vaegan.py 文件源码

def Encode(self, x):

        with tf.variable_scope('encode') as scope:

            conv1 = tf.nn.relu(batch_normal(conv2d(x, output_dim=64, name='e_c1'), scope='e_bn1'))
            conv2 = tf.nn.relu(batch_normal(conv2d(conv1, output_dim=128, name='e_c2'), scope='e_bn2'))
            conv3 = tf.nn.relu(batch_normal(conv2d(conv2 , output_dim=256, name='e_c3'), scope='e_bn3'))
            conv3 = tf.reshape(conv3, [self.batch_size, 256 * 8 * 8])
            fc1 = tf.nn.relu(batch_normal(fully_connect(conv3, output_size=1024, scope='e_f1'), scope='e_bn4'))
            z_mean = fully_connect(fc1 , output_size=128, scope='e_f2')
            z_sigma = fully_connect(fc1, output_size=128, scope='e_f3')

            return z_mean, z_sigma