SurAyush/github_issues huggingface dataset:
Issue: feat: 🎸 add a function to get a dataset config's split names
State: closed
Author: severo

Also: pass additional arguments (use_auth_token) to get private configs + info of private datasets on the hub

Questions:

- [x] I'm not sure how the versions work: I changed 1.12.1.dev0 to 1.12.1.dev1, was it correct?
    -> no: reverted
- [x] Should I add a section in https://github.com/huggingface/datasets/blob/master/docs/source/load_hub.rst? (there is no section for get_dataset_infos)
    -> yes: added

Comments:
> Should I add a section in https://github.com/huggingface/datasets/blob/master/docs/source/load_hub.rst? (there is no section for get_dataset_infos)

Yes totally :) This tutorial should indeed mention this, given how fundamental it is
Issue: FORCE_REDOWNLOAD does not work
State: open
Author: anoopkatti

## Describe the bug
With GenerateMode.FORCE_REDOWNLOAD, the documentation says 
    +------------------------------------+-----------+---------+
    |                                    | Downloads | Dataset |
    +====================================+===========+=========+
    | `REUSE_DATASET_IF_EXISTS` (default)| Reuse     | Reuse   |
    +------------------------------------+-----------+---------+
    | `REUSE_CACHE_IF_EXISTS`            | Reuse     | Fresh   |
    +------------------------------------+-----------+---------+
    | `FORCE_REDOWNLOAD`                 | Fresh     | Fresh   |
    +------------------------------------+-----------+---------+

However, the old dataset is loaded even when FORCE_REDOWNLOAD is chosen.

## Steps to reproduce the bug
```python

import pandas as pd
from datasets import load_dataset, GenerateMode
pd.DataFrame(range(5), columns=['numbers']).to_csv('/tmp/test.tsv.gz', index=False)
ee = load_dataset('csv', data_files=['/tmp/test.tsv.gz'], delimiter='\t', split='train', download_mode=GenerateMode.FORCE_REDOWNLOAD)
print(ee)
pd.DataFrame(range(10), columns=['numerals']).to_csv('/tmp/test.tsv.gz', index=False)
ee = load_dataset('csv', data_files=['/tmp/test.tsv.gz'], delimiter='\t', split='train', download_mode=GenerateMode.FORCE_REDOWNLOAD)
print(ee)

```

## Expected results
Dataset({
    features: ['numbers'],
    num_rows: 5
})
Dataset({
    features: ['numerals'],
    num_rows: 10
})

## Actual results
Dataset({
    features: ['numbers'],
    num_rows: 5
})
Dataset({
    features: ['numbers'],
    num_rows: 5
})


## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 1.8.0
- Platform: Linux-4.14.181-108.257.amzn1.x86_64-x86_64-with-glibc2.10
- Python version: 3.7.10
- PyArrow version: 3.0.0


Comments:
Hi ! Thanks for reporting. The error seems to happen only if you use compressed files.

The second dataset is prepared in another dataset cache directory than the first - which is normal, since the source file is different. However, it doesn't uncompress the new data file because it finds the old uncompressed data in the extraction cache directory.

If we fix the extraction cache mechanism to uncompress a local file if it changed then it should fix the issue.
Currently the extraction cache mechanism only takes into account the path of the compressed file, which is an issue.

Facing the same issue, is there any way to overtake this issue until it will be fixed? 

You can clear your extraction cache in the meantime (by default at `~/.cache/huggingface/datasets/downloads/extracted`)
Issue: Add WIT Dataset
State: closed
Author: nateraw

## Adding a Dataset
- **Name:** *WIT*
- **Description:** *Wikipedia-based Image Text Dataset*
- **Paper:** *[WIT: Wikipedia-based Image Text Dataset for Multimodal Multilingual Machine Learning
](https://arxiv.org/abs/2103.01913)*
- **Data:** *https://github.com/google-research-datasets/wit*
- **Motivation:**  (excerpt from their Github README.md)

> - The largest multimodal dataset (publicly available at the time of this writing) by the number of image-text examples.
> - A massively multilingual dataset (first of its kind) with coverage for over 100+ languages.
> - A collection of diverse set of concepts and real world entities.
> - Brings forth challenging real-world test sets.

Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).


Comments:
@hassiahk is working on it  #2810 

WikiMedia is now hosting the pixel values directly which should make it a lot easier!
The files can be found here:
https://techblog.wikimedia.org/2021/09/09/the-wikipedia-image-caption-matching-challenge-and-a-huge-release-of-image-data-for-research/
https://analytics.wikimedia.org/published/datasets/one-off/caption_competition/training/image_pixels/

> @hassiahk is working on it #2810

Thank you @bhavitvyamalik! Added this issue so we could track progress 😄 . Just linked the PR as well for visibility. 

Hey folks, we are now hosting the merged pixel values + embeddings + metadata ourselves. I gave it a try - [nateraw/wit](https://huggingface.co/datasets/nateraw/wit)

**⚠️ - Make sure you add `streaming=True` unless you're prepared to download 400GB of data!**

```python
from datasets import load_dataset

ds = load_dataset('nateraw/wit', streaming=True)
example = next(iter(ds))
```

```python
>>> example = next(iter(ds['train']))
>>> example.keys()
dict_keys(['b64_bytes', 'original_width', 'image_url', 'wit_features', 'original_height', 'metadata_url', 'mime_type', 'caption_attribution_description', 'embedding'])
>>> example['wit_features'].keys()
dict_keys(['hierarchical_section_title', 'language', 'attribution_passes_lang_id', 'context_section_description', 'is_main_image', 'page_title', 'caption_title_and_reference_description', 'caption_alt_text_description', 'caption_reference_description', 'page_url', 'context_page_description', 'section_title', 'page_changed_recently'])
```

Hi! `datasets` now hosts two versions of the WIT dataset:
* [`google/wit`](https://huggingface.co/datasets/google/wit): Google's version with the image URLs
* [`wikimedia/wit_base`](https://huggingface.co/datasets/wikimedia/wit_base): Wikimedia's version with the images + ResNet embeddings, but with less data than Google's version

Does this dataset work with `data_files` parameter. I tried and it doesn't. it attempts to download ~600 GB data even when i specify single file
Issue: Dataset
State: closed
Author: rcacho172

## Adding a Dataset
- **Name:** *name of the dataset*
- **Description:** *short description of the dataset (or link to social media or blog post)*
- **Paper:** *link to the dataset paper if available*
- **Data:** *link to the Github repository or current dataset location*
- **Motivation:** *what are some good reasons to have this dataset*

Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).

Comments:
Issue: Hug emoji
State: closed
Author: Jackg-08

## Adding a Dataset
- **Name:** *name of the dataset*
- **Description:** *short description of the dataset (or link to social media or blog post)*
- **Paper:** *link to the dataset paper if available*
- **Data:** *link to the Github repository or current dataset location*
- **Motivation:** *what are some good reasons to have this dataset*

Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).

Comments:
Issue: Add OpenAI's HumanEval dataset
State: closed
Author: lvwerra

This PR adds OpenAI's [HumanEval](https://github.com/openai/human-eval) dataset. The dataset consists of 164 handcrafted programming problems with solutions and unittests to verify solution. This dataset is useful to evaluate code generation models.

Comments:
I just fixed the class name, and added `[More Information Needed]` in empty sections in case people want to complete the dataset card :)
Issue: add multi-proc in `to_csv`
State: closed
Author: bhavitvyamalik

This PR extends the multi-proc method used in #2747 for`to_json` to `to_csv` as well. 

Results on my machine post benchmarking on `ascent_kb` dataset (giving ~45% improvement when compared to num_proc = 1):
```
Time taken on 1 num_proc, 10000 batch_size  674.2055702209473
Time taken on 4 num_proc, 10000 batch_size  425.6553490161896

Time taken on 1 num_proc, 50000 batch_size  623.5897650718689
Time taken on 4 num_proc, 50000 batch_size  380.0402421951294

Time taken on 4 num_proc, 100000 batch_size  361.7168130874634
```
This is a WIP as writing tests is pending for this PR. 

I'm also exploring [this](https://arrow.apache.org/docs/python/csv.html#incremental-writing) approach for which I'm using `pyarrow-5.0.0`.


Comments:
I think you can just add a test `test_dataset_to_csv_multiproc` in `tests/io/test_csv.py` and we'll be good

Hi @lhoestq, 
I've added `test_dataset_to_csv` apart from `test_dataset_to_csv_multiproc` as no test was there to check generated CSV file when `num_proc=1`. Please let me know if anything is also required!
Issue: Use pyarrow.Table.replace_schema_metadata instead of pyarrow.Table.cast
State: closed
Author: arsarabi

This PR partially addresses #2252.

``update_metadata_with_features`` uses ``Table.cast`` which slows down ``load_from_disk`` (and possibly other methods that use it) for very large datasets. Since ``update_metadata_with_features`` is only updating the schema metadata, it makes more sense to use ``pyarrow.Table.replace_schema_metadata`` which is much faster. This PR adds a ``replace_schema_metadata`` method to all table classes, and modifies  ``update_metadata_with_features`` to use it instead of ``cast``.

Comments:
Issue: add mbpp dataset
State: closed
Author: lvwerra

This PR adds the mbpp dataset introduced by Google [here](https://github.com/google-research/google-research/tree/master/mbpp) as mentioned in #2816.

The dataset contain two versions: a full and a sanitized one. They have a slightly different schema and it is current state the loading preserves the original schema. An open question is whether to harmonize the two schemas when loading the dataset or to preserve the original one. Since not all fields are overlapping the schema will not be exactly the same.

Comments:
I think it's fine to have the original schema
Issue: Error when encoding a dataset with None objects with a Sequence feature
State: closed
Author: lhoestq

There is an error when encoding a dataset with None objects with a Sequence feature

To reproduce:
```python
from datasets import Dataset, Features, Value, Sequence
data = {"a": [[0], None]}
features = Features({"a": Sequence(Value("int32"))})
dataset = Dataset.from_dict(data, features=features)
```
raises

```python
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-24-40add67f8751> in <module>
      2 data = {"a": [[0], None]}
      3 features = Features({"a": Sequence(Value("int32"))})
----> 4 dataset = Dataset.from_dict(data, features=features)
[...]
~/datasets/features.py in encode_nested_example(schema, obj)
    888         if isinstance(obj, str):  # don't interpret a string as a list
    889             raise ValueError("Got a string but expected a list instead: '{}'".format(obj))
--> 890         return [encode_nested_example(schema.feature, o) for o in obj]
    891     # Object with special encoding:
    892     # ClassLabel will convert from string to int, TranslationVariableLanguages does some checks

TypeError: 'NoneType' object is not iterable
```

Instead, if should run without error, as if the `features` were not passed

Comments:
This has been fixed by https://github.com/huggingface/datasets/pull/2900
We're doing a new release 1.12 today to make the fix available :)
Issue: 0x290B112ED1280537B24Ee6C268a004994a16e6CE
State: closed
Author: rcacho172

## Adding a Dataset
- **Name:** *name of the dataset*
- **Description:** *short description of the dataset (or link to social media or blog post)*
- **Paper:** *link to the dataset paper if available*
- **Data:** *link to the Github repository or current dataset location*
- **Motivation:** *what are some good reasons to have this dataset*

Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).

Comments:
Issue: Coc
State: closed
Author: Bwiggity

## Adding a Dataset
- **Name:** *name of the dataset*
- **Description:** *short description of the dataset (or link to social media or blog post)*
- **Paper:** *link to the dataset paper if available*
- **Data:** *link to the Github repository or current dataset location*
- **Motivation:** *what are some good reasons to have this dataset*

Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).

Comments:
Issue: v1.11.1 release date
State: closed
Author: fcakyon

Hello, i need to use latest features in one of my packages but there have been no new datasets release since 2 months ago.

When do you plan to publush v1.11.1 release?

Comments:
Hi ! Probably 1.12 on monday :)


@albertvillanova i think this issue is still valid and should not be closed till `>1.11.0` is published :)
Issue: In v1.4.1, all TIMIT train transcripts are "Would such an act of refusal be useful?"
State: closed
Author: rcgale

## Describe the bug
Using version 1.4.1 of `datasets`, TIMIT transcripts are all the same.

## Steps to reproduce the bug
I was following this tutorial
- https://huggingface.co/blog/fine-tune-wav2vec2-english

But here's a distilled repro:
```python
!pip install datasets==1.4.1
from datasets import load_dataset
timit = load_dataset("timit_asr", cache_dir="./temp")
unique_transcripts = set(timit["train"]["text"])
print(unique_transcripts)
assert len(unique_transcripts) > 1
```
## Expected results
Expected the correct TIMIT data. Or an error saying that this version of `datasets` can't produce it.

## Actual results
Every train transcript was "Would such an act of refusal be useful?" Every test transcript was "The bungalow was pleasantly situated near the shore."

## Environment info
- `datasets` version: 1.4.1
- Platform: Darwin-18.7.0-x86_64-i386-64bit
- Python version: 3.7.9
- PyTorch version (GPU?): 1.9.0 (False)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: tried both
- Using distributed or parallel set-up in script?: no
- 



Comments:
Hi @rcgale, thanks for reporting.

Please note that this bug was fixed on `datasets` version 1.5.0: https://github.com/huggingface/datasets/commit/a23c73e526e1c30263834164f16f1fdf76722c8c#diff-f12a7a42d4673bb6c2ca5a40c92c29eb4fe3475908c84fd4ce4fad5dc2514878

If you update `datasets` version, that should work.

On the other hand, would it be possible for @patrickvonplaten to update the [blog post](https://huggingface.co/blog/fine-tune-wav2vec2-english) with the correct version of `datasets`?

I just proposed a change in the blog post.

I had assumed there was a data format change that broke a previous version of the code, since presumably @patrickvonplaten tested the tutorial with the version they explicitly referenced. But that fix you linked suggests a problem in the code, which surprised me.

I still wonder, though, is there a way for downloads to be invalidated server-side? If the client can announce its version during a download request, perhaps the server could reject known incompatibilities? It would save much valuable time if `datasets` raised an informative error on a known problem ("Error: the requested data set requires `datasets>=1.5.0`."). This kind of API versioning is a prudent move anyhow, as there will surely come a time when you'll need to make a breaking change to data.

Also, thank you for a quick and helpful reply!
Issue: Don't keep the dummy data folder or dataset_infos.json when resolving data files
State: closed
Author: lhoestq

When there's no dataset script, all the data files of a folder or a repository on the Hub are loaded as data files.

There are already a few exceptions:
- files starting with "." are ignored
- the dataset card "README.md" is ignored
- any file named "config.json" is ignored (currently it isn't used anywhere, but it could be used in the future to define splits or configs for example, but not 100% sure)

However any data files in a folder named "dummy" should be ignored as well as they should only be used to test the dataset.
Same for "dataset_infos.json" which should only be used to get the `dataset.info`

Comments:
Hi @lhoestq I am new to huggingface datasets, I would like to work on this issue!


Thanks for the help :) 

As mentioned in the PR, excluding files named "dummy_data.zip" is actually more general than excluding the files inside a "dummy" folder. I just did the change in the PR, I think we can merge it now
Issue: Extend support for streaming datasets that use pathlib.Path.glob
State: closed
Author: albertvillanova

This PR extends the support in streaming mode for datasets that use `pathlib`, by patching the method `pathlib.Path.glob`.

Related to #2874, #2866.

CC: @severo

Comments:
I am thinking that ideally we should call `fs.glob()` instead...

Thanks, @lhoestq: the idea of adding the mock filesystem is to avoid network calls and reduce testing time ;) 

I have added `rglob` as well and fixed some bugs.
Issue: Add Congolese Swahili speech datasets
State: open
Author: osanseviero

## Adding a Dataset
- **Name:** Congolese Swahili speech corpora
- **Data:** https://gamayun.translatorswb.org/data/

Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).

Also related: https://mobile.twitter.com/OktemAlp/status/1435196393631764482

Comments:
Issue: Support streaming datasets that use pathlib
State: closed
Author: albertvillanova

This PR extends the support in streaming mode for datasets that use `pathlib.Path`.

Related to: #2866.
CC: @severo 

Comments:
I've tried https://github.com/huggingface/datasets/issues/2866 again, and I get the same error.

```python
import datasets as ds
ds.load_dataset('counter', split="train", streaming=False)
```

@severo Issue #2866 is not fully fixed yet: multiple patches need to be implemented for `pathlib`, as that dataset uses quite a lot of `pathlib` functions... 😅 

No worry and no stress, I just wanted to check for that case :) I'm very happy that you're working on issues I'm interested in!
Issue: adding swedish_medical_ner
State: closed
Author: bwang482

Adding the Swedish Medical NER dataset, listed in "Biomedical Datasets - BigScience Workshop 2021"

Code refactored 

Comments:
Hi, what's the current status of this request? It says Changes requested, but I can't see what changes?

Hi, it looks like this PR includes changes to other files that `swedish_medical_ner`.

Feel free to remove these changes, or simply create a new PR that only contains the addition of the dataset
Issue: datasets.config.PYARROW_VERSION has no attribute 'major'
State: closed
Author: bwang482

In the test_dataset_common.py script, line 288-289

```
if datasets.config.PYARROW_VERSION.major < 3:
   packaged_datasets = [pd for pd in packaged_datasets if pd["dataset_name"] != "parquet"]
```

which throws the error below. `datasets.config.PYARROW_VERSION` itself return the string '4.0.1'. I have tested this on both datasets.__version_=='1.11.0' and '1.9.0'. I am using Mac OS.

```
import datasets
datasets.config.PYARROW_VERSION.major
---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
/var/folders/1f/0wqmlgp90qjd5mpj53fnjq440000gn/T/ipykernel_73361/2547517336.py in <module>
      1 import datasets
----> 2 datasets.config.PYARROW_VERSION.major

AttributeError: 'str' object has no attribute 'major'
```

## Environment info
- `datasets` version: 1.11.0
- Platform: Darwin-20.6.0-x86_64-i386-64bit
- Python version: 3.7.11
- PyArrow version: 4.0.1


Comments:
I have changed line 288 to `if int(datasets.config.PYARROW_VERSION.split(".")[0]) < 3:` just to get around it.

Hi @bwang482,

I'm sorry but I'm not able to reproduce your bug.

Please note that in our current master branch, we made a commit (d03223d4d64b89e76b48b00602aba5aa2f817f1e) that simultaneously modified:
- test_dataset_common.py: https://github.com/huggingface/datasets/commit/d03223d4d64b89e76b48b00602aba5aa2f817f1e#diff-a1bc225bd9a5bade373d1f140e24d09cbbdc97971c2f73bb627daaa803ada002L289 that introduces the usage of `datasets.config.PYARROW_VERSION.major`
- but also changed config.py: https://github.com/huggingface/datasets/commit/d03223d4d64b89e76b48b00602aba5aa2f817f1e#diff-e021fcfc41811fb970fab889b8d245e68382bca8208e63eaafc9a396a336f8f2L40, so that `datasets.config.PYARROW_VERSION.major` exists


Sorted. Thanks!

Reopening this. Although the `test_dataset_common.py` script works fine now.

Has this got something to do with my pull request not passing `ci/circleci: run_dataset_script_tests_pyarrow` tests?

https://github.com/huggingface/datasets/pull/2873

Hi @bwang482,

If you click on `Details` (on the right of your non passing CI test names: `ci/circleci: run_dataset_script_tests_pyarrow`), you can have more information about the non-passing tests.

For example, for ["ci/circleci: run_dataset_script_tests_pyarrow_1" details](https://circleci.com/gh/huggingface/datasets/46324?utm_campaign=vcs-integration-link&utm_medium=referral&utm_source=github-build-link), you can see that the only non-passing test has to do with the dataset card (missing information in the `README.md` file): `test_changed_dataset_card`
```
=========================== short test summary info ============================
FAILED tests/test_dataset_cards.py::test_changed_dataset_card[swedish_medical_ner]
= 1 failed, 3214 passed, 2874 skipped, 2 xfailed, 1 xpassed, 15 warnings in 175.59s (0:02:55) =
```

Therefore, your PR non-passing test has nothing to do with this issue.
Issue: Add Common Objects in 3D (CO3D)
State: open
Author: nateraw

## Adding a Dataset
- **Name:** *Common Objects in 3D (CO3D)*
- **Description:** *See blog post [here](https://ai.facebook.com/blog/common-objects-in-3d-dataset-for-3d-reconstruction)*
- **Paper:** *[link to paper](https://arxiv.org/abs/2109.00512)*
- **Data:** *[link to data](https://ai.facebook.com/datasets/co3d-downloads/)*
- **Motivation:** *excerpt from above blog post:*

> As the first data set of its kind, CO3D will aptly enable reconstruction of real-life 3D objects. Indeed, CO3D already provides training data to enable our NeRFormer to tackle the new-view synthesis (NVS) task. Here, photorealistic NVS is a major step on the path to fully immersive AR/VR effects, where objects can be virtually transported across different environments, which will allow connecting users by sharing or recollecting their experiences.
> 
> Besides practical applications in AR/VR, we hope that the data set will become a standard testbed for the recent proliferation of methods (including NeRFormer, Implicit Differentiable Renderer, NeRF, and others) that reconstruct 3D scenes by means of an implicit shape model.
> 

Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).


Comments:
Issue: Add CaSiNo dataset
State: closed
Author: kushalchawla

Hi. I request you to add our dataset to the repository. 

This data was recently published at NAACL 2021: https://aclanthology.org/2021.naacl-main.254.pdf

Comments:
Hi @lhoestq  

Just a request to look at the dataset. Please let me know if any changes are necessary before merging it into the repo. Thank you.

Hey @lhoestq 

Thanks for merging it. One question: I still cannot find the dataset on https://huggingface.co/datasets. Does it take some time or did I miss something?

Hi ! It takes a few hours or a day for the list of datasets on the website to be updated ;)