// 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 #include #include "paddle/fluid/framework/ir/graph_helper.h" #include "paddle/fluid/framework/ir/graph_pattern_detector.h" #include "paddle/fluid/framework/ir/graph_traits.h" #include "paddle/fluid/framework/ir/graph_viz_pass.h" #include "paddle/fluid/platform/enforce.h" #include "paddle/fluid/string/pretty_log.h" #include "paddle/fluid/string/printf.h" namespace paddle { namespace framework { namespace ir { using string::PrettyLogEndl; using string::PrettyLog; using string::Style; size_t PDPattern::id_ = 0UL; PDNode* PDPattern::NewNode(const std::string& name) { if (!name.empty()) { PADDLE_ENFORCE_EQ(node_map_.count(name), 0, "PDNode's name should be unique, get duplicate [%s]", name); } nodes_.emplace_back(new PDNode(this, name)); auto* cur = nodes_.back().get(); node_map_[name] = cur; return cur; } PDNode* PDPattern::NewNode(PDNode::teller_t&& teller, const std::string& name) { if (!name.empty()) { PADDLE_ENFORCE_EQ(node_map_.count(name), 0, "PDNode's name should be unique, get duplicate [%s]", name); } nodes_.emplace_back(new PDNode(std::move(teller), this, name)); auto* cur = nodes_.back().get(); node_map_[name] = cur; return cur; } PDNode* PDPattern::RetrieveNode(const std::string& id) const { auto it = node_map_.find(id); if (it == node_map_.end()) { return nullptr; } return it->second; } void PDPattern::AddEdge(PDNode* a, PDNode* b) { PADDLE_ENFORCE(a); PADDLE_ENFORCE(b); PADDLE_ENFORCE(a != b, "can't connect to the same nodes."); edges_.emplace_back(a, b); } void GraphPatternDetector::operator()(Graph* graph, GraphPatternDetector::handle_t handler) { if (!MarkPDNodesInGraph(*graph)) { return; } auto subgraphs = DetectPatterns(); UniquePatterns(&subgraphs); RemoveOverlappedMatch(&subgraphs); ValidateByNodeRole(&subgraphs); if (subgraphs.empty()) return; PrettyLogEndl(Style::detail(), "--- detect %d subgraphs", subgraphs.size()); int id = 0; for (auto& g : subgraphs) { VLOG(3) << "optimizing #" << id++ << " subgraph"; handler(g, graph); } } bool GraphPatternDetector::MarkPDNodesInGraph(const ir::Graph& graph) { VLOG(3) << "mark pdnodes in graph"; if (graph.Nodes().empty()) return false; for (auto& node : GraphTraits::DFS(graph)) { for (const auto& pdnode : pattern_.nodes()) { if (pdnode->Tell(&node)) { VLOG(4) << "pdnode " << pdnode->name() << " marked"; pdnodes2nodes_[pdnode.get()].insert(&node); } } } // Check to early stop if some PDNode can't find matched Node. for (auto& pdnode : pattern_.nodes()) { if (!pdnodes2nodes_.count(pdnode.get())) { VLOG(4) << pdnode->name() << " can't find matched Node, early stop"; // return false; } } for (auto& item : pdnodes2nodes_) { for (auto& n : item.second) { GetMarkedNodes(const_cast(&graph)).insert(n); } } VLOG(3) << pdnodes2nodes_.size() << " nodes marked"; return !pdnodes2nodes_.empty(); } // The intermediate Nodes can only link to the nodes inside the pattern, or this // subgraph will be droped. void GraphPatternDetector::ValidateByNodeRole( std::vector* subgraphs) { std::vector result; subgraphs->erase( std::remove_if( subgraphs->begin(), subgraphs->end(), [](const GraphPatternDetector::subgraph_t& subgraph) -> bool { // Collect the inputs and outputs. std::unordered_set ios; for (auto& item : subgraph) { if (!item.first->IsIntermediate()) { ios.insert(item.second); } } for (auto& item : subgraph) { if (item.first->IsIntermediate()) { for (auto* x : item.second->inputs) { if (!ios.count(x)) { return true; } } for (auto* x : item.second->outputs) { if (!ios.count(x)) { return true; } } } } return false; }), subgraphs->end()); } struct HitGroup { std::unordered_map roles; bool Match(Node* node, PDNode* pat) { if (nodes_.count(node)) { if (!roles.count(pat)) return false; return roles[pat] == node; } return !roles.count(pat) || roles.at(pat) == node; } void Register(Node* node, PDNode* pat) { roles[pat] = node; nodes_.insert(node); } private: std::unordered_set nodes_; }; // Tell whether Node a links to b. bool IsNodesLink(Node* a, Node* b) { for (auto* node : a->outputs) { if (b == node) { return true; } } return false; } std::vector GraphPatternDetector::DetectPatterns() { // Init empty subgraphs. std::vector result; std::vector init_groups; std::array, 2> bi_records; // PADDLE_ENFORCE(!pattern_.edges().empty(), "At least one edge is needed"); auto* first_pnode = pattern_.edges().empty() ? pattern().nodes().front().get() : pattern_.edges().front().first; if (!pdnodes2nodes_.count(first_pnode)) return result; for (auto* node : pdnodes2nodes_[first_pnode]) { HitGroup group; group.roles[first_pnode] = node; init_groups.emplace_back(group); } int step = 0; bi_records[0] = std::move(init_groups); // Extend a PDNode to subgraphs by deducing the connection relations defined // in edges of PDNodes. for (const auto& edge : pattern_.edges()) { VLOG(4) << "check " << edge.first->name() << " -> " << edge.second->name(); // TODO(Superjomn) Fix bug here, the groups might be duplicate here. // Each role has two PDNodes, which indicates two roles. // Detect two Nodes that can match these two roles and they are connected. auto& pre_groups = bi_records[step % 2]; auto& cur_groups = bi_records[1 - (step++ % 2)]; cur_groups.clear(); if (pre_groups.empty()) break; // source -> target for (Node* source : pdnodes2nodes_[edge.first]) { for (Node* target : pdnodes2nodes_[edge.second]) { VLOG(8) << "check " << source->id() << " -- " << target->id(); // TODO(Superjomn) add some prune strategies. for (const auto& group : pre_groups) { HitGroup new_group = group; if (IsNodesLink(source, target) && new_group.Match(source, edge.first)) { new_group.Register(source, edge.first); if (new_group.Match(target, edge.second)) { new_group.Register(target, edge.second); cur_groups.push_back(new_group); // TODO(Superjomn) need to unique } } } } } VLOG(3) << "step " << step << " get records: " << cur_groups.size(); for (auto& group : cur_groups) { for (auto& item : group.roles) { VLOG(4) << "node " << item.second->id() << " as " << item.first->name(); } VLOG(4) << "========================================================="; } } for (auto& group : bi_records[step % 2]) { GraphPatternDetector::subgraph_t subgraph; for (auto& role : group.roles) { subgraph.emplace(role.first, role.second); } result.emplace_back(subgraph); } return result; } void GraphPatternDetector::UniquePatterns( std::vector* subgraphs) { if (subgraphs->empty()) return; std::vector result; std::unordered_set set; for (auto& g : *subgraphs) { size_t key = 0; for (auto& item : g) { key ^= std::hash{}(item.first); key ^= std::hash{}(item.second); } if (!set.count(key)) { result.emplace_back(g); set.insert(key); } } *subgraphs = result; } void GraphPatternDetector::RemoveOverlappedMatch( std::vector* subgraphs) { std::vector result; std::unordered_set node_set; for (const auto& subgraph : *subgraphs) { bool valid = true; for (auto& item : subgraph) { if (item.first->IsIntermediate() && node_set.count(item.second)) { valid = false; break; } } if (valid) { for (auto& item : subgraph) { node_set.insert(item.second); } result.push_back(subgraph); } } *subgraphs = result; } std::string PDPattern::DotString() const { using inference::analysis::Dot; Dot dot; int id = 0; // Create Nodes std::unordered_map node2dot; for (const auto& node : nodes()) { std::string node_id = "Node" + std::to_string(id++); dot.AddNode(node_id, {}, node->name()); node2dot[node.get()] = node_id; } // Create Edges for (const auto& edge : edges()) { if (!node2dot.count(edge.first) || !node2dot.count(edge.second)) { LOG(ERROR) << "no node " << edge.first << " " << edge.second; continue; } auto& src = node2dot.at(edge.first); auto& trg = node2dot.at(edge.second); dot.AddEdge(src, trg, {}); } return dot.Build(); } PDNode& PDNode::LinksTo(const std::vector& others) { // extend outlinks. for (PDNode* x : others) { pattern_->AddEdge(this, x); } return *this; } PDNode& PDNode::LinksFrom(const std::vector& others) { // extend outlinks. for (PDNode* x : others) { pattern_->AddEdge(x, this); } return *this; } PDNode* PDNode::assert_is_op() { asserts_.emplace_back([](Node* x) { return x && x->IsOp(); }); return this; } PDNode* PDNode::assert_is_op(const std::string& op_type) { asserts_.emplace_back([op_type](Node* x) { return x && x->IsOp() && x->Op()->Type() == op_type; }); return this; } PDNode* PDNode::assert_is_var() { asserts_.emplace_back([](Node* x) { return x && x->IsVar(); }); return this; } PDNode* PDNode::assert_var_not_persistable() { assert_is_var(); asserts_.emplace_back([](Node* x) { return !x->Var()->Persistable(); }); return this; } PDNode* PDNode::assert_is_persistable_var() { assert_is_var(); asserts_.emplace_back([=](Node* x) { return x->Var()->Persistable(); }); return this; } PDNode* PDNode::assert_is_op_nth_input(const std::string& op_type, const std::string& argument, int nth) { assert_is_var(); assert_is_op_input(op_type); asserts_.emplace_back([=](Node* x) { for (auto* op : x->outputs) { if (op->IsOp() && op->Op()->Type() == op_type && IsNthInput(x, op, argument, nth)) return true; } return false; }); return this; } PDNode* PDNode::assert_is_op_nth_output(const std::string& op_type, const std::string& argument, int nth) { assert_is_var(); asserts_.emplace_back([=](Node* x) { for (auto* op : x->inputs) { if (op->IsOp() && op->Op()->Type() == op_type && IsNthOutput(x, op, argument, nth)) return true; } return false; }); return this; } PDNode* PDNode::assert_is_only_input_of_op(const std::string& op_type) { assert_is_var(); asserts_.emplace_back([=](Node* x) { for (auto* op : x->outputs) { if (op && op->IsOp() && op->Op() && op->Op()->Type() == op_type && op->inputs.size() == 1) { return true; } } return false; }); return this; } PDNode* PDNode::assert_is_only_output_of_op(const std::string& op_type) { assert_is_var(); asserts_.emplace_back([=](Node* x) { for (auto* op : x->inputs) { if (op && op->IsOp() && op->Op() && op->Op()->Type() == op_type && op->outputs.size() == 1) { return true; } } return false; }); return this; } PDNode* PDNode::assert_is_op_output(const std::string& op_type) { assert_is_var(); asserts_.emplace_back([=](Node* x) { for (auto* op : x->inputs) { if (op && op->IsOp() && op->Op() && op->Op()->Type() == op_type) { return true; } } return false; }); return this; } PDNode* PDNode::assert_is_op_output(const std::string& op_type, const std::string& argument) { assert_is_var(); assert_is_op_nth_output(op_type, argument, 0); return this; } PDNode* PDNode::assert_is_op_input(const std::string& op_type) { assert_is_var(); asserts_.emplace_back([=](Node* x) { for (auto* op : x->outputs) { if (op && op->IsOp() && op->Op() && op->Op()->Type() == op_type) { return true; } } return false; }); return this; } PDNode* PDNode::assert_is_op_input(const std::string& op_type, const std::string& argument) { assert_is_var(); assert_is_op_nth_input(op_type, argument, 0); return this; } PDNode* PDNode::assert_op_has_n_inputs(const std::string& op_type, size_t n) { assert_is_op(op_type); asserts_.emplace_back([=](Node* x) { return x->inputs.size() == n; }); return this; } PDNode* PDNode::assert_op_has_n_outputs(const std::string& op_type, size_t n) { assert_is_op(op_type); asserts_.emplace_back([=](Node* x) { return x->outputs.size() == n; }); return this; } PDNode* PDNode::assert_more(PDNode::teller_t&& teller) { asserts_.emplace_back(std::move(teller)); return this; } bool VarLinksToOp(Node* node, const std::string& op_type) { for (auto* out : node->outputs) { if (out->IsOp() && out->Op()->Type() == op_type) { return true; } } return false; } bool IsNthInput(Node* var, Node* op, const std::string& argument, size_t nth) { PADDLE_ENFORCE(var->IsVar()); PADDLE_ENFORCE(op->IsOp()); if (op->Op()->Input(argument).size() <= nth) return false; return var->Name() == op->Op()->Input(argument)[nth]; } bool IsNthOutput(Node* var, Node* op, const std::string& argument, size_t nth) { PADDLE_ENFORCE(var->IsVar()); PADDLE_ENFORCE(op->IsOp()); if (op->Op()->Output(argument).size() <= nth) return false; return var->Name() == op->Op()->Output(argument)[nth]; } void GraphSafeRemoveNodes(Graph* graph, const std::unordered_set& nodes) { for (auto* node : nodes) { graph->RemoveNode(const_cast(node)); } for (auto* node : graph->Nodes()) { for (auto it = node->inputs.begin(); it != node->inputs.end();) { if (nodes.count(*it)) { it = const_cast(node)->inputs.erase(it); } else { it++; } } for (auto it = node->outputs.begin(); it != node->outputs.end();) { if (nodes.count(*it)) { it = const_cast(node)->outputs.erase(it); } else { it++; } } } } bool VarLinksFromOp(Node* node, const std::string& op_type) { for (auto* out : node->inputs) { if (out->IsOp() && out->Op()->Type() == op_type) { return true; } } return false; } PDNode* patterns::ConvReLU::operator()( paddle::framework::ir::PDNode* conv_input) { // Create Operators conv_input->assert_is_op_input("conv2d", "Input"); auto* conv_op = pattern->NewNode(conv_repr())->assert_is_op("conv2d"); auto* relu_op = pattern->NewNode(relu_repr())->assert_is_op("relu"); // Create variables // Filter auto* conv_weight_var = pattern->NewNode(conv_weight_repr()) ->AsInput() ->assert_is_persistable_var() ->assert_is_op_input("conv2d", "Filter"); // Bias auto* conv_bias_var = pattern->NewNode(conv_bias_repr()) ->AsInput() ->assert_is_persistable_var() ->assert_is_op_input("conv2d", "Bias"); // intermediate variable, will be removed in the IR after fuse. auto* conv_out_var = pattern->NewNode(conv_out_repr()) ->AsIntermediate() ->assert_is_only_output_of_op("conv2d") ->assert_is_op_input("relu"); // output auto* relu_out_var = pattern->NewNode(relu_out_repr()) ->AsOutput() ->assert_is_op_output("relu"); conv_op->LinksFrom({conv_input, conv_weight_var, conv_bias_var}) .LinksTo({conv_out_var}); relu_op->LinksFrom({conv_out_var}).LinksTo({relu_out_var}); return relu_out_var; } PDNode* patterns::FC::operator()(paddle::framework::ir::PDNode* x, bool with_bias) { // Create shared nodes. x->assert_is_op_input("mul", "X"); auto* mul = pattern->NewNode(mul_repr())->assert_is_op("mul"); auto* mul_w_var = pattern->NewNode(w_repr()) ->AsInput() ->assert_is_persistable_var() ->assert_is_op_input("mul", "Y"); auto* mul_out_var = pattern->NewNode(mul_out_repr())->assert_is_op_output("mul"); if (!with_bias) { // not with bias // Add links. mul->LinksFrom({x, mul_w_var}).LinksTo({mul_out_var}); return mul_out_var; } else { // with bias mul_out_var->AsIntermediate()->assert_is_op_input("elementwise_add"); // Create operators. auto* elementwise_add = pattern->NewNode(elementwise_add_repr()) ->assert_is_op("elementwise_add"); // Create variables. auto* bias = pattern->NewNode(bias_repr()) ->assert_is_op_input("elementwise_add") ->AsInput(); auto* fc_out = pattern->NewNode(Out_repr()) ->AsOutput() ->assert_is_op_output("elementwise_add"); mul->LinksFrom({mul_w_var, x}).LinksTo({mul_out_var}); elementwise_add->LinksFrom({mul_out_var, bias}).LinksTo({fc_out}); return fc_out; } } PDNode* patterns::LSTM::operator()(PDNode* x) { x->assert_is_op_input("lstm", "Input"); auto* lstm_op = pattern->NewNode(lstm_repr())->assert_is_op("lstm"); #define NEW_NODE(arg__, io__) \ auto* arg__ = \ pattern->NewNode(arg__##_repr())->assert_is_op_##io__("lstm", #arg__); // Currently, the H0 and C0 are optional // TODO(Superjomn) upgrade the fuse framework to support optional. // NEW_NODE(H0, input); // NEW_NODE(C0, input); NEW_NODE(Weight, input); NEW_NODE(Bias, input); NEW_NODE(Hidden, output); NEW_NODE(Cell, output); NEW_NODE(BatchGate, output); NEW_NODE(BatchCellPreAct, output); #undef NEW_NODE lstm_op->LinksFrom({x, Weight, Bias}); lstm_op->LinksTo({Hidden, Cell, BatchGate, BatchCellPreAct}); return Hidden; } PDNode* patterns::GRU::operator()(PDNode* x) { x->assert_is_op_input("gru", "Input"); auto* gru_op = pattern->NewNode(gru_repr())->assert_is_op("gru"); #define NEW_NODE(arg__, io__) \ auto* arg__ = \ pattern->NewNode(arg__##_repr())->assert_is_op_##io__("gru", #arg__); NEW_NODE(Weight, input); // TODO(Superjomn): upgrade the fuse framework to support optional. // H0 and bias are optional NEW_NODE(Bias, input); // also optional // NEW_NODE(H0, input); NEW_NODE(Hidden, output); // below are intermediate NEW_NODE(BatchGate, output); NEW_NODE(BatchResetHiddenPrev, output); NEW_NODE(BatchHidden, output); #undef NEW_NODE BatchGate->AsIntermediate(); BatchResetHiddenPrev->AsIntermediate(); BatchHidden->AsIntermediate(); gru_op->LinksFrom({x, Weight, Bias}); gru_op->LinksTo({Hidden, BatchGate, BatchResetHiddenPrev, BatchHidden}); return Hidden; } } // namespace ir } // namespace framework } // namespace paddle