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include/tenzr/modules/optim/sgd.h

Namespaces

Name
tenzr
tenzr::optim

Classes

Name
class tenzr::optim::SGD
Stochastic gradient descent with momentum, weight decay, and Nesterov options.

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_SGD_H_
#define TENZR_MODULES_OPTIM_SGD_H_

#include <string>
#include <unordered_map>

#include "tenzr/modules/optim/schedule.h"
#include "tenzr/modules/optim/transform.h"

namespace tenzr::optim {

  class SGD : public GradientTransformation {
   public:
    explicit SGD(double lr = 1.0e-3, double momentum = 0.0, double dampening = 0.0, double weight_decay = 0.0, bool nesterov = 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 Momentum() const { return momentum_; }
    double WeightDecay() const { return weight_decay_; }
    bool Nesterov() const { return nesterov_; }

   private:
    double lr_;
    double momentum_;
    double dampening_;
    double weight_decay_;
    bool nesterov_;
    ScheduleFn schedule_;
  };

}  // namespace tenzr::optim

#endif  // TENZR_MODULES_OPTIM_SGD_H_