学习进度笔记9

观看Tensorflow案例实战视频课程09 神经网路模型架构

import numpy as np
import tensorflow as tf
import matplotlib.pyplot as plt
import input_data

mnist=input_data.read_data_sets('data/',one_hot=True)

#NETWORK TOPOLOGIES
n_hidden_1=256
n_hidden_2=128
n_input=784
n_classes=10

#INPUTS AND OUTPUTS
x=tf.placeholder("float",[None,n_input])
y=tf.placeholder("float",[None,n_classes])

#NETWORK PARAMETERS
stddev=0.1
weights={
    'w1':tf.Variable(tf.random_normal([n_input,n_hidden_1],stddev=stddev)),
    'w2':tf.Variable(tf.random_normal([n_hidden_1,n_hidden_2],stddev=stddev)),
    'out':tf.Variable(tf.random_normal([n_hidden_2,n_classes],stddev=stddev))
}
biases={
    'b1':tf.Variable(tf.random_normal([n_hidden_1])),
    'b2':tf.Variable(tf.random_normal([n_hidden_2])),
    'out':tf.Variable(tf.random_normal([n_classes]))
}
print("NETWORK READY")