nets.py 文件源码

def __call__(self, z):
        with tf.variable_scope(self.name) as scope:
            g = tcl.fully_connected(z, self.size * self.size * 512, activation_fn=tf.nn.relu, normalizer_fn=tcl.batch_norm)
            g = tf.reshape(g, (-1, self.size, self.size, 512))  # size
            g = tcl.conv2d_transpose(g, 256, 3, stride=2, # size*2
                                    activation_fn=tf.nn.relu, normalizer_fn=tcl.batch_norm, padding='SAME', weights_initializer=tf.random_normal_initializer(0, 0.02))
            g = tcl.conv2d_transpose(g, 128, 3, stride=2, # size*4
                                    activation_fn=tf.nn.relu, normalizer_fn=tcl.batch_norm, padding='SAME', weights_initializer=tf.random_normal_initializer(0, 0.02))
            g = tcl.conv2d_transpose(g, 64, 3, stride=2, # size*8 32x32x64
                                    activation_fn=tf.nn.relu, normalizer_fn=tcl.batch_norm, padding='SAME', weights_initializer=tf.random_normal_initializer(0, 0.02))

            g = tcl.conv2d_transpose(g, self.channel, 3, stride=2, # size*16 
                                        activation_fn=tf.nn.sigmoid, padding='SAME', weights_initializer=tf.random_normal_initializer(0, 0.02))
            return g