DCGAN.py 文件源码

def discriminator(self, inpt, reuse, is_train):
        """
        Build D for training or testing. If reuse if True, the input should be the output of generator
        """
        with tf.variable_scope("discriminator"):
            if reuse:
                tf.get_variable_scope().reuse_variables()
            net = conv2d(x=inpt, num_kernels=self.d_init, name="conv1", activation=lkrelu, padding="SAME",
                         alpha=0.02, is_train=is_train, stddv=self.stddv)
            net = conv2d(x=net, num_kernels=self.d_init*2, name="conv2", activation=lkrelu, padding="SAME",
                         alpha=0.02, is_train=is_train, stddv=self.stddv)
            net = conv2d(x=net, num_kernels=self.d_init*4, name="conv3", activation=lkrelu, padding="SAME",
                         alpha=0.02, is_train=is_train, stddv=self.stddv)
            net = conv2d(x=net, num_kernels=self.d_init*8, name="conv4", activation=lkrelu, padding="SAME",
                         alpha=0.02, is_train=is_train, stddv=self.stddv)
            net = dense_layer(x=net, num_neurons=1, name="output", activation=tf.identity, is_train=is_train,
                              stddv=self.stddv)
        return net