// Copyright (c) 2021 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/fluid/framework/paddle2cinn/cinn_cache_key.h" #include #include #include #include #include #include "paddle/fluid/framework/ir/graph.h" #include "paddle/fluid/framework/lod_tensor.h" #include "paddle/phi/core/ddim.h" namespace paddle { namespace framework { namespace paddle2cinn { using GraphHashStrategy = CinnCacheKey::GraphHashStrategy; CinnCacheKey::CinnCacheKey(GraphHashStrategy graph_hash) : graph_hash_(graph_hash) {} CinnCacheKey::CinnCacheKey( const ir::Graph& graph, const std::map& input_tensors, const std::string& arch_str, GraphHashStrategy graph_hash) : graph_hash_(graph_hash) { this->SetKey(graph, input_tensors, arch_str); } CinnCacheKey::CinnCacheKey(const ir::Graph& graph, const std::map& input_shapes, const std::string& arch_str, GraphHashStrategy graph_hash) : graph_hash_(graph_hash) { this->SetKey(graph, input_shapes, arch_str); } void CinnCacheKey::SetKey( const ir::Graph& graph, const std::map& input_tensors, const std::string& arch_str) { graph_hash_val_ = graph_hash_(graph); for (const auto& name_tensor : input_tensors) { input_shapes_[name_tensor.first] = name_tensor.second->dims(); } arch_str_ = arch_str; } void CinnCacheKey::SetKey(const ir::Graph& graph, const std::map& input_shapes, const std::string& arch_str) { graph_hash_val_ = graph_hash_(graph); input_shapes_ = input_shapes; arch_str_ = arch_str; } bool CinnCacheKey::operator!=(const CinnCacheKey& other) const { return !this->operator==(other); } bool CinnCacheKey::operator==(const CinnCacheKey& other) const { return graph_hash_val_ == other.graph_hash_val_ && input_shapes_ == other.input_shapes_ && arch_str_ == other.arch_str_; } size_t CinnCacheKey::Hash::hash_combine(size_t seed, size_t value) { return seed ^ (value + 0x9e3779b9 + (seed << 6) + (seed >> 2)); } size_t CinnCacheKey::Hash::operator()(const CinnCacheKey& key) const { std::size_t ret = 0; std::hash string_hasher; for (const auto& name_shape : key.input_shapes_) { ret = hash_combine(ret, string_hasher(name_shape.first)); ret = hash_combine(ret, string_hasher(name_shape.second.to_str())); } ret = hash_combine(ret, key.graph_hash_val_); ret = hash_combine(ret, string_hasher(key.arch_str_)); return ret; } size_t CinnCacheKeyByStructure::HashGraph(const ir::Graph& graph) { // sort grad node by name and id. auto compare = [](ir::Node* n1, ir::Node* n2) { return (n1->Name() == n2->Name()) ? (n1->id() < n2->id()) : (n1->Name() < n2->Name()); }; // graph.Nodes() return unordered_set, here using set to avoid the same graph // may return different result std::set node_set(compare), output_set(compare); node_set.insert(graph.Nodes().begin(), graph.Nodes().end()); std::string hash_str; for (ir::Node* n : node_set) { hash_str.append(n->Name()); output_set.clear(); output_set.insert(n->outputs.begin(), n->outputs.end()); for (auto* out : output_set) { hash_str.append(out->Name()); } } VLOG(1) << "The hash graph:\n" << hash_str; size_t hash_val = std::hash()(hash_str); VLOG(4) << "The graph's hash value by graph structure is: " << hash_val; return hash_val; } size_t CinnCacheKeyByAddress::HashGraph(const ir::Graph& graph) { size_t hash_val = reinterpret_cast(&graph); VLOG(4) << "The graph's hash value by graph address is: " << hash_val; return hash_val; } } // namespace paddle2cinn } // namespace framework } // namespace paddle