DL之CNN：利用自定义DeepConvNet【7+1】算法对mnist数据集训练实现手写数字识别、模型评估(99.4%)

DL之CNN：利用自定义DeepConvNet【7+1】算法对mnist数据集训练实现手写数字识别、模型评估(99.4%)

 

 

目录

输出结果

设计思路

核心代码

 

 

 

输出结果

 

 

设计思路

 

 

 

核心代码

network = DeepConvNet()                         


network.load_params("data_input/DeepConvNet/deep_convnet_params.pkl")   

#T1、caluculate accuracy(float64)
print("DeepConvNet【7+1】 on mnist：caluculate accuracy (float64 type) ... ")
print(network.accuracy(x_test, t_test))          #caluculate accuracy(float64)


#T2、caluculate accuracy(float16)
x_test = x_test.astype(np.float16)        
for param in network.params.values():     
    param[...] = param.astype(np.float16)

print("DeepConvNet【7+1】 on mnist：caluculate accuracy (float16 type) ... ")
print(network.accuracy(x_test, t_test))