Method _add_inbound_node

tensorflow/python/keras/engine/base_layer.py:2063–2102

Internal method to create an inbound node for the layer. Arguments: input_tensors: list of input tensors. output_tensors: list of output tensors. arguments: dictionary of keyword arguments that were passed to the `call` method of the layer at the call that cr

(self,
                        input_tensors,
                        output_tensors,
                        arguments=None)

    return inputs, outputs

  def _add_inbound_node(self,
                        input_tensors,
                        output_tensors,
                        arguments=None):
    """Internal method to create an inbound node for the layer.

    Arguments:
        input_tensors: list of input tensors.
        output_tensors: list of output tensors.
        arguments: dictionary of keyword arguments that were passed to the
            `call` method of the layer at the call that created the node.
    """
    inbound_layers = nest.map_structure(lambda t: t._keras_history.layer,
                                        input_tensors)
    node_indices = nest.map_structure(lambda t: t._keras_history.node_index,
                                      input_tensors)
    tensor_indices = nest.map_structure(lambda t: t._keras_history.tensor_index,
                                        input_tensors)

    # Create node, add it to inbound nodes.
    node_module.Node(
        self,
        inbound_layers=inbound_layers,
        node_indices=node_indices,
        tensor_indices=tensor_indices,
        input_tensors=input_tensors,
        output_tensors=output_tensors,
        arguments=arguments)

    # Update tensor history metadata.
    # The metadata attribute consists of
    # 1) a layer instance
    # 2) a node index for the layer
    # 3) a tensor index for the node.
    # The allows layer reuse (multiple nodes per layer) and multi-output
    # or multi-input layers (e.g. a layer can return multiple tensors,
    # and each can be sent to a different layer).
    for i, tensor in enumerate(nest.flatten(output_tensors)):
      tensor._keras_history = KerasHistory(self,
                                           len(self._inbound_nodes) - 1, i)  # pylint: disable=protected-access

  def _get_node_attribute_at_index(self, node_index, attr, attr_name):
    """Private utility to retrieves an attribute (e.g. inputs) from a node.