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88 lines
3.1 KiB
88 lines
3.1 KiB
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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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 "paddle/fluid/operators/optimizers/lars_momentum_op.h"
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#include "paddle/fluid/operators/optimizers/momentum_op.h"
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namespace paddle {
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namespace operators {
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class LarsMomentumOpMaker : public framework::OpProtoAndCheckerMaker {
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public:
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void Make() override {
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AddInput("Param",
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"(LoDTensor, default LoDTensor<float>) "
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"Input parameter that has to be updated");
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AddInput("Grad",
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"(LoDTensor, default LoDTensor<float>) "
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"Input gradient of the parameter");
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AddInput("Velocity",
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"(LoDTensor, default LoDTensor<float>) "
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"Input velocity (corresponding to the parameter) "
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"that has to be updated");
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AddInput("LearningRate",
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"(LoDTensor, default LoDTensor<float>) "
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"Input learning rate");
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AddOutput("ParamOut",
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"(LoDTensor) This output is updated parameter. "
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"It shared memory with Input(Param).");
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AddOutput("VelocityOut",
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"(LoDTensor) This output is updated velocity. "
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"It shared memory with Input(Velocity).");
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AddAttr<float>("mu", "(float) Momentum coefficient");
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AddAttr<float>("lars_coeff", "(float, default 0.001) LARS coefficient.")
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.SetDefault(0.001);
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AddAttr<float>("lars_weight_decay",
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"(float, default 0.0005) LARS weight decay")
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.SetDefault(0.0005);
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AddComment(R"DOC(
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Lars Momentum Optimizer.
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This optimizer use LARS (https://arxiv.org/abs/1708.03888) to optimize each
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weight using a local learning rate:
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$$
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local\_lr = \eta *
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\frac{\left \| param \right \|}{\left \| grad \right \| + \beta *\left \| param \right \|} \\
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velocity = mu * velocity +
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local\_lr * (grad + \beta * param) \\
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param = param - velocity. \\
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$$
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Note that we use lars_weight_decay here to decay weights, you may need not to
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use L2 regularizers in case of using LARS.
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)DOC");
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}
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};
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class LarsMomentumOpVarTypeInference : public framework::VarTypeInference {
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public:
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void operator()(framework::InferVarTypeContext* ctx) const override {}
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};
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} // namespace operators
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} // namespace paddle
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namespace ops = paddle::operators;
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REGISTER_OPERATOR(
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lars_momentum, ops::MomentumOp, ops::LarsMomentumOpMaker,
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paddle::framework::EmptyGradOpMaker<paddle::framework::OpDesc>,
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paddle::framework::EmptyGradOpMaker<paddle::imperative::OpBase>,
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ops::LarsMomentumOpVarTypeInference);
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REGISTER_OP_CPU_KERNEL(lars_momentum, ops::LarsMomentumOpKernel<float>,
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ops::LarsMomentumOpKernel<double>);
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