few-nerd/62464ace912a40a0f33a11a8310f9041c9dc3590ff2b3c77c14d83ca53cfec53 (last modified on Wed Jun 2 11:34:25 2021) since it couldn't be found locally at /Users/Mehrad/Documents/GitHub/genienlp/few-nerd/few-nerd.py, or remotely (FileNotFoundError).
Downloading and preparing dataset few_nerd/supervised (download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size) to /Users/Mehrad/.cache/huggingface/datasets/few_nerd/supervised/0.0.0/62464ace912a40a0f33a11a8310f9041c9dc3590ff2b3c77c14d83ca53cfec53...
Traceback (most recent call last):
File "/Users/Mehrad/opt/anaconda3/lib/python3.7/site-packages/datasets/builder.py", line 693, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/Users/Mehrad/opt/anaconda3/lib/python3.7/site-packages/datasets/builder.py", line 1107, in _prepare_split
disable=bool(logging.get_verbosity() == logging.NOTSET),
File "/Users/Mehrad/opt/anaconda3/lib/python3.7/site-packages/tqdm/std.py", line 1133, in __iter__
for obj in iterable:
File "/Users/Mehrad/.cache/huggingface/modules/datasets_modules/datasets/few-nerd/62464ace912a40a0f33a11a8310f9041c9dc3590ff2b3c77c14d83ca53cfec53/few-nerd.py", line 196, in _generate_examples
with open(filepath, encoding="utf-8") as f:
FileNotFoundError: [Errno 2] No such file or directory: '/Users/Mehrad/.cache/huggingface/datasets/downloads/supervised/train.json'
```
The bug is probably in identifying and downloading the dataset. If I download the json splits directly from [link](https://github.com/nbroad1881/few-nerd/tree/main/uncompressed) and put them under the downloads directory, they will be processed into arrow format correctly.
## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.11.0
- Python version: 3.8
- PyArrow version: 1.0.1
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] | open | false | null | [] | null | [] | 2023-04-26T14:55:23Z | 2023-04-26T14:55:23Z | null | MEMBER | null | null | null | Sometimes when running our CI on Windows, we get a ZeroDivisionError:
```
FAILED tests/test_metric_common.py::LocalMetricTest::test_load_metric_frugalscore - ZeroDivisionError: float division by zero
```
See for example:
- https://github.com/huggingface/datasets/actions/runs/4809358266/jobs/8560513110
- https://github.com/huggingface/datasets/actions/runs/4798359836/jobs/8536573688
```
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
split = 'test', start_time = 1682516718.8236516, num_samples = 2, num_steps = 1
def speed_metrics(split, start_time, num_samples=None, num_steps=None):
"""
Measure and return speed performance metrics.
This function requires a time snapshot `start_time` before the operation to be measured starts and this function
should be run immediately after the operation to be measured has completed.
Args:
- split: name to prefix metric (like train, eval, test...)
- start_time: operation start time
- num_samples: number of samples processed
"""
runtime = time.time() - start_time
result = {f"{split}_runtime": round(runtime, 4)}
if num_samples is not None:
> samples_per_second = num_samples / runtime
E ZeroDivisionError: float division by zero
C:\hostedtoolcache\windows\Python\3.7.9\x64\lib\site-packages\transformers\trainer_utils.py:354: ZeroDivisionError
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/5365 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5365/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5365/comments | https://api.github.com/repos/huggingface/datasets/issues/5365/events | https://github.com/huggingface/datasets/pull/5365 | 1,498,422,466 | PR_kwDODunzps5Fi6ZD | 5,365 | fix: image array should support other formats than uint8 | {
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"_The documentation is not available anymore as the PR was closed or merged._",
"Hi, thanks for working on this! \r\n\r\nI agree that the current type-casting (always cast to `np.uint8` as Tensorflow Datasets does) is a bit too harsh. However, not all dtypes are supported in `Image.fromarray` (e.g. np.int64), so ... | 2022-12-15T13:17:50Z | 2023-01-26T18:46:45Z | 2023-01-26T18:39:36Z | CONTRIBUTOR | null | 0 | {
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} | Currently images that are provided as ndarrays, but not in `uint8` format are going to loose data. Namely, for example in a depth image where the data is in float32 format, the type-casting to uint8 will basically make the whole image blank.
`PIL.Image.fromarray` [does support mode `F`](https://pillow.readthedocs.io/en/stable/handbook/concepts.html#concept-modes).
although maybe some further metadata could be supplied via the [Image](https://huggingface.co/docs/datasets/v2.7.1/en/package_reference/main_classes#datasets.Image) object. | {
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https://api.github.com/repos/huggingface/datasets/issues/3818 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3818/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3818/comments | https://api.github.com/repos/huggingface/datasets/issues/3818/events | https://github.com/huggingface/datasets/issues/3818 | 1,158,788,545 | I_kwDODunzps5FEbXB | 3,818 | Support for "sources" parameter in the add() and add_batch() methods in datasets.metric - SARI | {
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"Hi, thanks for reporting! We can add a `sources: datasets.Value(\"string\")` feature to the `Features` dict in the `SARI` script to fix this. Would you be interested in submitting a PR?",
"Hi Mario,\r\n\r\nThanks for your message. I did try to add `sources` into the `Features` dict using a script for the metric:... | 2022-03-03T18:57:54Z | 2022-03-04T18:04:21Z | 2022-03-04T18:04:21Z | NONE | null | null | null | **Is your feature request related to a problem? Please describe.**
The methods `add_batch` and `add` from the `Metric` [class](https://github.com/huggingface/datasets/blob/1675ad6a958435b675a849eafa8a7f10fe0f43bc/src/datasets/metric.py) does not work with [SARI](https://github.com/huggingface/datasets/blob/master/metrics/sari/sari.py) metric. This metric not only relies on the predictions and references, but also in the input.
For example, when the `add_batch` method is used, then the `compute()` method fails:
```
metric = load_metric("sari")
metric.add_batch(
predictions=["About 95 you now get in ."],
references=[["About 95 species are currently known .","About 95 species are now accepted .","95 species are now accepted ."]])
metric.compute()
> TypeError: _compute() missing 1 required positional argument: 'sources'
```
Therefore, the `compute() `method can only be used standalone:
```
metric = load_metric("sari")
result = metric.compute(
sources=["About 95 species are currently accepted ."],
predictions=["About 95 you now get in ."],
references=[["About 95 species are currently known .","About 95 species are now accepted .","95 species are now accepted ."]])
> {'sari': 26.953601953601954}
```
**Describe the solution you'd like**
Support for an additional parameter `sources` in the `add_batch` and `add` of the `Metric` class.
```
add_batch(*, sources=None, predictions=None, references=None, **kwargs)
add(*, sources=None, predictions=None, references=None, **kwargs)
compute()
```
**Describe alternatives you've considered**
I've tried to override the `add_batch` and `add`, however, these are highly dependent to the `Metric` class. We could also write a simple function that compute the scores of a sentences list, but then we lose the functionality from the original [add](https://huggingface.co/docs/datasets/_modules/datasets/metric.html#Metric.add) and [add_batch method](https://huggingface.co/docs/datasets/_modules/datasets/metric.html#Metric.add_batch).
**Additional context**
These methods are used in the transformers [pytorch examples](https://github.com/huggingface/transformers/blob/master/examples/pytorch/summarization/run_summarization_no_trainer.py).
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https://api.github.com/repos/huggingface/datasets/issues/2884 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2884/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2884/comments | https://api.github.com/repos/huggingface/datasets/issues/2884/events | https://github.com/huggingface/datasets/pull/2884 | 992,135,698 | MDExOlB1bGxSZXF1ZXN0NzMwNTA4MTE1 | 2,884 | Add IC, SI, ER tasks to SUPERB | {
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"Sorry for the late PR, uploading 10+GB files to the hub through a VPN was an adventure :sweat_smile: ",
"Thank you so much for adding these subsets @anton-l! \r\n\r\n> These datasets either require manual downloads or have broken/unstable links. You can get all necessary archives in this repo: https://huggingfac... | 2021-09-09T11:56:03Z | 2021-09-20T09:17:58Z | 2021-09-20T09:00:49Z | MEMBER | null | 0 | {
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} | This PR adds 3 additional classification tasks to SUPERB
#### Intent Classification
Dataset URL seems to be down at the moment :( See the note below.
S3PRL source: https://github.com/s3prl/s3prl/blob/master/s3prl/downstream/fluent_commands/dataset.py
Instructions: https://github.com/s3prl/s3prl/tree/master/s3prl/downstream#ic-intent-classification---fluent-speech-commands
#### Speaker Identification
Manual download script:
```
mkdir VoxCeleb1
cd VoxCeleb1
wget https://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox1_dev_wav_partaa
wget https://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox1_dev_wav_partab
wget https://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox1_dev_wav_partac
wget https://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox1_dev_wav_partad
cat vox1_dev* > vox1_dev_wav.zip
unzip vox1_dev_wav.zip
wget https://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox1_test_wav.zip
unzip vox1_test_wav.zip
# download the official SUPERB train-dev-test split
wget https://raw.githubusercontent.com/s3prl/s3prl/master/s3prl/downstream/voxceleb1/veri_test_class.txt
```
S3PRL source: https://github.com/s3prl/s3prl/blob/master/s3prl/downstream/voxceleb1/dataset.py
Instructions: https://github.com/s3prl/s3prl/tree/master/s3prl/downstream#sid-speaker-identification
#### Intent Classification
Manual download requires going through a slow application process, see the note below.
S3PRL source: https://github.com/s3prl/s3prl/blob/master/s3prl/downstream/emotion/IEMOCAP_preprocess.py
Instructions: https://github.com/s3prl/s3prl/tree/master/s3prl/downstream#er-emotion-recognition
#### :warning: Note
These datasets either require manual downloads or have broken/unstable links. You can get all necessary archives in this repo: https://huggingface.co/datasets/anton-l/superb_source_data_dumps/tree/main | {
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https://api.github.com/repos/huggingface/datasets/issues/3798 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/3798/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/3798/comments | https://api.github.com/repos/huggingface/datasets/issues/3798/events | https://github.com/huggingface/datasets/pull/3798 | 1,154,411,066 | PR_kwDODunzps4zrl5Y | 3,798 | Fix error message in CSV loader for newer Pandas versions | {
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} | Fix the error message in the CSV loader for `Pandas >= 1.4`. To fix this, I directly print the current file name in the for-loop. An alternative would be to use a check similar to this:
```python
csv_file_reader.handle.handle if datasets.config.PANDAS_VERSION >= version.parse("1.4") else csv_file_reader.f
```
CC: @SBrandeis | {
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https://api.github.com/repos/huggingface/datasets/issues/5838 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5838/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5838/comments | https://api.github.com/repos/huggingface/datasets/issues/5838/events | https://github.com/huggingface/datasets/issues/5838 | 1,703,210,848 | I_kwDODunzps5lhO9g | 5,838 | Streaming support for `load_from_disk` | {
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"As the name says, `load_from_disk` load the data from your disk. If the data is hosted on S3, it is first downloaded locally and then loaded from your disk.\r\n\r\nThere is a discussion on streaming data from S3 here though: #5281 ",
"@lhoestq \r\nThanks for your comment. I have checked out the discussion before... | 2023-05-10T06:25:22Z | 2023-05-12T09:37:45Z | 2023-05-12T09:37:45Z | NONE | null | null | null | ### Feature request
Support for streaming datasets stored in object stores in `load_from_disk`.
### Motivation
The `load_from_disk` function supports fetching datasets stored in object stores such as `s3`. In many cases, the datasets that are stored in object stores are very large and being able to stream the data from the buckets becomes essential.
### Your contribution
I'd be happy to contribute this feature if I could get the guidance on how to do so. | {
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"Hi ! Yes we are working on making `filter` significantly faster. You can look at related PRs here: #2060 #2178 \r\n\r\nI think you can expect to have the fast version of `filter` available next week.\r\n\r\nWe'll make it only select one column, and we'll also make the overall filtering operation way faster by avoi... | 2021-04-08T18:16:14Z | 2021-04-26T16:13:59Z | 2021-04-26T16:13:59Z | CONTRIBUTOR | null | null | null | I'm currently using the `wikipedia` dataset— I'm tokenizing the articles with the `tokenizers` library using `map()` and also adding a new `num_tokens` column to the dataset as part of that map operation.
I want to be able to _filter_ the dataset based on this `num_tokens` column, but even when I specify `input_columns=['num_tokens']`, it seems that the entirety of each row is loaded into memory, which makes the operation take much longer than it should. Indeed, `filter` currently just calls `map`, and I found that in `_map_single` on lines 1690-1704 of `arrow_dataset.py`, the method is just grabbing slices of _all the rows_ of the dataset and then passing only the specified columns to the map function. It seems that, when the user passes a value for `input_columns`, the `map` function should create a temporary pyarrow table by selecting just those columns, and then get slices from that table. Or something like that— I'm not very familiar with the pyarrow API.
I know that in the meantime I can sort of get around this by simply only returning the rows that match my filter criterion from the tokenizing function I pass to `map()`, but I actually _also_ want to map on just the `num_tokens` column in order to compute batches with a roughly uniform number of tokens per batch. I would also ideally like to be able to change my minimum and maximum article lengths without having to re-tokenize the entire dataset.
PS: This is definitely not a "dataset request." I'm realizing that I don't actually know how to remove labels from my own issues on other people's repos, if that is even possible. | {
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https://api.github.com/repos/huggingface/datasets/issues/4413 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/4413/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/4413/comments | https://api.github.com/repos/huggingface/datasets/issues/4413/events | https://github.com/huggingface/datasets/issues/4413 | 1,250,259,822 | I_kwDODunzps5KhXNu | 4,413 | Dataset Viewer issue for ett | {
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"Thanks for reporting @dgcnz.\r\n\r\nI have checked that the dataset works fine in streaming mode.\r\n\r\nAdditionally, other datasets containing timestamps are properly rendered by the viewer: https://huggingface.co/datasets/blbooks\r\n\r\nI have tried to force the refresh of the preview, but the endpoint is not r... | 2022-05-27T02:12:35Z | 2022-06-15T07:30:46Z | 2022-06-15T07:30:46Z | NONE | null | null | null | ### Link
https://huggingface.co/datasets/ett
### Description
Timestamp is not JSON serializable.
```
Status code: 500
Exception: Status500Error
Message: Type is not JSON serializable: Timestamp
```
### Owner
No | {
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https://api.github.com/repos/huggingface/datasets/issues/5214 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5214/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5214/comments | https://api.github.com/repos/huggingface/datasets/issues/5214/events | https://github.com/huggingface/datasets/pull/5214 | 1,440,334,978 | PR_kwDODunzps5CbmWE | 5,214 | Update github pr docs actions | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_5214). All of your documentation changes will be reflected on that endpoint."
] | 2022-11-08T14:43:37Z | 2022-11-08T15:39:58Z | 2022-11-08T15:39:57Z | CONTRIBUTOR | null | 0 | {
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https://api.github.com/repos/huggingface/datasets/issues/5310 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/5310/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/5310/comments | https://api.github.com/repos/huggingface/datasets/issues/5310/events | https://github.com/huggingface/datasets/pull/5310 | 1,467,719,635 | PR_kwDODunzps5D3rGw | 5,310 | Support xPath for Windows pathnames | {
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"_The documentation is not available anymore as the PR was closed or merged._"
] | 2022-11-29T09:20:47Z | 2022-11-30T12:00:09Z | 2022-11-30T11:57:16Z | MEMBER | null | 0 | {
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} | This PR implements a string representation of `xPath`, which is valid for local paths (also windows) and remote URLs.
Additionally, some `os.path` methods are fixed for remote URLs on Windows machines.
Now, on Windows machines:
```python
In [2]: str(xPath("C:\\dir\\file.txt"))
Out[2]: 'C:\\dir\\file.txt'
In [3]: str(xPath("http://domain.com/file.txt"))
Out[3]: 'http://domain.com/file.txt'
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/6230 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/6230/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/6230/comments | https://api.github.com/repos/huggingface/datasets/issues/6230/events | https://github.com/huggingface/datasets/pull/6230 | 1,890,521,006 | PR_kwDODunzps5aBh6L | 6,230 | Don't skip hidden files in `dl_manager.iter_files` when they are given as input | {
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"<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_a... | 2023-09-11T13:29:19Z | 2023-09-13T18:21:28Z | 2023-09-13T18:12:09Z | CONTRIBUTOR | null | 0 | {
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} | Required for `load_dataset(<format>, data_files=["path/to/.hidden_file"])` to work as expected | {
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