
import collections
import gzip
import os
import urllib

import numpy
from tensorflow.python.framework import dtypes, random_seed
from tensorflow.python.platform import gfile
from tensorflow.python.util.deprecation import deprecated

_lowerCamelCase			:							Dict         =     collections.namedtuple('''_Datasets''', ['''train''', '''validation''', '''test'''])

# CVDF mirror of http://yann.lecun.com/exdb/mnist/
_lowerCamelCase			:							List[str]         =     '''https://storage.googleapis.com/cvdf-datasets/mnist/'''






def 			a_						(			__lowercase  :      str					)					->    Any:
			_snake_case            =     numpy.dtype(numpy.uintaa					).newbyteorder('>'					)
			return numpy.frombuffer(bytestream.read(4					)			,   dtype=__A					)[0]






@deprecated(__A			,   'Please use tf.data to implement this functionality.'					)
def 			a_						(			__lowercase  :      Union[str, Any]					)					->    List[str]:
			print('Extracting'			,   f.name					)
			with gzip.GzipFile(fileobj=__A					) as bytestream:
						_snake_case            =     _readaa(__A					)
						if magic != 2_051:
									raise ValueError(
									    'Invalid magic number %d in MNIST image file: %s' % (magic, f.name)					)
						_snake_case            =     _readaa(__A					)
						_snake_case            =     _readaa(__A					)
						_snake_case            =     _readaa(__A					)
						_snake_case            =     bytestream.read(rows * cols * num_images					)
						_snake_case            =     numpy.frombuffer(__A			,   dtype=numpy.uinta					)
						_snake_case            =     data.reshape(__A			,   __A			,   __A			,   1					)
						return data






@deprecated(__A			,   'Please use tf.one_hot on tensors.'					)
def 			a_						(			__lowercase  :      Dict			,   __lowercase  :      Any					)					->    List[str]:
			_snake_case            =     labels_dense.shape[0]
			_snake_case            =     numpy.arange(__A					) * num_classes
			_snake_case            =     numpy.zeros((num_labels, num_classes)					)
			_snake_case            =     1
			return labels_one_hot






@deprecated(__A			,   'Please use tf.data to implement this functionality.'					)
def 			a_						(			__lowercase  :      List[str]			,   __lowercase  :      Union[str, Any]=False			,   __lowercase  :      Tuple=10					)					->    Optional[int]:
			print('Extracting'			,   f.name					)
			with gzip.GzipFile(fileobj=__A					) as bytestream:
						_snake_case            =     _readaa(__A					)
						if magic != 2_049:
									raise ValueError(
									    'Invalid magic number %d in MNIST label file: %s' % (magic, f.name)					)
						_snake_case            =     _readaa(__A					)
						_snake_case            =     bytestream.read(__A					)
						_snake_case            =     numpy.frombuffer(__A			,   dtype=numpy.uinta					)
						if one_hot:
									return _dense_to_one_hot(__A			,   __A					)
						return labels




class   SCREAMING_SNAKE_CASE__	:





	'''simple docstring'''



	@deprecated(
	    lowercase     ,    'Please use alternatives such as official/mnist/_DataSet.py'
	    ' from tensorflow/models.'     ,    )
	def __init__(    self      :       Any     ,    lowercase      :       Tuple     ,    lowercase      :       Optional[int]     ,    lowercase      :       Dict=False     ,    lowercase      :       List[Any]=False     ,    lowercase      :       Optional[Any]=dtypes.floataa     ,    lowercase      :       Tuple=True     ,    lowercase      :       Tuple=None     ,    ):


				'''simple docstring'''


				_snake_case            =     random_seed.get_seed(lowercase      )
				# If op level seed is not set, use whatever graph level seed is returned
				numpy.random.seed(seeda if seed is None else seeda      )
				_snake_case            =     dtypes.as_dtype(lowercase      ).base_dtype
				if dtype not in (dtypes.uinta, dtypes.floataa):
							raise TypeError('Invalid image dtype %r, expected uint8 or float32' % dtype      )
				if fake_data:
							_snake_case            =     10_000
							_snake_case            =     one_hot
				else:
							assert (
							    images.shape[0] == labels.shape[0]
							), f'''images.shape: {images.shape} labels.shape: {labels.shape}'''
							_snake_case            =     images.shape[0]

							# Convert shape from [num examples, rows, columns, depth]
							# to [num examples, rows*columns] (assuming depth == 1)
							if reshape:
										assert images.shape[3] == 1
										_snake_case            =     images.reshape(
										    images.shape[0]     ,    images.shape[1] * images.shape[2]      )
							if dtype == dtypes.floataa:
										# Convert from [0, 255] -> [0.0, 1.0].
										_snake_case            =     images.astype(numpy.floataa      )
										_snake_case            =     numpy.multiply(lowercase     ,    1.0 / 255.0      )
				_snake_case            =     images
				_snake_case            =     labels
				_snake_case            =     0
				_snake_case            =     0



	@property
	def 					A				(    self      :       List[str]      ):


				'''simple docstring'''


				return self._images



	@property
	def 					A				(    self      :       str      ):


				'''simple docstring'''


				return self._labels



	@property
	def 					A				(    self      :       Optional[Any]      ):


				'''simple docstring'''


				return self._num_examples



	@property
	def 					A				(    self      :       Tuple      ):


				'''simple docstring'''


				return self._epochs_completed





	def 					A				(    self      :       List[str]     ,    lowercase      :       int     ,    lowercase      :       Union[str, Any]=False     ,    lowercase      :       str=True      ):


				'''simple docstring'''


				if fake_data:
							_snake_case            =     [1] * 784
							_snake_case            =     [1] + [0] * 9 if self.one_hot else 0
							return (
							    [fake_image for _ in range(lowercase      )],
							    [fake_label for _ in range(lowercase      )],
							)
				_snake_case            =     self._index_in_epoch
				# Shuffle for the first epoch
				if self._epochs_completed == 0 and start == 0 and shuffle:
							_snake_case            =     numpy.arange(self._num_examples      )
							numpy.random.shuffle(lowercase      )
							_snake_case            =     self.images[perma]
							_snake_case            =     self.labels[perma]
				# Go to the next epoch
				if start + batch_size > self._num_examples:
							# Finished epoch
							self._epochs_completed += 1
							# Get the rest examples in this epoch
							_snake_case            =     self._num_examples - start
							_snake_case            =     self._images[start : self._num_examples]
							_snake_case            =     self._labels[start : self._num_examples]
							# Shuffle the data
							if shuffle:
										_snake_case            =     numpy.arange(self._num_examples      )
										numpy.random.shuffle(lowercase      )
										_snake_case            =     self.images[perm]
										_snake_case            =     self.labels[perm]
							# Start next epoch
							_snake_case            =     0
							_snake_case            =     batch_size - rest_num_examples
							_snake_case            =     self._index_in_epoch
							_snake_case            =     self._images[start:end]
							_snake_case            =     self._labels[start:end]
							return (
							    numpy.concatenate((images_rest_part, images_new_part)     ,    axis=0      ),
							    numpy.concatenate((labels_rest_part, labels_new_part)     ,    axis=0      ),
							)
				else:
							self._index_in_epoch += batch_size
							_snake_case            =     self._index_in_epoch
							return self._images[start:end], self._labels[start:end]






@deprecated(__A			,   'Please write your own downloading logic.'					)
def 			a_						(			__lowercase  :      Optional[Any]			,   __lowercase  :      Union[str, Any]			,   __lowercase  :      Optional[int]					)					->    Dict:




			if not gfile.Exists(__A					):
						gfile.MakeDirs(__A					)
			_snake_case            =     os.path.join(__A			,   __A					)
			if not gfile.Exists(__A					):
						urllib.request.urlretrieve(__A			,   __A					)  # noqa: S310
						with gfile.GFile(__A					) as f:
									_snake_case            =     f.size()
						print('Successfully downloaded'			,   __A			,   __A			,   'bytes.'					)
			return filepath






@deprecated(
    __A			,   'Please use alternatives such as:' ' tensorflow_datasets.load(\'mnist\')'					)
def 			a_						(			__lowercase  :      Any			,   __lowercase  :      Union[str, Any]=False			,   __lowercase  :      Tuple=False			,   __lowercase  :      Optional[Any]=dtypes.floataa			,   __lowercase  :      List[Any]=True			,   __lowercase  :      str=5_000			,   __lowercase  :      Any=None			,   __lowercase  :      Any=DEFAULT_SOURCE_URL			,   )					->    Dict:




			if fake_data:

						def fake():
									return _DataSet(
									    []			,   []			,   fake_data=__A			,   one_hot=__A			,   dtype=__A			,   seed=__A					)

						_snake_case            =     fake()
						_snake_case            =     fake()
						_snake_case            =     fake()
						return _Datasets(train=__A			,   validation=__A			,   test=__A					)

			if not source_url:  # empty string check
						_snake_case            =     DEFAULT_SOURCE_URL

			_snake_case            =     '''train-images-idx3-ubyte.gz'''
			_snake_case            =     '''train-labels-idx1-ubyte.gz'''
			_snake_case            =     '''t10k-images-idx3-ubyte.gz'''
			_snake_case            =     '''t10k-labels-idx1-ubyte.gz'''

			_snake_case            =     _maybe_download(
			    __A			,   __A			,   source_url + train_images_file					)
			with gfile.Open(__A			,   'rb'					) as f:
						_snake_case            =     _extract_images(__A					)

			_snake_case            =     _maybe_download(
			    __A			,   __A			,   source_url + train_labels_file					)
			with gfile.Open(__A			,   'rb'					) as f:
						_snake_case            =     _extract_labels(__A			,   one_hot=__A					)

			_snake_case            =     _maybe_download(
			    __A			,   __A			,   source_url + test_images_file					)
			with gfile.Open(__A			,   'rb'					) as f:
						_snake_case            =     _extract_images(__A					)

			_snake_case            =     _maybe_download(
			    __A			,   __A			,   source_url + test_labels_file					)
			with gfile.Open(__A			,   'rb'					) as f:
						_snake_case            =     _extract_labels(__A			,   one_hot=__A					)

			if not 0 <= validation_size <= len(__A					):
						_snake_case            =     (
						    '''Validation size should be between 0 and '''
						    f'''{len(__A					)}. Received: {validation_size}.'''
						)
						raise ValueError(__A					)

			_snake_case            =     train_images[:validation_size]
			_snake_case            =     train_labels[:validation_size]
			_snake_case            =     train_images[validation_size:]
			_snake_case            =     train_labels[validation_size:]

			_snake_case            =     {'''dtype''': dtype, '''reshape''': reshape, '''seed''': seed}

			_snake_case            =     _DataSet(__A			,   __A			,   **__A					)
			_snake_case            =     _DataSet(__A			,   __A			,   **__A					)
			_snake_case            =     _DataSet(__A			,   __A			,   **__A					)

			return _Datasets(train=__A			,   validation=__A			,   test=__A					)







'''simple docstring'''



from ..utils import DummyObject, requires_backends
class UpperCAmelCase_       (     metaclass=__A					):




      """simple docstring"""




      UpperCamelCase_             =      ['''flax''']






      def __init__(			self      :		Dict  ,   *UpperCAmelCase      :		List[Any]  ,   **UpperCAmelCase      :		Union[str, Any]		)	->	List[Any]:


       '''simple docstring'''

       requires_backends(self  ,   ['''flax''']		)






      @classmethod
      def 					A__   (			cls      :		Any  ,   *UpperCAmelCase      :		Dict  ,   **UpperCAmelCase      :		List[str]		)	->	List[Any]:


       '''simple docstring'''

       requires_backends(cls  ,   ['''flax''']		)






      @classmethod
      def 					A__   (			cls      :		Dict  ,   *UpperCAmelCase      :		str  ,   **UpperCAmelCase      :		Any		)	->	Any:


       '''simple docstring'''

       requires_backends(cls  ,   ['''flax''']		)





class UpperCAmelCase_       (     metaclass=__A					):




      """simple docstring"""




      UpperCamelCase_             =      ['''flax''']






      def __init__(			self      :		Union[str, Any]  ,   *UpperCAmelCase      :		Optional[Any]  ,   **UpperCAmelCase      :		str		)	->	Optional[int]:


       '''simple docstring'''

       requires_backends(self  ,   ['''flax''']		)






      @classmethod
      def 					A__   (			cls      :		Tuple  ,   *UpperCAmelCase      :		Any  ,   **UpperCAmelCase      :		List[Any]		)	->	int:


       '''simple docstring'''

       requires_backends(cls  ,   ['''flax''']		)






      @classmethod
      def 					A__   (			cls      :		List[Any]  ,   *UpperCAmelCase      :		Union[str, Any]  ,   **UpperCAmelCase      :		List[str]		)	->	List[Any]:


       '''simple docstring'''

       requires_backends(cls  ,   ['''flax''']		)





class UpperCAmelCase_       (     metaclass=__A					):




      """simple docstring"""




      UpperCamelCase_             =      ['''flax''']






      def __init__(			self      :		Any  ,   *UpperCAmelCase      :		int  ,   **UpperCAmelCase      :		Optional[Any]		)	->	Any:


       '''simple docstring'''

       requires_backends(self  ,   ['''flax''']		)






      @classmethod
      def 					A__   (			cls      :		str  ,   *UpperCAmelCase      :		Tuple  ,   **UpperCAmelCase      :		Union[str, Any]		)	->	Optional[int]:


       '''simple docstring'''

       requires_backends(cls  ,   ['''flax''']		)






      @classmethod
      def 					A__   (			cls      :		Optional[int]  ,   *UpperCAmelCase      :		Dict  ,   **UpperCAmelCase      :		Optional[int]		)	->	List[str]:


       '''simple docstring'''

       requires_backends(cls  ,   ['''flax''']		)





class UpperCAmelCase_       (     metaclass=__A					):




      """simple docstring"""




      UpperCamelCase_             =      ['''flax''']






      def __init__(			self      :		Union[str, Any]  ,   *UpperCAmelCase      :		Optional[Any]  ,   **UpperCAmelCase      :		int		)	->	Optional[int]:


       '''simple docstring'''

       requires_backends(self  ,   ['''flax''']		)






      @classmethod
      def 					A__   (			cls      :		Tuple  ,   *UpperCAmelCase      :		Any  ,   **UpperCAmelCase      :		Optional[int]		)	->	List[Any]:


       '''simple docstring'''

       requires_backends(cls  ,   ['''flax''']		)






      @classmethod
      def 					A__   (			cls      :		int  ,   *UpperCAmelCase      :		int  ,   **UpperCAmelCase      :		Dict		)	->	Optional[Any]:


       '''simple docstring'''

       requires_backends(cls  ,   ['''flax''']		)





class UpperCAmelCase_       (     metaclass=__A					):




      """simple docstring"""




      UpperCamelCase_             =      ['''flax''']






      def __init__(			self      :		Optional[int]  ,   *UpperCAmelCase      :		Dict  ,   **UpperCAmelCase      :		Union[str, Any]		)	->	List[str]:


       '''simple docstring'''

       requires_backends(self  ,   ['''flax''']		)






      @classmethod
      def 					A__   (			cls      :		str  ,   *UpperCAmelCase      :		Optional[int]  ,   **UpperCAmelCase      :		List[str]		)	->	str:


       '''simple docstring'''

       requires_backends(cls  ,   ['''flax''']		)






      @classmethod
      def 					A__   (			cls      :		Dict  ,   *UpperCAmelCase      :		Union[str, Any]  ,   **UpperCAmelCase      :		List[Any]		)	->	Dict:


       '''simple docstring'''

       requires_backends(cls  ,   ['''flax''']		)





class UpperCAmelCase_       (     metaclass=__A					):




      """simple docstring"""




      UpperCamelCase_             =      ['''flax''']






      def __init__(			self      :		Union[str, Any]  ,   *UpperCAmelCase      :		Any  ,   **UpperCAmelCase      :		Union[str, Any]		)	->	str:


       '''simple docstring'''

       requires_backends(self  ,   ['''flax''']		)






      @classmethod
      def 					A__   (			cls      :		Optional[Any]  ,   *UpperCAmelCase      :		Optional[Any]  ,   **UpperCAmelCase      :		Optional[Any]		)	->	str:


       '''simple docstring'''

       requires_backends(cls  ,   ['''flax''']		)






      @classmethod
      def 					A__   (			cls      :		Optional[int]  ,   *UpperCAmelCase      :		Union[str, Any]  ,   **UpperCAmelCase      :		Dict		)	->	Dict:


       '''simple docstring'''

       requires_backends(cls  ,   ['''flax''']		)





class UpperCAmelCase_       (     metaclass=__A					):




      """simple docstring"""




      UpperCamelCase_             =      ['''flax''']






      def __init__(			self      :		int  ,   *UpperCAmelCase      :		List[Any]  ,   **UpperCAmelCase      :		Tuple		)	->	Union[str, Any]:


       '''simple docstring'''

       requires_backends(self  ,   ['''flax''']		)






      @classmethod
      def 					A__   (			cls      :		Any  ,   *UpperCAmelCase      :		int  ,   **UpperCAmelCase      :		Optional[Any]		)	->	str:


       '''simple docstring'''

       requires_backends(cls  ,   ['''flax''']		)






      @classmethod
      def 					A__   (			cls      :		Union[str, Any]  ,   *UpperCAmelCase      :		List[str]  ,   **UpperCAmelCase      :		List[str]		)	->	Optional[Any]:


       '''simple docstring'''

       requires_backends(cls  ,   ['''flax''']		)





class UpperCAmelCase_       (     metaclass=__A					):




      """simple docstring"""




      UpperCamelCase_             =      ['''flax''']






      def __init__(			self      :		Union[str, Any]  ,   *UpperCAmelCase      :		Union[str, Any]  ,   **UpperCAmelCase      :		List[str]		)	->	List[Any]:


       '''simple docstring'''

       requires_backends(self  ,   ['''flax''']		)






      @classmethod
      def 					A__   (			cls      :		Optional[Any]  ,   *UpperCAmelCase      :		Optional[Any]  ,   **UpperCAmelCase      :		Any		)	->	List[Any]:


       '''simple docstring'''

       requires_backends(cls  ,   ['''flax''']		)






      @classmethod
      def 					A__   (			cls      :		Dict  ,   *UpperCAmelCase      :		Any  ,   **UpperCAmelCase      :		Optional[Any]		)	->	List[Any]:


       '''simple docstring'''

       requires_backends(cls  ,   ['''flax''']		)





class UpperCAmelCase_       (     metaclass=__A					):




      """simple docstring"""




      UpperCamelCase_             =      ['''flax''']






      def __init__(			self      :		Optional[int]  ,   *UpperCAmelCase      :		Optional[int]  ,   **UpperCAmelCase      :		Any		)	->	Any:


       '''simple docstring'''

       requires_backends(self  ,   ['''flax''']		)






      @classmethod
      def 					A__   (			cls      :		Tuple  ,   *UpperCAmelCase      :		List[str]  ,   **UpperCAmelCase      :		Optional[int]		)	->	List[str]:


       '''simple docstring'''

       requires_backends(cls  ,   ['''flax''']		)






      @classmethod
      def 					A__   (			cls      :		Union[str, Any]  ,   *UpperCAmelCase      :		Any  ,   **UpperCAmelCase      :		int		)	->	Tuple:


       '''simple docstring'''

       requires_backends(cls  ,   ['''flax''']		)





class UpperCAmelCase_       (     metaclass=__A					):




      """simple docstring"""




      UpperCamelCase_             =      ['''flax''']






      def __init__(			self      :		Optional[int]  ,   *UpperCAmelCase      :		Union[str, Any]  ,   **UpperCAmelCase      :		Dict		)	->	int:


       '''simple docstring'''

       requires_backends(self  ,   ['''flax''']		)






      @classmethod
      def 					A__   (			cls      :		List[str]  ,   *UpperCAmelCase      :		Dict  ,   **UpperCAmelCase      :		Dict		)	->	List[Any]:


       '''simple docstring'''

       requires_backends(cls  ,   ['''flax''']		)






      @classmethod
      def 					A__   (			cls      :		str  ,   *UpperCAmelCase      :		Optional[Any]  ,   **UpperCAmelCase      :		str		)	->	int:


       '''simple docstring'''

       requires_backends(cls  ,   ['''flax''']		)





class UpperCAmelCase_       (     metaclass=__A					):




      """simple docstring"""




      UpperCamelCase_             =      ['''flax''']






      def __init__(			self      :		Optional[int]  ,   *UpperCAmelCase      :		Any  ,   **UpperCAmelCase      :		Optional[int]		)	->	Optional[int]:


       '''simple docstring'''

       requires_backends(self  ,   ['''flax''']		)






      @classmethod
      def 					A__   (			cls      :		Optional[int]  ,   *UpperCAmelCase      :		Dict  ,   **UpperCAmelCase      :		Optional[Any]		)	->	Dict:


       '''simple docstring'''

       requires_backends(cls  ,   ['''flax''']		)






      @classmethod
      def 					A__   (			cls      :		str  ,   *UpperCAmelCase      :		str  ,   **UpperCAmelCase      :		Any		)	->	int:


       '''simple docstring'''

       requires_backends(cls  ,   ['''flax''']		)





class UpperCAmelCase_       (     metaclass=__A					):




      """simple docstring"""




      UpperCamelCase_             =      ['''flax''']






      def __init__(			self      :		Optional[int]  ,   *UpperCAmelCase      :		str  ,   **UpperCAmelCase      :		Any		)	->	Optional[int]:


       '''simple docstring'''

       requires_backends(self  ,   ['''flax''']		)






      @classmethod
      def 					A__   (			cls      :		Optional[int]  ,   *UpperCAmelCase      :		Tuple  ,   **UpperCAmelCase      :		Any		)	->	Dict:


       '''simple docstring'''

       requires_backends(cls  ,   ['''flax''']		)






      @classmethod
      def 					A__   (			cls      :		Optional[int]  ,   *UpperCAmelCase      :		Optional[int]  ,   **UpperCAmelCase      :		Optional[Any]		)	->	Dict:


       '''simple docstring'''

       requires_backends(cls  ,   ['''flax''']		)





class UpperCAmelCase_       (     metaclass=__A					):




      """simple docstring"""




      UpperCamelCase_             =      ['''flax''']






      def __init__(			self      :		Optional[Any]  ,   *UpperCAmelCase      :		str  ,   **UpperCAmelCase      :		int		)	->	Tuple:


       '''simple docstring'''

       requires_backends(self  ,   ['''flax''']		)






      @classmethod
      def 					A__   (			cls      :		Dict  ,   *UpperCAmelCase      :		List[Any]  ,   **UpperCAmelCase      :		Optional[int]		)	->	str:


       '''simple docstring'''

       requires_backends(cls  ,   ['''flax''']		)






      @classmethod
      def 					A__   (			cls      :		Union[str, Any]  ,   *UpperCAmelCase      :		List[Any]  ,   **UpperCAmelCase      :		Union[str, Any]		)	->	Union[str, Any]:


       '''simple docstring'''

       requires_backends(cls  ,   ['''flax''']		)



