// 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/squeeze_grad_kernel.h" #include "paddle/phi/backends/all_context.h" #include "paddle/phi/core/kernel_registry.h" #include "paddle/phi/core/tensor_utils.h" namespace phi { template void SqueezeGradKernel(const Context& dev_ctx, const DenseTensor& x, const DenseTensor& dout, const IntArray& axes UNUSED, DenseTensor* dx) { // NOTE: [Why not to use x.dims() ?] // Because inplace strategy is different between old IR and PIR, // we need fix it into x.dims() after cleaning old IR system. auto x_dims = dx->dims(); dev_ctx.template Alloc(dx); phi::Copy(dev_ctx, dout, dev_ctx.GetPlace(), false, dx); dx->Resize(x_dims); } } // namespace phi PD_REGISTER_KERNEL(squeeze_grad, CPU, ALL_LAYOUT, phi::SqueezeGradKernel, float, double, bool, int, uint8_t, int8_t, int16_t, int64_t, phi::float16, phi::bfloat16, phi::complex64, phi::complex128) {} #if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP) PD_REGISTER_KERNEL(squeeze_grad, GPU, ALL_LAYOUT, phi::SqueezeGradKernel, float, double, phi::float16, phi::bfloat16, bool, int, uint8_t, int8_t, int16_t, int64_t, phi::complex64, phi::complex128) {} #endif #ifdef PADDLE_WITH_XPU PD_REGISTER_KERNEL(squeeze_grad, XPU, ALL_LAYOUT, phi::SqueezeGradKernel, float, double, phi::float16, phi::bfloat16, bool, int, uint8_t, int8_t, int64_t) {} #endif