/* Copyright (c) 2017 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. */ #pragma once #include #include #include #include #include #include #include "paddle/fluid/framework/operator.h" #include "paddle/fluid/platform/place.h" namespace paddle { #ifdef PADDLE_WITH_MKLDNN using MKLDNNMemoryFormat = mkldnn::memory::format; #endif namespace platform { using MKLDNNStream = mkldnn::stream; using MKLDNNEngine = mkldnn::engine; using MKLDNNMemory = mkldnn::memory; using MKLDNNMemoryDescriptor = mkldnn::memory::desc; using MKLDNNPrimitive = mkldnn::primitive; using MKLDNNPrimitiveDesc = mkldnn::handle; typedef std::unique_ptr MKLDNNStreamPtr; typedef std::unique_ptr MKLDNNEnginePtr; typedef std::unique_ptr MKLDNNMemoryPtr; typedef std::unique_ptr MKLDNNPrimitivePtr; typedef std::unique_ptr MKLDNNPrimitiveDescPtr; template void* to_void_cast(const Type* t) { return static_cast(const_cast(t)); } template void* to_void_reinterpret_cast(const Type* t) { return reinterpret_cast(const_cast(t)); } template using tf_desc = typename Type::desc; template using tf_pd = typename Type::primitive_desc; template std::shared_ptr> MKLDNNFwdPrimitiveDesc(const Engine& e, Args&&... args) { auto desc = tf_desc(mkldnn::prop_kind::forward, (args)...); auto pd = new tf_pd(desc, e); return std::shared_ptr>(pd); } template tf_pd MKLDNNBwdPrimitiveDesc(const Engine& e, const Primitive& p, Args&&... args) { auto desc = tf_desc(args...); return tf_pd(desc, e, p); } inline mkldnn::memory::desc MKLDNNMemDesc(const std::vector& dims, mkldnn::memory::data_type data_type, MKLDNNMemoryFormat format) { mkldnn::memory::dims tz = dims; return mkldnn::memory::desc({tz}, data_type, format); } inline bool CanMKLDNNBeUsed(const framework::ExecutionContext& ctx) { bool use_mkldnn = ctx.Attr("use_mkldnn"); return use_mkldnn && platform::is_cpu_place(ctx.GetPlace()); } template mkldnn::memory::data_type MKLDNNGetDataType() { return mkldnn::memory::data_type::data_undef; } template <> inline mkldnn::memory::data_type MKLDNNGetDataType() { return mkldnn::memory::data_type::f32; } template <> inline mkldnn::memory::data_type MKLDNNGetDataType() { return mkldnn::memory::data_type::s32; } template <> inline mkldnn::memory::data_type MKLDNNGetDataType() { return mkldnn::memory::data_type::s8; } template <> inline mkldnn::memory::data_type MKLDNNGetDataType() { return mkldnn::memory::data_type::u8; } inline void Reorder(const mkldnn::memory& src, const mkldnn::memory& dst) { auto reorder_prim = mkldnn::reorder(src, dst); std::vector pipeline; pipeline.push_back(reorder_prim); mkldnn::stream(mkldnn::stream::kind::eager).submit(pipeline).wait(); } inline MKLDNNMemoryFormat GetMKLDNNFormat(const mkldnn::memory memory) { return static_cast( memory.get_primitive_desc().desc().data.format); } inline MKLDNNMemoryFormat GetMKLDNNFormat( const mkldnn::sum::primitive_desc& memory) { return static_cast( memory.dst_primitive_desc().desc().data.format); } inline MKLDNNMemoryFormat MKLDNNFormatForSize(size_t dims_size, MKLDNNMemoryFormat data_format) { if (dims_size == 1) { return MKLDNNMemoryFormat::x; } else if (dims_size == 2) { return MKLDNNMemoryFormat::nc; } else if (dims_size == 3) { if (data_format == MKLDNNMemoryFormat::nchw) { return MKLDNNMemoryFormat::ncw; } else if (data_format == MKLDNNMemoryFormat::nhwc) { return MKLDNNMemoryFormat::nwc; } } else if (dims_size == 4) { if (data_format == MKLDNNMemoryFormat::goihw) { return MKLDNNMemoryFormat::oihw; } } else if (dims_size == 5) { if (data_format == MKLDNNMemoryFormat::goidhw) { return MKLDNNMemoryFormat::oidhw; } if (data_format == MKLDNNMemoryFormat::nchw) { return MKLDNNMemoryFormat::ncdhw; } else if (data_format == MKLDNNMemoryFormat::nhwc) { return MKLDNNMemoryFormat::ndhwc; } } return data_format; } inline MKLDNNMemoryFormat data_format_to_memory_format( const std::string& data_format) { switch (framework::StringToDataLayout(data_format)) { case framework::DataLayout::kNHWC: return MKLDNNMemoryFormat::nhwc; case framework::DataLayout::kNCHW: return MKLDNNMemoryFormat::nchw; default: return MKLDNNMemoryFormat::any; } } inline MKLDNNMemoryFormat StringToMKLDNNFormat(std::string* format) { std::transform(format->begin(), format->end(), format->begin(), ::tolower); if (!format->compare("nchw")) { return MKLDNNMemoryFormat::nchw; } else if (!format->compare("nchw16c")) { return MKLDNNMemoryFormat::nChw16c; } else if (!format->compare("nchw8c")) { return MKLDNNMemoryFormat::nChw8c; } else if (!format->compare("nhwc")) { return MKLDNNMemoryFormat::nhwc; } else { return MKLDNNMemoryFormat::any; } } inline std::string ThreadIDasStr(void) { return std::to_string( std::hash()(std::this_thread::get_id())); } template inline void AppendKey(std::string* key, const T& num) { key->append(std::to_string(num)); } inline void AppendKey(std::string* key, const std::string& str) { key->append(str); } inline void AppendKey(std::string* key, const char* str) { key->append(str); } inline void AppendKey(std::string* key, const std::vector& dims) { for (size_t i = 0; i < dims.size(); i++) { AppendKey(key, std::to_string(dims[i])); } } template inline std::string CreateKey(ArgTypes&&... args) { std::string key; key.reserve(64); using expand_type = int[]; expand_type{0, (AppendKey(&key, std::forward(args)), 0)...}; return key; } } // namespace platform } // namespace paddle