old_contents: #Copyright (C) 2016 Paolo Galeone <nessuno@nerdz.eu>
  #
  #This Source Code Form is subject to the terms of the Mozilla Public
  #License, v. 2.0. If a copy of the MPL was not distributed with this
  #file, you can obtain one at http://mozilla.org/MPL/2.0/.
  #Exhibit B is not attached; this software is compatible with the
  #licenses expressed under Section 1.12 of the MPL v2.
  """Define the interface to implement to defined an input"""
  
  import abc
  
  
  class Input(object, metaclass=abc.ABCMeta):
      """Input is the interface that classifiers must implement"""
  
      @abc.abstractmethod
      def distorted_inputs(self, batch_size):
          """Construct distorted input for training using the Reader ops.
  
          Args:
              batch_size: Number of images per batch.
  
          Returns:
              images: Images. 4D tensor of [batch_size, self._image_height, self._image_width, self._image_depth] size.
              labels: Labels. 1D tensor of [batch_size] size.
          """
          raise NotImplementedError(
              'users must define distorted_inputs to use this base class')
  
      @abc.abstractmethod
      def inputs(self, input_type, batch_size):
          """Construct input for evaluation using the Reader ops.
  
          Args:
              input_type: InputType enum
              batch_size: Number of images per batch.
  
          Returns:
              images: Images. 4D tensor of [batch_size, self._image_height, self._image_width, self._image_depth] size.
              labels: Labels. 1D tensor of [batch_size] size.
          """
          raise NotImplementedError(
              'users must define inputs to use this base class')
  
      @abc.abstractmethod
      def maybe_download_and_extract(self):
          """Acquire and save the sataset"""
          raise NotImplementedError(
              'users must define maybe_download_and_extract to use this base class'
          )
  
      @abc.abstractmethod
      def num_examples(self, input_type):
          """Returns the number of examples per the specified input_type
  
          Args:
              input_type: InputType enum
          """
          raise NotImplementedError(
              'users must define num_examples to use this base class')
  
      @abc.abstractmethod
      def num_classes(self):
          """Returns the number of classes """
          raise NotImplementedError(
              'users must define num_classes to use this base class')
  
new_contents: #Copyright (C) 2016 Paolo Galeone <nessuno@nerdz.eu>
  #
  #This Source Code Form is subject to the terms of the Mozilla Public
  #License, v. 2.0. If a copy of the MPL was not distributed with this
  #file, you can obtain one at http://mozilla.org/MPL/2.0/.
  #Exhibit B is not attached; this software is compatible with the
  #licenses expressed under Section 1.12 of the MPL v2.
  """Define the interface to implement to defined an input"""
  
  import abc
  
  
  class Input(object, metaclass=abc.ABCMeta):
      """Input is the interface that classifiers must implement"""
  
      @abc.abstractmethod
      def distorted_inputs(self, batch_size):
          """Construct distorted input for training using the Reader ops.
  
          Args:
              batch_size: Number of images per batch.
  
          Returns:
              images: distorted images. 4D tensor of [batch_size, self._image_height, self._image_width, self._image_depth] size.
              ground_truth: tensor with batch_size elements
          """
          raise NotImplementedError(
              'users must define distorted_inputs to use this base class')
  
      @abc.abstractmethod
      def inputs(self, input_type, batch_size):
          """Construct input for evaluation using the Reader ops.
  
          Args:
              input_type: InputType enum
              batch_size: Number of images per batch.
  
          Returns:
              images: Images. 4D tensor of [batch_size, self._image_height, self._image_width, self._image_depth] size.
              ground_truth: tensor with batch_size elements
          """
          raise NotImplementedError(
              'users must define inputs to use this base class')
  
      @abc.abstractmethod
      def maybe_download_and_extract(self):
          """Acquire and save the dataset"""
          raise NotImplementedError(
              'users must define maybe_download_and_extract to use this base class'
          )
  
      @abc.abstractmethod
      def num_examples(self, input_type):
          """Returns the number of examples per the specified input_type
  
          Args:
              input_type: InputType enum
          """
          raise NotImplementedError(
              'users must define num_examples to use this base class')
  
      @abc.abstractmethod
      def num_classes(self):
          """Returns the number of classes """
          raise NotImplementedError(
              'users must define num_classes to use this base class')
  
subject: fix doc