localisation.py 文件源码

def _create_fully_connected(self, prev_layer, num_neurones, layer_name, save_vars=False):

        with tf.variable_scope(layer_name) as scope:
            try:
                b, x, y, z = prev_layer.get_shape().as_list()
                flat_size = x*y*z
            except:
                flat_size = prev_layer.get_shape().as_list()[1]

            flat = tf.reshape(prev_layer,shape=[-1,flat_size])
            w = tf.get_variable(name="weights",shape=[flat_size,num_neurones],initializer=tf.contrib.layers.xavier_initializer())
            b = tf.get_variable(name="biases",shape=[num_neurones],initializer=tf.random_normal_initializer())
            out = tf.matmul(flat,w) + b
            full = tf.nn.relu(out)

            if save_vars:
                self.var_list += [w, b]

            return full