void FeedbackSolver<Dtype>::Restore(const char* state_file) {
SolverState state;
NetParameter net_param;
ReadProtoFromBinaryFile(state_file, &state);
if (state.has_learned_net()) {
LOG(INFO)<<"Copy trained model from "<<state.learned_net();
ReadProtoFromBinaryFile(state.learned_net().c_str(), &net_param);
net_->CopyTrainedLayersFrom(net_param);
}
iter_ = state.iter();
RestoreSolverState(state);
}
void Solver<Dtype>::Restore(const char* state_file) {
SolverState state;
NetParameter net_param;
ReadProtoFromBinaryFile(state_file, &state);
if (state.has_learned_net()) {
ReadNetParamsFromBinaryFileOrDie(state.learned_net().c_str(), &net_param);
net_->CopyTrainedLayersFrom(net_param);
}
iter_ = state.iter();
current_step_ = state.current_step();
RestoreSolverState(state);
}
void SGDSolver<Dtype>::RestoreSolverStateFromBinaryProto(
const string& state_file) {
SolverState state;
ReadProtoFromBinaryFile(state_file, &state);
this->iter_ = state.iter();
if (state.has_learned_net()) {
NetParameter net_param;
ReadNetParamsFromBinaryFileOrDie(state.learned_net().c_str(), &net_param);
this->net_->CopyTrainedLayersFrom(net_param);
}
this->current_step_ = state.current_step();
CHECK_EQ(state.history_size(), history_.size())
<< "Incorrect length of history blobs.";
LOG(INFO) << "SGDSolver: restoring history";
for (int i = 0; i < history_.size(); ++i) {
history_[i]->FromProto(state.history(i));
}
}