#coding=utf-8 import tensorflow as tf #case 2 input = 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]
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