我训练了一段时间的GoogleNet模型,现在我想从检查点重新启动,添加一个测试阶段。我已经在我的train_val.prototxt文件中进行了测试,并且我将正确的参数添加到了我的solver.prototxt ...但是我在重启时遇到错误:
I0712 15:53:02.615947 47646 net.cpp:278] This network produces output loss2/loss1
I0712 15:53:02.615964 47646 net.cpp:278] This network produces output loss3/loss3
I0712 15:53:02.616109 47646 net.cpp:292] Network initialization done.
F0712 15:53:02.616665 47646 solver.cpp:128] Check failed: param_.test_iter_size() == num_test_nets (1 vs. 0) test_iter must be specified for each test network.
*** Check failure stack trace: ***
@ 0x7f550cf70e6d (unknown)
@ 0x7f550cf72ced (unknown)
@ 0x7f550cf70a5c (unknown)
@ 0x7f550cf7363e (unknown)
@ 0x7f550d3b605b caffe::Solver<>::InitTestNets()
@ 0x7f550d3b63ed caffe::Solver<>::Init()
@ 0x7f550d3b6738 caffe::Solver<>::Solver()
@ 0x7f550d4fa633 caffe::Creator_SGDSolver<>()
@ 0x7f550da5bb76 caffe::SolverRegistry<>::CreateSolver()
@ 0x7f550da548f4 train()
@ 0x7f550da52316 main
@ 0x7f5508f43b15 __libc_start_main
@ 0x7f550da52d3d (unknown)
solver.prototxt
train_net: "<my_path>/train_val.prototxt"
test_iter: 1000
test_interval: 4000
test_initialization: false
display: 40
average_loss: 40
base_lr: 0.01
lr_policy: "step"
stepsize: 320000
gamma: 0.96
max_iter: 10000000
momentum: 0.9
weight_decay: 0.0002
snapshot: 40000
snapshot_prefix: "models/<my_path>"
solver_mode: CPU
train_val.prototxt列车和测试层:
name: "GoogleNet"
layer {
name: "data"
type: "Data"
top: "data"
top: "label"
include {
phase: TRAIN
}
transform_param {
mirror: true
crop_size: 224
mean_value: 104
mean_value: 117
mean_value: 123
}
data_param {
source: "/<blah>/ilsvrc12_train_lmdb"
batch_size: 32
backend: LMDB
}
}
layer {
name: "data"
type: "Data"
top: "data"
top: "label"
include {
phase: TEST
}
transform_param {
mirror: true
crop_size: 224
mean_value: 104
mean_value: 117
mean_value: 123
}
data_param {
source: "/<blah>/ilsvrc12_val_lmdb"
batch_size: 32
backend: LMDB
}
}
答案 0 :(得分:8)
您应该从
修改solver.prototxt中的一个位置train_net: "/train_val.prototxt"
到
net: "/train_val.prototxt"
因为Solver不使用&#34; train_net&#34;的值初始化测试网,因此您添加的测试阶段不是由解算器创建的。
实际上,参数&#34; train_net&#34;和&#34; test_net&#34;分别用于初始化火车网和测试网,而&#34; net&#34;用于两者。