#coding=utf-8import tensorflow as tf#case 2input = tf.Variable(tf.round(10 * tf.random_normal([1,3,3,2])))filter = tf.Variable(tf.round(5 * tf.random_normal([1,1,2,1])))op2 = tf.nn.conv2d(input, filter, strides=[1, 1, 1, 1], padding='VALID')#对于filter，多个输入通道，变成一个输入通道，是对各个通道上的卷积值进行相加init = tf.global_variables_initializer()with tf.Session() as sess:    sess.run(init)    print("case 2")    print("input: ", sess.run(input))    print("filter: ", sess.run(filter))    print("conv ", sess.run(op2))

# case 2# input:  [[[[-14. -11.]# [ 2. 2.] # [ 25. 18.]] # # [[ 8. 13.] # [ -7. -7.] # [ 11. 6.]] # # [[ -1. 8.] # [ 18. 10.] # [ -2. 19.]]]] # filter: [[[[-3.] # [ 2.]]]] # conv [[[[ 20.] # [ -2.] # [-39.]] # # [[ 2.] # [ 7.] # [-21.]] # # [[ 19.] # [-34.] # [ 44.]]]]

 

#转换：输入为3*3的2通道数据#通道1：#[-14 2 25], #[8 -7 11], #[-1 18 -2] #通道2： #[-11 2 18], #[13 -7 6], #[8 10 19] #conv转换 #[20 -2 -39], #[2 -7 -21], #[9 -34 44] #计算过程 #[-14 2 25], #[8 -7 11], * [-3] + #[-1 18 -2] #[-11 2 18], #[13 -7 6], * [2] #[8 10 19] #result #[20 -2 -39], #[2 -7 -21], #[9 -34 44]