wehub-resource-sync
74 lines
2.6 KiB
C++
74 lines
2.6 KiB
C++
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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//
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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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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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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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#pragma once
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#include "paddle/phi/kernels/inverse_grad_kernel.h"
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#include "paddle/phi/backends/cpu/cpu_context.h"
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#include "paddle/phi/backends/gpu/gpu_context.h"
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#include "paddle/phi/kernels/complex_kernel.h"
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#include "paddle/phi/kernels/funcs/blas/blas.h"
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#include "paddle/phi/kernels/funcs/matrix_inverse.h"
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namespace phi {
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template <typename T, typename Context>
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void InverseGradKernel(const Context& dev_ctx,
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const DenseTensor& out,
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const DenseTensor& out_grad,
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DenseTensor* in_grad) {
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if (in_grad) {
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dev_ctx.template Alloc<T>(in_grad);
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if (out_grad.numel() == 0) {
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return;
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}
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auto blas = funcs::GetBlas<Context, T>(dev_ctx);
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DenseTensor tmp_out;
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tmp_out.Resize(out.dims());
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dev_ctx.template Alloc<T>(&tmp_out);
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if (IsComplexType(out.dtype())) {
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DenseTensor out_conj;
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out_conj.Resize(out.dims());
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dev_ctx.template Alloc<T>(&out_conj);
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ConjKernel<T, Context>(dev_ctx, out, &out_conj);
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auto mat_dim_a0 =
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funcs::CreateMatrixDescriptor(out_grad.dims(), 0, false);
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auto mat_dim_b0 = funcs::CreateMatrixDescriptor(out.dims(), 0, true);
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blas.MatMul(
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out_grad, mat_dim_a0, out_conj, mat_dim_b0, T(1), &tmp_out, T(0));
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auto mat_dim_a1 = funcs::CreateMatrixDescriptor(out.dims(), 0, true);
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auto mat_dim_b1 = funcs::CreateMatrixDescriptor(tmp_out.dims(), 0, false);
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blas.MatMul(
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out_conj, mat_dim_a1, tmp_out, mat_dim_b1, T(-1), in_grad, T(0));
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} else {
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auto mat_dim_a0 =
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funcs::CreateMatrixDescriptor(out_grad.dims(), 0, false);
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auto mat_dim_b0 = funcs::CreateMatrixDescriptor(out.dims(), 0, true);
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blas.MatMul(out_grad, mat_dim_a0, out, mat_dim_b0, T(1), &tmp_out, T(0));
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auto mat_dim_a1 = funcs::CreateMatrixDescriptor(out.dims(), 0, true);
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auto mat_dim_b1 = funcs::CreateMatrixDescriptor(tmp_out.dims(), 0, false);
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blas.MatMul(out, mat_dim_a1, tmp_out, mat_dim_b1, T(-1), in_grad, T(0));
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}
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}
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}
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} // namespace phi
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