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103 lines
3.9 KiB
103 lines
3.9 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/cast_op.h"
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#include <memory>
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#include "paddle/fluid/framework/op_registry.h"
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#include "paddle/fluid/platform/float16.h"
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namespace paddle {
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namespace operators {
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class CastOpProtoMaker : public framework::OpProtoAndCheckerMaker {
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public:
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void Make() override {
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AddInput("X", "The input tensor of cast op");
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AddOutput("Out", "The output tensor of cast op");
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AddAttr<int>("out_dtype", "output data type");
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AddAttr<int>("in_dtype", "input data type");
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AddComment(R"DOC(
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Cast Operator.
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This Operator casts the input tensor to another data type and
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returns the Output Tensor. It's meaningless if the output dtype equals
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the input dtype, but it's fine if you do so.
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)DOC");
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}
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};
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template <typename T>
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class CastOpGradMaker : public framework::SingleGradOpMaker<T> {
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public:
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using framework::SingleGradOpMaker<T>::SingleGradOpMaker;
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protected:
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void Apply(GradOpPtr<T> grad) const override {
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grad->SetType("cast");
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grad->SetInput("X", this->OutputGrad("Out"));
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grad->SetOutput("Out", this->InputGrad("X"));
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grad->SetAttr("out_dtype", this->GetAttr("in_dtype"));
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grad->SetAttr("in_dtype", this->GetAttr("out_dtype"));
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}
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};
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class CastOp : 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 *context) const override {
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OP_INOUT_CHECK(context->HasInput("X"), "Input", "X", "cast");
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OP_INOUT_CHECK(context->HasOutput("Out"), "Output", "Out", "cast");
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context->SetOutputDim("Out", context->GetInputDim("X"));
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context->ShareLoD("X", "Out");
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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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// CastOp kernel's device type is decided by input tensor place
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auto *tensor = ctx.Input<framework::LoDTensor>("X");
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PADDLE_ENFORCE_EQ(tensor->IsInitialized(), true,
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platform::errors::PreconditionNotMet(
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"The tensor of Input(X) is not initialized."));
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auto &tensor_place = tensor->place();
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// NOTE: cuda pinned tensor need to copy its data to target place
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if (platform::is_cuda_pinned_place(tensor_place)) {
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return framework::OpKernelType(tensor->type(), ctx.device_context());
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}
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return framework::OpKernelType(tensor->type(), tensor_place);
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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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using CPU = paddle::platform::CPUDeviceContext;
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REGISTER_OPERATOR(cast, ops::CastOp,
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ops::CastOpGradMaker<paddle::framework::OpDesc>,
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ops::CastOpGradMaker<paddle::imperative::OpBase>,
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ops::CastOpProtoMaker);
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REGISTER_OP_CPU_KERNEL(cast, ops::CastOpKernel<CPU, float>,
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ops::CastOpKernel<CPU, double>,
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ops::CastOpKernel<CPU, int>,
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ops::CastOpKernel<CPU, int64_t>,
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ops::CastOpKernel<CPU, bool>,
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ops::CastOpKernel<CPU, uint8_t>,
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ops::CastOpKernel<CPU, paddle::platform::float16>,
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ops::CastOpKernel<CPU, paddle::platform::bfloat16>,
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ops::CastOpKernel<CPU, paddle::platform::complex64>,
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ops::CastOpKernel<CPU, paddle::platform::complex128>);
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