(
    train_dir,
    fake_data=False,  # pylint:disable=unused-argument
    one_hot=False,
    dtype=np.float32,
    reshape=True,
    validation_size=5000,
    seed=None,
)
return train, validation, test
Read multiple datasets.
Read multiple datasets.
Read multiple datasets .
def read_data_sets(
    train_dir,
    fake_data=False,  # pylint:disable=unused-argument
    one_hot=False,
    dtype=np.float32,
    reshape=True,
    validation_size=5000,
    seed=None,
):
  """Read multiple datasets."""
  # pylint:disable=invalid-name
  TRAIN_IMAGES = 'train-images-idx3-ubyte.gz'
  TRAIN_LABELS = 'train-labels-idx1-ubyte.gz'
  TEST_IMAGES = 't10k-images-idx3-ubyte.gz'
  TEST_LABELS = 't10k-labels-idx1-ubyte.gz'

  local_file = os.path.join(train_dir, TRAIN_IMAGES)
  with gfile.Open(local_file, 'rb') as f:
    train_images = extract_images(f)

  local_file = os.path.join(train_dir, TRAIN_LABELS)
  with gfile.Open(local_file, 'rb') as f:
    train_labels = extract_labels(f, one_hot=one_hot)

  local_file = os.path.join(train_dir, TEST_IMAGES)
  with gfile.Open(local_file, 'rb') as f:
    test_images = extract_images(f)

  local_file = os.path.join(train_dir, TEST_LABELS)
  with gfile.Open(local_file, 'rb') as f:
    test_labels = extract_labels(f, one_hot=one_hot)

  if not 0 <= validation_size <= len(train_images):
    raise ValueError(
        'Validation size should be between 0 and {}. Received: {}.'.format(
            len(train_images), validation_size))

  validation_images = train_images[:validation_size]
  validation_labels = train_labels[:validation_size]
  train_images = train_images[validation_size:]
  train_labels = train_labels[validation_size:]

  options = dict(dtype=dtype, reshape=reshape, seed=seed)

  train = DataSet(train_images, train_labels, **options)
  validation = DataSet(validation_images, validation_labels, **options)
  test = DataSet(test_images, test_labels, **options)

  return train, validation, test
def read_data_sets ( train_dir , fake_data = False , # pylint:disable=unused-argument one_hot = False , dtype = np . float32 , reshape = True , validation_size = 5000 , seed = None , ) : # pylint:disable=invalid-name TRAIN_IMAGES = 'train-images-idx3-ubyte.gz' TRAIN_LABELS = 'train-labels-idx1-ubyte.gz' TEST_IMAGES = 't10k-images-idx3-ubyte.gz' TEST_LABELS = 't10k-labels-idx1-ubyte.gz' local_file = os . path . join ( train_dir , TRAIN_IMAGES ) with gfile . Open ( local_file , 'rb' ) as f : train_images = extract_images ( f ) local_file = os . path . join ( train_dir , TRAIN_LABELS ) with gfile . Open ( local_file , 'rb' ) as f : train_labels = extract_labels ( f , one_hot = one_hot ) local_file = os . path . join ( train_dir , TEST_IMAGES ) with gfile . Open ( local_file , 'rb' ) as f : test_images = extract_images ( f ) local_file = os . path . join ( train_dir , TEST_LABELS ) with gfile . Open ( local_file , 'rb' ) as f : test_labels = extract_labels ( f , one_hot = one_hot ) if not 0 <= validation_size <= len ( train_images ) : raise ValueError ( 'Validation size should be between 0 and {}. Received: {}.' . format ( len ( train_images ) , validation_size ) ) validation_images = train_images [ : validation_size ] validation_labels = train_labels [ : validation_size ] train_images = train_images [ validation_size : ] train_labels = train_labels [ validation_size : ] options = dict ( dtype = dtype , reshape = reshape , seed = seed ) train = DataSet ( train_images , train_labels , * * options ) validation = DataSet ( validation_images , validation_labels , * * options ) test = DataSet ( test_images , test_labels , * * options ) return train , validation , test