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[kashif]

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[Mita23456]

Hello

[hnqh888]

when I use the following code to download the fashion mnist dataset , it reports the following type error:
i use the tf-gpu virtual environment ,the tensorflow-datasets=4.9.2,tensorflow-gpu=2.3.0,the same problem occurs in MNIST datasets, i download the dataset file from tensorflow-datasets relative GitHub site and extracted normally.

code:
import tensorflow_datasets as tfds

data_dir = 'F:/TensorFlow/Tensorflow-vioce/fashiong mnist datasets'
(train_data, test_data), metadata = tfds.load('fashion_mnist',
split=['train', 'test'],
data_dir=data_dir,
download=True,
as_supervised=True,
with_info=True)

result:
TypeError Traceback (most recent call last)
Cell In[2], line 4
1 import tensorflow_datasets as tfds
3 data_dir = 'F:/TensorFlow/Tensorflow-vioce/fashiong mnist datasets' # 指定数据存储目录
----> 4 (train_data, test_data), metadata = tfds.load('fashion_mnist',
5 split=['train', 'test'],
6 data_dir=data_dir,
7 download=True,
8 as_supervised=True,
9 with_info=True)

File D:\anaconda3\envs\tf-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:\anaconda3\envs\tf-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:\anaconda3\envs\tf-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:\anaconda3\envs\tf-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:\anaconda3\envs\tf-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:\anaconda3\envs\tf-gpu\lib\site-packages\tensorflow_datasets\core\dataset_builder.py:1535, in GeneratorBasedBuilder._download_and_prepare(self, dl_manager, download_config)
1523 for split_name, generator in utils.tqdm(
1524 split_generators.items(),
1525 desc="Generating splits...",
1526 unit=" splits",
1527 leave=False,
1528 ):
1529 filename_template = naming.ShardedFileTemplate(
1530 split=split_name,
1531 dataset_name=self.name,
1532 data_dir=self.data_path,
1533 filetype_suffix=path_suffix,
1534 )
-> 1535 future = split_builder.submit_split_generation(
1536 split_name=split_name,
1537 generator=generator,
1538 filename_template=filename_template,
1539 disable_shuffling=self.info.disable_shuffling,
1540 )
1541 split_info_futures.append(future)
1543 # Process the result of the beam pipeline.

File D:\anaconda3\envs\tf-gpu\lib\site-packages\tensorflow_datasets\core\split_builder.py:341, in SplitBuilder.submit_split_generation(self, split_name, generator, filename_template, disable_shuffling)
338 # Depending on the type of generator, we use the corresponding
339 # _build_from_xyz method.
340 if isinstance(generator, collections.abc.Iterable):
--> 341 return self._build_from_generator(**build_kwargs)
342 else: # Otherwise, beam required
343 unknown_generator_type = TypeError(
344 f'Invalid split generator value for split {split_name}. '
345 'Expected generator or apache_beam object. Got: '
346 f'{type(generator)}'
347 )

File D:\anaconda3\envs\tf-gpu\lib\site-packages\tensorflow_datasets\core\split_builder.py:406, in SplitBuilder._build_from_generator(self, split_name, generator, filename_template, disable_shuffling)
396 serialized_info = self._features.get_serialized_info()
397 writer = writer_lib.Writer(
398 serializer=example_serializer.ExampleSerializer(serialized_info),
399 filename_template=filename_template,
(...)
404 shard_config=self._shard_config,
405 )
--> 406 for key, example in utils.tqdm(
407 generator,
408 desc=f'Generating {split_name} examples...',
409 unit=' examples',
410 total=total_num_examples,
411 leave=False,
412 ):
413 try:
414 example = self._features.encode_example(example)

File D:\anaconda3\envs\tf-gpu\lib\site-packages\tqdm\std.py:1182, in tqdm.iter(self)
1179 time = self._time
1181 try:
-> 1182 for obj in iterable:
1183 yield obj
1184 # Update and possibly print the progressbar.
1185 # Note: does not call self.update(1) for speed optimisation.

File D:\anaconda3\envs\tf-gpu\lib\site-packages\tensorflow_datasets\image_classification\mnist.py:156, in MNIST._generate_examples(self, num_examples, data_path, label_path)
145 """Generate MNIST examples as dicts.
146
147 Args:
(...)
153 Generator yielding the next examples
154 """
155 images = _extract_mnist_images(data_path, num_examples)
--> 156 labels = _extract_mnist_labels(label_path, num_examples)
157 data = list(zip(images, labels))
159 # Using index as key since data is always loaded in same order.

File D:\anaconda3\envs\tf-gpu\lib\site-packages\tensorflow_datasets\image_classification\mnist.py:393, in _extract_mnist_labels(labels_filepath, num_labels)
391 def _extract_mnist_labels(labels_filepath, num_labels):
392 with tf.io.gfile.GFile(labels_filepath, "rb") as f:
--> 393 f.read(8) # header
394 buf = f.read(num_labels)
395 labels = np.frombuffer(buf, dtype=np.uint8).astype(np.int64)

File ~\AppData\Roaming\Python\Python38\site-packages\tensorflow\python\lib\io\file_io.py:116, in FileIO.read(self, n)
104 def read(self, n=-1):
105 """Returns the contents of a file as a string.
106
107 Starts reading from current position in file.
(...)
114 string if in string (regular) mode.
115 """
--> 116 self._preread_check()
117 if n == -1:
118 length = self.size() - self.tell()

File ~\AppData\Roaming\Python\Python38\site-packages\tensorflow\python\lib\io\file_io.py:79, in FileIO._preread_check(self)
76 raise errors.PermissionDeniedError(None, None,
77 "File isn't open for reading")
78 print("self.__name:",self.__name)
---> 79 self._read_buf = _pywrap_file_io.BufferedInputStream(self.__name, 1024 * 1024)

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('F:\TensorFlow\Tensorflow-vioce\fashiong mnist datasets\downloads\extracted\GZIP.fashion-mnist_train-labels-idx1-ubyteoE8XE0rANWCkfjdk4RuS_JfeTRv6-LoaOqKa9UzJCEU.gz'), 1048576

[Felipe-Ordenes]

Hola, no puedo descargar la data