/* Copyright (c) 2018 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 #include "paddle/fluid/operators/concat_op.h" #include "paddle/fluid/platform/mkldnn_helper.h" #include "paddle/fluid/platform/mkldnn_reuse.h" namespace paddle { namespace operators { using framework::DataLayout; using framework::Tensor; using mkldnn::memory; using mkldnn::primitive; using mkldnn::concat; using mkldnn::stream; using platform::to_void_cast; static void EnforceLayouts(const std::vector inputs) { for (auto* input : inputs) { const bool is_layout_correct = input->layout() == DataLayout::kMKLDNN; const bool is_format_defined = input->format() != memory::format::format_undef; PADDLE_ENFORCE(is_layout_correct && is_format_defined, "Wrong layout/format set for Input tensor"); } } static memory::primitive_desc CreateMemPrimDesc(const Tensor& input, const mkldnn::engine& engine, const memory::data_type& dt) { const auto dims = paddle::framework::vectorize2int(input.dims()); const auto format = input.format(); auto description = memory::desc(dims, dt, format); auto mem_prim_desc = memory::primitive_desc(description, engine); return mem_prim_desc; } static mkldnn::memory::format GetDstMemFormat( const concat::primitive_desc& concat_pd) { return (memory::format)concat_pd.dst_primitive_desc().desc().data.format; } static platform::CPUPlace GetCpuPlace( const paddle::framework::ExecutionContext& ctx) { auto place = ctx.GetPlace(); PADDLE_ENFORCE(paddle::platform::is_cpu_place(place), "It must use CPUPlace."); return boost::get(place); } static const mkldnn::engine& GetMKLDNNEngine( const paddle::framework::ExecutionContext& ctx) { auto& dev_ctx = ctx.template device_context(); return dev_ctx.GetEngine(); } std::string CreateKey(const paddle::framework::ExecutionContext& ctx, const std::vector multi_input, const int64_t& concat_axis, const memory::data_type& dt) { std::string key; key.reserve(platform::MKLDNNHandler::MaxKeyLength); for (size_t i = 0; i < multi_input.size(); i++) { platform::MKLDNNHandler::AppendKeyDims( &key, paddle::framework::vectorize2int(multi_input[i]->dims())); } platform::MKLDNNHandler::AppendKey(&key, std::to_string(concat_axis)); platform::MKLDNNHandler::AppendKey(&key, ctx.op().Output("Out")); platform::MKLDNNHandler::AppendKey(&key, std::to_string(dt)); return key; } template class ConcatPrimitiveFactory { public: concat::primitive_desc CreateConcatPrimDescriptor( const std::vector multi_input, Tensor* output, int concat_axis, const mkldnn::engine& mkldnn_engine, const memory::data_type& dt = memory::data_type::f32) { CreateSourcesDescriptors(multi_input, mkldnn_engine, dt); auto dst_desc = CreateDstMemDescriptor(output, dt); return concat::primitive_desc(dst_desc, concat_axis, srcs_pd); } concat CreateConcatPrimitive(const concat::primitive_desc& concat_pd, Tensor* output, platform::CPUPlace place) { CreateSourcePrimitiveAts(); dst_mem = CreateDstMemory(concat_pd, output, place); return concat(concat_pd, inputs, dst_mem.get()); } void SetSrcDataHandleByIndex(const std::vector& srcs, const size_t& i, void* handler) { srcs[i].set_data_handle(handler); } void SetDstDataHandle(const memory& dst_mem, void* handler) { dst_mem.set_data_handle(handler); } std::vector GetSrcs() { return srcs; } memory GetDst() { return dst_mem.get(); } private: memory::desc CreateDstMemDescriptor(Tensor* output, const memory::data_type& dt) { auto dst_dims = paddle::framework::vectorize2int(output->dims()); return memory::desc(dst_dims, dt, memory::format::any); } mkldnn::memory CreateDstMemory(const concat::primitive_desc& concat_pd, Tensor* output, const platform::CPUPlace& place) { return memory(concat_pd.dst_primitive_desc(), output->mutable_data(place)); } void CreateSourcesDescriptors(const std::vector multi_input, const mkldnn::engine& mkldnn_engine, const memory::data_type& dt) { for (size_t i = 0; i < multi_input.size(); i++) { auto mem_prim_desc = CreateMemPrimDesc(*multi_input[i], mkldnn_engine, dt); srcs_pd.push_back(mem_prim_desc); srcs.push_back( memory(mem_prim_desc, to_void_cast(multi_input[i]->data()))); } } void CreateSourcePrimitiveAts() { inputs.reserve(srcs.size()); for (size_t i = 0; i < srcs.size(); i++) { inputs.push_back(srcs[i]); } } private: std::vector srcs_pd; std::vector srcs; std::vector inputs; boost::optional dst_mem; // TODO(mgallus): change to std::optional }; // upon introduction of C++17 to paddle template class ConcatMKLDNNOpKernel : public paddle::framework::OpKernel { public: void Compute(const paddle::framework::ExecutionContext& ctx) const override { auto multi_input = ctx.MultiInput("X"); EnforceLayouts(multi_input); Tensor* output = ctx.Output("Out"); int64_t concat_axis = static_cast(ctx.Attr("axis")); auto& dev_ctx = ctx.template device_context(); auto place = GetCpuPlace(ctx); memory::data_type dt = paddle::framework::ToMKLDNNDataType(multi_input[0]->type()); ConcatPrimitiveFactory prim_creator; std::string key = CreateKey(ctx, multi_input, concat_axis, dt); const std::string key_prim = key + "@concat_p"; const std::string key_concat_pd = key + "@concat_pd"; const std::string key_srcs = key + "@concat_srcs"; const std::string key_dst = key + "@concat_dst"; std::shared_ptr concat_pd; std::shared_ptr> srcs; std::shared_ptr dst_mem; auto concat_p = std::static_pointer_cast(dev_ctx.GetBlob(key_prim)); if (concat_p == nullptr) { const auto& mkldnn_engine = dev_ctx.GetEngine(); concat_pd = std::make_shared( prim_creator.CreateConcatPrimDescriptor(multi_input, output, static_cast(concat_axis), mkldnn_engine, dt)); concat_p = std::make_shared( prim_creator.CreateConcatPrimitive(*concat_pd, output, place)); srcs = std::make_shared>(prim_creator.GetSrcs()); dst_mem = std::make_shared(prim_creator.GetDst()); dev_ctx.SetBlob(key_prim, concat_p); dev_ctx.SetBlob(key_concat_pd, concat_pd); dev_ctx.SetBlob(key_srcs, srcs); dev_ctx.SetBlob(key_dst, dst_mem); } else { srcs = std::static_pointer_cast>( dev_ctx.GetBlob(key_srcs)); dst_mem = std::static_pointer_cast(dev_ctx.GetBlob(key_dst)); concat_pd = std::static_pointer_cast( dev_ctx.GetBlob(key_concat_pd)); for (size_t i = 0; i < multi_input.size(); i++) { prim_creator.SetSrcDataHandleByIndex( *srcs, i, to_void_cast(multi_input[i]->data())); } prim_creator.SetDstDataHandle(*dst_mem, output->mutable_data(place)); } stream(stream::kind::eager).submit({*concat_p}).wait(); output->set_mkldnn_prim_desc(concat_pd->dst_primitive_desc()); } }; } // namespace operators } // namespace paddle namespace ops = paddle::operators; REGISTER_OP_KERNEL(concat, MKLDNN, ::paddle::platform::CPUPlace, ops::ConcatMKLDNNOpKernel, ops::ConcatMKLDNNOpKernel, ops::ConcatMKLDNNOpKernel);