parameters: (self, include_arguments=False)
docstring: Returns a list of tuples representing the inbound data.
  
      Arguments:
        include_arguments: Whether to also iterate over any Keras Tensors
          passed as args, kwargs.
  
      Returns:
        List of tuples like: (inbound_layer, node_index, tensor_index, tensor).
docstring_summary: Returns a list of tuples representing the inbound data.
docstring_tokens: Returns a list of tuples representing the inbound data .
function: def iterate_inbound(self, include_arguments=False):
      """Returns a list of tuples representing the inbound data.
  
      Arguments:
        include_arguments: Whether to also iterate over any Keras Tensors
          passed as args, kwargs.
  
      Returns:
        List of tuples like: (inbound_layer, node_index, tensor_index, tensor).
      """
      inputs_inbound = list(
          zip(
              nest.flatten(self.inbound_layers),
              nest.flatten(self.node_indices),
              nest.flatten(self.tensor_indices),
              nest.flatten(self.input_tensors)))
  
      if include_arguments:
        keras_tensor_arguments = [
            kt for kt in nest.flatten(self.arguments)
            if hasattr(kt, '_keras_history')
        ]
  
        def _get_inbound(keras_tensor):
          kh = keras_tensor._keras_history
          return kh.layer, kh.node_index, kh.tensor_index, keras_tensor
  
        arguments_inbound = nest.map_structure(_get_inbound,
                                               keras_tensor_arguments)
  
        return inputs_inbound + arguments_inbound
      else:
        return inputs_inbound
function_tokens: def iterate_inbound ( self , include_arguments = False ) : inputs_inbound = list ( zip ( nest . flatten ( self . inbound_layers ) , nest . flatten ( self . node_indices ) , nest . flatten ( self . tensor_indices ) , nest . flatten ( self . input_tensors ) ) ) if include_arguments : keras_tensor_arguments = [ kt for kt in nest . flatten ( self . arguments ) if hasattr ( kt , '_keras_history' ) ] def _get_inbound ( keras_tensor ) : kh = keras_tensor . _keras_history return kh . layer , kh . node_index , kh . tensor_index , keras_tensor arguments_inbound = nest . map_structure ( _get_inbound , keras_tensor_arguments ) return inputs_inbound + arguments_inbound else : return inputs_inbound