Title: Add AudioFolder packaged loader
State: closed
Labels: description: New feature or request
name: enhancement

will close  #3964

AudioFolder is almost identical to ImageFolder except for inferring labels is not the default behavior (`drop_labels` is set to True in config), the option of inferring them is preserved though.

The weird thing is happening with the `test_data_files_with_metadata_and_archives` when `streaming` is `True`. Here is the log from the CI:
```

../.pyenv/versions/3.6.15/lib/python3.6/site-packages/datasets/features/audio.py:237: in _decode_non_mp3_path_like
    array, sampling_rate = librosa.load(f, sr=self.sampling_rate, mono=self.mono)
../.pyenv/versions/3.6.15/lib/python3.6/site-packages/librosa/util/decorators.py:88: in inner_f
    return f(*args, **kwargs)
../.pyenv/versions/3.6.15/lib/python3.6/site-packages/librosa/core/audio.py:176: in load
    raise (exc)
../.pyenv/versions/3.6.15/lib/python3.6/site-packages/librosa/core/audio.py:155: in load
    context = sf.SoundFile(path)
../.pyenv/versions/3.6.15/lib/python3.6/site-packages/soundfile.py:629: in __init__
    self._file = self._open(file, mode_int, closefd)
../.pyenv/versions/3.6.15/lib/python3.6/site-packages/soundfile.py:1184: in _open
    "Error opening {0!r}: ".format(self.name))
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

err = 72
prefix = "Error opening <zipfile.ZipExtFile name='audio_file.wav' mode='r' compress_type=deflate>: "

    def _error_check(err, prefix=""):
        """Pretty-print a numerical error code if there is an error."""
        if err != 0:
            err_str = _snd.sf_error_number(err)
>           raise RuntimeError(prefix + _ffi.string(err_str).decode('utf-8', 'replace'))
E           RuntimeError: Error opening <zipfile.ZipExtFile name='audio_file.wav' mode='r' compress_type=deflate>: Error in WAV file. No 'data' chunk marker.
```
I hadn't been able to reproduce this locally until I created the same test environment (I mean with `pip install .[tests]`) with python3.6. The same env but with python3.8 passes the test! I didn't manage to figure out what's wrong, I also tried simply to replace the test wav file and still got the same error. Versions of `soundfile`, `librosa` and `libsndfile` are identical. Might it be something with zip compression? Sounds weird but I don't have any other ideas... 
 
TODO:

- [x] align with #4622
- [x] documentation
- [x] tests for AutoFolder?

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

@lhoestq @mariosasko I don't know what to do with the test, do you have any ideas? :)

also it's passed in `pyarrow_latest_WIN`

If the error only happens on 3.6, maybe #4460 can help ^^' It seems to work in 3.7 on the windows CI

> inferring labels is not the default behavior (drop_labels is set to True in config)

I think it a missed opportunity to have a consistent API between imagefolder and audiofolder, since they do everything the same way. Can you give more details why you think we should drop the labels by default ?

Considering audio classification in audio is not as common as image classification in image, I'm ok with having different config defaults as long as they are properly documented (check [Papers With Code](https://paperswithcode.com/datasets) for stats and compare the classification numbers to the other tasks, do this for both modalities)

Also, WDYT about creating a generic folder loader that ImageFolder and AudioFolder then subclass to avoid having to update both of them when there is something to update/fix?

@lhoestq I think it doesn't change the API itself, it just doesn't infer labels by default, but you can **still** set `drop_labels=False` to `load_dataset` and the labels will be inferred. 
Suppose that one has data structured as follows:
```
data/
   train/
      audio/
          file1.wav
          file2.wav
          file3.wav
      metadata.jsonl
   test/
      audio/
          file1.wav
          file2.wav
          file3.wav
      metadata.jsonl
```
If users load this dataset with `load_dataset("audiofolder", data_dir="data")` (the most native way), they will get a `label` feature that will always be equal to 0 (= "audio"). To mitigate this, they will have to always specify `load_dataset("audiofolder", data_dir="data", drop_labels=True)` explicitly and I believe it's not convenient. 

At the same time, `label` column can be added just as easy as adding one argument:` load_dataset("audiofolder", data_dir="data", drop_labels=False)`. As classification task is not as common, I think it should require more symbols to be added to the code :D  

But this is definitely should be explained in the docs, which I've forgotten to update... I'll add this section soon.

Also +to the generic loader, will work on it. 



If a metadata.jsonl file is present, then it doesn't have to infer the labels I agree. Note that this is already the case for imagefolder ;) in your case `load_dataset("audiofolder", data_dir="data")` won't return labels !

Labels are only inferred if there are no metadata.jsonl

Feel free to merge the `main` branch into yours after updating your fork of `datasets`: https://github.com/huggingface/datasets/issues/4629

This should fix some errors in the CI

@mariosasko  could you please review this PR again? :)

most of the tests for AutoFolder (base class for AudioFolder and ImageFolder) are now basically copied from Image/AudioFolder (their tests are also almost identical too) and adapted to test other methods. it should be refactored but i think this is not that important for now and might be done in the future PR, wdyt?

@mariosasko thank you for the review! I'm sorry I accidentally asked for the review again, ignore it.