/* 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. */ #pragma once #include #include #include #include "paddle/fluid/operators/jit/gen_base.h" #include "paddle/fluid/operators/jit/kernel_base.h" #include "paddle/fluid/operators/jit/kernel_key.h" #include "paddle/fluid/operators/jit/kernel_pool.h" #include "paddle/fluid/platform/place.h" namespace paddle { namespace operators { namespace jit { template inline typename std::enable_if< std::is_same::value && std::is_same::value, typename KernelTuples::func_type>::type GetJitCode(const typename KernelTuples::attr_type& attr) { using Func = typename KernelTuples::func_type; using Attr = typename KernelTuples::attr_type; size_t key = JitCodeKey(attr); auto& codes = JitCodePool().Instance(); if (codes.Has(key)) { return codes.AllKernels().at(key)->template getCode(); } // creator is not related with attr, so can use KernelKey as key KernelKey kkey(KT, PlaceType()); // pool: (KernelKey(type, place), vector) auto& creator_map = JitCodeCreatorPool().Instance().AllCreators(); auto iter = creator_map.find(kkey); if (iter != creator_map.end()) { auto& creators = iter->second; for (auto& cur : creators) { auto i = dynamic_cast*>(cur.get()); if (i && i->UseMe(attr)) { auto p = i->CreateJitCode(attr); if (p) { auto f = p->template getCode(); codes.Insert(key, std::move(p)); return f; } } } } return nullptr; } template inline typename std::enable_if< !std::is_same::value || !std::is_same::value, typename KernelTuples::func_type>::type GetJitCode(const typename KernelTuples::attr_type& attr) { return nullptr; } // Refer code do not related with attr, which is just for cast // Refer is always on CPUPlace template inline typename KernelTuples::func_type GetRefer() { auto& ref_pool = ReferKernelPool().Instance().AllKernels(); KernelKey kkey(KT, platform::CPUPlace()); auto ref_iter = ref_pool.find(kkey); PADDLE_ENFORCE(ref_iter != ref_pool.end(), "Every Kernel should have reference function."); auto& ref_impls = ref_iter->second; for (auto& impl : ref_impls) { auto i = dynamic_cast*>(impl.get()); if (i) { return i->GetFunc(); } } return nullptr; } template typename KernelTuples::func_type Get( const typename KernelTuples::attr_type& attr) { auto jitfunc = GetJitCode(attr); if (jitfunc) { return jitfunc; } // pool: (KernelKey(type, place), vector) KernelKey kkey(KT, PlaceType()); auto& pool = KernelPool().Instance().AllKernels(); auto iter = pool.find(kkey); if (iter != pool.end()) { auto& impls = iter->second; for (auto& impl : impls) { auto i = dynamic_cast*>(impl.get()); if (i && i->UseMe(attr)) { return i->GetFunc(); } } } // The last implementation should be reference function on CPUPlace. return GetRefer(); } template class KernelFuncs { public: KernelFuncs() = default; static KernelFuncs& Cache() { static thread_local KernelFuncs g_func_cache; return g_func_cache; } bool Has(int key) const { return funcs_.find(key) != funcs_.end(); } void Insert(int key, typename KernelTuples::func_type func) { funcs_.emplace(key, func); } typename KernelTuples::func_type At(int key) { if (Has(key)) { return funcs_.at(key); } auto func = Get(key); Insert(key, func); return func; } private: std::unordered_map funcs_; DISABLE_COPY_AND_ASSIGN(KernelFuncs); }; const char* to_string(KernelType kt); const char* to_string(SeqPoolType kt); KernelType to_kerneltype(const std::string& act); inline std::ostream& operator<<(std::ostream& os, const lstm_attr_t& attr) { os << "dim_size[" << attr.d << "],act_gate[" << to_string(attr.act_gate) << "],act_cand[" << to_string(attr.act_cand) << "],act_cell[" << to_string(attr.act_cell) << "],use_peephole[" << (attr.use_peephole ? "True" : "False") << "]"; return os; } inline std::ostream& operator<<(std::ostream& os, const gru_attr_t& attr) { os << "dim_size[" << attr.d << "],act_gate[" << to_string(attr.act_gate) << "],act_cand[" << to_string(attr.act_cand) << "]"; return os; } inline std::ostream& operator<<(std::ostream& os, const seq_pool_attr_t& attr) { os << "height_size[" << attr.h << "],width_size[" << attr.w << "],pool_type[" << to_string(attr.type) << "]"; return os; } inline std::ostream& operator<<(std::ostream& os, const emb_seq_pool_attr_t& attr) { os << "table_height[" << attr.table_height << "],table_width[" << attr.table_width << "],index_height[" << attr.index_height << "],index_width[" << attr.index_width << "],output_width[" << attr.out_width << "],pool_type[" << to_string(attr.pool_type) << "]"; return os; } inline std::ostream& operator<<(std::ostream& os, const matmul_attr_t& attr) { os << "M[" << attr.m << "],N[" << attr.n << "],K[" << attr.k << "]"; return os; } // expose the method to pack matmul weight template void pack_weights(const T* src, T* dst, int n, int k); } // namespace jit } // namespace operators } // namespace paddle