import tensorflow as tf

                out, num_outputs=num_filters, kernel_size=8, stride=4,
                activation_fn=tf.nn.relu, weights_initializer=gauss_initializer,
                trainable=False)
        out = layers.flatten(out)
        with tf.variable_scope("action_value"):
            out = layers.fully_connected(out, num_outputs=num_actions, activation_fn=None)

        return out
