// 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/fill_diagonal_grad_kernel.h" #include "paddle/phi/core/kernel_registry.h" #include "paddle/phi/kernels/funcs/common_shape.h" namespace phi { template void FillDiagonalGradKernel(const Context& ctx, const DenseTensor& out_grad, float value UNUSED, int offset, bool wrap, DenseTensor* x_grad) { if (x_grad) { T* data = ctx.template Alloc(x_grad); phi::Copy(ctx, out_grad, ctx.GetPlace(), false, x_grad); auto dx_dims = x_grad->dims(); auto strides = funcs::CalStride(dx_dims); auto size = x_grad->numel(); auto wrapsize = std::min(size, dx_dims[1] * dx_dims[1]); // The wrap mode supported only the dims equels to 2; In wrap mode, the // value will be filled in cycles if (wrap) { wrapsize = size; } for (int64_t i = 0; i < wrapsize; i += strides) { if (i % dx_dims[1] + offset >= 0 && i % dx_dims[1] + offset < dx_dims[1]) { data[i + offset] = T(0); } } } } } // namespace phi PD_REGISTER_KERNEL(fill_diagonal_grad, CPU, ALL_LAYOUT, phi::FillDiagonalGradKernel, float, double, int64_t, int, phi::dtype::float16, bool) {}