NyssaW/github-issues huggingface dataset:
[LibriSpeech] Fix dev split local_extracted_archive for 'all' config

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.


Comments:
_The documentation is not available anymore as the PR was closed or merged._

This PR fixes a bug introduced in:
- #4184
Name the default config `default`

Currently, if a dataset has no configuration, a default configuration is created from the dataset name.

For example, for a dataset loaded from the hub repository, such as https://huggingface.co/datasets/user/dataset (repo id is `user/dataset`), the default configuration will be `user--dataset`.

It might be easier to handle to set it to `default`, or another reserved word.

Comments:
Addressed in #5331.
Re-add code and und language tags

This PR fixes the removal of 2 language tags done by:
- #4882

The tags are:
- "code": this is not a IANA tag but needed
- "und": this is one of the special scoped tags removed by 0d53202b9abce6fd0358cb00d06fcfd904b875af
  - used in "mc4" and "udhr" datasets

Comments:
_The documentation is not available anymore as the PR was closed or merged._
Dataset Viewer issue for timit_asr

### Link

_No response_

### Description

_No response_

### Owner

_No response_

Comments:
Yes, the dataset viewer is based on `datasets`, and the following does not work:

```
>>> from datasets import get_dataset_split_names
>>> get_dataset_split_names('timit_asr')
Downloading builder script: 7.48kB [00:00, 6.69MB/s]
Traceback (most recent call last):
  File "/home/slesage/hf/datasets-server/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 354, in get_dataset_config_info
    for split_generator in builder._split_generators(
  File "/home/slesage/.cache/huggingface/modules/datasets_modules/datasets/timit_asr/43f9448dd5db58e95ee48a277f466481b151f112ea53e27f8173784da9254fb2/timit_asr.py", line 117, in _split_generators
    data_dir = os.path.abspath(os.path.expanduser(dl_manager.manual_dir))
  File "/home/slesage/.pyenv/versions/3.9.6/lib/python3.9/posixpath.py", line 231, in expanduser
    path = os.fspath(path)
TypeError: expected str, bytes or os.PathLike object, not NoneType

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/slesage/hf/datasets-server/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 404, in get_dataset_split_names
    info = get_dataset_config_info(
  File "/home/slesage/hf/datasets-server/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 359, in get_dataset_config_info
    raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.
```

cc @huggingface/datasets 

Due to license restriction, this dataset needs manual downloading of the original data.

This information is in the dataset card: https://huggingface.co/datasets/timit_asr
> The dataset needs to be downloaded manually from https://catalog.ldc.upenn.edu/LDC93S1

Maybe a better error message for datasets that need manual downloading? @severo 

Maybe we can raise a specific excpetion as done from `load_dataset`...

Yes, ideally something like https://github.com/huggingface/datasets/blob/main/src/datasets/builder.py#L81


The preview is now disabled (and a descriptive warning is displayed) for datasets requiring manual download. See:

![timit_asr-manual-download](https://user-images.githubusercontent.com/8515462/193578572-3d21b790-f848-4257-9e9b-7cab3d76a269.png)
datasets generate large arrow file

Checking the large file in disk, and found the large cache file in the cifar10 data directory:

![image](https://user-images.githubusercontent.com/18533904/186830449-ba96cdeb-0fe8-4543-994d-2abe7145933f.png)

As we know, the size of cifar10 dataset is ~130MB, but the cache file has almost 30GB size, there may be some problems here.

Comments:
Hi ! The cache files are the results of all the transforms you applied to the dataset using `map` for example.
Did you run a transform that could potentially blow up the size of the dataset ?

@lhoestq,
I don't remember, but I can't imagine what kind of transform may generate data that grow over 200 times in size. 
I think maybe it doesn' matter, it's just cache after all.
Fix missing tags in dataset cards

Fix missing tags in dataset cards:
- anli
- coarse_discourse
- commonsense_qa
- cos_e
- ilist
- lc_quad
- web_questions
- xsum

This PR partially fixes the missing tags in dataset cards. Subsequent PRs will follow to complete this task.

Related to:
- #4833
- #4891

Comments:
_The documentation is not available anymore as the PR was closed or merged._
Add citation to ro_sts and ro_sts_parallel datasets

This PR adds the citation information to `ro_sts_parallel` and `ro_sts_parallel` datasets, once they have replied our request for that information:
- https://github.com/dumitrescustefan/RO-STS/issues/4

Comments:
The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_4892). All of your documentation changes will be reflected on that endpoint.
add Dataset.from_list

As discussed in #4885 

I initially added this bit at the end, thinking filling this field was necessary as it is done in from_dict. 
However, it seems the constructor takes care of filling info when it is empty.
```
if info.features is None:
  info.features = Features(
      {
          col: generate_from_arrow_type(coldata.type)
          for col, coldata in zip(pa_table.column_names, pa_table.columns)
      }
  )
```

Comments:
_The documentation is not available anymore as the PR was closed or merged._

@albertvillanova it seems tests fail on pyarrow 6, perhaps from_pylist is a v7 method? How do you usually handle these version differences?
Added something that at least works
Dataset Viewer issue for subjqa

### Link

https://huggingface.co/datasets/subjqa

### Description

Getting the following error for this dataset:

```
Status code:   500
Exception:     Status500Error
Message:       2 or more items returned, instead of 1
```

Not sure what's causing it though 🤔 

### Owner

Yes

Comments:
It's a bug in the viewer, thanks for reporting it. We're hoping to update to a new version in the next few days which should fix it.

Fixed 

https://huggingface.co/datasets/subjqa

<img width="1040" alt="Capture d’écran 2022-09-08 à 10 23 26" src="https://user-images.githubusercontent.com/1676121/189073210-2a57ff88-8bb1-44bd-851e-0e75473cea3f.png">
Create dataset from list of dicts

I often find myself with data from a variety of sources, and a list of dicts is very common among these.
However, converting this to a Dataset is a little awkward, requiring either

```Dataset.from_pandas(pd.DataFrame(formatted_training_data))```
Which can error out on some more exotic values as 2-d arrays for reasons that are not entirely clear
> ArrowInvalid: ('Can only convert 1-dimensional array values', 'Conversion failed for column labels with type object')

Alternatively:
```Dataset.from_dict({k: [s[k] for s in formatted_training_data] for k in  formatted_training_data[0].keys()})```
Which works, but is a little ugly.

**Describe the solution you'd like**
Either `.from_dict` accepting a list of dicts, or a `.from_records` function accepting such.

I am happy to PR this, just wanted to check you are happy to accept this I haven't missed something obvious, and which of the solutions would be prefered.


Comments:
Hi @sanderland, thanks for your enhancement proposal.

I agree with you that this would be useful.

Please note that under the hood, we use PyArrow tables as backend:
- The implementation  of `Dataset.from_dict` uses the PyArrow `Table.from_pydict`

Therefore, I would suggest:
- Implementing `Dataset.from_list` using the PyArrow `Table.from_pylist`

What do you think?
Let's see if other people have other suggestions...

Thanks for the quick and positive reply @albertvillanova! 
`from_list` seems sensible. Have opened a PR so we can discuss details there.

Resolved via #4890.
Fix language tags resource file

This PR fixes/updates/adds ALL language tags from IANA (as of 2022-08-08).

This PR also removes all BCP47 suffixes (the languages file only contains language subtags, i.e. ISO 639 1 or 2 codes; no script/region/variant suffixes). See:
- #4753

Comments:
The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_4882). All of your documentation changes will be reflected on that endpoint.
Added names of less-studied languages

Added names of less-studied languages (nru – Narua and jya – Japhug) for existing datasets.

Comments:
OK, I removed Glottolog codes and only added ISO 639-3 ones. The former are for the moment in corpus card description, language details, and in subcorpora names.

The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_4880). All of your documentation changes will be reflected on that endpoint.
Fix Citation Information section in dataset cards

Fix Citation Information section in dataset cards:
- cc_news
- conllpp
- datacommons_factcheck
- gnad10
- id_panl_bppt
- jigsaw_toxicity_pred
- kinnews_kirnews
- kor_sarcasm
- makhzan
- reasoning_bg
- ro_sts
- ro_sts_parallel
- sanskrit_classic
- telugu_news
- thaiqa_squad
- wiki_movies

This PR partially fixes the Citation Information section in dataset cards. Subsequent PRs will follow to complete this task.

Comments:
The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_4879). All of your documentation changes will be reflected on that endpoint.
[not really a bug] `identical_ok` is deprecated in huggingface-hub's `upload_file`

In the huggingface-hub dependency, the `identical_ok` argument has no effect in `upload_file` (and it will be removed soon)

See

https://github.com/huggingface/huggingface_hub/blob/43499582b19df1ed081a5b2bd7a364e9cacdc91d/src/huggingface_hub/hf_api.py#L2164-L2169

It's used here:

https://github.com/huggingface/datasets/blob/fcfcc951a73efbc677f9def9a8707d0af93d5890/src/datasets/dataset_dict.py#L1373-L1381

https://github.com/huggingface/datasets/blob/fdcb8b144ce3ef241410281e125bd03e87b8caa1/src/datasets/arrow_dataset.py#L4354-L4362

https://github.com/huggingface/datasets/blob/fdcb8b144ce3ef241410281e125bd03e87b8caa1/src/datasets/arrow_dataset.py#L4197-L4213

We should remove it.

Maybe the third code sample has an unexpected behavior since it uses the non-default value `identical_ok = False`, but the argument is ignored.

Comments:
Resolved via https://github.com/huggingface/datasets/pull/4937.
Multiple dataloader memory error

For the use of multiple datasets and tasks, we use around more than 200+ dataloaders, then pass it into `dataloader1, dataloader2, ..., dataloader200=accelerate.prepare(dataloader1, dataloader2, ..., dataloader200)`
It causes the memory error when generating batches. Any solutions to it?

```bash
  File "/home/xxx/my_code/src/utils/data_utils.py", line 54, in generate_batch
    x = next(iterator)
  File "/home/xxx/anaconda3/envs/pt1.7/lib/python3.7/site-packages/accelerate/data_loader.py", line 301, in __iter__
    for batch in super().__iter__():
  File "/home/xxx/anaconda3/envs/pt1.7/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 435, in __next__
    data = self._next_data()
  File "/home/xxx/anaconda3/envs/pt1.7/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 475, in _next_data
    data = self._dataset_fetcher.fetch(index)  # may raise StopIteration
  File "/home/xxx/anaconda3/envs/pt1.7/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 28, in fetch
    data.append(next(self.dataset_iter))
  File "/home/xxx/anaconda3/envs/pt1.7/lib/python3.7/site-packages/accelerate/data_loader.py", line 249, in __iter__
    for element in self.dataset:
  File "/home/xxx/anaconda3/envs/pt1.7/lib/python3.7/site-packages/datasets/iterable_dataset.py", line 503, in __iter__
    for key, example in self._iter():
  File "/home/xxx/anaconda3/envs/pt1.7/lib/python3.7/site-packages/datasets/iterable_dataset.py", line 500, in _iter
    yield from ex_iterable
  File "/home/xxx/anaconda3/envs/pt1.7/lib/python3.7/site-packages/datasets/iterable_dataset.py", line 231, in __iter__
    new_key = "_".join(str(key) for key in keys)
MemoryError
```

Comments:
Hi!

200+ data loaders is a lot. Have you tried to reduce the number of datasets by concatenating/interleaving the ones with the same structure/task (the API is `{concatenate_datasets/interleave_datasets}([dset1, ..., dset_N])`)?

Hi @mariosasko, thank you for your reply. I tried pre-concatenating different datasets into one, but one key need is to keep each batch the same data type. Considering that the concatenate-then-segment operation for prefetched samples may span across different data types after concatenating/interleaving (cuz different data sources are mixed), any solution to remain the same data source for each batch?

@cyk1337 have you found any solutions to it?
@mariosasko I tried with interleave_datasets to sample batches from two large datasets (wikipedia alike) and it results in out-of-memory error during data loading (16gpus, >1TB physical memory). Do you have any idea about it?
Docs for creating an audio dataset

This PR is a first draft of how to create audio datasets (`AudioFolder` and loading script). Feel free to let me know if there are any specificities I'm missing for this. 🙂

Comments:
_The documentation is not available anymore as the PR was closed or merged._

Awesome thanks ! I think we can also encourage TAR archives as for image dataset scripts (feel free to copy paste some parts from there lol)

Thanks for all the great feedback @polinaeterna and @lhoestq! 🥰

I added all the other feedback, and I'll look into the `librivox-indonesia` script now!

If you don't mind, I'm taking over this PR since we'll do a release pretty soon

@lhoestq no, I do :D 

haha sorry ^^
Fix: wmt datasets - fix CWMT zh subsets

Fix https://github.com/huggingface/datasets/issues/4575

TODO: run `datasets-cli test`:
- [x] wmt17
- [x] wmt18
- [x] wmt19

Comments:
The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_4871). All of your documentation changes will be reflected on that endpoint.
adding mafand to datasets

I'm addding the MAFAND dataset by Masakhane based on the paper/repository below:

Paper: https://aclanthology.org/2022.naacl-main.223/
Code: https://github.com/masakhane-io/lafand-mt

Please, help merge this

Everything works except for creating dummy data file

Comments:
_The documentation is not available anymore as the PR was closed or merged._

Hi @dadelani, thanks for your awesome contribution!!! :heart: 

However, now we are using the Hub to add new datasets, instead of this GitHub repo. 

You could share this dataset under your Hub organization namespace: [Masakhane NLP](https://huggingface.co/masakhane). This way the dataset will be accessible using:
```python
ds = load_dataset("masakhane/mafand")
```

You have the procedure documented in our online docs: 
- [Create a dataset loading script](https://huggingface.co/docs/datasets/dataset_script)
- [Share](https://huggingface.co/docs/datasets/share)

Moreover, datasets shared on the Hub no longer need the dummy data files.

Please, feel free to ping me if you need any further guidance/support.

thank you for the comment. I have moved it to the Hub https://huggingface.co/datasets/masakhane/mafand

Great job, @dadelani!!

Please, note that in the README.md file, the YAML tags should be preceded and followed by three dashes `---`, so that they are properly parsed. See, e.g.: https://raw.githubusercontent.com/huggingface/datasets/main/templates/README.md

Also you could replace the line:
```
# Dataset Card for [Needs More Information]
```
with
```
# Dataset Card for MAFAND-MT
```

Great, thank you for the feedback. I have fixed both issues.
Dataset Viewer issue for MoritzLaurer/multilingual_nli

### 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

_No response_

Comments:
Thanks for reporting  @MoritzLaurer.

Currently, the dataset preview is working properly: https://huggingface.co/datasets/MoritzLaurer/multilingual_nli

Please note that when a dataset is modified, it might take some time until the preview is completely updated.

@severo might it be worth adding a clearer error message, something like "The preview is updating, please retry later"?

Thanks for your response. You are right, its now working well. I had waited for 30 min or so and refreshed several times and thought there was some other error. Yeah, a different error message sounds like a good idea to avoid confusion. 

I'm closing this issue then.

> @severo might it be worth adding a clearer error message, something like "The preview is updating, please retry later"?

Yes, it's a known issue, and we're about to ship a better version
Allow pathlib PoxisPath in Dataset.read_json

**Is your feature request related to a problem? Please describe.**
```
from pathlib import Path
from datasets import Dataset
ds = Dataset.read_json(Path('data.json'))
```
causes an error
```
AttributeError: 'PosixPath' object has no attribute 'decode'
```

**Describe the solution you'd like**

It should be able to accept PosixPath and read the json from inside.

Comments:
This same error will occur using `ds = datasets.load_dataset('json', data_files=['test.jsonl'])`

@cccntu I want to make a quick fix for this, but I am struggling to find where the json dataset builder is. Do you know?

@vvvm23 I think you mean think:
```python
ds = datasets.load_dataset('json', data_files=[Path('test.jsonl')])
```
And the place you want to modify is here:
```
utils/file_utils.py:64, in is_remote_url(url_or_filename)
     63 def is_remote_url(url_or_filename: str) -> bool:
---> 64     parsed = urlparse(url_or_filename)
     65     return parsed.scheme in ("http", "https", "s3", "gs", "hdfs", "ftp")
```

Probably just need to check first if `url_or_filename` is [PathLike](https://docs.python.org/3/library/os.html#os.PathLike) and return False early.

Btw, I tried installing from main, and ran my code above and got a different error. Probably because the API have changed.
`AttributeError: module 'datasets' has no attribute 'read_json'`


> @vvvm23 I think you mean think:

You are correct, thanks!

> Probably just need to check first if url_or_filename is [PathLike](https://docs.python.org/3/library/os.html#os.PathLike) and return False early.

Is PathLike sufficient, or should I check the file exists here? Or is that handled later?

I think here we just want to avoid passing Path to urlparse. A simpler solution is to add a str() call and convert the input to string before passing to the next step. No need to check anything.

Above PR should do your first suggestion. Hope that works for you, as I am going on holiday and won't be able to change much :wink: 

I just came across this problem with `DatasetDict.from_parquet()`. The error still seems to originate from the same place:
```
  File "/usr/local/lib/python3.12/dist-packages/datasets/utils/file_utils.py", line 88, in is_relative_path
    return urlparse(url_or_filename).scheme == "" and not os.path.isabs(url_or_filename)
           ^^^^^^^^^^^^^^^^^^^^^^^^^
```
The PR looks like it would still solve everything. Is there a reason this got delayed?
TFDS wiki_dialog dataset to Huggingface dataset

## Adding a Dataset
- **Name:** *Wiki_dialog*
- **Description: https://github.com/google-research/dialog-inpainting#:~:text=JSON%20object%2C%20for-,example,-%3A
- **Paper: https://arxiv.org/abs/2205.09073
- **Data: https://github.com/google-research/dialog-inpainting
- **Motivation:** *Research and Development on biggest corpus of dialog data*

Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/main/ADD_NEW_DATASET.md).


Comments:
@albertvillanova any help ? The linked dataset is in beam format which is similar to wikipedia dataset in huggingface that you  scripted..

Nvm, I was able to port it to huggingface datasets, will upload to the hub soon

https://huggingface.co/datasets/djaym7/wiki_dialog

Thanks for the addition, @djaym7.
Using disk for memory with the method `from_dict`

**Is your feature request related to a problem? Please describe.**
I start with an empty dataset. In a loop, at each iteration, I create a new dataset with the method `from_dict` (based on some data I load) and I concatenate this new dataset with the one at the previous iteration. After some iterations, I have an OOM error.

**Describe the solution you'd like**
The method `from_dict` loads the data in RAM. It could be good to add an option to use the disk instead.

**Describe alternatives you've considered**
To solve the problem, I have to do an intermediate step where I save the new datasets at each iteration with `save_to_disk`. Once it's done, I open them all and concatenate them.


Comments:
This issue was also causing an OOM in @nateraw 's workflow and shows again that behavior is confusing - we should definitely switch to using the disk IMO
Add collection3 dataset


Comments:
Hi @pefimov. Thanks for you awesome work on this dataset contribution.

However, now we are using the Hub to add new datasets, instead of this GitHub repo. 

You could share this dataset under the appropriate Hub organization namespace. This way the dataset will be accessible using:
```python
ds = load_dataset("<org_namespace>/collection3")
```

You have the procedure documented in our online docs: 
- [Create a dataset loading script](https://huggingface.co/docs/datasets/dataset_script)
- [Share](https://huggingface.co/docs/datasets/share)

Moreover, datasets shared on the Hub no longer need the dummy data files.

Please, feel free to ping me if you need any further guidance/support. 

> However, now we are using the Hub to add new datasets, instead of this GitHub repo.
> 
> You could share this dataset under the appropriate Hub organization namespace. This way the dataset will be accessible using:
> 
> ```python
> ds = load_dataset("<org_namespace>/collection3")
> ```
> 
Hi @albertvillanova . Thank you for your response.

I thought that Collection3 is large and important dataset in Russian presented in 2016 but not represented in huggingface.

Also I am not related to authors or organisation of dataset

The current policy of sharing datasets on the Hub instead of in this GitHub repo has no relation with the importance of the dataset: https://huggingface.co/docs/datasets/share#datasets-on-github-legacy 
> The distinction between a Hub dataset and a dataset from GitHub only comes from the legacy sharing workflow. It does not involve any ranking, decisioning, or opinion regarding the contents of the dataset itself.

It is not required to be an author/owner (or belong to the organization that is owner) of the dataset in order to share it on the Hub (as it was not the case when sharing them on this GitHub repo). 

It is recommended to share it under an organization namespace that makes sense though. For this specific dataset, do you know of a clear organization under which it could be shared on the Hub? Maybe "labinform", or "Information Research Laboratory" or "Lomonosov Moscow State University"?

In cases like this, where the org is not evident, one possibility could be to contact the dataset owners/creators and ask them. According the publication paper, the authors are:
- V.A. Mozharova
- N.V. Loukachevitch

I think maybe it would be worth contacting them.

@pefimov I have contacted the authors (and put you in CC).

Reply from the authors:
> It is better to use name: Research Computing Center of Lomonosov Moscow State University (short name RCC-MSU)
> https://rcc.msu.ru/en

I have created the corresponding org namespace and dataset empty repository: https://huggingface.co/datasets/RCC-MSU/collection3

@pefimov feel free to open a PR on the Hub if you are willing to do so: 
- Go to the *Community* tab on the repo: https://huggingface.co/datasets/RCC-MSU/collection3/discussions
- And click: *New pull request* button

Docs: [Pull requests and Discussions](https://huggingface.co/docs/hub/repositories-pull-requests-discussions) on the Hub

Thanks
can't install using conda on Windows 10

## Describe the bug
I wanted to install using conda or Anaconda navigator. That didn't work, so I had to install using pip.

## Steps to reproduce the bug
conda install -c huggingface -c conda-forge datasets

## Expected results
Should have indicated successful installation.

## Actual results
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Solving environment: failed with repodata from current_repodata.json, will retry with next repodata source.
... took forever, so I cancelled it with ctrl-c

## Environment info
- `datasets` version: 2.4.0  # after installing with pip
- Platform: Windows-10-10.0.19044-SP0
- Python version: 3.9.12
- PyArrow version: 9.0.0
- Pandas version: 1.4.2
- conda version: 4.13.0

conda info

     active environment : base
    active env location : G:\anaconda2022
            shell level : 1
       user config file : C:\Users\michael\.condarc
 populated config files : C:\Users\michael\.condarc
          conda version : 4.13.0
    conda-build version : 3.21.8
         python version : 3.9.12.final.0
       virtual packages : __cuda=11.1=0
                          __win=0=0
                          __archspec=1=x86_64
       base environment : G:\anaconda2022  (writable)
      conda av data dir : G:\anaconda2022\etc\conda
  conda av metadata url : None
           channel URLs : https://conda.anaconda.org/pytorch/win-64
                          https://conda.anaconda.org/pytorch/noarch
                          https://conda.anaconda.org/huggingface/win-64
                          https://conda.anaconda.org/huggingface/noarch
                          https://conda.anaconda.org/conda-forge/win-64
                          https://conda.anaconda.org/conda-forge/noarch
                          https://conda.anaconda.org/anaconda-fusion/win-64
                          https://conda.anaconda.org/anaconda-fusion/noarch
                          https://repo.anaconda.com/pkgs/main/win-64
                          https://repo.anaconda.com/pkgs/main/noarch
                          https://repo.anaconda.com/pkgs/r/win-64
                          https://repo.anaconda.com/pkgs/r/noarch
                          https://repo.anaconda.com/pkgs/msys2/win-64
                          https://repo.anaconda.com/pkgs/msys2/noarch
          package cache : G:\anaconda2022\pkgs
                          C:\Users\michael\.conda\pkgs
                          C:\Users\michael\AppData\Local\conda\conda\pkgs
       envs directories : G:\anaconda2022\envs
                          C:\Users\michael\.conda\envs
                          C:\Users\michael\AppData\Local\conda\conda\envs
               platform : win-64
             user-agent : conda/4.13.0 requests/2.27.1 CPython/3.9.12 Windows/10 Windows/10.0.19044
          administrator : False
             netrc file : None
           offline mode : False


Comments:
map() function removes columns when input_columns is not None

## Describe the bug
The map function, removes features from the dataset that are not present in the _input_columns_ list of columns, despite the columns being removed not mentioned in the _remove_columns_ argument.
## Steps to reproduce the bug
```python
from datasets import Dataset
ds = Dataset.from_dict({"a" : [1,2,3],"b" : [0,1,0], "c" : [2,4,5]})

def double(x,y):
  x = x*2
  y = y*2
  return {"d" : x, "e" : y}

ds.map(double, input_columns=["a","c"])
```

## Expected results
```
Dataset({
    features: ['a', 'b', 'c', 'd', 'e'],
    num_rows: 3
})
```
## Actual results
```
Dataset({
    features: ['a', 'c', 'd', 'e'],
    num_rows: 3
})
```

In this specific example feature **b** should not be removed.

## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 2.4.0
- Platform: linux (colab)
- Python version: 3.7.13
- PyArrow version: 6.0.1


Comments:
Hi! Thanks for reporting! This looks like a bug. I've just opened a PR with the fix.

Awesome! Thank you. I'll close the issue once the PR gets merged. :-)

I guess we should reopen after the revert by:
- #5006
No preprocessed wikipedia is working on huggingface/datasets

## Describe the bug
20220301 wikipedia dump has been deprecated, so now there is no working wikipedia dump on huggingface

https://huggingface.co/datasets/wikipedia

https://dumps.wikimedia.org/enwiki/




Comments:
Thanks for reporting @aninrusimha.

Please, note that the preprocessed datasets are still available, as described in the dataset card, e.g.: https://huggingface.co/datasets/wikipedia
```python
ds = load_dataset("wikipedia", "20220301.en")
``` 

This is working now, but I was getting an error a few days ago when running an existing script. Unfortunately I did not do a proper bug report, but for some reason I was unable to load the dataset due to a request being made to the wikimedia website. However, its working now. Thanks for the reply!
file missing when load_dataset with openwebtext on windows

## Describe the bug
0015896-b1054262f7da52a0518521e29c8e352c.txt is missing when I run run_mlm.py with openwebtext. I check the cache_path and can not find 0015896-b1054262f7da52a0518521e29c8e352c.txt. but I can find this file in the 17ecf461bfccd469a1fbc264ccb03731f8606eea7b3e2e8b86e13d18040bf5b3/urlsf_subset00-16_data.xz  with 7-zip.

## Steps to reproduce the bug
```sh
python run_mlm.py --model_type roberta --tokenizer_name roberta-base --dataset_name openwebtext --per_device_train_batch_size 8 --per_device_eval_batch_size 8 --do_train --do_eval --output_dir F:/model/roberta-base
```
or 
```python
from datasets import load_dataset
load_dataset("openwebtext", None, cache_dir=None, use_auth_token=None)
```

## Expected results
Loading is successful
## Actual results
Traceback (most recent call last):
  File "D:\Python\v3.8.5\lib\site-packages\datasets\builder.py", line 704, in download_and_prepare
    self._download_and_prepare(
  File "D:\Python\v3.8.5\lib\site-packages\datasets\builder.py", line 1227, in _download_and_prepare
    super()._download_and_prepare(dl_manager, verify_infos, check_duplicate_keys=verify_infos)
  File "D:\Python\v3.8.5\lib\site-packages\datasets\builder.py", line 795, in _download_and_prepare
    raise OSError(
OSError: Cannot find data file. 
Original error:
[Errno 22] Invalid argument: 'F://huggingface/datasets/downloads/extracted/0901d27f43b7e9ac0577da0d0061c8c632ba0b70ecd1b4bfb21562d9b7486faa/0015896-b1054262f7da52a0518521e29c8e352c.txt'

## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 2.4.0
- Platform: windows
- Python version: 3.8.5 
- PyArrow version: 9.0.0


Comments:
I have tried to extract ```0015896-b1054262f7da52a0518521e29c8e352c.txt``` from ```17ecf461bfccd469a1fbc264ccb03731f8606eea7b3e2e8b86e13d18040bf5b3/urlsf_subset00-16_data.xz``` with 7-zip
and put the file into cache_path ```F://huggingface/datasets/downloads/extracted/0901d27f43b7e9ac0577da0d0061c8c632ba0b70ecd1b4bfb21562d9b7486faa```
there is still raise the same error and I  find the file  was removed from cache_path after I run the run_mlm.py with ```python run_mlm.py --model_type roberta --tokenizer_name roberta-base --dataset_name openwebtext --per_device_train_batch_size 8 --per_device_eval_batch_size 8 --do_train --do_eval --output_dir F:/model/roberta-base```.
Fix test of _get_extraction_protocol for TAR files

While working in another PR, I discovered an xpass test (a test that is supposed to xfail but nevertheless passes) when testing `_get_extraction_protocol`: https://github.com/huggingface/datasets/runs/7818845285?check_suite_focus=true
```
XPASS tests/test_streaming_download_manager.py::test_streaming_dl_manager_get_extraction_protocol_throws[https://foo.bar/train.tar] 
```

This PR:
- refactors the test so that it tests the raise of the exceptions instead of xfailing
- fixes the test for TAR files: it does not raise an exception, but returns "tar"
- fixes some tests wrongly named: exchange `test_streaming_dl_manager_get_extraction_protocol` with `test_streaming_dl_manager_get_extraction_protocol_gg_drive`

Comments:
_The documentation is not available anymore as the PR was closed or merged._
Update documentation card of miam dataset

Hi !
Paper has been published at EMNLP.

Comments:
_The documentation is not available anymore as the PR was closed or merged._

Ahahah :D not sur how i broke something by updating the README :D 

Thanks for the fix @PierreColombo. 

Once a README is modified, our CI runs tests on it, requiring additional quality fixes, so that all READMEs are progressively improved and have some minimal tags/sections/information.

For this specific README file, the additional quality requirements of the CI are: https://github.com/huggingface/datasets/runs/7819924428?check_suite_focus=true
```
E           The following issues were found for the README at `/home/runner/work/datasets/datasets/datasets/miam/README.md`:
E           -	Section `Additional Information` is missing subsection: `Dataset Curators`.
E           -	Section `Additional Information` is missing subsection: `Contributions`.
E           -	`Additional Information` has an extra subsection: `Benchmark Curators`. Skipping further validation checks for this subsection as expected structure is unknown.
```

Thanks a lot Albert :)))
Mark CI tests as xfail if Hub HTTP error

In order to make testing more robust (and avoid merges to master with red tests), we could mark tests as xfailed (instead of failed) when the Hub raises some temporary HTTP errors.

This PR:
- marks tests as xfailed only if the Hub raises a 500 error for:
  - test_upstream_hub
- makes pytest report the xfailed/xpassed tests.

More tests could also be marked if needed.

Examples of CI failures due to temporary Hub HTTP errors:
- FAILED tests/test_upstream_hub.py::TestPushToHub::test_push_dataset_dict_to_hub_multiple_files
  - https://github.com/huggingface/datasets/runs/7806855399?check_suite_focus=true
    `requests.exceptions.HTTPError: 500 Server Error: Internal Server Error for url: https://hub-ci.huggingface.co/api/datasets/__DUMMY_TRANSFORMERS_USER__/test-16603108028233/commit/main (Request ID: aZeAQ5yLktoGHQYBcJ3zo)`
- FAILED tests/test_upstream_hub.py::TestPushToHub::test_push_dataset_dict_to_hub_no_token
  - https://github.com/huggingface/datasets/runs/7840022996?check_suite_focus=true
    `requests.exceptions.HTTPError: 500 Server Error: Internal Server Error for url: https://s3.us-east-1.amazonaws.com/lfs-staging.huggingface.co/repos/81/e3/81e3b831fa9bf23190ec041f26ef7ff6d6b71c1a937b8ec1ef1f1f05b508c089/caae596caa179cf45e7c9ac0c6d9a9cb0fe2d305291bfbb2d8b648ae26ed38b6?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Credential=AKIA4N7VTDGOZQA2IKWK%2F20220815%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20220815T144713Z&X-Amz-Expires=900&X-Amz-Signature=5ddddfe8ef2b0601e80ab41c78a4d77d921942b0d8160bcab40ff894095e6823&X-Amz-SignedHeaders=host&x-id=PutObject`
- FAILED tests/test_upstream_hub.py::TestPushToHub::test_push_dataset_dict_to_hub_private
  - https://github.com/huggingface/datasets/runs/7835921082?check_suite_focus=true
    `requests.exceptions.HTTPError: 500 Server Error: Internal Server Error for url: https://hub-ci.huggingface.co/api/repos/create (Request ID: gL_1I7i2dii9leBhlZen-) - Internal Error - We're working hard to fix that as soon as possible!`
- FAILED tests/test_upstream_hub.py::TestPushToHub::test_push_dataset_to_hub_custom_features_image_list
  - https://github.com/huggingface/datasets/runs/7835920900?check_suite_focus=true
  - This is not 500, but 404:
    `requests.exceptions.HTTPError: 404 Client Error: Not Found for url: [https://hub-ci.huggingface.co/datasets/__DUMMY_TRANSFORMERS_USER__/test-16605586458339.git/info/lfs/objects](https://hub-ci.huggingface.co/datasets/__DUMMY_TRANSFORMERS_USER__/test-16605586458339.git/info/lfs/objects/batch)`


Comments:
_The documentation is not available anymore as the PR was closed or merged._
Add 'val' to  VALIDATION_KEYWORDS. 

This PR fixes #4839 by adding the word `"val"` to the `VALIDATION_KEYWORDS` so that the `load_dataset()` method with `imagefolder` (and probably, some other directives as well) reads folders named `"val"` as well.

I think the supported keywords have to be mentioned in the documentation as well, but I couldn't think of a proper place to add that.

Comments:
@mariosasko not sure about how the reviewing process works. Maybe you can have a look because we discussed this elsewhere?

Hi, thanks! 

Let's add one pattern with `val` to this test before merging: 
https://github.com/huggingface/datasets/blob/b88a656cf94c4ad972154371c83c1af759fde522/tests/test_data_files.py#L598

_The documentation is not available anymore as the PR was closed or merged._

@akt42 note that there is some info about splits keywords in the docs: https://huggingface.co/docs/datasets/main/en/repository_structure#split-names-keywords. I agree it's not clear that it applies not only to filenames, but to directories as well.

I think "val" should be now added to the documentation source file here: https://github.com/huggingface/datasets/blob/main/docs/source/repository_structure.mdx?plain=1#L98

@polinaeterna Thanks for notifying us that there is a list of supported keywords

I've added "val" to that list and a test.
Dataset Viewer issue for darragh/demo_data_raw3

### Link

https://huggingface.co/datasets/darragh/demo_data_raw3

### Description

```
Exception:     ValueError
Message:       Arrow type extension<arrow.py_extension_type<pyarrow.lib.UnknownExtensionType>> does not have a datasets dtype equivalent.
```
reported by @NielsRogge 

### Owner

No

Comments:
do you have an idea of why it can occur @huggingface/datasets? The dataset consists of a single parquet file.

Thanks for reporting @severo.

I'm not able to reproduce that error. I get instead:
```
FileNotFoundError: [Errno 2] No such file or directory: 'orix/data/ChiSig/唐合乐-9-3.jpg'
```

Which pyarrow version are you using? Mine is 6.0.1. 

OK, I get now your error when not streaming.

OK!

If it's useful, the pyarrow version is 7.0.0:

https://github.com/huggingface/datasets-server/blob/487c39d87998f8d5a35972f1027d6c8e588e622d/services/worker/poetry.lock#L1537-L1543

Apparently, there is something weird with that Parquet file: its schema is:
```
images: extension<arrow.py_extension_type<pyarrow.lib.UnknownExtensionType>>
```

I have forced a right schema:
```python
from datasets import Features, Image, load_dataset

features = Features({"images": Image()})
ds = datasets.load_dataset("parquet", split="train", data_files="train-00000-of-00001.parquet", features=features)
```
and then recreated a new Parquet file:
```python
ds.to_parquet("train.parquet")
```

Now this Parquet file has the right schema:
```
images: struct<bytes: binary, path: string>
  child 0, bytes: binary
  child 1, path: string
```
and can be loaded normally:
```python
In [26]: ds = load_dataset("parquet", split="train", data_files="dataset.parquet")
n [27]: ds
Out[27]: 
Dataset({
    features: ['images'],
    num_rows: 20
})
```
ImageFolder dataset builder does not read the validation data set if it is named as "val"

**Is your feature request related to a problem? Please describe.**

Currently, the `'imagefolder'` data set builder in [`load_dataset()`](https://github.com/huggingface/datasets/blob/2.4.0/src/datasets/load.py#L1541] ) only [supports](https://github.com/huggingface/datasets/blob/6c609a322da994de149b2c938f19439bca99408e/src/datasets/data_files.py#L31) the following names as the validation data set directory name: `["validation", "valid", "dev"]`. When the validation directory is named as `'val'`, the Data set will not have a validation split. I expected this to be a trivial task but ended up spending a lot of time before knowing that only the above names are supported.

Here's a minimal example of `val` not being recognized:

```python
import os
import numpy as np
import cv2   
from datasets import load_dataset

# creating a dummy data set with the following structure:

# ROOT
# | -- train
# | ---- class_1
# | ---- class_2
# | -- val
# | ---- class_1
# | ---- class_2


ROOT = "data"


for which in ["train", "val"]:
  for class_name in ["class_1", "class_2"]:
    dir_name = os.path.join(ROOT, which, class_name)
    if not os.path.exists(dir_name):
      os.makedirs(dir_name)
    for i in range(10):
       cv2.imwrite(
           os.path.join(dir_name, f"{i}.png"),
           np.random.random((224, 224))
           )

# trying to create a data set
dataset = load_dataset(
    "imagefolder", 
    data_dir=ROOT
)

>> dataset
DatasetDict({
    train: Dataset({
        features: ['image', 'label'],
        num_rows: 20
    })
})

# ^ note how the dataset only has a 'train' subset

```

**Describe the solution you'd like**

The suggestion is to include `"val"` to  [that list ](https://github.com/huggingface/datasets/blob/6c609a322da994de149b2c938f19439bca99408e/src/datasets/data_files.py#L31) as that's a commonly used phrase to name the validation directory. 

Also, In the documentation, explicitly mention that only such directory names are supported as train/val/test directories to avoid confusion.

**Describe alternatives you've considered**

In the documentation, explicitly mention that only such directory names are supported as train/val/test directories without adding `val` to the above list.


**Additional context**

A question asked in the forum: [
Loading an imagenet-style image dataset with train/val directories](https://discuss.huggingface.co/t/loading-an-imagenet-style-image-dataset-with-train-val-directories/21554)

Comments:
#take
Add support for CSV metadata files to ImageFolder

Fix #4814

Comments:
_The documentation is not available anymore as the PR was closed or merged._

Cool thanks ! Maybe let's include this change after the refactoring from FolderBasedBuilder in #3963 to avoid dealing with too many unpleasant conflicts ?

@lhoestq I resolved the conflicts (AudioFolder also supports CSV metadata now). Let me know what you think.


@lhoestq Thanks for the suggestion! Indeed it makes more sense to use CSV as the default format in the folder-based builders.
Is it possible to pass multiple links to a split in load script?

**Is your feature request related to a problem? Please describe.**
I wanted to use a python loading script in hugging face datasets that use different sources of text (it's somehow a compilation of multiple datasets + my own dataset) based on how `load_dataset` [works](https://huggingface.co/docs/datasets/loading) I assumed I could do something like bellow in my loading script:

```python
...
_URL = "MY_DATASET_URL/resolve/main/data/"
_URLS = {
    "train": [
        "FIRST_URL_TO.txt",
        _URL + "train-00000-of-00001-676bfebbc8742592.parquet"
    ]
}
...
```
but when loading the dataset it raises the following error:
```python
File ~/.local/lib/python3.8/site-packages/datasets/builder.py:704, in DatasetBuilder.download_and_prepare(self, download_config, download_mode, ignore_verifications, try_from_hf_gcs, dl_manager, base_path, use_auth_token, **download_and_prepare_kwargs)
    702         logger.warning("HF google storage unreachable. Downloading and preparing it from source")
    703 if not downloaded_from_gcs:
--> 704     self._download_and_prepare(
    705         dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
...
    668     if isinstance(a, str):
    669         # Force-cast str subclasses to str (issue #21127)
    670         parts.append(str(a))

TypeError: expected str, bytes or os.PathLike object, not list
```

**Describe the solution you'd like**
I believe since it's possible for `load_dataset` to get list of URLs instead of just a URL for `train` split it can be possible here too.

**Describe alternatives you've considered**
An alternative solution would be to download all needed datasets locally and `push_to_hub` them all, but since the datasets I'm talking about are huge it's not among my options. 

**Additional context**
I think loading `text` beside the `parquet` is completely a different issue but I believe I can figure it out by proposing a config for my dataset to load each entry of `_URLS['train']` separately either by `load_dataset("text", ...` or `load_dataset("parquet", ...`.


Comments:
Fix missing tags in dataset cards

Fix missing tags in dataset cards:
- boolq
- break_data
- definite_pronoun_resolution
- emo
- kor_nli
- pg19
- quartz
- sciq
- squad_es
- wmt14
- wmt15
- wmt16
- wmt17
- wmt18
- wmt19
- wmt_t2t

This PR partially fixes the missing tags in dataset cards. Subsequent PRs will follow to complete this task.

Comments:
_The documentation is not available anymore as the PR was closed or merged._
Misalignment between card tag validation and docs

## Describe the bug
As pointed out in other issue: https://github.com/huggingface/datasets/pull/4827#discussion_r943536284
the validation of the dataset card tags is not aligned with its documentation: e.g.
- implementation: `license: List[str]`
- docs: `license: Union[str, List[str]]`

They should be aligned.

CC: @julien-c 


Comments:
(Note that the doc is aligned with the hub validation rules, and the "ground truth" is the hub validation rules given that they apply to all datasets, not just the canonical ones)

Instead of our own implementation, we now use `huggingface_hub`'s `DatasetCardData`, which has the correct type hint, so I think we can close this issue.