Caffe 关于 LetNet-5 之 lenet_solver.prototxt 解析

# The train/test net protocol buffer definition   // 参数描述文件
net: "examples/mnist/lenet_train_test.prototxt"   //位置
# test_iter specifies how many forward passes the test should carry out. 
# In the case of MNIST, we have test batch size 100 and 100 test iterations,
# covering the full 10,000 testing images. // 一共10000张测试图像，test batch size 100 每次测试处理100张
test_iter: 100  // 进行100次前向计算，test_iter*test batch size =10000
# Carry out testing every 500 training iterations.
test_interval: 500 // 每训练500次，进行一次测试
# The base learning rate, momentum and the weight decay of the network.
base_lr: 0.01  //基础学习率
momentum: 0.9  //学习率 改变的动量
weight_decay: 0.0005 //学习率衰减系数
# The learning rate policy  //学习策略 及相关参数
lr_policy: "inv"
gamma: 0.0001
power: 0.75
# Display every 100 iterations
display: 100   //迭代100次 打印输出一次结果
# The maximum number of iterations
max_iter: 10000   //最大迭代数
# snapshot intermediate results
snapshot: 5000     //5000次迭代保存一次临时模型，名称为lenet_iter_5000.caffemodel
snapshot_prefix: "examples/mnist/lenet"
# solver mode: CPU or GPU // 使用CPU还是GPU
solver_mode: GPU   //打开GPU