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84 lines
3.1 KiB
84 lines
3.1 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 "paddle/operators/dropout_op.h"
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namespace paddle {
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namespace operators {
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using framework::Tensor;
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class DropoutOp : 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(const framework::InferShapeContext &ctx) const override {
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PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("X"), "Input(X) must not be null.");
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auto dims = ctx.Input<Tensor>("X")->dims();
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ctx.Output<Tensor>("Out")->Resize(dims);
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ctx.Output<Tensor>("Mask")->Resize(dims);
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}
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};
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class DropoutOpMaker : public framework::OpProtoAndCheckerMaker {
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public:
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DropoutOpMaker(framework::OpProto *proto,
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framework::OpAttrChecker *op_checker)
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: OpProtoAndCheckerMaker(proto, op_checker) {
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AddAttr<float>("dropout_prob", "Dropout probability.").SetDefault(.5f);
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AddAttr<int>("seed", "Dropout random seed.").SetDefault(0);
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AddInput("X", "The input of dropout op.");
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AddOutput("Out", "The output of dropout op.");
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AddOutput("Mask", "The dropout mask.").AsIntermediate();
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AddComment(R"DOC(Dropout Operator.)DOC");
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}
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};
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class DropoutOpGrad : 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(const framework::InferShapeContext &ctx) const override {
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PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("X"), "Input(X) must not be null.");
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PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("Mask"), "Mask must not be null.");
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PADDLE_ENFORCE_NOT_NULL(ctx.InputVar(framework::GradVarName("Out")),
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"Input(Out@GRAD) must not be null.");
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auto x_dims = ctx.Input<Tensor>("X")->dims();
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auto mask_dims = ctx.Input<Tensor>("Mask")->dims();
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auto out_dims = ctx.Input<Tensor>(framework::GradVarName("Out"))->dims();
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PADDLE_ENFORCE_EQ(x_dims, out_dims,
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"Dimensions of Input(X) and Out@Grad must be the same.");
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PADDLE_ENFORCE_EQ(x_dims, mask_dims,
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"Dimensions of Input(X) and Mask must be the same.");
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auto *x_grad = ctx.Output<Tensor>(framework::GradVarName("X"));
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x_grad->Resize(x_dims);
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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(dropout, ops::DropoutOp, ops::DropoutOpMaker, dropout_grad,
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ops::DropoutOpGrad);
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REGISTER_OP_CPU_KERNEL(
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dropout, ops::CPUDropoutKernel<paddle::platform::CPUPlace, float>);
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REGISTER_OP_CPU_KERNEL(
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dropout_grad, ops::DropoutGradKernel<paddle::platform::CPUPlace, float>);
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