run_dqn_atari.py 文件源码

def simple_model_w_feat_eng(img_in, num_actions, scope, reuse=False):
    with tf.variable_scope(scope, reuse=reuse):
        out = img_in
        out = layers.flatten(out)
        # stddev = 1/n, where n = number of inputs
        gauss_initializer = initializers.xavier_initializer(uniform=False)
        with tf.variable_scope("action_value"):
            out = layers.fully_connected(
                out,
                num_outputs=num_actions,
                activation_fn=tf.nn.relu,
                biases_initializer=None,
                weights_initializer=gauss_initializer,
                weights_regularizer=None)
        return out