我们通过LeNet网络模型中的solver参数进行详解
LeNet的solver层
# The train/test net protocol buffer definition
net: "examples/mnist/lenet_train_test.prototxt"
# 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.
test_iter: 100
# Carry out testing every 500 training iterations.
test_interval: 500
# The base learning rate, momentum and the weight decay of the network.
base_lr: 0.01
momentum: 0.9
weight_decay: 0.0005
# The learning rate policy
lr_policy: "inv"
gamma: 0.0001
power: 0.75
# 每训练100次，在屏幕上显示一次。如果设置为0，则不显示。
display: 100
# The maximum number of iterations
max_iter: 10000
# 用于设置训练多少次后进行保存，默认为0，不保存。snapshot_prefix设置保存路径。
snapshot: 5000
snapshot_prefix: "examples/mnist/lenet"
# solver mode: CPU or GPU
solver_mode: GPU