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tf.contrib.receptive_field.get_compute_order

tf.contrib.receptive_field.get_compute_order(
    graph_def,
    input_node_name='',
    input_node_size=None
)

Defined in tensorflow/contrib/receptive_field/python/util/graph_compute_order.py.

Computes order of computation for a given CNN graph.

Optionally, the function may also compute the input and output feature map resolutions at each node. In this case, input_node_name and input_node_size must be set. Note that if a node's op type is unknown, the input and output resolutions are ignored and set to None.

Args:

  • graph_def: GraphDef object.
  • input_node_name: Name of node with fixed input resolution (optional). This is usually the node name for the input image in a CNN.
  • input_node_size: 2D list of integers, fixed input resolution to use (optional). This is usually the input resolution used for the input image in a CNN (common examples are: [224, 224], [299, 299], [321, 321]).

Returns:

  • node_info: Default dict keyed by node name, mapping to a named tuple with the following fields:
    • order: Integer denoting topological order;
    • node: NodeDef for the given node;
    • input_size: 2D list of integers, denoting the input spatial resolution to the node;
    • output_size: 2D list of integers, denoting the output spatial resolution of the node.
  • name_to_node: Dict keyed by node name, each entry containing the node's NodeDef.