// Copyright (c) 2024 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/backends/onednn/onednn_reuse.h" #include "paddle/phi/core/kernel_registry.h" namespace phi { template class ShuffleChannelONEDNNHandler : public funcs::OneDNNHandlerNoCachingT { public: ShuffleChannelONEDNNHandler(const DenseTensor* x, const int group, const dnnl::engine engine, phi::Place cpu_place) : funcs::OneDNNHandlerNoCachingT(engine, cpu_place) { static constexpr int channel_axis = 1; this->AcquireForwardPrimitiveDescriptor(dnnl::prop_kind::forward_training, x->mem_desc(), x->mem_desc(), channel_axis, group); } }; template void ShuffleChannelMKLDNNKernel(const Context& dev_ctx, const DenseTensor& x, int group, DenseTensor* out) { const auto& onednn_engine = dev_ctx.GetEngine(); // oneDNN handles group using C/g instead of g const int tmp_group = x.dims()[1] / group; ShuffleChannelONEDNNHandler handler( &x, tmp_group, onednn_engine, dev_ctx.GetPlace()); auto src_memory_p = handler.AcquireSrcMemory(&x); auto dst_memory_p = handler.AcquireDstMemory(out); auto shuffle_p = handler.AcquireForwardPrimitive(); auto& astream = OneDNNContext::tls().get_stream(); shuffle_p->execute( astream, {{DNNL_ARG_SRC, *src_memory_p}, {DNNL_ARG_DST, *dst_memory_p}}); astream.wait(); out->set_mem_desc(dst_memory_p->get_desc()); } } // namespace phi PD_REGISTER_KERNEL(shuffle_channel, OneDNN, ONEDNN, phi::ShuffleChannelMKLDNNKernel, float, phi::bfloat16) {}