tf.contrib.receptive_field.get_compute_order
Computes order of computation for a given CNN graph.
tf.contrib.receptive_field.get_compute_order(
graph_def, input_node_name='', input_node_size=None
)
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.
|
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Last updated 2020-10-01 UTC.
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