Function build_map

tensorflow/python/keras/engine/network.py:1678–1732

Builds a map of the graph of layers. This recursively updates the map `layer_indices`, the list `nodes_in_decreasing_depth` and the set `network_nodes`. Arguments: tensor: Some tensor in a graph. finished_nodes: Set of nodes whose subgraphs have been traversed

(tensor,
                finished_nodes,
                nodes_in_progress,
                layer,
                node_index,
                tensor_index)

  nodes_in_decreasing_depth = []

  def build_map(tensor,
                finished_nodes,
                nodes_in_progress,
                layer,
                node_index,
                tensor_index):
    """Builds a map of the graph of layers.

    This recursively updates the map `layer_indices`,
    the list `nodes_in_decreasing_depth` and the set `network_nodes`.

    Arguments:
        tensor: Some tensor in a graph.
        finished_nodes: Set of nodes whose subgraphs have been traversed
            completely. Useful to prevent duplicated work.
        nodes_in_progress: Set of nodes that are currently active on the
            recursion stack. Useful to detect cycles.
        layer: Layer from which `tensor` comes from. If not provided,
            will be obtained from `tensor._keras_history`.
        node_index: Node index from which `tensor` comes from.
        tensor_index: Tensor_index from which `tensor` comes from.

    Raises:
        ValueError: if a cycle is detected.
    """
    node = layer._inbound_nodes[node_index]  # pylint: disable=protected-access

    # Prevent cycles.
    if node in nodes_in_progress:
      raise ValueError('The tensor ' + str(tensor) + ' at layer "' +
                       layer.name + '" is part of a cycle.')

    # Don't repeat work for shared subgraphs
    if node in finished_nodes:
      return

    node_key = _make_node_key(layer.name, node_index)
    # Update network_nodes.
    network_nodes.add(node_key)

    # Store the traversal order for layer sorting.
    if layer not in layer_indices:
      layer_indices[layer] = len(layer_indices)

    nodes_in_progress.add(node)

    # Propagate to all previous tensors connected to this node.
    for layer, node_index, tensor_index, tensor in node.iterate_inbound(
        include_arguments=True):
      build_map(tensor, finished_nodes, nodes_in_progress, layer, node_index,
                tensor_index)

    finished_nodes.add(node)
    nodes_in_progress.remove(node)
    nodes_in_decreasing_depth.append(node)

  finished_nodes = set()
  nodes_in_progress = set()