使用tensorflow把GAN搭建好了，除錯過程出現ValueError: Shapes (100, 14, 14, 64) and (100, 12, 12, 64) are not compatible，這個小錯誤差點把人弄崩潰，經過一番折騰，終於解決，直接給出該錯誤的問題出處吧：

def deconv_layer(input,kernel_size_x,kernel_size_y,channel_in,channel_out,output_shape_n,isnorm=True,name="conv",active="relu"):
	with tf.name_scope(name):
		w = tf.Variable(tf.truncated_normal(shape=[kernel_size_x,kernel_size_y,channel_in,channel_out], stddev=0.01), name="W")
		b = tf.Variable(tf.zeros([channel_in])+0.1, name="B")
		conv = tf.nn.conv2d_transpose(input,w,output_shape=output_shape_n,strides=[1,2,2,1],padding="SAME")
		if isnorm:
			conv = tf.contrib.layers.batch_norm(inputs = conv, center=True, scale=True, is_training=True)
		if active == "relu":
			act = tf.nn.relu(conv + b)
		if active == "tanh":
			act = tf.nn.tanh(conv + b)	
		return act
 

在我的程式碼中生成器的反捲積過程為：1. $batchsize$

解決方案：在5. $batchsize*12*12*64$–>6. $batchsize*28*28*1$中的填充模式改為VALID即可。