mmd_vae_eval.py 文件源码

def encoder(x, z_dim):
    with tf.variable_scope('encoder'):
        conv1 = conv2d_lrelu(x, 64, 4, 2)   # None x 14 x 14 x 64
        conv2 = conv2d_lrelu(conv1, 128, 4, 2)   # None x 7 x 7 x 128
        conv2 = tf.reshape(conv2, [-1, np.prod(conv2.get_shape().as_list()[1:])]) # None x (7x7x128)
        fc1 = fc_lrelu(conv2, 1024)
        mean = tf.contrib.layers.fully_connected(fc1, z_dim, activation_fn=tf.identity)
        stddev = tf.contrib.layers.fully_connected(fc1, z_dim, activation_fn=tf.sigmoid)
        stddev = tf.maximum(stddev, 0.005)
        return mean, stddev