// Copyright (c) 2022 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/phi/kernels/eig_grad_kernel.h" #include "paddle/phi/kernels/cpu/eig.h" #include "paddle/phi/core/kernel_registry.h" namespace phi { template void EigGradKernel(const Context& dev_ctx, const DenseTensor& out_w, const DenseTensor& out_v, const optional& dout_w, const optional& dout_v, DenseTensor* dx) { auto* dx_data = dev_ctx.template Alloc>(dx); if (dx->numel() == 0) { return; } int batch_count = BatchCount(out_v); const int order = static_cast(out_v.dims(-1)); ComputeBackwardForComplexInput, Context>( out_w, out_v, dout_w, dout_v, dx_data, batch_count, order, dev_ctx); } } // namespace phi PD_REGISTER_KERNEL(eig_grad, CPU, ALL_LAYOUT, phi::EigGradKernel, float, double, phi::complex64, phi::complex128) { kernel->InputAt(0).SetDataType(phi::dtype::ToReal(kernel_key.dtype())); kernel->InputAt(2).SetDataType(phi::dtype::ToReal(kernel_key.dtype())); kernel->OutputAt(0).SetDataType(phi::dtype::ToComplex(kernel_key.dtype())); }