graph_mscoco.py 文件源码

def channel_wise_fc_layer(self, input, name): # bottom: (7x7x512)
        _, width, height, n_feat_map = input.get_shape().as_list()
        input_reshape = tf.reshape( input, [-1, width*height, n_feat_map] )
        input_transpose = tf.transpose( input_reshape, [2,0,1] )

        with tf.variable_scope(name):
            W = tf.get_variable(
                    "W",
                    shape=[n_feat_map,width*height, width*height], # (512,49,49)
                    initializer=tf.random_normal_initializer(0., 0.005))
            output = tf.batch_matmul(input_transpose, W)

        output_transpose = tf.transpose(output, [1,2,0])
        output_reshape = tf.reshape( output_transpose, [-1, height, width, n_feat_map] )

        return output_reshape