python卷积模型.txt
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WL
2026-02-21
shape
v2d
return
initial
bias
con
weight
def
max
tf.nn.relu
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# -*- coding: utf-8 -*-"""Spyder EditorThis is a temporary script file."""import tensorflow as tffrom tensorflow.examples.tutorials.mnist import input_datamnist=input_data.read_data_sets("MNIST_data/",one_hot=True)x=tf.placeholder(tf.float32,[None,784])y_=tf.placeholder(tf.float32,[None,10])x_image=tf.reshape(x,[-1,28,28,1])def weight_variable(shape): initial=tf.truncated_normal(shape,stddev=0.1) return tf.Variable(initial)def bias_variable(shape): initial=tf.constant(0.1,shape=shape) return tf.Variable(initial)def conv2d(x,W): return tf.nn.conv2d(x,W,strides=[1,1,1,1],padding='SAME')def max_pool_2x2(x): return tf.nn.max_pool(x,ksize=[1,2,2,1],strides=[1,1,1,1],padding='SAME')W_conv1=weight_variable([5,5,1,32])b_conv1=bias_variable([32])h_conv1=tf.nn.relu(conv2d(x_image,W_conv1)+b_conv1)h_pooll=max_pool_2x2(h_conv1)W_conv2=weight_variable([5,5,32,64])b_conv2=bias_variable([64])h_conv2=tf.nn.relu(conv2d(h_pooll,W_conv2)+b_conv2)h_pool2=max_pool_2x2(h_conv2)W_fcl=weight
shape/v2d/return/initial/bias_variable/con/weight_variable/def/max_pool_2/tf.nn.relu/
shape/v2d/return/initial/bias_variable/con/weight_variable/def/max_pool_2/tf.nn.relu/
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