You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
70 lines
2.2 KiB
70 lines
2.2 KiB
#include <glog/logging.h>
|
|
#include "adadelta_optimizer.h"
|
|
#include "adagrad_optimizer.h"
|
|
#include "adam_optimizer.h"
|
|
#include "lr_policy.h"
|
|
#include "sgd_optimizer.h"
|
|
|
|
#include "parameter_optimizer.h"
|
|
|
|
namespace paddle {
|
|
namespace optimizer {
|
|
|
|
ParameterOptimizer *ParameterOptimizer::create(
|
|
const ::std::string &config_proto) {
|
|
paddle::OptimizerConfig config;
|
|
CHECK(config.ParseFromString(config_proto) == 0)
|
|
<< "error : optimizer config";
|
|
|
|
auto select_lr_policy = [=](const OptimizerConfig &config) -> BaseLr * {
|
|
std::string s(config.lr_policy());
|
|
if (s == "ConstLr") return new ConstLr(config.const_lr().learning_rate());
|
|
if (s == "LinearLr")
|
|
return new LinearLr(config.linear_lr().learning_rate(),
|
|
config.linear_lr().lr_decay_a(),
|
|
config.linear_lr().lr_decay_b());
|
|
// default
|
|
return nullptr;
|
|
};
|
|
BaseLr *lr = select_lr_policy(config);
|
|
auto select_optimizer =
|
|
[=](const OptimizerConfig &config) -> ParameterOptimizer * {
|
|
std::string s(config.optimizer_name());
|
|
if (s == "SGD") {
|
|
return new SGDOptimizer(config.sgd().momentum(),
|
|
config.sgd().decay(),
|
|
config.sgd().nesterov(),
|
|
lr);
|
|
}
|
|
if (s == "Adadelta") {
|
|
return new AdagradOptimizer(
|
|
config.adagrad().epsilon(), config.adagrad().decay(), lr);
|
|
}
|
|
if (s == "Adagrad") {
|
|
return new AdagradOptimizer(
|
|
config.adagrad().epsilon(), config.adagrad().decay(), lr);
|
|
}
|
|
if (s == "Adam") {
|
|
return new AdadeltaOptimizer(config.adadelta().rho(),
|
|
config.adadelta().epsilon(),
|
|
config.adadelta().decay(),
|
|
lr);
|
|
}
|
|
// default
|
|
return new SGDOptimizer(config.sgd().momentum(),
|
|
config.sgd().decay(),
|
|
config.sgd().nesterov(),
|
|
lr);
|
|
};
|
|
return select_optimizer(config);
|
|
}
|
|
|
|
real *ParameterOptimizer::get_weight() const {
|
|
return parameter_->get_buffer();
|
|
}
|
|
|
|
void ParameterOptimizer::set_weight(Tensor *p) { parameter_ = p; }
|
|
|
|
} // namespace optimizer
|
|
} // namespace paddle
|