def res_block(input, filters, kernel_size = (3, 3), strides = (1, 1), use_dropout = False):
#使用步长为1的卷积操作,保持输入数据的尺寸不变?
x = KL.Conv2D(filters=filters, kernel_size=kernel_size, strides=strides, padding='same')(input)
此处可以保持输入尺寸不变,是不是在卷积变换后,在卷积周围补0了