network_ops.py 文件源码

def mu_sigma_layer(inputs, n_outputs):
    """
    Create a layer that makes a mu and sigma,
    e.g. to use in continuous action spaces.
    """

    mu = tf.contrib.layers.fully_connected(
        inputs=inputs,
        num_outputs=n_outputs,
        activation_fn=None,
        weights_initializer=tf.truncated_normal_initializer(mean=0.0, stddev=0.02),
        biases_initializer=tf.zeros_initializer(),
        scope="mu")
    mu = tf.squeeze(mu, name="mu")

    sigma = tf.contrib.layers.fully_connected(
        inputs=inputs,
        num_outputs=n_outputs,
        activation_fn=None,
        weights_initializer=tf.truncated_normal_initializer(mean=0.0, stddev=0.02),
        biases_initializer=tf.zeros_initializer(),
        scope="sigma")
    sigma = tf.squeeze(sigma)
    sigma = tf.nn.softplus(sigma) + 1e-5
    return mu, sigma