/usr/local/lib64/python3.6/site-packages/torch/include/torch/csrc/api/include/torch/optim
Edit: /usr/local/lib64/python3.6/site-packages/torch/include/torch/csrc/api/include/torch/optim/adam.h (2951B)
#pragma once
#include
#include
#include
#include
#include
namespace torch {
namespace serialize {
class OutputArchive;
class InputArchive;
} // namespace serialize
} // namespace torch
namespace torch {
namespace optim {
struct TORCH_API AdamOptions : public OptimizerCloneableOptions {
AdamOptions(double lr = 1e-3);
TORCH_ARG(double, lr) = 1e-3;
typedef std::tuple betas_t;
TORCH_ARG(betas_t, betas) = std::make_tuple(0.9, 0.999);
TORCH_ARG(double, eps) = 1e-8;
TORCH_ARG(double, weight_decay) = 0;
TORCH_ARG(bool, amsgrad) = false;
public:
void serialize(torch::serialize::InputArchive& archive) override;
void serialize(torch::serialize::OutputArchive& archive) const override;
TORCH_API friend bool operator==(const AdamOptions& lhs, const AdamOptions& rhs);
~AdamOptions() override = default;
double get_lr() const override;
void set_lr(const double lr) override;
};
struct TORCH_API AdamParamState : public OptimizerCloneableParamState {
TORCH_ARG(int64_t, step) = 0;
TORCH_ARG(torch::Tensor, exp_avg);
TORCH_ARG(torch::Tensor, exp_avg_sq);
TORCH_ARG(torch::Tensor, max_exp_avg_sq) = {};
public:
void serialize(torch::serialize::InputArchive& archive) override;
void serialize(torch::serialize::OutputArchive& archive) const override;
TORCH_API friend bool operator==(const AdamParamState& lhs, const AdamParamState& rhs);
~AdamParamState() override = default;
};
class TORCH_API Adam : public Optimizer {
public:
explicit Adam(std::vector param_groups,
AdamOptions defaults = {}) : Optimizer(std::move(param_groups), std::make_unique(defaults)) {
TORCH_CHECK(defaults.lr() >= 0, "Invalid learning rate: ", defaults.lr());
TORCH_CHECK(defaults.eps() >= 0, "Invalid epsilon value: ", defaults.eps());
auto betas = defaults.betas();
TORCH_CHECK(0 <= std::get<0>(betas) && std::get<0>(betas) < 1.0, "Invalid beta parameter at index 0: ", std::get<0>(betas));
TORCH_CHECK(0 <= std::get<1>(betas) && std::get<1>(betas) < 1.0, "Invalid beta parameter at index 1: ", std::get<1>(betas));
TORCH_CHECK(defaults.weight_decay() >= 0, "Invalid weight_decay value: ", defaults.weight_decay());
}
explicit Adam(
std::vector params,
// NOLINTNEXTLINE(performance-move-const-arg)
AdamOptions defaults = {}) : Adam({std::move(OptimizerParamGroup(params))}, defaults) {}
torch::Tensor step(LossClosure closure = nullptr) override;
void save(serialize::OutputArchive& archive) const override;
void load(serialize::InputArchive& archive) override;
private:
template
static void serialize(Self& self, Archive& archive) {
_TORCH_OPTIM_SERIALIZE_WITH_TEMPLATE_ARG(Adam);
}
};
} // namespace optim
} // namespace torch