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70 lines
2.4 KiB
70 lines
2.4 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/sgd_op.h"
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namespace paddle {
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namespace operators {
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class SGDOp : public framework::OperatorWithKernel {
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public:
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using framework::OperatorWithKernel::OperatorWithKernel;
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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 SGDOp should not be null.");
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PADDLE_ENFORCE(ctx->HasInput("Grad"),
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"Input(Grad) of SGDOp should not be null.");
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PADDLE_ENFORCE(ctx->HasInput("LearningRate"),
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"Input(LearningRate) of SGDOp should not be null.");
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PADDLE_ENFORCE(ctx->HasOutput("ParamOut"),
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"Output(ParamOut) of SGDOp should not be null.");
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auto lr_dims = ctx->GetInputDim("LearningRate");
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PADDLE_ENFORCE_EQ(framework::product(lr_dims), 1,
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"Learning rate should have 1 element");
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auto param_dim = ctx->GetInputDim("Param");
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// TODO(qijun): check dimensions of Param and Grad at complie
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// and run time.
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ctx->SetOutputDim("ParamOut", param_dim);
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}
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};
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class SGDOpMaker : public framework::OpProtoAndCheckerMaker {
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public:
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SGDOpMaker(OpProto* proto, OpAttrChecker* op_checker)
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: OpProtoAndCheckerMaker(proto, op_checker) {
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AddInput("Param", "(Tensor) Input parameter");
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AddInput("LearningRate", "(Tensor) Learning rate of SGD");
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AddInput("Grad", "(Tensor) Input gradient");
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AddOutput("ParamOut", "(Tensor) Output parameter");
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AddComment(R"DOC(
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SGD operator
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This operator implements one step of the stochastic gradient descent algorithm.
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$$param\_out = param - learning\_rate * grad$$
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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(sgd, ops::SGDOp, ops::SGDOpMaker);
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REGISTER_OP_CPU_KERNEL(sgd, ops::SGDOpKernel<float>, ops::SGDOpKernel<double>);
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