parameters: (graph, node)
return_statement: return ops.OpStats("weight_parameters", (filter_height * filter_width *
                                             filter_in_depth *
                                             filter_channel_multiplier))
docstring: Calculates the on-disk size of the weights for DepthwiseConv2dNative.
docstring_summary: Calculates the on-disk size of the weights for DepthwiseConv2dNative.
docstring_tokens: Calculates the on - disk size of the weights for DepthwiseConv2dNative .
function: def _calc_depthwise_conv_weight_params(graph, node):
    """Calculates the on-disk size of the weights for DepthwiseConv2dNative."""
    input_shape = graph_util.tensor_shape_from_node_def_name(graph, node.input[0])
    input_shape.assert_is_fully_defined()
    filter_shape = graph_util.tensor_shape_from_node_def_name(graph,
                                                              node.input[1])
    filter_shape.assert_is_fully_defined()
    output_shape = graph_util.tensor_shape_from_node_def_name(graph, node.name)
    output_shape.assert_is_fully_defined()
    filter_height = int(filter_shape[0])
    filter_width = int(filter_shape[1])
    filter_in_depth = int(filter_shape[2])
    filter_channel_multiplier = int(filter_shape[3])
    return ops.OpStats("weight_parameters", (filter_height * filter_width *
                                             filter_in_depth *
                                             filter_channel_multiplier))
function_tokens: def _calc_depthwise_conv_weight_params ( graph , node ) : input_shape = graph_util . tensor_shape_from_node_def_name ( graph , node . input [ 0 ] ) input_shape . assert_is_fully_defined ( ) filter_shape = graph_util . tensor_shape_from_node_def_name ( graph , node . input [ 1 ] ) filter_shape . assert_is_fully_defined ( ) output_shape = graph_util . tensor_shape_from_node_def_name ( graph , node . name ) output_shape . assert_is_fully_defined ( ) filter_height = int ( filter_shape [ 0 ] ) filter_width = int ( filter_shape [ 1 ] ) filter_in_depth = int ( filter_shape [ 2 ] ) filter_channel_multiplier = int ( filter_shape [ 3 ] ) return ops . OpStats ( "weight_parameters" , ( filter_height * filter_width * filter_in_depth * filter_channel_multiplier ) )