include/tenzr/modules/optim/adam.h¶
Namespaces¶
| Name |
|---|
| tenzr |
| tenzr::optim |
Classes¶
| Name | |
|---|---|
| class | tenzr::optim::Adam Adam optimizer with optional AMSGrad and decoupled weight decay. |
| class | tenzr::optim::AdamW Adam variant that applies decoupled weight decay. |
Source code¶
// Copyright 2026 The Tenzr Project Authors
//
// SPDX-License-Identifier: Apache-2.0
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// https://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
#ifndef TENZR_MODULES_OPTIM_ADAM_H_
#define TENZR_MODULES_OPTIM_ADAM_H_
#include <string>
#include <unordered_map>
#include "tenzr/modules/optim/schedule.h"
#include "tenzr/modules/optim/transform.h"
namespace tenzr::optim {
class Adam : public GradientTransformation {
public:
explicit Adam(double lr = 1.0e-3, double beta1 = 0.9, double beta2 = 0.999, double eps = 1.0e-8, double weight_decay = 0.0, bool amsgrad = false,
bool decoupled_weight_decay = false, ScheduleFn schedule = nullptr);
OptState Init(const std::unordered_map<std::string, Tensor>& params) override;
std::unordered_map<std::string, Tensor> Update(const std::unordered_map<std::string, Tensor>& grads, OptState& state,
const std::unordered_map<std::string, Tensor>& params) override;
double Lr() const { return lr_; }
double Beta1() const { return beta1_; }
double Beta2() const { return beta2_; }
double Eps() const { return eps_; }
double WeightDecay() const { return weight_decay_; }
bool Amsgrad() const { return amsgrad_; }
protected:
double lr_;
double beta1_;
double beta2_;
double eps_;
double weight_decay_;
bool amsgrad_;
bool decoupled_weight_decay_;
ScheduleFn schedule_;
};
class AdamW : public Adam {
public:
explicit AdamW(double lr = 1.0e-3, double beta1 = 0.9, double beta2 = 0.999, double eps = 1.0e-8, double weight_decay = 1.0e-2, bool amsgrad = false,
ScheduleFn schedule = nullptr)
: Adam(lr, beta1, beta2, eps, weight_decay, amsgrad, true, std::move(schedule)) {}
};
} // namespace tenzr::optim
#endif // TENZR_MODULES_OPTIM_ADAM_H_