Datasets:

facebook

/

voxpopuli

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Hi folks,

I wanted to load this dataset as part of the audio course, but it fails to load on my windows machine, for any language subset. I tried on my mac and it works fine. Someone else on the Discord channel tried on Linux and it worked.
I feel like it doesn't write itself correctly in .cache, compared to other datasets.

It is the only audio dataset I fail to load.

I get the following error:

OSError Traceback (most recent call last)
Cell In[6], line 1
----> 1 dataset = load_dataset("facebook/voxpopuli", "nl")
2 len(dataset)

File C:\ProgramData\anaconda3\envs\hf_audio_course\Lib\site-packages\datasets\load.py:2154, in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, verification_mode, keep_in_memory, save_infos, revision, token, streaming, num_proc, storage_options, trust_remote_code, **config_kwargs)
2151 return builder_instance.as_streaming_dataset(split=split)
2153 # Download and prepare data
-> 2154 builder_instance.download_and_prepare(
2155 download_config=download_config,
2156 download_mode=download_mode,
2157 verification_mode=verification_mode,
2158 num_proc=num_proc,
2159 storage_options=storage_options,
2160 )
2162 # Build dataset for splits
2163 keep_in_memory = (
2164 keep_in_memory if keep_in_memory is not None else is_small_dataset(builder_instance.info.dataset_size)
2165 )

File C:\ProgramData\anaconda3\envs\hf_audio_course\Lib\site-packages\datasets\builder.py:924, in DatasetBuilder.download_and_prepare(self, output_dir, download_config, download_mode, verification_mode, dl_manager, base_path, file_format, max_shard_size, num_proc, storage_options, **download_and_prepare_kwargs)
922 if num_proc is not None:
923 prepare_split_kwargs["num_proc"] = num_proc
--> 924 self._download_and_prepare(
925 dl_manager=dl_manager,
926 verification_mode=verification_mode,
927 **prepare_split_kwargs,
928 **download_and_prepare_kwargs,
929 )
930 # Sync info
931 self.info.dataset_size = sum(split.num_bytes for split in self.info.splits.values())

File C:\ProgramData\anaconda3\envs\hf_audio_course\Lib\site-packages\datasets\builder.py:1648, in GeneratorBasedBuilder._download_and_prepare(self, dl_manager, verification_mode, **prepare_splits_kwargs)
1647 def _download_and_prepare(self, dl_manager, verification_mode, **prepare_splits_kwargs):
-> 1648 super()._download_and_prepare(
1649 dl_manager,
1650 verification_mode,
1651 check_duplicate_keys=verification_mode == VerificationMode.BASIC_CHECKS
1652 or verification_mode == VerificationMode.ALL_CHECKS,
1653 **prepare_splits_kwargs,
1654 )

File C:\ProgramData\anaconda3\envs\hf_audio_course\Lib\site-packages\datasets\builder.py:978, in DatasetBuilder._download_and_prepare(self, dl_manager, verification_mode, **prepare_split_kwargs)
976 split_dict = SplitDict(dataset_name=self.dataset_name)
977 split_generators_kwargs = self._make_split_generators_kwargs(prepare_split_kwargs)
--> 978 split_generators = self._split_generators(dl_manager, **split_generators_kwargs)
980 # Checksums verification
981 if verification_mode == VerificationMode.ALL_CHECKS and dl_manager.record_checksums:

File ~.cache\huggingface\modules\datasets_modules\datasets\facebook--voxpopuli\b5ff837284f0778eefe0f642734e142d8c3f574eba8c9c8a4b13602297f73604\voxpopuli.py:146, in Voxpopuli._split_generators(self, dl_manager)
142 meta_paths = dl_manager.download_and_extract(meta_urls)
143 audio_paths = dl_manager.download(audio_urls)
145 local_extracted_audio_paths = (
--> 146 dl_manager.extract(audio_paths) if not dl_manager.is_streaming else
147 {
148 split: {lang: [None] * len(audio_paths[split][lang]) for lang in self.config.languages} for split in splits
149 }
150 )
151 if self.config.name == "en_accented":
152 return [
153 datasets.SplitGenerator(
154 name=datasets.Split.TEST,
(...)
163 ),
164 ]

File C:\ProgramData\anaconda3\envs\hf_audio_course\Lib\site-packages\datasets\download\download_manager.py:299, in DownloadManager.extract(self, path_or_paths)
297 download_config.extract_compressed_file = True
298 extract_func = partial(self._download_single, download_config=download_config)
--> 299 extracted_paths = map_nested(
300 extract_func,
301 path_or_paths,
302 num_proc=download_config.num_proc,
303 desc="Extracting data files",
304 )
305 path_or_paths = NestedDataStructure(path_or_paths)
306 extracted_paths = NestedDataStructure(extracted_paths)

File C:\ProgramData\anaconda3\envs\hf_audio_course\Lib\site-packages\datasets\utils\py_utils.py:512, in map_nested(function, data_struct, dict_only, map_list, map_tuple, map_numpy, num_proc, parallel_min_length, batched, batch_size, types, disable_tqdm, desc)
509 batch_size = max(len(iterable) // num_proc + int(len(iterable) % num_proc > 0), 1)
510 iterable = list(iter_batched(iterable, batch_size))
511 mapped = [
--> 512 _single_map_nested((function, obj, batched, batch_size, types, None, True, None))
513 for obj in hf_tqdm(iterable, disable=disable_tqdm, desc=desc)
514 ]
515 if batched:
516 mapped = [mapped_item for mapped_batch in mapped for mapped_item in mapped_batch]

File C:\ProgramData\anaconda3\envs\hf_audio_course\Lib\site-packages\datasets\utils\py_utils.py:396, in _single_map_nested(args)
393 with hf_tqdm(pbar_iterable, disable=disable_tqdm, position=rank, unit="obj", desc=pbar_desc) as pbar:
394 if isinstance(data_struct, dict):
395 return {
--> 396 k: _single_map_nested((function, v, batched, batch_size, types, None, True, None)) for k, v in pbar
397 }
398 else:
399 mapped = [_single_map_nested((function, v, batched, batch_size, types, None, True, None)) for v in pbar]

File C:\ProgramData\anaconda3\envs\hf_audio_course\Lib\site-packages\datasets\utils\py_utils.py:399, in _single_map_nested(args)
395 return {
396 k: _single_map_nested((function, v, batched, batch_size, types, None, True, None)) for k, v in pbar
397 }
398 else:
--> 399 mapped = [_single_map_nested((function, v, batched, batch_size, types, None, True, None)) for v in pbar]
400 if isinstance(data_struct, list):
401 return mapped

File C:\ProgramData\anaconda3\envs\hf_audio_course\Lib\site-packages\datasets\utils\py_utils.py:373, in _single_map_nested(args)
371 return function([data_struct])[0]
372 else:
--> 373 return function(data_struct)
374 if (
375 batched
376 and not isinstance(data_struct, dict)
377 and isinstance(data_struct, types)
378 and all(not isinstance(v, (dict, types)) for v in data_struct)
379 ):
380 return [mapped_item for batch in iter_batched(data_struct, batch_size) for mapped_item in function(batch)]

File C:\ProgramData\anaconda3\envs\hf_audio_course\Lib\site-packages\datasets\download\download_manager.py:229, in DownloadManager._download_single(self, url_or_filename, download_config)
226 if is_relative_path(url_or_filename):
227 # append the relative path to the base_path
228 url_or_filename = url_or_path_join(self._base_path, url_or_filename)
--> 229 out = cached_path(url_or_filename, download_config=download_config)
230 out = tracked_str(out)
231 out.set_origin(url_or_filename)

File C:\ProgramData\anaconda3\envs\hf_audio_course\Lib\site-packages\datasets\utils\file_utils.py:251, in cached_path(url_or_filename, download_config, **download_kwargs)
248 return output_path
250 # Eager extraction
--> 251 output_path = ExtractManager(cache_dir=download_config.cache_dir).extract(
252 output_path, force_extract=download_config.force_extract
253 )
254 return relative_to_absolute_path(output_path)

File C:\ProgramData\anaconda3\envs\hf_audio_course\Lib\site-packages\datasets\utils\extract.py:48, in ExtractManager.extract(self, input_path, force_extract)
46 output_path = self._get_output_path(input_path)
47 if self._do_extract(output_path, force_extract):
---> 48 self.extractor.extract(input_path, output_path, extractor_format)
49 return output_path

File C:\ProgramData\anaconda3\envs\hf_audio_course\Lib\site-packages\datasets\utils\extract.py:332, in Extractor.extract(cls, input_path, output_path, extractor_format)
330 shutil.rmtree(output_path, ignore_errors=True)
331 extractor = cls.extractors[extractor_format]
--> 332 return extractor.extract(input_path, output_path)

File C:\ProgramData\anaconda3\envs\hf_audio_course\Lib\site-packages\datasets\utils\extract.py:126, in TarExtractor.extract(input_path, output_path)
124 os.makedirs(output_path, exist_ok=True)
125 tar_file = tarfile.open(input_path)
--> 126 tar_file.extractall(output_path, members=TarExtractor.safemembers(tar_file, output_path))
127 tar_file.close()

File C:\ProgramData\anaconda3\envs\hf_audio_course\Lib\tarfile.py:2302, in TarFile.extractall(self, path, members, numeric_owner, filter)
2297 if tarinfo.isdir():
2298 # For directories, delay setting attributes until later,
2299 # since permissions can interfere with extraction and
2300 # extracting contents can reset mtime.
2301 directories.append(tarinfo)
-> 2302 self._extract_one(tarinfo, path, set_attrs=not tarinfo.isdir(),
2303 numeric_owner=numeric_owner)
2305 # Reverse sort directories.
2306 directories.sort(key=lambda a: a.name, reverse=True)

File C:\ProgramData\anaconda3\envs\hf_audio_course\Lib\tarfile.py:2369, in TarFile._extract_one(self, tarinfo, path, set_attrs, numeric_owner)
2365 self._extract_member(tarinfo, os.path.join(path, tarinfo.name),
2366 set_attrs=set_attrs,
2367 numeric_owner=numeric_owner)
2368 except OSError as e:
-> 2369 self._handle_fatal_error(e)
2370 except ExtractError as e:
2371 self._handle_nonfatal_error(e)

File C:\ProgramData\anaconda3\envs\hf_audio_course\Lib\tarfile.py:2365, in TarFile._extract_one(self, tarinfo, path, set_attrs, numeric_owner)
2362 self._check("r")
2364 try:
-> 2365 self._extract_member(tarinfo, os.path.join(path, tarinfo.name),
2366 set_attrs=set_attrs,
2367 numeric_owner=numeric_owner)
2368 except OSError as e:
2369 self._handle_fatal_error(e)

File C:\ProgramData\anaconda3\envs\hf_audio_course\Lib\tarfile.py:2448, in TarFile._extract_member(self, tarinfo, targetpath, set_attrs, numeric_owner)
2445 self._dbg(1, tarinfo.name)
2447 if tarinfo.isreg():
-> 2448 self.makefile(tarinfo, targetpath)
2449 elif tarinfo.isdir():
2450 self.makedir(tarinfo, targetpath)

File C:\ProgramData\anaconda3\envs\hf_audio_course\Lib\tarfile.py:2494, in TarFile.makefile(self, tarinfo, targetpath)
2492 source.seek(tarinfo.offset_data)
2493 bufsize = self.copybufsize
-> 2494 with bltn_open(targetpath, "wb") as target:
2495 if tarinfo.sparse is not None:
2496 for offset, size in tarinfo.sparse:

OSError: [Errno 22] Invalid argument: 'C:\Users\APU.cache\huggingface\datasets\downloads\extracted\49afd6ed6a1455c643d97d6bc9dcba821db2c51ee26fe1279355df74a0d10a31\train_part_4\20140116-0900-PLENARY-4-nl_20140116-10:46:51_1.wav'