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explicitly specify capture mode for lambdas (PaddlePaddle#55)
explicitly specify capture mode for lambdas
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Feiyu Chan
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Sep 16, 2021
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,167 @@ | ||
| /* Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. | ||
| Licensed under the Apache License, Version 2.0 (the "License"); | ||
| you may not use this file except in compliance with the License. | ||
| You may obtain a copy of the License at | ||
| http://www.apache.org/licenses/LICENSE-2.0 | ||
| Unless required by applicable law or agreed to in writing, software | ||
| distributed under the License is distributed on an "AS IS" BASIS, | ||
| WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| See the License for the specific language governing permissions and | ||
| limitations under the License. */ | ||
|
|
||
| #include "paddle/fluid/operators/eigh_op.h" | ||
|
|
||
| namespace paddle { | ||
| namespace operators { | ||
|
|
||
| using framework::Tensor; | ||
|
|
||
| class EighOp : public framework::OperatorWithKernel { | ||
| public: | ||
| using framework::OperatorWithKernel::OperatorWithKernel; | ||
|
|
||
| void InferShape(framework::InferShapeContext* ctx) const override { | ||
| OP_INOUT_CHECK(ctx->HasInput("X"), "Input", "X", "Eigh"); | ||
| OP_INOUT_CHECK(ctx->HasOutput("Eigenvalues"), "Output", "Eigenvalues", | ||
| "Eigh"); | ||
| OP_INOUT_CHECK(ctx->HasOutput("Eigenvectors"), "Output", "Eigenvectors", | ||
| "Eigh"); | ||
|
|
||
| auto input_dim = ctx->GetInputDim("X"); | ||
| auto rank = input_dim.size(); | ||
|
|
||
| PADDLE_ENFORCE_GE(rank, 2, | ||
| platform::errors::InvalidArgument( | ||
| "The Input(X) should have at least 2 dimensions." | ||
| "But received a %d dimension tensor.", | ||
| rank)); | ||
| PADDLE_ENFORCE_EQ( | ||
| input_dim[rank - 2], input_dim[rank - 1], | ||
| platform::errors::InvalidArgument( | ||
| "Eigh op is designed for square matrix, consequently" | ||
| "inner-most 2 dimensions of Input(X) should be symmetric." | ||
| "But received X's shape[-2] = %d and shape[-1] = %d.", | ||
| input_dim[rank - 2], input_dim[rank - 1])); | ||
|
|
||
| std::vector<int64_t> values_dim; | ||
| if (rank > 2) { | ||
| for (auto i = 0; i < rank - 1; i++) { | ||
| values_dim.emplace_back(input_dim[i]); | ||
| } | ||
| } else { | ||
| values_dim = {input_dim[1]}; | ||
| } | ||
|
|
||
| ctx->SetOutputDim("Eigenvalues", framework::make_ddim(values_dim)); | ||
| ctx->SetOutputDim("Eigenvectors", input_dim); | ||
| } | ||
| }; | ||
|
|
||
| class EignOpMaker : public framework::OpProtoAndCheckerMaker { | ||
| public: | ||
| void Make() override { | ||
| AddInput("X", | ||
| "(Tensor), Hermitian or real symmetric matrices." | ||
| "Its shape should be [*, N, N] where * is zero or" | ||
| "more batch dimensions. The data type is float32 ," | ||
| "float64, complex64, complex128."); | ||
| AddOutput("Eigenvalues", | ||
| "(Tensor), The eigenvalues in ascending order." | ||
| "The data type is float32 or float64."); | ||
| AddOutput( | ||
| "Eigenvectors", | ||
| "(Tensor), The column is the normalized eigenvector " | ||
| "corresponding to the eigenvalue. The data type is the same as ``X``."); | ||
| AddAttr<std::string>( | ||
| "UPLO", | ||
| "(string, default 'L'), 'L' represents the lower triangular matrix," | ||
| "'U' represents the upper triangular matrix.") | ||
| .SetDefault("L"); | ||
| AddComment(R"DOC( | ||
| Eigh Operator. | ||
| Computes the eigenvalues and eigenvectors of a complex Hermitian | ||
| (conjugate symmetric) or a real symmetric matrix. | ||
| )DOC"); | ||
| } | ||
| }; | ||
|
|
||
| class EighGradOp : public framework::OperatorWithKernel { | ||
| public: | ||
| using framework::OperatorWithKernel::OperatorWithKernel; | ||
|
|
||
| void InferShape(framework::InferShapeContext* ctx) const override { | ||
| OP_INOUT_CHECK(ctx->HasInput("Eigenvalues"), "Input", "Eigenvalues", | ||
| "EighGrad"); | ||
| OP_INOUT_CHECK(ctx->HasInput("Eigenvectors"), "Input", "Eigenvectors", | ||
| "EighGrad"); | ||
| OP_INOUT_CHECK(ctx->HasInputs(framework::GradVarName("Eigenvalues")), | ||
| "Input", "Eigenvalues@GRAD", "EighGrad"); | ||
| OP_INOUT_CHECK(ctx->HasInputs(framework::GradVarName("Eigenvectors")), | ||
| "Input", "Eigenvectors@GRAD", "EighGrad"); | ||
| auto dims = ctx->GetInputDim("Eigenvectors"); | ||
| auto x_grad_name = framework::GradVarName("X"); | ||
| if (ctx->HasOutput(x_grad_name)) { | ||
| ctx->SetOutputDim(x_grad_name, dims); | ||
| } | ||
| } | ||
|
|
||
| protected: | ||
| framework::OpKernelType GetExpectedKernelType( | ||
| const framework::ExecutionContext& ctx) const override { | ||
| return framework::OpKernelType( | ||
| OperatorWithKernel::IndicateVarDataType( | ||
| ctx, framework::GradVarName("Eigenvectors")), | ||
| ctx.device_context()); | ||
| } | ||
| }; | ||
|
|
||
| template <typename T> | ||
| class EighGradOpMaker : public framework::SingleGradOpMaker<T> { | ||
| public: | ||
| using framework::SingleGradOpMaker<T>::SingleGradOpMaker; | ||
|
|
||
| protected: | ||
| void Apply(GradOpPtr<T> op) const override { | ||
| op->SetType(this->ForwardOpType() + "_grad"); | ||
| op->SetInput("Eigenvalues", this->Output("Eigenvalues")); | ||
| op->SetInput("Eigenvectors", this->Output("Eigenvectors")); | ||
| op->SetInput(framework::GradVarName("Eigenvalues"), | ||
| this->OutputGrad("Eigenvalues")); | ||
| op->SetInput(framework::GradVarName("Eigenvectors"), | ||
| this->OutputGrad("Eigenvectors")); | ||
| op->SetAttrMap(this->Attrs()); | ||
| op->SetOutput(framework::GradVarName("X"), this->InputGrad("X")); | ||
| } | ||
| }; | ||
|
|
||
| } // namespace operators | ||
| } // namespace paddle | ||
|
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| namespace ops = paddle::operators; | ||
|
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| REGISTER_OPERATOR(eigh, ops::EighOp, ops::EignOpMaker, | ||
| ops::EighGradOpMaker<paddle::framework::OpDesc>, | ||
| ops::EighGradOpMaker<paddle::imperative::OpBase>); | ||
| REGISTER_OPERATOR(eigh_grad, ops::EighGradOp); | ||
|
|
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| REGISTER_OP_CPU_KERNEL( | ||
| eigh, ops::EighKernel<paddle::platform::CPUDeviceContext, float, float>, | ||
| ops::EighKernel<paddle::platform::CPUDeviceContext, double, double>, | ||
| ops::EighKernel<paddle::platform::CPUDeviceContext, float, | ||
| paddle::platform::complex<float>>, | ||
| ops::EighKernel<paddle::platform::CPUDeviceContext, double, | ||
| paddle::platform::complex<double>>); | ||
|
|
||
| REGISTER_OP_CPU_KERNEL( | ||
| eigh_grad, | ||
| ops::EighGradKernel<paddle::platform::CPUDeviceContext, float, float>, | ||
| ops::EighGradKernel<paddle::platform::CPUDeviceContext, double, double>, | ||
| ops::EighGradKernel<paddle::platform::CPUDeviceContext, float, | ||
| paddle::platform::complex<float>>, | ||
| ops::EighGradKernel<paddle::platform::CPUDeviceContext, double, | ||
| paddle::platform::complex<double>>); |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,53 @@ | ||
| /* Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. | ||
| Licensed under the Apache License, Version 2.0 (the "License"); | ||
| you may not use this file except in compliance with the License. | ||
| You may obtain a copy of the License at | ||
| http://www.apache.org/licenses/LICENSE-2.0 | ||
| Unless required by applicable law or agreed to in writing, software | ||
| distributed under the License is distributed on an "AS IS" BASIS, | ||
| WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| See the License for the specific language governing permissions and | ||
| limitations under the License. */ | ||
|
|
||
| #include "paddle/fluid/operators/eigh_op.h" | ||
|
|
||
| namespace paddle { | ||
| namespace operators { | ||
|
|
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| using Tensor = framework::Tensor; | ||
|
|
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| template <typename ValueType, typename T> | ||
| class EighGPUKernel : public framework::OpKernel<T> { | ||
| public: | ||
| void Compute(const framework::ExecutionContext &ctx) const override { | ||
| auto input_var = ctx.Input<Tensor>("X"); | ||
| auto output_w_var = ctx.Output<Tensor>("Eigenvalues"); | ||
| auto output_v_var = ctx.Output<Tensor>("Eigenvectors"); | ||
| std::string lower = ctx.Attr<std::string>("UPLO"); | ||
| bool is_lower = (lower == "L"); | ||
| math::MatrixEighFunctor<ValueType, T> functor; | ||
| functor(ctx, *input_var, output_w_var, output_v_var, is_lower, true); | ||
| } | ||
| }; | ||
|
|
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| } // namespace operators | ||
| } // namespace paddle | ||
|
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| namespace ops = paddle::operators; | ||
|
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| REGISTER_OP_CUDA_KERNEL( | ||
| eigh, ops::EighGPUKernel<float, float>, ops::EighGPUKernel<double, double>, | ||
| ops::EighGPUKernel<float, paddle::platform::complex<float>>, | ||
| ops::EighGPUKernel<double, paddle::platform::complex<double>>); | ||
|
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| REGISTER_OP_CUDA_KERNEL( | ||
| eigh_grad, | ||
| ops::EighGradKernel<paddle::platform::CUDADeviceContext, float, float>, | ||
| ops::EighGradKernel<paddle::platform::CUDADeviceContext, double, double>, | ||
| ops::EighGradKernel<paddle::platform::CUDADeviceContext, float, | ||
| paddle::platform::complex<float>>, | ||
| ops::EighGradKernel<paddle::platform::CUDADeviceContext, double, | ||
| paddle::platform::complex<double>>); |
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