【发布时间】:2016-07-14 01:12:34
【问题描述】:
我训练了一段时间的 GoogleNet 模型,现在我想从检查点重新开始,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,并且我在我的solver.prototxt 中添加了正确的参数......但我在重新启动时收到错误:
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 训练和测试层:
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
}
}
【问题讨论】:
标签: caffe