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116 lines
4.2 KiB
116 lines
4.2 KiB
/* Copyright (c) 2016 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/momentum_op.h"
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namespace paddle {
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namespace operators {
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using Tensor = framework::Tensor;
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class MomentumOp : public framework::OperatorWithKernel {
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public:
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using framework::OperatorWithKernel::OperatorWithKernel;
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protected:
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void InferShape(framework::InferShapeContext *ctx) const override {
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PADDLE_ENFORCE(ctx->HasInput("Param"),
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"Input(param) of Momentum should not be null.");
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PADDLE_ENFORCE(ctx->HasInput("Grad"),
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"Input(grad) of Momentum should not be null.");
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PADDLE_ENFORCE(ctx->HasInput("Velocity"),
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"Input(velocity) of Momentum should not be null.");
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PADDLE_ENFORCE(ctx->HasInput("LearningRate"),
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"Input(LearningRate) of Momentum should not be null.");
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PADDLE_ENFORCE(ctx->HasOutput("ParamOut"),
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"Output(ParamOut) of Momentum should not be null.");
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PADDLE_ENFORCE(ctx->HasOutput("VelocityOut"),
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"Output(VelocityOut) of Momentum should not be null.");
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auto param_dim = ctx->GetInputDim("Param");
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PADDLE_ENFORCE_EQ(
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param_dim, ctx->GetInputDim("Grad"),
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"Param and Grad input of MomentumOp should have the same dimension.");
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PADDLE_ENFORCE_EQ(
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param_dim, ctx->GetInputDim("Velocity"),
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"Param and Velocity of MomentumOp should have the same dimension.");
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PADDLE_ENFORCE_EQ(framework::product(ctx->GetInputDim("LearningRate")), 1,
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"Learning_rate should be a scalar");
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ctx->SetOutputDim("ParamOut", param_dim);
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ctx->SetOutputDim("VelocityOut", param_dim);
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}
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framework::OpKernelType GetExpectedKernelType(
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const framework::ExecutionContext &ctx) const override {
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auto input_data_type =
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framework::ToDataType(ctx.Input<Tensor>("Param")->type());
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return framework::OpKernelType(input_data_type, ctx.GetPlace());
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}
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};
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class MomentumOpMaker : 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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"(Tensor, default Tensor<float>) "
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"Input parameter that has to be updated");
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AddInput("Grad",
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"(Tensor, default Tensor<float>) "
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"Input gradient of the parameter");
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AddInput("Velocity",
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"(Tensor, default Tensor<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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"(Tensor, default Tensor<float>) "
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"Input learning rate");
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AddOutput("ParamOut",
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"(Tensor) 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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"(Tensor) 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<bool>("use_nesterov",
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"(bool, default false) "
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"Use Nesterov Momentum")
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.SetDefault(false);
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AddComment(R"DOC(
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Momentum Optimizer.
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This optimizer has a flag for Nestrov Momentum.
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The update equations are as follows:
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$$
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velocity = mu * velocity + gradient \\
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if (use\_nesterov): \\
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param = param - (gradient + mu * velocity) * learning\_rate \\
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else: \\
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param = param - learning\_rate * velocity. \\
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$$
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)DOC");
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}
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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_OP_WITHOUT_GRADIENT(momentum, ops::MomentumOp, ops::MomentumOpMaker);
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REGISTER_OP_CPU_KERNEL(momentum, ops::MomentumOpKernel<float>,
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ops::MomentumOpKernel<double>);
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