wehub-resource-sync
87 lines
3.1 KiB
C++
87 lines
3.1 KiB
C++
/* Copyright (c) 2022 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/phi/kernels/cholesky_kernel.h"
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#include "Eigen/Cholesky"
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#include "Eigen/Core"
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#include "paddle/phi/backends/cpu/cpu_context.h"
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#include "paddle/phi/core/kernel_registry.h"
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#include "paddle/phi/kernels/funcs/eigen/common.h"
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namespace phi {
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template <typename T, typename Context>
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void CholeskyKernel(const Context& dev_ctx,
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const DenseTensor& x,
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bool upper,
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DenseTensor* out) {
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using EigenMatrix =
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Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor>;
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using InputMatrixMap = Eigen::Map<const EigenMatrix>;
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using OutputMatrixMap = Eigen::Map<EigenMatrix>;
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if (out->numel() == 0) {
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dev_ctx.template Alloc<T>(out);
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return;
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}
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auto& dims = x.dims();
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int batch_count = 1;
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for (int i = 0; i < dims.size() - 2; i++) {
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batch_count *= static_cast<int>(dims[i]);
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}
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auto m = dims[dims.size() - 1];
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const auto* x_data = x.data<T>();
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auto* out_data = dev_ctx.template Alloc<T>(out);
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// Cholesky decomposition for each matrix, maybe can use multi threads
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for (int i = 0; i < batch_count; i++) {
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auto input = InputMatrixMap(x_data + i * m * m, m, m);
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auto output = OutputMatrixMap(out_data + i * m * m, m, m);
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if (upper) {
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Eigen::LLT<
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Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor>,
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Eigen::UpLoType::Upper>
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llt_decomposition(input);
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PADDLE_ENFORCE_EQ(llt_decomposition.info(),
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Eigen::Success,
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errors::InvalidArgument(
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"Cholesky decomposition was not successful. The "
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"%d-th input matrice "
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"might not be not be positive definite.",
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i));
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output = llt_decomposition.matrixU();
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} else {
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Eigen::LLT<
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Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor>,
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Eigen::UpLoType::Lower>
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llt_decomposition(input);
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PADDLE_ENFORCE_EQ(llt_decomposition.info(),
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Eigen::Success,
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errors::InvalidArgument(
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"Cholesky decomposition was not successful. The "
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"%d-th input matrice "
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"might not be not be positive definite.",
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i));
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output = llt_decomposition.matrixL();
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}
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}
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}
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} // namespace phi
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PD_REGISTER_KERNEL(
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cholesky, CPU, ALL_LAYOUT, phi::CholeskyKernel, float, double) {}
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