coldmooon / code-for-mpelu Goto Github PK
View Code? Open in Web Editor NEWCode for Improving Deep Neural Network with Multiple Parametric Exponential Linear Units
Code for Improving Deep Neural Network with Multiple Parametric Exponential Linear Units
I wonder if this torch version of code can run in Pytorch? I use Pytorch. I don't know how to use the module you wrote in pytorch.
Use your code on caffe can be compiled successfully and successfully trained, but in the right straight visualization: "F0724 12:23:30.799641 24843 layer_factory.hpp:81] Check failed: registry.count(type) == 1 (0 vs. 1) Unknown layer type: M2PELU "
[----------] 12 tests from SGDSolverTest/0, where TypeParam = caffe::CPUDevice
[ RUN ] SGDSolverTest/0.TestLeastSquaresUpdateLROneHundredth
[libprotobuf ERROR google/protobuf/text_format.cc:245] Error parsing text-format caffe.SolverParameter: 1:113: Message type "caffe.SolverParameter" has no field named "layer_wise_reduce".
F0509 09:21:30.853242 5167 test_gradient_based_solver.cpp:56] Check failed: google::protobuf::TextFormat::ParseFromString(proto, ¶m)
The latest 'caffe-master' can be compiled completely. So the 'caffe-master' files has no problem.
Is there anyone who meets and solves this problem?
layer {
name: "m2pelu_conv1"
type: "M2PELU"
bottom: "conv1"
top: "conv1"
param {
lr_mult: 10
decay_mult: 0
}
param {
lr_mult: 10
decay_mult: 0
}
m2pelu_param {
alpha_filler {
type: "constant"
value: 1
}
beta_filler {
type: "constant"
value: 1
}
}
}
base_lr: 0.0001
lr_policy: "multistep"
gamma: 0.1
stepvalue: 100000
stepvalue: 600000
momentum: 0.9
weight_decay: 0.0005
max_iter: 930000
Sorry.
Check failed: false Unknown filler name: taylor.
How can I have the filter? Can you help me ?
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