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104 lines
3.8 KiB
104 lines
3.8 KiB
/* Copyright (c) 2019 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/fill_any_like_op.h"
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#include <string>
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namespace paddle {
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namespace operators {
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class FillAnyLikeOp : 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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OP_INOUT_CHECK(ctx->HasInput("X"), "Input", "X", "fill_any_like");
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OP_INOUT_CHECK(ctx->HasOutput("Out"), "Output", "Out", "fill_any_like");
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ctx->SetOutputDim("Out", ctx->GetInputDim("X"));
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ctx->ShareLoD("X", /*->*/ "Out");
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}
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protected:
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framework::OpKernelType GetExpectedKernelType(
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const framework::ExecutionContext &ctx) const override {
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framework::OpKernelType kt = OperatorWithKernel::GetExpectedKernelType(ctx);
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const auto &data_type = ctx.Attr<int>("dtype");
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if (data_type >= 0) {
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kt.data_type_ = static_cast<framework::proto::VarType::Type>(data_type);
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}
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return kt;
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}
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framework::OpKernelType GetKernelTypeForVar(
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const std::string &var_name, const framework::Tensor &tensor,
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const framework::OpKernelType &expected_kernel_type) const override {
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return framework::OpKernelType(expected_kernel_type.data_type_,
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expected_kernel_type.place_,
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tensor.layout());
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}
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};
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class FillAnyLikeOpMaker : public framework::OpProtoAndCheckerMaker {
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public:
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void Make() override {
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AddInput("X", "The input of fill-zeros-like op.");
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AddOutput("Out", "The variable will be filled up with specified value.");
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AddAttr<float>("value", "The filled value").SetDefault(0.0);
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AddAttr<int>("dtype",
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"Output tensor data type. defalut value is -1,"
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"according to the input dtype.")
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.SetDefault(-1);
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AddComment(R"DOC(
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FillAnyLike Operator.
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Fill up a variable with Attr(value).
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The output will have the same shape and dtype as the input.
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)DOC");
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}
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};
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class FillAnyLikeVarTypeInference : public framework::VarTypeInference {
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public:
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void operator()(framework::InferVarTypeContext *ctx) const override {
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auto var_data_type = static_cast<framework::proto::VarType::Type>(
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boost::get<int>(ctx->GetAttr("dtype")));
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if (var_data_type < 0) {
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ctx->SetOutputDataType("Out", ctx->GetInputDataType("X"));
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} else {
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ctx->SetOutputDataType("Out", var_data_type);
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}
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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_OPERATOR(
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fill_any_like, ops::FillAnyLikeOp, ops::FillAnyLikeOpMaker,
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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::FillAnyLikeVarTypeInference)
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REGISTER_OP_CPU_KERNEL(
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fill_any_like,
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ops::FillAnyLikeKernel<paddle::platform::CPUDeviceContext, int>,
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ops::FillAnyLikeKernel<paddle::platform::CPUDeviceContext, int64_t>,
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ops::FillAnyLikeKernel<paddle::platform::CPUDeviceContext, float>,
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ops::FillAnyLikeKernel<paddle::platform::CPUDeviceContext, double>,
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ops::FillAnyLikeKernel<paddle::platform::CPUDeviceContext,
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paddle::platform::float16>,
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ops::FillAnyLikeKernel<paddle::platform::CPUDeviceContext, bool>);
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