padding的规则
· padding=‘VALID’时,输出的宽度和高度的计算公式(下图gif为例)
输出宽度:output_width = (in_width-filter_width+1)/strides_width =(5-3+1)/2=1.5【向上取整=2】
输出高度:output_height = (in_height-filter_height+1)/strides_height =(5-3+1)/2=1.5【向上取整=2】
输出的形状[1,2,2,1]
import tensorflow as tf image = [0,1.0,1,2,2,0,1,1,0,0,1,1,0,1,0,1,0,1,1,1,0,2,0,1,0] input = tf.Variable(tf.constant(image,shape=[1,5,5,1])) ##1通道输入 fil1 = [-1.0,0,1,-2,0,2,-1,0,1] filter = tf.Variable(tf.constant(fil1,shape=[3,3,1,1])) ##1个卷积核对应1个featuremap输出 op = tf.nn.conv2d(input,filter,strides=[1,2,2,1],padding='VALID') ##步长2,VALID不补0操作 init = tf.global_variables_initializer() with tf.Session() as sess: sess.run(init) # print('input:n', sess.run(input)) # print('filter:n', sess.run(filter)) print('op:n',sess.run(op)) ##输出结果 ''' [[[[ 2.] [-1.]] [[-1.] [ 0.]]]] '''
VALID步长2
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