






'''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

SCREAMING_SNAKE_CASE							=						collections.namedtuple('_Datasets', ['train', 'validation', 'test'])

# CVDF mirror of http://yann.lecun.com/exdb/mnist/
SCREAMING_SNAKE_CASE							=						'https://storage.googleapis.com/cvdf-datasets/mnist/'


def 				lowercase_					(     __A			:							str      )							->   Any:



 """simple docstring"""




 lowercase       : Dict						=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 				lowercase_					(     __A			:							Union[str, Any]      )							->   List[str]:



 """simple docstring"""




 print('''Extracting'''       ,   f.name      )
 with gzip.GzipFile(fileobj=__A      ) as bytestream:
  lowercase       : int						=_readaa(__A      )
  if magic != 2_0_5_1:
   raise ValueError(
       '''Invalid magic number %d in MNIST image file: %s''' % (magic, f.name)      )
  lowercase       : Optional[Any]						=_readaa(__A      )
  lowercase       : int						=_readaa(__A      )
  lowercase       : Dict						=_readaa(__A      )
  lowercase       : Union[str, Any]						=bytestream.read(rows * cols * num_images      )
  lowercase       : Union[str, Any]						=numpy.frombuffer(__A       ,   dtype=numpy.uinta      )
  lowercase       : Tuple						=data.reshape(__A       ,   __A       ,   __A       ,   1      )
  return data


@deprecated(__A       ,   '''Please use tf.one_hot on tensors.'''      )
def 				lowercase_					(     __A			:							Dict       ,   __A			:							Any      )							->   List[str]:



 """simple docstring"""




 lowercase       : str						=labels_dense.shape[0]
 lowercase       : int						=numpy.arange(__A      ) * num_classes
 lowercase       : List[str]						=numpy.zeros((num_labels, num_classes)      )
 lowercase       : Tuple						=1
 return labels_one_hot


@deprecated(__A       ,   '''Please use tf.data to implement this functionality.'''      )
def 				lowercase_					(     __A			:							List[str]       ,   __A			:							Union[str, Any]=False       ,   __A			:							Tuple=1_0      )							->   Optional[int]:



 """simple docstring"""




 print('''Extracting'''       ,   f.name      )
 with gzip.GzipFile(fileobj=__A      ) as bytestream:
  lowercase       : List[Any]						=_readaa(__A      )
  if magic != 2_0_4_9:
   raise ValueError(
       '''Invalid magic number %d in MNIST label file: %s''' % (magic, f.name)      )
  lowercase       : str						=_readaa(__A      )
  lowercase       : Optional[int]						=bytestream.read(__A      )
  lowercase       : List[str]						=numpy.frombuffer(__A       ,   dtype=numpy.uinta      )
  if one_hot:
   return _dense_to_one_hot(__A       ,   __A      )
  return labels
class UpperCAmelCase_       :




      """simple docstring"""




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


       '''simple docstring'''

       lowercase	,		lowercase       : Union[str, Any]						=random_seed.get_seed(UpperCAmelCase		)
       # 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       : Optional[int]						=dtypes.as_dtype(UpperCAmelCase		).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       : Dict						=1_0000
        lowercase       : Union[str, Any]						=one_hot
       else:
        assert (
            images.shape[0] == labels.shape[0]
        ), f'images.shape: {images.shape} labels.shape: {labels.shape}'
        lowercase       : List[str]						=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       : int						=images.reshape(
             images.shape[0]  ,   images.shape[1] * images.shape[2]		)
        if dtype == dtypes.floataa:
         # Convert from [0, 255] -> [0.0, 1.0].
         lowercase       : Optional[Any]						=images.astype(numpy.floataa		)
         lowercase       : Tuple						=numpy.multiply(UpperCAmelCase  ,   1.0 / 2_5_5.0		)
       lowercase       : Tuple						=images
       lowercase       : Optional[int]						=labels
       lowercase       : Union[str, Any]						=0
       lowercase       : Any						=0






      @property
      def 					A__   (			self      :		List[str]		)	->	int:


       '''simple docstring'''

       return self._images






      @property
      def 					A__   (			self      :		str		)	->	Dict:


       '''simple docstring'''

       return self._labels






      @property
      def 					A__   (			self      :		Optional[Any]		)	->	List[Any]:


       '''simple docstring'''

       return self._num_examples






      @property
      def 					A__   (			self      :		Tuple		)	->	List[Any]:


       '''simple docstring'''

       return self._epochs_completed






      def 					A__   (			self      :		List[str]  ,   UpperCAmelCase      :		int  ,   UpperCAmelCase      :		Union[str, Any]=False  ,   UpperCAmelCase      :		str=True		)	->	int:


       '''simple docstring'''

       if fake_data:
        lowercase       : Optional[Any]						=[1] * 784
        lowercase       : Any						=[1] + [0] * 9 if self.one_hot else 0
        return (
            [fake_image for _ in range(UpperCAmelCase		)],
            [fake_label for _ in range(UpperCAmelCase		)],
        )
       lowercase       : List[str]						=self._index_in_epoch
       # Shuffle for the first epoch
       if self._epochs_completed == 0 and start == 0 and shuffle:
        lowercase       : int						=numpy.arange(self._num_examples		)
        numpy.random.shuffle(UpperCAmelCase		)
        lowercase       : Union[str, Any]						=self.images[perma]
        lowercase       : List[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
        lowercase       : Optional[int]						=self._num_examples - start
        lowercase       : Tuple						=self._images[start : self._num_examples]
        lowercase       : Optional[Any]						=self._labels[start : self._num_examples]
        # Shuffle the data
        if shuffle:
         lowercase       : List[str]						=numpy.arange(self._num_examples		)
         numpy.random.shuffle(UpperCAmelCase		)
         lowercase       : Optional[int]						=self.images[perm]
         lowercase       : Union[str, Any]						=self.labels[perm]
        # Start next epoch
        lowercase       : str						=0
        lowercase       : Optional[int]						=batch_size - rest_num_examples
        lowercase       : Optional[int]						=self._index_in_epoch
        lowercase       : str						=self._images[start:end]
        lowercase       : Dict						=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       : Union[str, Any]						=self._index_in_epoch
        return self._images[start:end], self._labels[start:end]





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



 """simple docstring"""




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





@deprecated(
    __A       ,   '''Please use alternatives such as:''' ''' tensorflow_datasets.load(\'mnist\')'''      )
def 				lowercase_					(     __A			:							Any       ,   __A			:							Union[str, Any]=False       ,   __A			:							Tuple=False       ,   __A			:							Optional[Any]=dtypes.floataa       ,   __A			:							List[Any]=True       ,   __A			:							str=5_0_0_0       ,   __A			:							Any=None       ,   __A			:							Any=DEFAULT_SOURCE_URL       ,   )							->   Dict:



 """simple docstring"""




 if fake_data:

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

  lowercase       : Tuple						=fake()
  lowercase       : Union[str, Any]						=fake()
  lowercase       : int						=fake()
  return _Datasets(train=__A       ,   validation=__A       ,   test=__A      )

 if not source_url:  # empty string check
  lowercase       : List[Any]						=DEFAULT_SOURCE_URL

 lowercase       : List[Any]						='''train-images-idx3-ubyte.gz'''
 lowercase       : List[str]						='''train-labels-idx1-ubyte.gz'''
 lowercase       : List[Any]						='''t10k-images-idx3-ubyte.gz'''
 lowercase       : List[str]						='''t10k-labels-idx1-ubyte.gz'''

 lowercase       : Dict						=_maybe_download(
     __A       ,   __A       ,   source_url + train_images_file      )
 with gfile.Open(__A       ,   '''rb'''      ) as f:
  lowercase       : Union[str, Any]						=_extract_images(__A      )

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

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

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

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

 lowercase       : int						=train_images[:validation_size]
 lowercase       : Any						=train_labels[:validation_size]
 lowercase       : List[Any]						=train_images[validation_size:]
 lowercase       : List[Any]						=train_labels[validation_size:]

 lowercase       : int						={'''dtype''': dtype, '''reshape''': reshape, '''seed''': seed}

 lowercase       : Any						=_DataSet(__A       ,   __A       ,   **__A      )
 lowercase       : List[str]						=_DataSet(__A       ,   __A       ,   **__A      )
 lowercase       : Tuple						=_DataSet(__A       ,   __A       ,   **__A      )

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











'''simple docstring'''



import unittest

from transformers.testing_utils import CaptureStdout
from transformers.tools.python_interpreter import evaluate


def 				lowercase_					(     __A			:							str      )							->   Union[str, Any]:



 """simple docstring"""




 return x + 2





class UpperCAmelCase_       (     unittest.TestCase					):




      """simple docstring"""




      def 					A__   (			self      :		Dict		)	->	List[Any]:


       '''simple docstring'''

       lowercase       : Optional[int]						='''x = 3'''
       lowercase       : Any						={}
       lowercase       : Union[str, Any]						=evaluate(UpperCAmelCase  ,   {}  ,   state=UpperCAmelCase		)
       assert result == 3
       self.assertDictEqual(UpperCAmelCase  ,   {'''x''': 3}		)

       lowercase       : str						='''x = y'''
       lowercase       : Optional[int]						={'''y''': 5}
       lowercase       : List[str]						=evaluate(UpperCAmelCase  ,   {}  ,   state=UpperCAmelCase		)
       # evaluate returns the value of the last assignment.
       assert result == 5
       self.assertDictEqual(UpperCAmelCase  ,   {'''x''': 5, '''y''': 5}		)






      def 					A__   (			self      :		str		)	->	Optional[int]:


       '''simple docstring'''

       lowercase       : Optional[int]						='''y = add_two(x)'''
       lowercase       : str						={'''x''': 3}
       lowercase       : List[str]						=evaluate(UpperCAmelCase  ,   {'''add_two''': add_two}  ,   state=UpperCAmelCase		)
       assert result == 5
       self.assertDictEqual(UpperCAmelCase  ,   {'''x''': 3, '''y''': 5}		)

       # Won't work without the tool
       with CaptureStdout() as out:
        lowercase       : Optional[Any]						=evaluate(UpperCAmelCase  ,   {}  ,   state=UpperCAmelCase		)
       assert result is None
       assert "tried to execute add_two" in out.out






      def 					A__   (			self      :		List[Any]		)	->	Optional[int]:


       '''simple docstring'''

       lowercase       : int						='''x = 3'''
       lowercase       : Dict						={}
       lowercase       : List[Any]						=evaluate(UpperCAmelCase  ,   {}  ,   state=UpperCAmelCase		)
       assert result == 3
       self.assertDictEqual(UpperCAmelCase  ,   {'''x''': 3}		)






      def 					A__   (			self      :		str		)	->	Tuple:


       '''simple docstring'''

       lowercase       : Optional[Any]						='''test_dict = {\'x\': x, \'y\': add_two(x)}'''
       lowercase       : str						={'''x''': 3}
       lowercase       : Tuple						=evaluate(UpperCAmelCase  ,   {'''add_two''': add_two}  ,   state=UpperCAmelCase		)
       self.assertDictEqual(UpperCAmelCase  ,   {'''x''': 3, '''y''': 5}		)
       self.assertDictEqual(UpperCAmelCase  ,   {'''x''': 3, '''test_dict''': {'''x''': 3, '''y''': 5}}		)






      def 					A__   (			self      :		Union[str, Any]		)	->	Union[str, Any]:


       '''simple docstring'''

       lowercase       : Optional[Any]						='''x = 3\ny = 5'''
       lowercase       : int						={}
       lowercase       : List[str]						=evaluate(UpperCAmelCase  ,   {}  ,   state=UpperCAmelCase		)
       # evaluate returns the value of the last assignment.
       assert result == 5
       self.assertDictEqual(UpperCAmelCase  ,   {'''x''': 3, '''y''': 5}		)






      def 					A__   (			self      :		Any		)	->	Tuple:


       '''simple docstring'''

       lowercase       : List[str]						='''text = f\'This is x: {x}.\''''
       lowercase       : Union[str, Any]						={'''x''': 3}
       lowercase       : Tuple						=evaluate(UpperCAmelCase  ,   {}  ,   state=UpperCAmelCase		)
       # evaluate returns the value of the last assignment.
       assert result == "This is x: 3."
       self.assertDictEqual(UpperCAmelCase  ,   {'''x''': 3, '''text''': '''This is x: 3.'''}		)






      def 					A__   (			self      :		Union[str, Any]		)	->	List[Any]:


       '''simple docstring'''

       lowercase       : Tuple						='''if x <= 3:\n    y = 2\nelse:\n    y = 5'''
       lowercase       : Union[str, Any]						={'''x''': 3}
       lowercase       : Any						=evaluate(UpperCAmelCase  ,   {}  ,   state=UpperCAmelCase		)
       # evaluate returns the value of the last assignment.
       assert result == 2
       self.assertDictEqual(UpperCAmelCase  ,   {'''x''': 3, '''y''': 2}		)

       lowercase       : Optional[Any]						={'''x''': 8}
       lowercase       : str						=evaluate(UpperCAmelCase  ,   {}  ,   state=UpperCAmelCase		)
       # evaluate returns the value of the last assignment.
       assert result == 5
       self.assertDictEqual(UpperCAmelCase  ,   {'''x''': 8, '''y''': 5}		)






      def 					A__   (			self      :		str		)	->	Optional[Any]:


       '''simple docstring'''

       lowercase       : List[str]						='''test_list = [x, add_two(x)]'''
       lowercase       : Any						={'''x''': 3}
       lowercase       : Tuple						=evaluate(UpperCAmelCase  ,   {'''add_two''': add_two}  ,   state=UpperCAmelCase		)
       self.assertListEqual(UpperCAmelCase  ,   [3, 5]		)
       self.assertDictEqual(UpperCAmelCase  ,   {'''x''': 3, '''test_list''': [3, 5]}		)






      def 					A__   (			self      :		Any		)	->	Tuple:


       '''simple docstring'''

       lowercase       : str						='''y = x'''
       lowercase       : Dict						={'''x''': 3}
       lowercase       : Tuple						=evaluate(UpperCAmelCase  ,   {}  ,   state=UpperCAmelCase		)
       assert result == 3
       self.assertDictEqual(UpperCAmelCase  ,   {'''x''': 3, '''y''': 3}		)






      def 					A__   (			self      :		str		)	->	List[str]:


       '''simple docstring'''

       lowercase       : Any						='''test_list = [x, add_two(x)]\ntest_list[1]'''
       lowercase       : Any						={'''x''': 3}
       lowercase       : Union[str, Any]						=evaluate(UpperCAmelCase  ,   {'''add_two''': add_two}  ,   state=UpperCAmelCase		)
       assert result == 5
       self.assertDictEqual(UpperCAmelCase  ,   {'''x''': 3, '''test_list''': [3, 5]}		)

       lowercase       : int						='''test_dict = {\'x\': x, \'y\': add_two(x)}\ntest_dict[\'y\']'''
       lowercase       : Union[str, Any]						={'''x''': 3}
       lowercase       : Tuple						=evaluate(UpperCAmelCase  ,   {'''add_two''': add_two}  ,   state=UpperCAmelCase		)
       assert result == 5
       self.assertDictEqual(UpperCAmelCase  ,   {'''x''': 3, '''test_dict''': {'''x''': 3, '''y''': 5}}		)






      def 					A__   (			self      :		List[str]		)	->	Tuple:


       '''simple docstring'''

       lowercase       : Optional[int]						='''x = 0\nfor i in range(3):\n    x = i'''
       lowercase       : List[str]						={}
       lowercase       : Union[str, Any]						=evaluate(UpperCAmelCase  ,   {'''range''': range}  ,   state=UpperCAmelCase		)
       assert result == 2
       self.assertDictEqual(UpperCAmelCase  ,   {'''x''': 2, '''i''': 2}		)



