// 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/where_grad_kernel.h" #include "paddle/phi/core/kernel_registry.h" #include "paddle/phi/kernels/full_kernel.h" namespace phi { template void WhereGradKernel(const Context& dev_ctx, const DenseTensor& condition, const DenseTensor& x UNUSED, const DenseTensor& y UNUSED, const DenseTensor& out_grad, DenseTensor* x_grad, DenseTensor* y_grad) { const auto* cond_data = condition.data(); auto numel = condition.numel(); auto* dout = out_grad.data(); if (out_grad.numel() == 0) { if (x_grad) { Full(dev_ctx, x_grad->dims(), static_cast(0), x_grad); } if (y_grad) { Full(dev_ctx, y_grad->dims(), static_cast(0), y_grad); } return; } if (x_grad != nullptr) { auto* dx = dev_ctx.template Alloc(x_grad); for (int i = 0; i < numel; i++) { dx[i] = cond_data[i] ? dout[i] : T{}; } } if (y_grad != nullptr) { auto* dy = dev_ctx.template Alloc(y_grad); for (int i = 0; i < numel; i++) { dy[i] = cond_data[i] ? T{} : dout[i]; } } } } // namespace phi PD_REGISTER_KERNEL(where_grad, CPU, ALL_LAYOUT, phi::WhereGradKernel, float, double, int, int64_t, bool, phi::complex64, phi::complex128) {}