old_contents: import theano.tensor as T
  from athenet.algorithm.derest.layers.layer import DerestLayer
  from athenet.algorithm.derest.utils import get_derest_layer
  
  
  class DerestInceptionLayer(DerestLayer):
  
      def __init__(self, layer):
          super(DerestInceptionLayer, layer)
          self.derest_layer_lists = []
          for layer_list in self.layer.layers_lists:
              derest_layer_list = []
              for l in layer_list:
                  derest_layer_list.append(get_derest_layer(l))
              self.derest_layer_lists.append(derest_layer_list)
  
      def count_activation(self, input):
          results = []
          for derest_layer_list in self.derest_layer_lists:
              inp = input
              for derest_layer in derest_layer_list:
                  derest_layer.activation = inp
                  inp = derest_layer.count_activation(inp)
              results.append(inp)
          return T.concatenate(results)
  
      def count_derivatives(self, output, input_shape):
          output_list = []
          last = 0
          for layer in self.layer.top_layers:
              width = layer.output_shape[1]
              output_list.append(output[:, last : (last + width), ::])
              last += width
  
          result = None
          for output, derest_list in zip(output, self.derest_layer_lists):
              out = output
              for derest_layer in reversed(derest_list):
                  out = derest_list.count_derivatives(out)
                  derest_layer.derivatives = out
              if result is None:
                  result = out
              else:
                  result += out
  
          return result
  
      def count_derest(self, f):
          results = []
          for derest_layer_list in self.derest_layer_lists:
              for derest_layer in derest_layer_list:
                  results += derest_layer.count_derest(f)
          return res
new_contents: import theano.tensor as T
  from athenet.algorithm.derest.layers.layer import DerestLayer
  from athenet.algorithm.derest.utils import get_derest_layer
  
  
  class DerestInceptionLayer(DerestLayer):
  
      def __init__(self, layer):
          super(DerestInceptionLayer, layer)
          self.derest_layer_lists = []
          for layer_list in self.layer.layers_lists:
              derest_layer_list = []
              for l in layer_list:
                  derest_layer_list.append(get_derest_layer(l))
              self.derest_layer_lists.append(derest_layer_list)
  
      def count_activation(self, input):
          results = []
          for derest_layer_list in self.derest_layer_lists:
              inp = input
              for derest_layer in derest_layer_list:
                  derest_layer.activation = inp
                  inp = derest_layer.count_activation(inp)
              results.append(inp)
          return T.concatenate(results)
  
      def count_derivatives(self, output, input_shape):
          output_list = []
          last = 0
          for layer in self.layer.top_layers:
              width = layer.output_shape[1]
              output_list.append(output[:, last : (last + width), ::])
              last += width
  
          result = None
          for output, derest_list in zip(output, self.derest_layer_lists):
              out = output
              for derest_layer in reversed(derest_list):
                  out = derest_list.count_derivatives(out)
                  derest_layer.derivatives = out
              if result is None:
                  result = out
              else:
                  result += out
  
          return result
  
      def count_derest(self, f):
          results = []
          for derest_layer_list in self.derest_layer_lists:
              for derest_layer in derest_layer_list:
                  results += derest_layer.count_derest(f)
          return results
  
subject: Fix in inception