fsspec.exceptions.FSTimeoutError when downloading dataset
State: open | Author: timonmerk (NONE)

### Describe the bug

I am trying to download the `librispeech_asr` `clean` dataset, which results in a `FSTimeoutError` exception after downloading around 61% of the data.

### Steps to reproduce the bug

```
import datasets
datasets.load_dataset("librispeech_asr", "clean")
```

The output is as follows:

> Downloading data:  61%|██████████████▋         | 3.92G/6.39G [05:00<03:06, 13.2MB/s]Traceback (most recent call last):
>   File "/Users/Timon/Documents/iEEG_deeplearning/wav2vec_pretrain/.venv/lib/python3.12/site-packages/fsspec/asyn.py", line 56, in _runner
>     result[0] = await coro
>                 ^^^^^^^^^^
>   File "/Users/Timon/Documents/iEEG_deeplearning/wav2vec_pretrain/.venv/lib/python3.12/site-packages/fsspec/implementations/http.py", line 262, in _get_file
>     chunk = await r.content.read(chunk_size)
>             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
>   File "/Users/Timon/Documents/iEEG_deeplearning/wav2vec_pretrain/.venv/lib/python3.12/site-packages/aiohttp/streams.py", line 393, in read
>     await self._wait("read")
>   File "/Users/Timon/Documents/iEEG_deeplearning/wav2vec_pretrain/.venv/lib/python3.12/site-packages/aiohttp/streams.py", line 311, in _wait
>     with self._timer:
>          ^^^^^^^^^^^
>   File "/Users/Timon/Documents/iEEG_deeplearning/wav2vec_pretrain/.venv/lib/python3.12/site-packages/aiohttp/helpers.py", line 713, in __exit__
>     raise asyncio.TimeoutError from None
> TimeoutError
> 
> The above exception was the direct cause of the following exception:
> 
> Traceback (most recent call last):
>   File "/Users/Timon/Documents/iEEG_deeplearning/wav2vec_pretrain/load_dataset.py", line 3, in <module>
>     datasets.load_dataset("librispeech_asr", "clean")
>   File "/Users/Timon/Documents/iEEG_deeplearning/wav2vec_pretrain/.venv/lib/python3.12/site-packages/datasets/load.py", line 2096, in load_dataset
>     builder_instance.download_and_prepare(
>   File "/Users/Timon/Documents/iEEG_deeplearning/wav2vec_pretrain/.venv/lib/python3.12/site-packages/datasets/builder.py", line 924, in download_and_prepare
>     self._download_and_prepare(
>   File "/Users/Timon/Documents/iEEG_deeplearning/wav2vec_pretrain/.venv/lib/python3.12/site-packages/datasets/builder.py", line 1647, in _download_and_prepare
>     super()._download_and_prepare(
>   File "/Users/Timon/Documents/iEEG_deeplearning/wav2vec_pretrain/.venv/lib/python3.12/site-packages/datasets/builder.py", line 977, in _download_and_prepare
>     split_generators = self._split_generators(dl_manager, **split_generators_kwargs)
>                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
>   File "/Users/Timon/.cache/huggingface/modules/datasets_modules/datasets/librispeech_asr/2712a8f82f0d20807a56faadcd08734f9bdd24c850bb118ba21ff33ebff0432f/librispeech_asr.py", line 115, in _split_generators
>     archive_path = dl_manager.download(_DL_URLS[self.config.name])
>                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
>   File "/Users/Timon/Documents/iEEG_deeplearning/wav2vec_pretrain/.venv/lib/python3.12/site-packages/datasets/download/download_manager.py", line 159, in download
>     downloaded_path_or_paths = map_nested(
>                                ^^^^^^^^^^^
>   File "/Users/Timon/Documents/iEEG_deeplearning/wav2vec_pretrain/.venv/lib/python3.12/site-packages/datasets/utils/py_utils.py", line 512, in map_nested
>     _single_map_nested((function, obj, batched, batch_size, types, None, True, None))
>   File "/Users/Timon/Documents/iEEG_deeplearning/wav2vec_pretrain/.venv/lib/python3.12/site-packages/datasets/utils/py_utils.py", line 380, in _single_map_nested
>     return [mapped_item for batch in iter_batched(data_struct, batch_size) for mapped_item in function(batch)]
>                                                                                               ^^^^^^^^^^^^^^^
>   File "/Users/Timon/Documents/iEEG_deeplearning/wav2vec_pretrain/.venv/lib/python3.12/site-packages/datasets/download/download_manager.py", line 216, in _download_batched
>     self._download_single(url_or_filename, download_config=download_config)
>   File "/Users/Timon/Documents/iEEG_deeplearning/wav2vec_pretrain/.venv/lib/python3.12/site-packages/datasets/download/download_manager.py", line 225, in _download_single
>     out = cached_path(url_or_filename, download_config=download_config)
>           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
>   File "/Users/Timon/Documents/iEEG_deeplearning/wav2vec_pretrain/.venv/lib/python3.12/site-packages/datasets/utils/file_utils.py", line 205, in cached_path
>     output_path = get_from_cache(
>                   ^^^^^^^^^^^^^^^
>   File "/Users/Timon/Documents/iEEG_deeplearning/wav2vec_pretrain/.venv/lib/python3.12/site-packages/datasets/utils/file_utils.py", line 415, in get_from_cache
>     fsspec_get(url, temp_file, storage_options=storage_options, desc=download_desc, disable_tqdm=disable_tqdm)
>   File "/Users/Timon/Documents/iEEG_deeplearning/wav2vec_pretrain/.venv/lib/python3.12/site-packages/datasets/utils/file_utils.py", line 334, in fsspec_get
>     fs.get_file(path, temp_file.name, callback=callback)
>   File "/Users/Timon/Documents/iEEG_deeplearning/wav2vec_pretrain/.venv/lib/python3.12/site-packages/fsspec/asyn.py", line 118, in wrapper
>     return sync(self.loop, func, *args, **kwargs)
>            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
>   File "/Users/Timon/Documents/iEEG_deeplearning/wav2vec_pretrain/.venv/lib/python3.12/site-packages/fsspec/asyn.py", line 101, in sync
>     raise FSTimeoutError from return_result
> fsspec.exceptions.FSTimeoutError
> Downloading data:  61%|██████████████▋         | 3.92G/6.39G [05:00<03:09, 13.0MB/s]

### Expected behavior

Complete the download

### Environment info

Python version 3.12.6

Dependencies:
> dependencies = [
>     "accelerate>=0.34.2",
>     "datasets[audio]>=3.0.0",
>     "ipython>=8.18.1",
>     "librosa>=0.10.2.post1",
>     "torch>=2.4.1",
>     "torchaudio>=2.4.1",
>     "transformers>=4.44.2",
> ]

MacOS 14.6.1 (23G93)

Comments: Hi ! If you check the dataset loading script [here](https://huggingface.co/datasets/openslr/librispeech_asr/blob/main/librispeech_asr.py) you'll see that it downloads the data from OpenSLR, and apparently their storage has timeout issues. It would be great to ultimately host the dataset on Hugging Face instead.

In the meantime I can only recommend to try again later :/

Ok, still many thanks!

I'm also getting this same error but for `CSTR-Edinburgh/vctk`, so I don't think it's the remote host that's timing out, since I also time out at exactly 5 minutes.  It seems there is a universal fsspec timeout that's getting hit starting in v3.

in v3 we cleaned the download parts of the library to make it more robust for HF downloads and to simplify support of script-based datasets. As a side effect it's not the same code that is used for other hosts, maybe time out handling changed. Anyway it should be possible to tweak fsspec to use retries

For example using [aiohttp_retry](https://github.com/inyutin/aiohttp_retry) maybe (haven't tried) ?

```python
import fsspec
from aiohttp_retry import RetryClient

fsspec.filesystem("http")._session = RetryClient()
```

related topic : https://github.com/huggingface/datasets/issues/7175

Adding a timeout argument to the `fs.get_file` call in `fsspec_get` in `datasets/utils/file_utils.py` might fix this ([source code](https://github.com/huggingface/datasets/blob/65f6eb54aa0e8bb44cea35deea28e0e8fecc25b9/src/datasets/utils/file_utils.py#L330)):

```python
fs.get_file(path, temp_file.name, callback=callback, timeout=3600)
```

Setting `timeout=1` fails after about one second, so setting it to 3600 should give us 1h. Havn't really tested this though. I'm also not sure what implications this has and if it causes errors for other `fs` implementations/configurations.

This is using `datasets==3.0.1` and Python 3.11.6.

---

Edit: This doesn't seem to change the timeout time, but add a second timeout counter (probably in `fsspec/asyn.py/sync`). So one can reduce the time for downloading like this, but not expand.

---

Edit 2: `fs` is of type `fsspec.implementations.http.HTTPFileSystem` which initializes a `aiohttp.ClientSession` using `client_kwargs`. We can pass these when calling `load_dataset`.

**TLDR; This fixes it:**

```python
import datasets, aiohttp
dataset = datasets.load_dataset(
    dataset_name,
    storage_options={'client_kwargs': {'timeout': aiohttp.ClientTimeout(total=3600)}}
)
```

I've handled the issue like this to ensure smoother downloads when using the `datasets` library.  
If modifying the library is not too inconvenient, this approach could be a good (but tentative) solution.

### Changes Made

Modified `datasets.utils.file_utils.fsspec_get` to handle storage options and set a timeout:

```python
def fsspec_get(url, temp_file, storage_options=None, desc=None, disable_tqdm=False):

    # ---> [ADD]
    if storage_options is None:
        storage_options = {}
    if "client_kwargs" not in storage_options:
        storage_options["client_kwargs"] = {}
    storage_options["client_kwargs"]["timeout"] = aiohttp.ClientTimeout(total=3600)
    # <---

    # The rest of the original code remains unchanged