暑假第五周
作者：互联网
这周进行的主要是手写数字的卷积神经网络的编写，不过由于对于自己来说难度较大，只写了第一层卷积。
import numpy as np
import matplotlib.pyplot as plt
import tensorflow as tf
import time from datetime
import timedelta
import math from tensorflow.examples.tutorials.mnist import input_data
def weights(shape):
return tf.Variable(tf.truncated_normal(shape,stddev=0.05))
def biases(length):
return tf.Variable(tf.constant(0.1,shape=length))
def conv2d(a,b):
return tf.nn.conv2d(a,b,strides=[1,1,1,1],padding='SAME')
def max_pool_2x2(inputx):
return tf.nn.max_pool(inputx,ksize=[1,2,2,1],strides=[1,2,2,1],padding='SAME')
data = input_data.read_data_sets("./data", one_hot=True)
print("Size of:")
print("--Training-set:\t{}".format(len(data.train.labels)))
print("--Testing-set:\t{}".format(len(data.test.labels)))
print("--Validation-set:\t{}".format(len(data.validation.labels)))
data.test.cls = np.argmax(data.test.labels,axis=1)
x = tf.placeholder("float",shape=[None,784],name='x')
x_image = tf.reshape(x,[-1,28,28,1])
y_true = tf.placeholder("float",shape=[None,10],name='y_true')
y_true_cls = tf.argmax(y_true,dimension=1)
layer_conv1 = {"weights":weights([5,5,1,32]),"biases":biases([32])}
h_conv1 = tf.nn.relu(conv2d(x_image,layer_conv1["weights"])+layer_conv1["biases"])
h_pool1 = max_pool_2x2(h_conv1)
下周尽量完成手写数字。
标签：labels,conv1,shape,第五,暑假,tf,import,data 来源： https://www.cnblogs.com/studya/p/11335774.html