



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

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

# CVDF mirror of http://yann.lecun.com/exdb/mnist/
a__   :					Union[str, Any] 						=      "https://storage.googleapis.com/cvdf-datasets/mnist/"

def 	_lowerCAmelCase (    A__						):
      lowercase__  =	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 	_lowerCAmelCase (    A__						):
      print('Extracting'    ,	f.name						)
      with gzip.GzipFile(fileobj=A__						) as bytestream:
            lowercase__  =	_readaa(A__						)
            if magic != 2_051:
                  raise ValueError(
                      'Invalid magic number %d in MNIST image file: %s' % (magic, f.name)						)
            lowercase__  =	_readaa(A__						)
            lowercase__  =	_readaa(A__						)
            lowercase__  =	_readaa(A__						)
            lowercase__  =	bytestream.read(rows * cols * num_images						)
            lowercase__  =	numpy.frombuffer(A__    ,	dtype=numpy.uinta						)
            lowercase__  =	data.reshape(A__    ,	A__    ,	A__    ,	1						)
            return data

@deprecated(A__    ,	'Please use tf.one_hot on tensors.'						)
def 	_lowerCAmelCase (    A__    ,	A__						):
      lowercase__  =	labels_dense.shape[0]
      lowercase__  =	numpy.arange(A__						) * num_classes
      lowercase__  =	numpy.zeros((num_labels, num_classes)						)
      lowercase__  =	1
      return labels_one_hot

@deprecated(A__    ,	'Please use tf.data to implement this functionality.'						)
def 	_lowerCAmelCase (    A__    ,	A__=False    ,	A__=10						):
      print('Extracting'    ,	f.name						)
      with gzip.GzipFile(fileobj=A__						) as bytestream:
            lowercase__  =	_readaa(A__						)
            if magic != 2_049:
                  raise ValueError(
                      'Invalid magic number %d in MNIST label file: %s' % (magic, f.name)						)
            lowercase__  =	_readaa(A__						)
            lowercase__  =	bytestream.read(A__						)
            lowercase__  =	numpy.frombuffer(A__    ,	dtype=numpy.uinta						)
            if one_hot:
                  return _dense_to_one_hot(A__    ,	A__						)
            return labels



class    UpperCAmelCase__:

   '''simple docstring'''




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




         """simple docstring"""

         lowercase__,						lowercase__  =	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)
         lowercase__  =	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:
               lowercase__  =	1_00_00
               lowercase__  =	one_hot
         else:
               assert (
                   images.shape[0] == labels.shape[0]
               ), f'''images.shape: {images.shape} labels.shape: {labels.shape}'''
               lowercase__  =	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
                     lowercase__  =	images.reshape(
                         images.shape[0]      ,					images.shape[1] * images.shape[2])
               if dtype == dtypes.floataa:
                     # Convert from [0, 255] -> [0.0, 1.0].
                     lowercase__  =	images.astype(numpy.floataa)
                     lowercase__  =	numpy.multiply(lowerCAmelCase      ,					1.0 / 2_55.0)
         lowercase__  =	images
         lowercase__  =	labels
         lowercase__  =	0
         lowercase__  =	0


   @property
   def       UpperCAmelCase		(    self	:      Optional[int])						->					Optional[Any]:




         """simple docstring"""

         return self._images


   @property
   def       UpperCAmelCase		(    self	:      str)						->					Tuple:




         """simple docstring"""

         return self._labels


   @property
   def       UpperCAmelCase		(    self	:      str)						->					Optional[Any]:




         """simple docstring"""

         return self._num_examples


   @property
   def       UpperCAmelCase		(    self	:      int)						->					int:




         """simple docstring"""

         return self._epochs_completed



   def       UpperCAmelCase		(    self	:      Union[str, Any]      ,					lowerCAmelCase	:      Dict      ,					lowerCAmelCase	:      Any=False      ,					lowerCAmelCase	:      str=True)						->					Optional[int]:




         """simple docstring"""

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

@deprecated(A__    ,	'Please write your own downloading logic.'						)
def 	_lowerCAmelCase (    A__    ,	A__    ,	A__						):
      if not gfile.Exists(A__						):
            gfile.MakeDirs(A__						)
      lowercase__  =	os.path.join(A__    ,	A__						)
      if not gfile.Exists(A__						):
            urllib.request.urlretrieve(A__    ,	A__						)  # noqa: S310
            with gfile.GFile(A__						) as f:
                  lowercase__  =	f.size()
            print('Successfully downloaded'    ,	A__    ,	A__    ,	'bytes.'						)
      return filepath

@deprecated(
    A__    ,	'Please use alternatives such as:' ' tensorflow_datasets.load(\'mnist\')'						)
def 	_lowerCAmelCase (    A__    ,	A__=False    ,	A__=False    ,	A__=dtypes.floataa    ,	A__=True    ,	A__=5_000    ,	A__=None    ,	A__=DEFAULT_SOURCE_URL    ,	):
      if fake_data:

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

            lowercase__  =	fake()
            lowercase__  =	fake()
            lowercase__  =	fake()
            return _Datasets(train=A__    ,	validation=A__    ,	test=A__						)

      if not source_url:  # empty string check
            lowercase__  =	DEFAULT_SOURCE_URL

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

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

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

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

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

      if not 0 <= validation_size <= len(A__						):
            lowercase__  =	(
                'Validation size should be between 0 and '
                F'''{len(A__						)}. Received: {validation_size}.'''
            )
            raise ValueError(A__						)

      lowercase__  =	train_images[:validation_size]
      lowercase__  =	train_labels[:validation_size]
      lowercase__  =	train_images[validation_size:]
      lowercase__  =	train_labels[validation_size:]

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

      lowercase__  =	_DataSet(A__    ,	A__    ,	**A__						)
      lowercase__  =	_DataSet(A__    ,	A__    ,	**A__						)
      lowercase__  =	_DataSet(A__    ,	A__    ,	**A__						)

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





from datasets.utils.patching import _PatchedModuleObj, patch_submodule

from . import _test_patching

def 	_lowerCAmelCase (    ):
      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

      lowercase__  =	'__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 	_lowerCAmelCase (    ):
      assert _test_patching.open is open

      lowercase__  =	'__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 	_lowerCAmelCase (    ):
      # pandas.read_csv is not present in _test_patching
      lowercase__  =	'__test_patch_submodule_missing_mock__'
      with patch_submodule(_test_patching    ,	'pandas.read_csv'    ,	A__						):
            pass

def 	_lowerCAmelCase (    ):
      # builtin should always be mocked even if they're not in the globals
      # in case they're loaded at one point
      lowercase__  =	'__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 	_lowerCAmelCase (    ):
      lowercase__  =	'__test_patch_submodule_start_and_stop_mock__'
      lowercase__  =	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 	_lowerCAmelCase (    ):
      from os import rename as original_rename
      from os.path import dirname as original_dirname
      from os.path import join as original_join

      lowercase__  =	'__test_patch_submodule_successive_join__'
      lowercase__  =	'__test_patch_submodule_successive_dirname__'
      lowercase__  =	'__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 	_lowerCAmelCase (    ):
      lowercase__  =	'__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
