// 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/scale_kernel.h" #include "paddle/phi/backends/onednn/onednn_reuse.h" #include "paddle/phi/core/kernel_registry.h" namespace phi { template void ScaleKernel(const Context& dev_ctx, const DenseTensor& x, const Scalar& scale, float bias, bool bias_after_scale, DenseTensor* out) { float alpha = scale.to(); float beta = bias_after_scale ? bias : bias * alpha; funcs::ActivationOneDNNHandler handler(dnnl::algorithm::eltwise_linear, alpha, beta, dev_ctx.GetEngine(), dev_ctx.GetPlace(), &x); auto src_memory_p = handler.AcquireSrcMemory(&x); auto activation_p = handler.AcquireForwardPrimitive(); bool is_inplaced = x.IsSharedBufferWith(*out); std::shared_ptr dst_memory_p = nullptr; if (is_inplaced) { dst_memory_p = src_memory_p; dev_ctx.template Alloc(out); } else { dst_memory_p = handler.AcquireDstMemory(out); } auto& astream = OneDNNContext::tls().get_stream(); activation_p->execute( astream, {{DNNL_ARG_FROM, *src_memory_p}, {DNNL_ARG_TO, *dst_memory_p}}); astream.wait(); out->set_mem_desc(dst_memory_p->get_desc()); } } // namespace phi PD_REGISTER_KERNEL( scale, OneDNN, ALL_LAYOUT, phi::ScaleKernel, float, phi::dtype::bfloat16) {}