问tensorflow2中tensorflow_datasets的函数load遇到的问题？

TypeError                                 Traceback (most recent call last)
Input In [3], in <cell line: 1>()
----> 1 (train_data,test_data,info)=tfds.load("imdb_reviews/subwords8k",
      2                                      split=(tfds.Split.TRAIN,tfds.Split.TEST),
      3                                      with_info=True,
      4                                      as_supervised=True)

File D:\anaconda\envs\tensorflow_gpu\lib\site-packages\tensorflow_datasets\core\logging\__init__.py:169, in _FunctionDecorator.__call__(self, function, instance, args, kwargs)
    167 metadata = self._start_call()
    168 try:
--> 169   return function(*args, **kwargs)
    170 except Exception:
    171   metadata.mark_error()

File D:\anaconda\envs\tensorflow_gpu\lib\site-packages\tensorflow_datasets\core\load.py:640, in load(name, split, data_dir, batch_size, shuffle_files, download, as_supervised, decoders, read_config, with_info, builder_kwargs, download_and_prepare_kwargs, as_dataset_kwargs, try_gcs)
    521 """Loads the named dataset into a `tf.data.Dataset`.
    522 
    523 `tfds.load` is a convenience method that:
   (...)
    632     Split-specific information is available in `ds_info.splits`.
    633 """
    634 dbuilder = _fetch_builder(
    635     name,
    636     data_dir,
    637     builder_kwargs,
    638     try_gcs,
    639 )
--> 640 _download_and_prepare_builder(dbuilder, download, download_and_prepare_kwargs)
    642 if as_dataset_kwargs is None:
    643   as_dataset_kwargs = {}

File D:\anaconda\envs\tensorflow_gpu\lib\site-packages\tensorflow_datasets\core\load.py:499, in _download_and_prepare_builder(dbuilder, download, download_and_prepare_kwargs)
    497 if download:
    498   download_and_prepare_kwargs = download_and_prepare_kwargs or {}
--> 499   dbuilder.download_and_prepare(**download_and_prepare_kwargs)

File D:\anaconda\envs\tensorflow_gpu\lib\site-packages\tensorflow_datasets\core\logging\__init__.py:169, in _FunctionDecorator.__call__(self, function, instance, args, kwargs)
    167 metadata = self._start_call()
    168 try:
--> 169   return function(*args, **kwargs)
    170 except Exception:
    171   metadata.mark_error()

File D:\anaconda\envs\tensorflow_gpu\lib\site-packages\tensorflow_datasets\core\dataset_builder.py:646, in DatasetBuilder.download_and_prepare(self, download_dir, download_config, file_format)
    644   self.info.read_from_directory(self._data_dir)
    645 else:
--> 646   self._download_and_prepare(
    647       dl_manager=dl_manager,
    648       download_config=download_config,
    649   )
    651   # NOTE: If modifying the lines below to put additional information in
    652   # DatasetInfo, you'll likely also want to update
    653   # DatasetInfo.read_from_directory to possibly restore these attributes
    654   # when reading from package data.
    655   self.info.download_size = dl_manager.downloaded_size

File D:\anaconda\envs\tensorflow_gpu\lib\site-packages\tensorflow_datasets\core\dataset_builder.py:1498, in GeneratorBasedBuilder._download_and_prepare(self, dl_manager, download_config)
   1496 else:
   1497   optional_pipeline_kwargs = {}
-> 1498 split_generators = self._split_generators(  # pylint: disable=unexpected-keyword-arg
   1499     dl_manager, **optional_pipeline_kwargs
   1500 )
   1501 # TODO(tfds): Could be removed once all datasets are migrated.
   1502 # https://github.com/tensorflow/datasets/issues/2537
   1503 # Legacy mode (eventually convert list[SplitGeneratorLegacy] -> dict)
   1504 split_generators = split_builder.normalize_legacy_split_generators(
   1505     split_generators=split_generators,
   1506     generator_fn=self._generate_examples,
   1507     is_beam=isinstance(self, BeamBasedBuilder),
   1508 )

File D:\anaconda\envs\tensorflow_gpu\lib\site-packages\tensorflow_datasets\datasets\imdb_reviews\imdb_reviews_dataset_builder.py:115, in Builder._split_generators(self, dl_manager)
    112 archive = lambda: dl_manager.iter_archive(arch_path)
    114 # Generate vocabulary from training data if SubwordTextEncoder configured
--> 115 self.info.features["text"].maybe_build_from_corpus(
    116     self._vocab_text_gen(archive())
    117 )
    119 return [
    120     tfds.core.SplitGenerator(
    121         name=tfds.Split.TRAIN,
   (...)
    141     ),
    142 ]

File D:\anaconda\envs\tensorflow_gpu\lib\site-packages\tensorflow_datasets\core\features\text_feature.py:169, in Text.maybe_build_from_corpus(self, corpus_generator, **kwargs)
    166   return
    168 vocab_size = self._encoder_config.vocab_size
--> 169 self.encoder = text_lib.SubwordTextEncoder.build_from_corpus(
    170     corpus_generator=corpus_generator,
    171     target_vocab_size=vocab_size,
    172     **kwargs,
    173 )

File D:\anaconda\envs\tensorflow_gpu\lib\site-packages\tensorflow_datasets\core\deprecated\text\subword_text_encoder.py:294, in SubwordTextEncoder.build_from_corpus(cls, corpus_generator, target_vocab_size, max_subword_length, max_corpus_chars, reserved_tokens)
    288 reserved_tokens = reserved_tokens or []
    289 _validate_build_arguments(
    290     max_subword_length=max_subword_length,
    291     reserved_tokens=reserved_tokens,
    292     target_vocab_size=target_vocab_size,
    293 )
--> 294 token_counts = _token_counts_from_generator(
    295     generator=corpus_generator,
    296     max_chars=max_corpus_chars,
    297     reserved_tokens=reserved_tokens,
    298 )
    300 # Binary search on the minimum token count to build a vocabulary with
    301 # approximately the right size
    302 def _binary_search(min_token_count, max_token_count):

File D:\anaconda\envs\tensorflow_gpu\lib\site-packages\tensorflow_datasets\core\deprecated\text\subword_text_encoder.py:413, in _token_counts_from_generator(generator, max_chars, reserved_tokens)
    411 num_chars = 0
    412 token_counts = collections.defaultdict(int)
--> 413 for s in generator:
    414   s = tf.compat.as_text(s)
    415   if max_chars and (num_chars + len(s)) >= max_chars:

File D:\anaconda\envs\tensorflow_gpu\lib\site-packages\tensorflow_datasets\datasets\imdb_reviews\imdb_reviews_dataset_builder.py:105, in Builder._vocab_text_gen(self, archive)
    104 def _vocab_text_gen(self, archive):
--> 105   for _, ex in self._generate_examples(
    106       archive, os.path.join("aclImdb", "train")
    107   ):
    108     yield ex["text"]

File D:\anaconda\envs\tensorflow_gpu\lib\site-packages\tensorflow_datasets\datasets\imdb_reviews\imdb_reviews_dataset_builder.py:151, in Builder._generate_examples(self, archive, directory, labeled)
    147 reg_path = "(?P<label>neg|pos)" if labeled else "unsup"
    148 reg = re.compile(
    149     os.path.join("^%s" % directory, reg_path, "").replace("\\", "\\\\")
    150 )
--> 151 for path, imdb_f in archive:
    152   res = reg.match(path)
    153   if not res:

File D:\anaconda\envs\tensorflow_gpu\lib\site-packages\tensorflow_datasets\core\download\extractor.py:179, in iter_tar(arch_f, stream)
    176 read_type = 'r' + ('|' if stream else ':') + '*'
    178 with _open_or_pass(arch_f) as fobj:
--> 179   tar = tarfile.open(mode=read_type, fileobj=fobj)
    180   for member in tar:
    181     if stream and (member.islnk() or member.issym()):
    182       # Links cannot be dereferenced in stream mode.

File D:\anaconda\envs\tensorflow_gpu\lib\tarfile.py:1599, in TarFile.open(cls, name, mode, fileobj, bufsize, **kwargs)
   1597 func = getattr(cls, cls.OPEN_METH[comptype])
   1598 if fileobj is not None:
-> 1599     saved_pos = fileobj.tell()
   1600 try:
   1601     return func(name, "r", fileobj, **kwargs)

File D:\anaconda\envs\tensorflow_gpu\lib\site-packages\tensorflow\python\lib\io\file_io.py:186, in FileIO.tell(self)
    184 """Returns the current position in the file."""
    185 if self._read_check_passed:
--> 186   self._preread_check()
    187   return self._read_buf.tell()
    188 else:

File D:\anaconda\envs\tensorflow_gpu\lib\site-packages\tensorflow\python\lib\io\file_io.py:78, in FileIO._preread_check(self)
     75 if not self._read_check_passed:
     76   raise errors.PermissionDeniedError(None, None,
     77                                      "File isn't open for reading")
---> 78 self._read_buf = _pywrap_file_io.BufferedInputStream(
     79     self.__name, 1024 * 512)

TypeError: __init__(): incompatible constructor arguments. The following argument types are supported:
    1. tensorflow.python._pywrap_file_io.BufferedInputStream(arg0: str, arg1: int)

Invoked with: WindowsGPath('C:\\Users\\123456\\tensorflow_datasets\\downloads\\ai.stanfor.edu_amaas_sentime_aclImdb_v1xA90oY07YfkP66HhdzDg046Ll8Bf3nAIlC6Rkj0WWP4.tar.gz'), 524288