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66 lines
2.2 KiB
66 lines
2.2 KiB
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License. */
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#include "sgd_optimizer.h"
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#include "serialization.h"
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namespace paddle {
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namespace optimizer {
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void SGDOptimizer::Update(const Tensor *gradient) {
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num_sample_passed_ += 1;
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double learning_rate = lr_policy_->LearningRate(num_sample_passed_);
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float velocity = 0.0;
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Tensor ¶m = *parameter_;
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const Tensor &grad = *gradient;
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Tensor &m = *momentums_;
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for (size_t i = 0; i < param.size(); ++i) {
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if (momentum_ == 0.0) {
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velocity = -learning_rate * grad[i] - learning_rate * decay_ * param[i];
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} else {
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m[i] = momentum_ * m[i] - learning_rate * grad[i] -
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learning_rate * decay_ * param[i];
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velocity = m[i];
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}
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if (nesterov_) {
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param[i] += momentum_ * velocity - learning_rate * grad[i];
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} else {
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param[i] += velocity;
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}
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}
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}
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std::string SGDOptimizer::SerializeState() {
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SGDOptimizerState state;
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state.set_num_sample_passed(num_sample_passed_);
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std::string lr_str = this->lr_policy_->SerializeState();
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state.mutable_lr_state()->ParseFromString(lr_str);
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TensorToProto(*parameter_, state.mutable_parameter());
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if (momentum_ != 0.0) TensorToProto(*momentums_, state.mutable_momentums());
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return state.SerializeAsString();
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}
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void SGDOptimizer::DeserializeState(const std::string &str) {
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SGDOptimizerState state;
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state.ParseFromString(str);
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auto lr_state = state.lr_state();
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this->lr_policy_->DeserializeState(lr_state.SerializeAsString());
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num_sample_passed_ = state.num_sample_passed();
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ProtoToTensor(state.parameter(), parameter_);
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if (momentum_ != 0.0) ProtoToTensor(state.momentums(), momentums_);
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}
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} // namespace optimizer
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} // namespace paddle
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