
'''simple docstring'''

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

__snake_case:  List[str]								=			collections.namedtuple("_Datasets", ["train", "validation", "test"])

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






def 	_snake_case						(      A_       :    List[Any]   ):
  """simple docstring"""







  a_      :	str      =							numpy.dtype(numpy.uintaa   ).newbyteorder(""">"""   )
  return numpy.frombuffer(bytestream.read(4   )     ,		dtype=_lowerCamelCase   )[0]






@deprecated(_lowerCamelCase     ,		"""Please use tf.data to implement this functionality."""   )
def 	_snake_case						(      A_       :    int   ):
  """simple docstring"""







  print("""Extracting"""     ,		f.name   )
  with gzip.GzipFile(fileobj=_lowerCamelCase   ) as bytestream:
    a_      :	str      =							_readaa(_lowerCamelCase   )
    if magic != 2051:
      raise ValueError(
          """Invalid magic number %d in MNIST image file: %s""" % (magic, f.name)   )
    a_      :	List[str]      =							_readaa(_lowerCamelCase   )
    a_      :	Dict      =							_readaa(_lowerCamelCase   )
    a_      :	Optional[int]      =							_readaa(_lowerCamelCase   )
    a_      :	Dict      =							bytestream.read(rows * cols * num_images   )
    a_      :	Optional[int]      =							numpy.frombuffer(_lowerCamelCase     ,		dtype=numpy.uinta   )
    a_      :	Dict      =							data.reshape(_lowerCamelCase     ,		_lowerCamelCase     ,		_lowerCamelCase     ,		1   )
    return data






@deprecated(_lowerCamelCase     ,		"""Please use tf.one_hot on tensors."""   )
def 	_snake_case						(      A_       :    List[str]     ,		A_       :    List[str]   ):
  """simple docstring"""







  a_      :	str      =							labels_dense.shape[0]
  a_      :	str      =							numpy.arange(_lowerCamelCase   ) * num_classes
  a_      :	str      =							numpy.zeros((num_labels, num_classes)   )
  a_      :	Tuple      =							1
  return labels_one_hot






@deprecated(_lowerCamelCase     ,		"""Please use tf.data to implement this functionality."""   )
def 	_snake_case						(      A_       :    Union[str, Any]     ,		A_       :    Optional[int]=False     ,		A_       :    Optional[int]=10   ):
  """simple docstring"""







  print("""Extracting"""     ,		f.name   )
  with gzip.GzipFile(fileobj=_lowerCamelCase   ) as bytestream:
    a_      :	int      =							_readaa(_lowerCamelCase   )
    if magic != 2049:
      raise ValueError(
          """Invalid magic number %d in MNIST label file: %s""" % (magic, f.name)   )
    a_      :	Any      =							_readaa(_lowerCamelCase   )
    a_      :	List[Any]      =							bytestream.read(_lowerCamelCase   )
    a_      :	Dict      =							numpy.frombuffer(_lowerCamelCase     ,		dtype=numpy.uinta   )
    if one_hot:
      return _dense_to_one_hot(_lowerCamelCase     ,		_lowerCamelCase   )
    return labels


class  _UpperCAmelCase :

     """simple docstring"""

     @deprecated(
         lowerCAmelCase_							,		"""Please use alternatives such as official/mnist/_DataSet.py"""
         """ from tensorflow/models."""							,		)
     def __init__(      self							,		lowerCAmelCase_							,		lowerCAmelCase_							,		lowerCAmelCase_=False							,		lowerCAmelCase_=False							,		lowerCAmelCase_=dtypes.floataa							,		lowerCAmelCase_=True							,		lowerCAmelCase_=None							,		):

       '''simple docstring'''

       a_      :	Optional[int]      =							random_seed.get_seed(lowerCAmelCase_ )
       # If op level seed is not set, use whatever graph level seed is returned
       numpy.random.seed(seeda if seed is None else seeda )
       a_      :	Optional[Any]      =							dtypes.as_dtype(lowerCAmelCase_ ).base_dtype
       if dtype not in (dtypes.uinta, dtypes.floataa):
         raise TypeError("""Invalid image dtype %r, expected uint8 or float32""" % dtype )
       if fake_data:
         a_      :	str      =							1_00_00
         a_      :	Optional[Any]      =							one_hot
       else:
         assert (
             images.shape[0] == labels.shape[0]
         ), f'''images.shape: {images.shape} labels.shape: {labels.shape}'''
         a_      :	Any      =							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
           a_      :	Union[str, Any]      =							images.reshape(
               images.shape[0]							,		images.shape[1] * images.shape[2] )
         if dtype == dtypes.floataa:
           # Convert from [0, 255] -> [0.0, 1.0].
           a_      :	List[Any]      =							images.astype(numpy.floataa )
           a_      :	Optional[Any]      =							numpy.multiply(lowerCAmelCase_							,		1.0 / 255.0 )
       a_      :	Optional[Any]      =							images
       a_      :	List[Any]      =							labels
       a_      :	str      =							0
       a_      :	Union[str, Any]      =							0


     @property
     def 							_lowerCAmelCase  (      self ):

       '''simple docstring'''

       return self._images


     @property
     def 							_lowerCAmelCase  (      self ):

       '''simple docstring'''

       return self._labels


     @property
     def 							_lowerCAmelCase  (      self ):

       '''simple docstring'''

       return self._num_examples


     @property
     def 							_lowerCAmelCase  (      self ):

       '''simple docstring'''

       return self._epochs_completed






     def 							_lowerCAmelCase  (      self							,		lowerCAmelCase_							,		lowerCAmelCase_=False							,		lowerCAmelCase_=True ):

       '''simple docstring'''

       if fake_data:
         a_      :	Any      =							[1] * 7_84
         a_      :	Union[str, Any]      =							[1] + [0] * 9 if self.one_hot else 0
         return (
             [fake_image for _ in range(lowerCAmelCase_ )],
             [fake_label for _ in range(lowerCAmelCase_ )],
         )
       a_      :	str      =							self._index_in_epoch
       # Shuffle for the first epoch
       if self._epochs_completed == 0 and start == 0 and shuffle:
         a_      :	Any      =							numpy.arange(self._num_examples )
         numpy.random.shuffle(lowerCAmelCase_ )
         a_      :	int      =							self.images[perma]
         a_      :	str      =							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
         a_      :	Optional[int]      =							self._num_examples - start
         a_      :	Optional[int]      =							self._images[start : self._num_examples]
         a_      :	int      =							self._labels[start : self._num_examples]
         # Shuffle the data
         if shuffle:
           a_      :	Optional[int]      =							numpy.arange(self._num_examples )
           numpy.random.shuffle(lowerCAmelCase_ )
           a_      :	Optional[Any]      =							self.images[perm]
           a_      :	Tuple      =							self.labels[perm]
         # Start next epoch
         a_      :	Tuple      =							0
         a_      :	Union[str, Any]      =							batch_size - rest_num_examples
         a_      :	List[str]      =							self._index_in_epoch
         a_      :	Dict      =							self._images[start:end]
         a_      :	str      =							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
         a_      :	Union[str, Any]      =							self._index_in_epoch
         return self._images[start:end], self._labels[start:end]







@deprecated(_lowerCamelCase     ,		"""Please write your own downloading logic."""   )
def 	_snake_case						(      A_       :    Tuple     ,		A_       :    Union[str, Any]     ,		A_       :    Union[str, Any]   ):
  """simple docstring"""







  if not gfile.Exists(_lowerCamelCase   ):
    gfile.MakeDirs(_lowerCamelCase   )
  a_      :	Optional[Any]      =							os.path.join(_lowerCamelCase     ,		_lowerCamelCase   )
  if not gfile.Exists(_lowerCamelCase   ):
    urllib.request.urlretrieve(_lowerCamelCase     ,		_lowerCamelCase   )  # noqa: S310
    with gfile.GFile(_lowerCamelCase   ) as f:
      a_      :	Any      =							f.size()
    print("""Successfully downloaded"""     ,		_lowerCamelCase     ,		_lowerCamelCase     ,		"""bytes."""   )
  return filepath






@deprecated(
    _lowerCamelCase     ,		"""Please use alternatives such as:""" """ tensorflow_datasets.load('mnist')"""   )
def 	_snake_case						(      A_       :    str     ,		A_       :    List[Any]=False     ,		A_       :    str=False     ,		A_       :    List[str]=dtypes.floataa     ,		A_       :    Any=True     ,		A_       :    Union[str, Any]=5000     ,		A_       :    str=None     ,		A_       :    Optional[int]=DEFAULT_SOURCE_URL     ,		):
  """simple docstring"""







  if fake_data:

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

    a_      :	Optional[int]      =							fake()
    a_      :	Tuple      =							fake()
    a_      :	List[str]      =							fake()
    return _Datasets(train=_lowerCamelCase     ,		validation=_lowerCamelCase     ,		test=_lowerCamelCase   )

  if not source_url:  # empty string check
    a_      :	str      =							DEFAULT_SOURCE_URL

  a_      :	Optional[int]      =							"train-images-idx3-ubyte.gz"
  a_      :	Dict      =							"train-labels-idx1-ubyte.gz"
  a_      :	List[str]      =							"t10k-images-idx3-ubyte.gz"
  a_      :	List[str]      =							"t10k-labels-idx1-ubyte.gz"

  a_      :	Optional[int]      =							_maybe_download(
      _lowerCamelCase     ,		_lowerCamelCase     ,		source_url + train_images_file   )
  with gfile.Open(_lowerCamelCase     ,		"""rb"""   ) as f:
    a_      :	int      =							_extract_images(_lowerCamelCase   )

  a_      :	Optional[Any]      =							_maybe_download(
      _lowerCamelCase     ,		_lowerCamelCase     ,		source_url + train_labels_file   )
  with gfile.Open(_lowerCamelCase     ,		"""rb"""   ) as f:
    a_      :	int      =							_extract_labels(_lowerCamelCase     ,		one_hot=_lowerCamelCase   )

  a_      :	int      =							_maybe_download(
      _lowerCamelCase     ,		_lowerCamelCase     ,		source_url + test_images_file   )
  with gfile.Open(_lowerCamelCase     ,		"""rb"""   ) as f:
    a_      :	Optional[int]      =							_extract_images(_lowerCamelCase   )

  a_      :	str      =							_maybe_download(
      _lowerCamelCase     ,		_lowerCamelCase     ,		source_url + test_labels_file   )
  with gfile.Open(_lowerCamelCase     ,		"""rb"""   ) as f:
    a_      :	List[str]      =							_extract_labels(_lowerCamelCase     ,		one_hot=_lowerCamelCase   )

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

  a_      :	Any      =							train_images[:validation_size]
  a_      :	Optional[Any]      =							train_labels[:validation_size]
  a_      :	Optional[int]      =							train_images[validation_size:]
  a_      :	Tuple      =							train_labels[validation_size:]

  a_      :	List[str]      =							{"dtype": dtype, "reshape": reshape, "seed": seed}

  a_      :	Union[str, Any]      =							_DataSet(_lowerCamelCase     ,		_lowerCamelCase     ,		**_lowerCamelCase   )
  a_      :	str      =							_DataSet(_lowerCamelCase     ,		_lowerCamelCase     ,		**_lowerCamelCase   )
  a_      :	Optional[Any]      =							_DataSet(_lowerCamelCase     ,		_lowerCamelCase     ,		**_lowerCamelCase   )

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




'''simple docstring'''

from datasets.utils.patching import _PatchedModuleObj, patch_submodule

from . import _test_patching






def 	_snake_case						(      ):
  """simple docstring"""







  import os as original_os
  from os import path as original_path
  from os import rename as original_rename
  from os.path import dirname as original_dirname
  from os.path import join as original_join

  assert _test_patching.os is original_os
  assert _test_patching.path is original_path
  assert _test_patching.join is original_join

  assert _test_patching.renamed_os is original_os
  assert _test_patching.renamed_path is original_path
  assert _test_patching.renamed_join is original_join

  a_      :	List[str]      =							"""__test_patch_submodule_mock__"""
  with patch_submodule(_test_patching     ,		"""os.path.join"""     ,		A_   ):
    # Every way to access os.path.join must be patched, and the rest must stay untouched

    # check os.path.join
    assert isinstance(_test_patching.os     ,		_PatchedModuleObj   )
    assert isinstance(_test_patching.os.path     ,		_PatchedModuleObj   )
    assert _test_patching.os.path.join is mock

    # check path.join
    assert isinstance(_test_patching.path     ,		_PatchedModuleObj   )
    assert _test_patching.path.join is mock

    # check join
    assert _test_patching.join is mock

    # check that the other attributes are untouched
    assert _test_patching.os.rename is original_rename
    assert _test_patching.path.dirname is original_dirname
    assert _test_patching.os.path.dirname is original_dirname

    # Even renamed modules or objects must be patched

    # check renamed_os.path.join
    assert isinstance(_test_patching.renamed_os     ,		_PatchedModuleObj   )
    assert isinstance(_test_patching.renamed_os.path     ,		_PatchedModuleObj   )
    assert _test_patching.renamed_os.path.join is mock

    # check renamed_path.join
    assert isinstance(_test_patching.renamed_path     ,		_PatchedModuleObj   )
    assert _test_patching.renamed_path.join is mock

    # check renamed_join
    assert _test_patching.renamed_join is mock

    # check that the other attributes are untouched
    assert _test_patching.renamed_os.rename is original_rename
    assert _test_patching.renamed_path.dirname is original_dirname
    assert _test_patching.renamed_os.path.dirname is original_dirname

  # check that everthing is back to normal when the patch is over

  assert _test_patching.os is original_os
  assert _test_patching.path is original_path
  assert _test_patching.join is original_join

  assert _test_patching.renamed_os is original_os
  assert _test_patching.renamed_path is original_path
  assert _test_patching.renamed_join is original_join






def 	_snake_case						(      ):
  """simple docstring"""







  assert _test_patching.open is open

  a_      :	Tuple      =							"""__test_patch_submodule_builtin_mock__"""
  # _test_patching has "open" in its globals
  assert _test_patching.open is open
  with patch_submodule(_test_patching     ,		"""open"""     ,		A_   ):
    assert _test_patching.open is mock

  # check that everthing is back to normal when the patch is over

  assert _test_patching.open is open






def 	_snake_case						(      ):
  """simple docstring"""







  a_      :	Any      =							"""__test_patch_submodule_missing_mock__"""
  with patch_submodule(_test_patching     ,		"""pandas.read_csv"""     ,		A_   ):
    pass






def 	_snake_case						(      ):
  """simple docstring"""







  a_      :	int      =							"""__test_patch_submodule_missing_builtin_mock__"""
  # _test_patching doesn't have "len" in its globals
  assert getattr(_test_patching     ,		"""len"""     ,		A_   ) is None
  with patch_submodule(_test_patching     ,		"""len"""     ,		A_   ):
    assert _test_patching.len is mock
  assert _test_patching.len is len






def 	_snake_case						(      ):
  """simple docstring"""







  a_      :	List[str]      =							"""__test_patch_submodule_start_and_stop_mock__"""
  a_      :	int      =							patch_submodule(_test_patching     ,		"""open"""     ,		A_   )
  assert _test_patching.open is open
  patch.start()
  assert _test_patching.open is mock
  patch.stop()
  assert _test_patching.open is open






def 	_snake_case						(      ):
  """simple docstring"""







  from os import rename as original_rename
  from os.path import dirname as original_dirname
  from os.path import join as original_join

  a_      :	Any      =							"""__test_patch_submodule_successive_join__"""
  a_      :	Optional[Any]      =							"""__test_patch_submodule_successive_dirname__"""
  a_      :	Optional[int]      =							"""__test_patch_submodule_successive_rename__"""
  assert _test_patching.os.path.join is original_join
  assert _test_patching.os.path.dirname is original_dirname
  assert _test_patching.os.rename is original_rename

  with patch_submodule(_test_patching     ,		"""os.path.join"""     ,		A_   ):
    with patch_submodule(_test_patching     ,		"""os.rename"""     ,		A_   ):
      with patch_submodule(_test_patching     ,		"""os.path.dirname"""     ,		A_   ):
        assert _test_patching.os.path.join is mock_join
        assert _test_patching.os.path.dirname is mock_dirname
        assert _test_patching.os.rename is mock_rename

    # try another order
  with patch_submodule(_test_patching     ,		"""os.rename"""     ,		A_   ):
    with patch_submodule(_test_patching     ,		"""os.path.join"""     ,		A_   ):
      with patch_submodule(_test_patching     ,		"""os.path.dirname"""     ,		A_   ):
        assert _test_patching.os.path.join is mock_join
        assert _test_patching.os.path.dirname is mock_dirname
        assert _test_patching.os.rename is mock_rename

  assert _test_patching.os.path.join is original_join
  assert _test_patching.os.path.dirname is original_dirname
  assert _test_patching.os.rename is original_rename






def 	_snake_case						(      ):
  """simple docstring"""







  a_      :	Optional[int]      =							"""__test_patch_submodule_doesnt_exist_mock__"""
  with patch_submodule(_test_patching     ,		"""__module_that_doesn_exist__.__attribute_that_doesn_exist__"""     ,		A_   ):
    pass
  with patch_submodule(_test_patching     ,		"""os.__attribute_that_doesn_exist__"""     ,		A_   ):
    pass


