[Apple M1] MemoryError: Cannot allocate write+execute memory for ffi.callback()
COLLABORATOR
Hi! This seems like a bug in `soundfile`. Could you please open an issue in their repo? `soundfile` works without any issues on my M1, so I'm not sure we can help.
2022-09-16T15:47:28Z
https://github.com/huggingface/datasets/issues/4965#issuecomment-1249523881
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Hi @mariosasko, can you share how you installed `soundfile` on your mac M1?
2022-09-17T14:51:21Z
https://github.com/huggingface/datasets/issues/4965#issuecomment-1250084865
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Hi @hoangtnm  - I upgraded to python 3.10 and it fixed the problem for me. I was also running 3.8 on an M1 mac.
2022-11-18T23:45:02Z
https://github.com/huggingface/datasets/issues/4965#issuecomment-1320661602
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Same here, upgrade python didn't work for me 

MemoryError: Cannot allocate write+execute memory for ffi.callback()

any idea?
2024-01-12T03:22:05Z
https://github.com/huggingface/datasets/issues/4965#issuecomment-1888371659
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COLLABORATOR
This is a `soundfile` issue, so there isn't much we can do about it. Hopefully, it gets fixed soon.
2024-01-12T14:37:31Z
https://github.com/huggingface/datasets/issues/4965#issuecomment-1889381100
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> Hi @hoangtnm - I upgraded to python 3.10 and it fixed the problem for me. I was also running 3.8 on an M1 mac.

it work for me too 

2024-03-21T17:25:52Z
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## Describe the bug
I'm trying to run `cast_column("audio", Audio())` on Apple M1 Pro, but it seems that it doesn't work.

## Steps to reproduce the bug
```python
import datasets

dataset = load_dataset("csv", data_files="./train.csv")["train"]
dataset = dataset.map(lambda x: {"audio": str(DATA_DIR / "audio" / x["audio"])})
dataset = dataset.cast_column("audio", Audio())
dataset[0]
```

## Expected results
```
{'audio': {'bytes': None,
  'path': '/root/.cache/huggingface/datasets/downloads/extracted/f14948e0e84be638dd7943ac36518a4cf3324e8b7aa331c5ab11541518e9368c/en-US~JOINT_ACCOUNT/602ba55abb1e6d0fbce92065.wav'},
 'english_transcription': 'I would like to set up a joint account with my partner',
 'intent_class': 11,
 'lang_id': 4,
 'path': '/root/.cache/huggingface/datasets/downloads/extracted/f14948e0e84be638dd7943ac36518a4cf3324e8b7aa331c5ab11541518e9368c/en-US~JOINT_ACCOUNT/602ba55abb1e6d0fbce92065.wav',
 'transcription': 'I would like to set up a joint account with my partner'}
```


## Actual results
````---------------------------------------------------------------------------
MemoryError                               Traceback (most recent call last)
Input In [6], in <cell line: 1>()
----> 1 dataset[0]

File ~/miniconda3/envs/rodan/lib/python3.8/site-packages/datasets/arrow_dataset.py:2165, in Dataset.__getitem__(self, key)
   2163 def __getitem__(self, key):  # noqa: F811
   2164     """Can be used to index columns (by string names) or rows (by integer index or iterable of indices or bools)."""
-> 2165     return self._getitem(
   2166         key,
   2167     )

File ~/miniconda3/envs/rodan/lib/python3.8/site-packages/datasets/arrow_dataset.py:2150, in Dataset._getitem(self, key, decoded, **kwargs)
   2148 formatter = get_formatter(format_type, features=self.features, decoded=decoded, **format_kwargs)
   2149 pa_subtable = query_table(self._data, key, indices=self._indices if self._indices is not None else None)
-> 2150 formatted_output = format_table(
   2151     pa_subtable, key, formatter=formatter, format_columns=format_columns, output_all_columns=output_all_columns
   2152 )
   2153 return formatted_output

File ~/miniconda3/envs/rodan/lib/python3.8/site-packages/datasets/formatting/formatting.py:532, in format_table(table, key, formatter, format_columns, output_all_columns)
    530 python_formatter = PythonFormatter(features=None)
    531 if format_columns is None:
--> 532     return formatter(pa_table, query_type=query_type)
    533 elif query_type == "column":
    534     if key in format_columns:

File ~/miniconda3/envs/rodan/lib/python3.8/site-packages/datasets/formatting/formatting.py:281, in Formatter.__call__(self, pa_table, query_type)
    279 def __call__(self, pa_table: pa.Table, query_type: str) -> Union[RowFormat, ColumnFormat, BatchFormat]:
    280     if query_type == "row":
--> 281         return self.format_row(pa_table)
    282     elif query_type == "column":
    283         return self.format_column(pa_table)

File ~/miniconda3/envs/rodan/lib/python3.8/site-packages/datasets/formatting/formatting.py:312, in PythonFormatter.format_row(self, pa_table)
    310 row = self.python_arrow_extractor().extract_row(pa_table)
    311 if self.decoded:
--> 312     row = self.python_features_decoder.decode_row(row)
    313 return row

File ~/miniconda3/envs/rodan/lib/python3.8/site-packages/datasets/formatting/formatting.py:221, in PythonFeaturesDecoder.decode_row(self, row)
    220 def decode_row(self, row: dict) -> dict:
--> 221     return self.features.decode_example(row) if self.features else row

File ~/miniconda3/envs/rodan/lib/python3.8/site-packages/datasets/features/features.py:1647, in Features.decode_example(self, example, token_per_repo_id)
   1634 def decode_example(self, example: dict, token_per_repo_id: Optional[Dict[str, Union[str, bool, None]]] = None):
   1635     """Decode example with custom feature decoding.
   1636 
   1637     Args:
   (...)
   1644         :obj:`dict[str, Any]`
   1645     """
-> 1647     return {
   1648         column_name: decode_nested_example(feature, value, token_per_repo_id=token_per_repo_id)
   1649         if self._column_requires_decoding[column_name]
   1650         else value
   1651         for column_name, (feature, value) in zip_dict(
   1652             {key: value for key, value in self.items() if key in example}, example
   1653         )
   1654     }

File ~/miniconda3/envs/rodan/lib/python3.8/site-packages/datasets/features/features.py:1648, in <dictcomp>(.0)
   1634 def decode_example(self, example: dict, token_per_repo_id: Optional[Dict[str, Union[str, bool, None]]] = None):
   1635     """Decode example with custom feature decoding.
   1636 
   1637     Args:
   (...)
   1644         :obj:`dict[str, Any]`
   1645     """
   1647     return {
-> 1648         column_name: decode_nested_example(feature, value, token_per_repo_id=token_per_repo_id)
   1649         if self._column_requires_decoding[column_name]
   1650         else value
   1651         for column_name, (feature, value) in zip_dict(
   1652             {key: value for key, value in self.items() if key in example}, example
   1653         )
   1654     }

File ~/miniconda3/envs/rodan/lib/python3.8/site-packages/datasets/features/features.py:1260, in decode_nested_example(schema, obj, token_per_repo_id)
   1257 # Object with special decoding:
   1258 elif isinstance(schema, (Audio, Image)):
   1259     # we pass the token to read and decode files from private repositories in streaming mode
-> 1260     return schema.decode_example(obj, token_per_repo_id=token_per_repo_id) if obj is not None else None
   1261 return obj

File ~/miniconda3/envs/rodan/lib/python3.8/site-packages/datasets/features/audio.py:156, in Audio.decode_example(self, value, token_per_repo_id)
    154         array, sampling_rate = self._decode_non_mp3_file_like(file)
    155     else:
--> 156         array, sampling_rate = self._decode_non_mp3_path_like(path, token_per_repo_id=token_per_repo_id)
    157 return {"path": path, "array": array, "sampling_rate": sampling_rate}

File ~/miniconda3/envs/rodan/lib/python3.8/site-packages/datasets/features/audio.py:257, in Audio._decode_non_mp3_path_like(self, path, format, token_per_repo_id)
    254     use_auth_token = None
    256 with xopen(path, "rb", use_auth_token=use_auth_token) as f:
--> 257     array, sampling_rate = librosa.load(f, sr=self.sampling_rate, mono=self.mono)
    258 return array, sampling_rate

File ~/miniconda3/envs/rodan/lib/python3.8/site-packages/librosa/util/decorators.py:88, in deprecate_positional_args.<locals>._inner_deprecate_positional_args.<locals>.inner_f(*args, **kwargs)
     86 extra_args = len(args) - len(all_args)
     87 if extra_args <= 0:
---> 88     return f(*args, **kwargs)
     90 # extra_args > 0
     91 args_msg = [
     92     "{}={}".format(name, arg)
     93     for name, arg in zip(kwonly_args[:extra_args], args[-extra_args:])
     94 ]

File ~/miniconda3/envs/rodan/lib/python3.8/site-packages/librosa/core/audio.py:164, in load(path, sr, mono, offset, duration, dtype, res_type)
    161 else:
    162     # Otherwise try soundfile first, and then fall back if necessary
    163     try:
--> 164         y, sr_native = __soundfile_load(path, offset, duration, dtype)
    166     except RuntimeError as exc:
    167         # If soundfile failed, try audioread instead
    168         if isinstance(path, (str, pathlib.PurePath)):

File ~/miniconda3/envs/rodan/lib/python3.8/site-packages/librosa/core/audio.py:195, in __soundfile_load(path, offset, duration, dtype)
    192     context = path
    193 else:
    194     # Otherwise, create the soundfile object
--> 195     context = sf.SoundFile(path)
    197 with context as sf_desc:
    198     sr_native = sf_desc.samplerate

File ~/miniconda3/envs/rodan/lib/python3.8/site-packages/soundfile.py:629, in SoundFile.__init__(self, file, mode, samplerate, channels, subtype, endian, format, closefd)
    626 self._mode = mode
    627 self._info = _create_info_struct(file, mode, samplerate, channels,
    628                                  format, subtype, endian)
--> 629 self._file = self._open(file, mode_int, closefd)
    630 if set(mode).issuperset('r+') and self.seekable():
    631     # Move write position to 0 (like in Python file objects)
    632     self.seek(0)

File ~/miniconda3/envs/rodan/lib/python3.8/site-packages/soundfile.py:1179, in SoundFile._open(self, file, mode_int, closefd)
   1177     file_ptr = _snd.sf_open_fd(file, mode_int, self._info, closefd)
   1178 elif _has_virtual_io_attrs(file, mode_int):
-> 1179     file_ptr = _snd.sf_open_virtual(self._init_virtual_io(file),
   1180                                     mode_int, self._info, _ffi.NULL)
   1181 else:
   1182     raise TypeError("Invalid file: {0!r}".format(self.name))

File ~/miniconda3/envs/rodan/lib/python3.8/site-packages/soundfile.py:1197, in SoundFile._init_virtual_io(self, file)
   1194 def _init_virtual_io(self, file):
   1195     """Initialize callback functions for sf_open_virtual()."""
   1196     @_ffi.callback("sf_vio_get_filelen")
-> 1197     def vio_get_filelen(user_data):
   1198         curr = file.tell()
   1199         file.seek(0, SEEK_END)

MemoryError: Cannot allocate write+execute memory for ffi.callback(). You might be running on a system that prevents this. For more information, see https://cffi.readthedocs.io/en/latest/using.html#callbacks
```

## Environment info
- `datasets` version: 2.4.0
- Platform: macOS-12.5.1-arm64-arm-64bit
- Python version: 3.8.13
- PyArrow version: 9.0.0
- Pandas version: 1.4.4