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121 lines
4.8 KiB
121 lines
4.8 KiB
/* Copyright (c) 2020 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/tril_triu_op.h"
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#include <memory>
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namespace paddle {
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namespace operators {
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class TrilTriuOp : 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_EQ(
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ctx->HasInput("X"), true,
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platform::errors::NotFound("Input(X) of TrilTriuOp is not found."));
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PADDLE_ENFORCE_EQ(
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ctx->HasOutput("Out"), true,
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platform::errors::NotFound("Output(Out) of TrilTriuOp is not found."));
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const auto& x_dims = ctx->GetInputDim("X");
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PADDLE_ENFORCE_GE(x_dims.size(), 2,
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platform::errors::InvalidArgument(
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"Input(X)'s rank must be at least 2 in TrilTriuOp."));
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ctx->SetOutputDim("Out", x_dims);
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ctx->ShareLoD("X", /*->*/ "Out");
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}
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};
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class TrilTriuOpMaker : public framework::OpProtoAndCheckerMaker {
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public:
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void Make() override {
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AddInput("X", "Tensor, the input of tril_triu op");
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AddOutput("Out",
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"Tensor, the output tensor, with the same shape and data type as "
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"input(x)");
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AddAttr<int>("diagonal", "int number, the diagonal to consider.")
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.SetDefault(0);
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AddAttr<bool>("lower", "boolnumber, lower triangular or upper triangular.");
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AddComment(R"DOC(
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TrilTriu Operator.
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The tril operator returns the lower triangular part of the matrix (2-D tensor)
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or batch of matrices $input$. The lower triangular part of the matrix is defined
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as the elements on and below the diagonal.
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The triu operator returns the upper triangular part of a matrix (2-D tensor)
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or batch of matrices $input$. The upper triangular part of the matrix is defined
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as the elements on and above the diagonal.
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The other elements of the result tensor out are set to 0.
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The argument diagonal controls which diagonal to consider, default value is 0.
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)DOC");
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}
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};
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class TrilTriuGradOp : 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_EQ(ctx->HasInput(framework::GradVarName("Out")), true,
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platform::errors::NotFound(
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"Input(Out@GRAD) of TrilTriuOp should not be null"));
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PADDLE_ENFORCE_EQ(ctx->HasOutput(framework::GradVarName("X")), true,
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platform::errors::NotFound(
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"Output(X@Grad) of TrilTriuOp should not be null"));
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ctx->SetOutputDim(framework::GradVarName("X"),
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ctx->GetInputDim(framework::GradVarName("Out")));
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}
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};
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template <typename T>
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class TrilTriuGradOpMaker : 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> op) const override {
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op->SetType("tril_triu_grad");
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op->SetInput(framework::GradVarName("Out"), this->OutputGrad("Out"));
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op->SetOutput(framework::GradVarName("X"), this->InputGrad("X"));
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op->SetAttrMap(this->Attrs());
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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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namespace plat = paddle::platform;
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REGISTER_OPERATOR(tril_triu, ops::TrilTriuOp, ops::TrilTriuOpMaker,
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ops::TrilTriuGradOpMaker<paddle::framework::OpDesc>,
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ops::TrilTriuGradOpMaker<paddle::imperative::OpBase>);
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REGISTER_OPERATOR(tril_triu_grad, ops::TrilTriuGradOp);
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REGISTER_OP_CPU_KERNEL(
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tril_triu, ops::TrilTriuOpKernel<paddle::platform::CPUDeviceContext, float>,
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ops::TrilTriuOpKernel<paddle::platform::CPUDeviceContext, double>,
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ops::TrilTriuOpKernel<paddle::platform::CPUDeviceContext, int>,
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ops::TrilTriuOpKernel<paddle::platform::CPUDeviceContext, int64_t>,
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ops::TrilTriuOpKernel<paddle::platform::CPUDeviceContext, plat::float16>);
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REGISTER_OP_CPU_KERNEL(
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tril_triu_grad,
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ops::TrilTriuGradOpKernel<paddle::platform::CPUDeviceContext, float>,
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ops::TrilTriuGradOpKernel<paddle::platform::CPUDeviceContext, double>,
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ops::TrilTriuGradOpKernel<paddle::platform::CPUDeviceContext, int>,
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ops::TrilTriuGradOpKernel<paddle::platform::CPUDeviceContext, int64_t>,
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ops::TrilTriuGradOpKernel<paddle::platform::CPUDeviceContext,
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plat::float16>);
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