(dataset, training)
return dataset.map(flatten_image)
Preprocessing for downsampled_imagenet.

  Args:
    dataset: the dataset.
    training: unused option.

  Returns:
    Flattened dataset.

  Preprocessing for downsampled_imagenet 32x32 and 64x64 generation from
  http://arxiv.org/abs/1601.06759 (page 8).
Preprocessing for downsampled_imagenet.
Preprocessing for downsampled_imagenet .
def downsampled_imagenet_flatten_bare_preprocess(dataset, training):
  """Preprocessing for downsampled_imagenet.

  Args:
    dataset: the dataset.
    training: unused option.

  Returns:
    Flattened dataset.

  Preprocessing for downsampled_imagenet 32x32 and 64x64 generation from
  http://arxiv.org/abs/1601.06759 (page 8).
  """
  del training

  def flatten_image(features):
    img = features['image']
    flat = tf.cast(tf.reshape(img, [-1]), tf.int64)

    new_features = {'image': flat}
    return new_features

  return dataset.map(flatten_image)
def downsampled_imagenet_flatten_bare_preprocess ( dataset , training ) : del training def flatten_image ( features ) : img = features [ 'image' ] flat = tf . cast ( tf . reshape ( img , [ - 1 ] ) , tf . int64 ) new_features = { 'image' : flat } return new_features return dataset . map ( flatten_image )