graph_pattern_detector.cc

// 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 <array>
#include <string>
#include <vector>

#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"

namespace paddle {
namespace framework {
namespace ir {

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;
  LOG(INFO) << "detect " << subgraphs.size() << " subgraph matches the pattern";
  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*>(&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<GraphPatternDetector::subgraph_t>* subgraphs) {
  std::vector<GraphPatternDetector::subgraph_t> result;

  subgraphs->erase(
      std::remove_if(
          subgraphs->begin(), subgraphs->end(),
          [](const GraphPatternDetector::subgraph_t& subgraph) -> bool {
            // Collect the inputs and outputs.
            std::unordered_set<Node*> 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<PDNode*, Node*> 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<Node*> 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::subgraph_t>
GraphPatternDetector::DetectPatterns() {
  // Init empty subgraphs.
  std::vector<GraphPatternDetector::subgraph_t> result;
  std::vector<HitGroup> init_groups;
  std::array<std::vector<HitGroup>, 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<GraphPatternDetector::subgraph_t>* subgraphs) {
  if (subgraphs->empty()) return;
  std::vector<GraphPatternDetector::subgraph_t> result;

  std::unordered_set<size_t> set;
  for (auto& g : *subgraphs) {
    size_t key = 0;
    for (auto& item : g) {
      key ^= std::hash<void*>{}(item.first);
      key ^= std::hash<void*>{}(item.second);
    }
    if (!set.count(key)) {
      result.emplace_back(g);
      set.insert(key);
    }
  }
  *subgraphs = result;
}

void GraphPatternDetector::RemoveOverlappedMatch(
    std::vector<subgraph_t>* subgraphs) {
  std::vector<subgraph_t> result;
  std::unordered_set<Node*> 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<PDNode*, std::string> 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<PDNode*>& others) {
  // extend outlinks.
  for (PDNode* x : others) {
    pattern_->AddEdge(this, x);
  }
  return *this;
}

PDNode& PDNode::LinksFrom(const std::vector<PDNode*>& 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<const Node*>& nodes) {
  for (auto* node : nodes) {
    graph->RemoveNode(const_cast<Node*>(node));
  }

  for (auto* node : graph->Nodes()) {
    for (auto it = node->inputs.begin(); it != node->inputs.end();) {
      if (nodes.count(*it)) {
        it = const_cast<Node*>(node)->inputs.erase(it);
      } else {
        it++;
      }
    }
    for (auto it = node->outputs.begin(); it != node->outputs.end();) {
      if (nodes.count(*it)) {
        it = const_cast<Node*>(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::FC(PDPattern* pattern, const std::string& name_scope,
                     PDNode* x, bool with_bias) {
  // mul op
  auto* mul_op = pattern->NewNode(name_scope, "mul")->assert_is_op("mul");
  auto* mul_weight_var = pattern->NewNode(name_scope, "w")
                             ->AsInput()
                             ->assert_is_persistable_var()
                             ->assert_is_op_input("mul", "Y");

  PDNode* fc_out{nullptr};
  if (with_bias) {
    PDNode* elementwise_add_op{nullptr};
    PDNode *mul_out_var{nullptr}, *bias{nullptr};
    elementwise_add_op = pattern->NewNode(name_scope, "elementwise_add")
                             ->assert_is_op("elementwise_add");
    // intermediate variable, will be removed in the IR after fuse.
    mul_out_var = pattern->NewNode(name_scope, "mul_out")
                      ->AsIntermediate()
                      ->assert_is_only_output_of_op("mul")
                      ->assert_is_op_input("elementwise_add", "X");
    // bias
    bias = pattern->NewNode(name_scope, "fc_bias")
               ->AsInput()
               ->assert_is_persistable_var()
               ->assert_is_op_input("elementwise_add", "Y");
    // output
    fc_out = pattern->NewNode(name_scope, "fc_out")
                 ->AsOutput()
                 ->assert_is_op_output("elementwise_add", "Out");
    mul_op->LinksFrom({x, mul_weight_var}).LinksTo({mul_out_var});
    elementwise_add_op->LinksFrom({mul_out_var, bias}).LinksTo({fc_out});
  } else {
    fc_out = pattern->NewNode(name_scope, "fc_out")
                 ->AsOutput()
                 ->assert_is_op_output("mul", "Out");
    mul_op->LinksFrom({mul_weight_var, x}).LinksTo({fc_out});
  }
  return fc_out;
}

#define NEW_NODE(op__, arg__, io__)                  \
  auto* arg__ = pattern->NewNode(name_scope, #arg__) \
                    ->assert_is_op_##io__(#op__, #arg__);

PDNode* patterns::LSTM(PDPattern* pattern, const std::string& name_scope,
                       PDNode* x) {
  x->assert_is_op_input("lstm", "Input");
  auto* lstm_op = pattern->NewNode(name_scope, "lstm")->assert_is_op("lstm");

  // 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(lstm, Weight, input);
  NEW_NODE(lstm, Bias, input);

  NEW_NODE(lstm, Hidden, output);
  NEW_NODE(lstm, Cell, output);
  NEW_NODE(lstm, BatchGate, output);
  NEW_NODE(lstm, BatchCellPreAct, output);

  lstm_op->LinksFrom({x, Weight, Bias});
  lstm_op->LinksTo({Hidden, Cell, BatchGate, BatchCellPreAct});
  return Hidden;
}

PDNode* patterns::GRU(PDPattern* pattern, const std::string& name_scope,
                      PDNode* x) {
  x->assert_is_op_input("gru", "Input");
  auto* gru_op = pattern->NewNode(name_scope, "gru")->assert_is_op("gru");

  NEW_NODE(gru, Weight, input);
  // TODO(Superjomn): upgrade the fuse framework to support optional.
  // H0 and bias are optional
  NEW_NODE(gru, Bias, input);  // also optional
  // NEW_NODE(H0, input);

  NEW_NODE(gru, Hidden, output);
  // below are intermediate
  NEW_NODE(gru, BatchGate, output);
  NEW_NODE(gru, BatchResetHiddenPrev, output);
  NEW_NODE(gru, BatchHidden, output);

  BatchGate->AsIntermediate();
  BatchResetHiddenPrev->AsIntermediate();
  BatchHidden->AsIntermediate();

  gru_op->LinksFrom({x, Weight, Bias});
  gru_op->LinksTo({Hidden, BatchGate, BatchResetHiddenPrev, BatchHidden});
  return Hidden;
}
#undef NEW_NODE

}  // namespace ir
}  // namespace framework
}  // namespace paddle