深度学习（pytorch）-1.基于简单神经网络的图片自动分类

这是pytorch官方的一个例子

官方教程地址：http://pytorch.org/tutorials/beginner/blitz/cifar10_tutorial.html#sphx-glr-beginner-blitz-cifar10-tutorial-py

代码如下

[1,  2000] loss: 2.219
[1,  4000] loss: 1.869
[1,  6000] loss: 1.669
[1,  8000] loss: 1.581
[1, 10000] loss: 1.537
[1, 12000] loss: 1.488
[2,  2000] loss: 1.406
[2,  4000] loss: 1.385
[2,  6000] loss: 1.343
[2,  8000] loss: 1.318
[2, 10000] loss: 1.348
[2, 12000] loss: 1.305
[3,  2000] loss: 1.234
[3,  4000] loss: 1.206
[3,  6000] loss: 1.219
[3,  8000] loss: 1.213
[3, 10000] loss: 1.205
[3, 12000] loss: 1.199
[4,  2000] loss: 1.115
[4,  4000] loss: 1.127
[4,  6000] loss: 1.123
[4,  8000] loss: 1.118
[4, 10000] loss: 1.143
[4, 12000] loss: 1.106
[5,  2000] loss: 1.023
[5,  4000] loss: 1.022
[5,  6000] loss: 1.073
[5,  8000] loss: 1.076
[5, 10000] loss: 1.060
[5, 12000] loss: 1.048
[6,  2000] loss: 0.965
[6,  4000] loss: 0.985
[6,  6000] loss: 0.988
[6,  8000] loss: 1.008
[6, 10000] loss: 1.017
[6, 12000] loss: 0.999
[7,  2000] loss: 0.902
[7,  4000] loss: 0.925
[7,  6000] loss: 0.974
[7,  8000] loss: 0.955
[7, 10000] loss: 0.968
[7, 12000] loss: 0.979
[8,  2000] loss: 0.866
[8,  4000] loss: 0.893
[8,  6000] loss: 0.909
[8,  8000] loss: 0.932
[8, 10000] loss: 0.934
[8, 12000] loss: 0.937
[9,  2000] loss: 0.837
[9,  4000] loss: 0.858
[9,  6000] loss: 0.865
[9,  8000] loss: 0.873
[9, 10000] loss: 0.906
[9, 12000] loss: 0.907
[10,  2000] loss: 0.809
[10,  4000] loss: 0.810
[10,  6000] loss: 0.832
[10,  8000] loss: 0.865
[10, 10000] loss: 0.878
[10, 12000] loss: 0.877