//TODO: lazily generate feature vectors for hyperarcs (because some of them will be pruned). this means 1) storing ref to rule for those features 2) providing ff interface for regenerating its feature vector from hyperedge+states and probably 3) still caching feat. vect on hyperedge once it's been generated. ff would normally just contribute its weighted score and result state, not component features. however, the hypergraph drops the state used by ffs after rescoring is done, so recomputation would have to start at the leaves and work bottom up. question: which takes more space, feature id+value, or state? #include "hg.h" #include #include #include #include #include #include #include #include "viterbi.h" #include "inside_outside.h" #include "tdict.h" using namespace std; std::string Hypergraph::stats(std::string const& name) const { ostringstream o; o<(*this); } struct ScaledTransitionEventWeightFunction { ScaledTransitionEventWeightFunction(double alpha) : scale_(alpha) {} inline SparseVector operator()(const Hypergraph::Edge& e) const { SparseVector result; result.set_value(e.id_, e.edge_prob_.pow(scale_)); return result; } const double scale_; }; struct TropicalValue { TropicalValue() : v_() {} explicit TropicalValue(int v) { if (v == 0) v_ = prob_t::Zero(); else if (v == 1) v_ = prob_t::One(); else { cerr << "Bad value in TropicalValue(int).\n"; abort(); } } explicit TropicalValue(const prob_t& v) : v_(v) {} inline TropicalValue& operator+=(const TropicalValue& o) { if (v_ < o.v_) v_ = o.v_; return *this; } inline TropicalValue& operator*=(const TropicalValue& o) { v_ *= o.v_; return *this; } inline bool operator==(const TropicalValue& o) const { return v_ == o.v_; } prob_t v_; }; struct ViterbiWeightFunction { inline TropicalValue operator()(const Hypergraph::Edge& e) const { return TropicalValue(e.edge_prob_); } }; struct ViterbiTransitionEventWeightFunction { inline SparseVector operator()(const Hypergraph::Edge& e) const { SparseVector result; result.set_value(e.id_, TropicalValue(e.edge_prob_)); return result; } }; prob_t Hypergraph::ComputeEdgePosteriors(double scale, vector* posts) const { const ScaledEdgeProb weight(scale); const ScaledTransitionEventWeightFunction w2(scale); SparseVector pv; const double inside = InsideOutside, ScaledTransitionEventWeightFunction>(*this, &pv, weight, w2); posts->resize(edges_.size()); for (int i = 0; i < edges_.size(); ++i) (*posts)[i] = prob_t(pv.value(i)); return prob_t(inside); } prob_t Hypergraph::ComputeBestPathThroughEdges(vector* post) const { SparseVector pv; const TropicalValue viterbi_weight = InsideOutside, ViterbiTransitionEventWeightFunction>(*this, &pv); post->resize(edges_.size()); for (int i = 0; i < edges_.size(); ++i) (*post)[i] = pv.value(i).v_; return viterbi_weight.v_; } void Hypergraph::PushWeightsToSource(double scale) { vector posts; ComputeEdgePosteriors(scale, &posts); for (int i = 0; i < nodes_.size(); ++i) { const Hypergraph::Node& node = nodes_[i]; prob_t z = prob_t::Zero(); for (int j = 0; j < node.out_edges_.size(); ++j) z += posts[node.out_edges_[j]]; for (int j = 0; j < node.out_edges_.size(); ++j) { edges_[node.out_edges_[j]].edge_prob_ = posts[node.out_edges_[j]] / z; } } } void Hypergraph::PushWeightsToGoal(double scale) { vector posts; ComputeEdgePosteriors(scale, &posts); for (int i = 0; i < nodes_.size(); ++i) { const Hypergraph::Node& node = nodes_[i]; prob_t z = prob_t::Zero(); for (int j = 0; j < node.in_edges_.size(); ++j) z += posts[node.in_edges_[j]]; for (int j = 0; j < node.in_edges_.size(); ++j) { edges_[node.in_edges_[j]].edge_prob_ = posts[node.in_edges_[j]] / z; } } } struct EdgeExistsWeightFunction { EdgeExistsWeightFunction(const std::vector& prunes) : prunes_(prunes) {} bool operator()(const Hypergraph::Edge& edge) const { return !prunes_[edge.id_]; } private: const vector& prunes_; }; void Hypergraph::PruneEdges(const std::vector& prune_edge, bool run_inside_algorithm) { assert(prune_edge.size() == edges_.size()); vector filtered = prune_edge; if (run_inside_algorithm) { const EdgeExistsWeightFunction wf(prune_edge); // use double, not bool since vector causes problems with the Inside algorithm. // I don't know a good c++ way to resolve this short of template specialization which // I dislike. If you know of a better way that doesn't involve specialization, // fix this! vector reachable; bool goal_derivable = Inside/* */(*this, &reachable, wf); if (!goal_derivable) { edges_.clear(); nodes_.clear(); nodes_.push_back(Node()); return; } assert(reachable.size() == nodes_.size()); for (int i = 0; i < edges_.size(); ++i) { bool prune = prune_edge[i]; if (!prune) { const Edge& edge = edges_[i]; for (int j = 0; j < edge.tail_nodes_.size(); ++j) { if (!reachable[edge.tail_nodes_[j]]) { prune = true; break; } } } filtered[i] = prune; } } TopologicallySortNodesAndEdges(nodes_.size() - 1, &filtered); } void Hypergraph_finish_prune(Hypergraph &hg,vector const& io,double cutoff,vector const* preserve_mask,bool verbose=false) { const double EPSILON=1e-5; //TODO: //FIXME: if EPSILON is 0, then remnants (useless edges that don't connect to top? or top-connected but not bottom-up buildable referneced?) are left in the hypergraph output that cause mr_vest_map to segfault. adding EPSILON probably just covers up the symptom by making it far less frequent; I imagine any time threshold is set by DensityPrune, cutoff is exactly equal to the io of several nodes, but because of how it's computed, some round slightly down vs. slightly up. probably the flaw is in PruneEdges. cutoff=cutoff-EPSILON; vector prune(hg.NumberOfEdges()); if (verbose) { if (preserve_mask) cerr << preserve_mask->size() << " " << prune.size() << endl; cerr<<"Finishing prune for "<* preserve_mask) { assert(density >= 1.0); const int plen = ViterbiPathLength(*this); vector bp; int rnum = min(static_cast(edges_.size()), static_cast(density * static_cast(plen))); cerr << "Density pruning: keep "< io(edges_.size()); if (use_sum_prod_semiring) { ComputeEdgePosteriors(scale, &io); assert(scale > 0.0); } else ComputeBestPathThroughEdges(&io); assert(edges_.size() == io.size()); vector sorted = io; nth_element(sorted.begin(), sorted.begin() + rnum, sorted.end(), greater()); Hypergraph_finish_prune(*this,io,sorted[rnum],preserve_mask); } void Hypergraph::BeamPruneInsideOutside( const double scale, const bool use_sum_prod_semiring, const double alpha, const vector* preserve_mask) { assert(alpha >= 0.0); vector io(edges_.size()); if (use_sum_prod_semiring) { ComputeEdgePosteriors(scale, &io); assert(scale > 0.0); } else ComputeBestPathThroughEdges(&io); assert(edges_.size() == io.size()); prob_t best; // initializes to zero for (int i = 0; i < io.size(); ++i) if (io[i] > best) best = io[i]; Hypergraph_finish_prune(*this,io,best*exp(-alpha),preserve_mask); } void Hypergraph::PrintGraphviz() const { int ei = 0; cerr << "digraph G {\n rankdir=LR;\n nodesep=.05;\n"; for (vector::const_iterator i = edges_.begin(); i != edges_.end(); ++i) { const Edge& edge=*i; ++ei; static const string none = ""; string rule = (edge.rule_ ? edge.rule_->AsString(false) : none); cerr << " A_" << ei << " [label=\"" << rule << " p=" << edge.edge_prob_ << " F:" << edge.feature_values_ << "\" shape=\"rect\"];\n"; Hypergraph::TailNodeVector indorder(edge.tail_nodes_.size(), 0); int ntc = 0; for (int i = 0; i < edge.rule_->e_.size(); ++i) { if (edge.rule_->e_[i] <= 0) indorder[ntc++] = 1 + (-1 * edge.rule_->e_[i]); } for (int i = 0; i < edge.tail_nodes_.size(); ++i) { cerr << " " << edge.tail_nodes_[i] << " -> A_" << ei; if (edge.tail_nodes_.size() > 1) { cerr << " [label=\"" << indorder[i] << "\"]"; } cerr << ";\n"; } cerr << " A_" << ei << " -> " << edge.head_node_ << ";\n"; } for (vector::const_iterator ni = nodes_.begin(); ni != nodes_.end(); ++ni) { cerr << " " << ni->id_ << "[label=\"" << (ni->cat_ < 0 ? TD::Convert(ni->cat_ * -1) : "") //cerr << " " << ni->id_ << "[label=\"" << ni->cat_ << " n=" << ni->id_ // << ",x=" << &*ni // << ",in=" << ni->in_edges_.size() // << ",out=" << ni->out_edges_.size() << "\"];\n"; } cerr << "}\n"; } void Hypergraph::Union(const Hypergraph& other) { if (&other == this) return; if (nodes_.empty()) { nodes_ = other.nodes_; edges_ = other.edges_; return; } int noff = nodes_.size(); int eoff = edges_.size(); int ogoal = other.nodes_.size() - 1; int cgoal = noff - 1; // keep a single goal node, so add nodes.size - 1 nodes_.resize(nodes_.size() + ogoal); // add all edges edges_.resize(edges_.size() + other.edges_.size()); for (int i = 0; i < ogoal; ++i) { const Node& on = other.nodes_[i]; Node& cn = nodes_[i + noff]; cn.id_ = i + noff; cn.in_edges_.resize(on.in_edges_.size()); for (int j = 0; j < on.in_edges_.size(); ++j) cn.in_edges_[j] = on.in_edges_[j] + eoff; cn.out_edges_.resize(on.out_edges_.size()); for (int j = 0; j < on.out_edges_.size(); ++j) cn.out_edges_[j] = on.out_edges_[j] + eoff; } for (int i = 0; i < other.edges_.size(); ++i) { const Edge& oe = other.edges_[i]; Edge& ce = edges_[i + eoff]; ce.id_ = i + eoff; ce.rule_ = oe.rule_; ce.feature_values_ = oe.feature_values_; if (oe.head_node_ == ogoal) { ce.head_node_ = cgoal; nodes_[cgoal].in_edges_.push_back(ce.id_); } else { ce.head_node_ = oe.head_node_ + noff; } ce.tail_nodes_.resize(oe.tail_nodes_.size()); for (int j = 0; j < oe.tail_nodes_.size(); ++j) ce.tail_nodes_[j] = oe.tail_nodes_[j] + noff; } TopologicallySortNodesAndEdges(cgoal); } void Hypergraph::PruneUnreachable(int goal_node_id) { TopologicallySortNodesAndEdges(goal_node_id, NULL); } void Hypergraph::RemoveNoncoaccessibleStates(int goal_node_id) { if (goal_node_id < 0) goal_node_id += nodes_.size(); assert(goal_node_id >= 0); assert(goal_node_id < nodes_.size()); // TODO finish implementation abort(); } struct DFSContext { int node; int edge_iter; int tail_iter; DFSContext(int n, int e, int t) : node(n), edge_iter(e), tail_iter(t) {} }; enum ColorType { WHITE, GRAY, BLACK }; template struct BadId { bool operator()(const T& obj) const { return obj.id_ == -1; } }; template struct IdCompare { bool operator()(const T& a, const T& b) { return a.id_ < b.id_; } }; void Hypergraph::TopologicallySortNodesAndEdges(int goal_index, const vector* prune_edges) { // figure out which nodes are reachable from the goal vector reloc_node(nodes_.size(), -1); vector reloc_edge(edges_.size(), -1); vector color(nodes_.size(), WHITE); vector stack; stack.reserve(nodes_.size()); stack.push_back(DFSContext(goal_index, 0, 0)); int node_count = 0; int edge_count = 0; while(!stack.empty()) { const DFSContext& p = stack.back(); int cur_ni = p.node; int edge_i = p.edge_iter; int tail_i = p.tail_iter; stack.pop_back(); const Node* cur_node = &nodes_[cur_ni]; int edge_end = cur_node->in_edges_.size(); while (edge_i != edge_end) { const Edge& cur_edge = edges_[cur_node->in_edges_[edge_i]]; const int tail_end = cur_edge.tail_nodes_.size(); if ((tail_end == tail_i) || (prune_edges && (*prune_edges)[cur_edge.id_])) { ++edge_i; tail_i = 0; continue; } const int tail_ni = cur_edge.tail_nodes_[tail_i]; const int tail_color = color[tail_ni]; if (tail_color == WHITE) { stack.push_back(DFSContext(cur_ni, edge_i, ++tail_i)); cur_ni = tail_ni; cur_node = &nodes_[cur_ni]; color[cur_ni] = GRAY; edge_i = 0; edge_end = cur_node->in_edges_.size(); tail_i = 0; } else if (tail_color == BLACK) { ++tail_i; } else if (tail_color == GRAY) { // this can happen if, e.g., it is possible to rederive // a single cell in the CKY chart via a cycle. cerr << "Detected forbidden cycle in HG:\n"; cerr << " " << cur_edge.rule_->AsString() << endl; while(!stack.empty()) { const DFSContext& p = stack.back(); cerr << " " << edges_[nodes_[p.node].in_edges_[p.edge_iter]].rule_->AsString() << endl; stack.pop_back(); } abort(); } } color[cur_ni] = BLACK; reloc_node[cur_ni] = node_count++; if (prune_edges) { for (int i = 0; i < edge_end; ++i) { int ei = cur_node->in_edges_[i]; if (!(*prune_edges)[ei]) reloc_edge[cur_node->in_edges_[i]] = edge_count++; } } else { for (int i = 0; i < edge_end; ++i) reloc_edge[cur_node->in_edges_[i]] = edge_count++; } } #ifndef HG_EDGES_TOPO_SORTED int ec = 0; for (int i = 0; i < reloc_edge.size(); ++i) { int& cp = reloc_edge[i]; if (cp >= 0) { cp = ec++; } } #endif #if 0 cerr << "TOPO:"; for (int i = 0; i < reloc_node.size(); ++i) cerr << " " << reloc_node[i]; cerr << endl; cerr << "EDGE:"; for (int i = 0; i < reloc_edge.size(); ++i) cerr << " " << reloc_edge[i]; cerr << endl; #endif bool no_op = true; for (int i = 0; i < reloc_node.size() && no_op; ++i) if (reloc_node[i] != i) no_op = false; for (int i = 0; i < reloc_edge.size() && no_op; ++i) if (reloc_edge[i] != i) no_op = false; if (no_op) return; for (int i = 0; i < reloc_node.size(); ++i) { Node& node = nodes_[i]; node.id_ = reloc_node[i]; int c = 0; for (int j = 0; j < node.in_edges_.size(); ++j) { const int new_index = reloc_edge[node.in_edges_[j]]; if (new_index >= 0) node.in_edges_[c++] = new_index; } node.in_edges_.resize(c); c = 0; for (int j = 0; j < node.out_edges_.size(); ++j) { const int new_index = reloc_edge[node.out_edges_[j]]; if (new_index >= 0) node.out_edges_[c++] = new_index; } node.out_edges_.resize(c); } for (int i = 0; i < reloc_edge.size(); ++i) { Edge& edge = edges_[i]; edge.id_ = reloc_edge[i]; edge.head_node_ = reloc_node[edge.head_node_]; for (int j = 0; j < edge.tail_nodes_.size(); ++j) edge.tail_nodes_[j] = reloc_node[edge.tail_nodes_[j]]; } edges_.erase(remove_if(edges_.begin(), edges_.end(), BadId()), edges_.end()); nodes_.erase(remove_if(nodes_.begin(), nodes_.end(), BadId()), nodes_.end()); sort(nodes_.begin(), nodes_.end(), IdCompare()); #ifndef HG_EDGES_TOPO_SORTED sort(edges_.begin(), edges_.end(), IdCompare()); #endif } TRulePtr Hypergraph::kEPSRule; TRulePtr Hypergraph::kUnaryRule; void Hypergraph::EpsilonRemove(WordID eps) { if (!kEPSRule) { kEPSRule.reset(new TRule("[X] ||| ||| ")); kUnaryRule.reset(new TRule("[X] ||| [X,1] ||| [X,1]")); } vector kill(edges_.size(), false); for (int i = 0; i < edges_.size(); ++i) { const Edge& edge = edges_[i]; if (edge.tail_nodes_.empty() && edge.rule_->f_.size() == 1 && edge.rule_->f_[0] == eps) { kill[i] = true; if (!edge.feature_values_.empty()) { Node& node = nodes_[edge.head_node_]; if (node.in_edges_.size() != 1) { cerr << "[WARNING] edge with features going into non-empty node - can't promote\n"; // this *probably* means that there are multiple derivations of the // same sequence via different paths through the input forest // this needs to be investigated and fixed } else { for (int j = 0; j < node.out_edges_.size(); ++j) edges_[node.out_edges_[j]].feature_values_ += edge.feature_values_; // cerr << "PROMOTED " << edge.feature_values_ << endl; } } } } bool created_eps = false; PruneEdges(kill); for (int i = 0; i < nodes_.size(); ++i) { const Node& node = nodes_[i]; if (node.in_edges_.empty()) { for (int j = 0; j < node.out_edges_.size(); ++j) { Edge& edge = edges_[node.out_edges_[j]]; if (edge.rule_->Arity() == 2) { assert(edge.rule_->f_.size() == 2); assert(edge.rule_->e_.size() == 2); edge.rule_ = kUnaryRule; int cur = node.id_; int t = -1; assert(edge.tail_nodes_.size() == 2); for (int i = 0; i < 2; ++i) if (edge.tail_nodes_[i] != cur) { t = edge.tail_nodes_[i]; } assert(t != -1); edge.tail_nodes_.resize(1); edge.tail_nodes_[0] = t; } else { edge.rule_ = kEPSRule; edge.rule_->f_[0] = eps; edge.rule_->e_[0] = eps; edge.tail_nodes_.clear(); created_eps = true; } } } } vector k2(edges_.size(), false); PruneEdges(k2); if (created_eps) EpsilonRemove(eps); } struct EdgeWeightSorter { const Hypergraph& hg; EdgeWeightSorter(const Hypergraph& h) : hg(h) {} bool operator()(int a, int b) const { return hg.edges_[a].edge_prob_ > hg.edges_[b].edge_prob_; } }; void Hypergraph::SortInEdgesByEdgeWeights() { for (int i = 0; i < nodes_.size(); ++i) { Node& node = nodes_[i]; sort(node.in_edges_.begin(), node.in_edges_.end(), EdgeWeightSorter(*this)); } } Hypergraph* Hypergraph::CreateViterbiHypergraph(const vector* edges) const { vector vit_edges; if (edges) { assert(edges->size() == edges_.size()); Viterbi, ViterbiPathTraversal, prob_t, EdgeSelectEdgeWeightFunction>(*this, &vit_edges, ViterbiPathTraversal(), EdgeSelectEdgeWeightFunction(*edges)); } else { Viterbi, ViterbiPathTraversal, prob_t, EdgeProb>(*this, &vit_edges); } map old2new_node; int num_new_nodes = 0; for (int i = 0; i < vit_edges.size(); ++i) { const Edge& edge = *vit_edges[i]; for (int j = 0; j < edge.tail_nodes_.size(); ++j) assert(old2new_node.count(edge.tail_nodes_[j]) > 0); if (old2new_node.count(edge.head_node_) == 0) { old2new_node[edge.head_node_] = num_new_nodes; ++num_new_nodes; } } Hypergraph* out = new Hypergraph(num_new_nodes, vit_edges.size(), is_linear_chain_); for (map::iterator it = old2new_node.begin(); it != old2new_node.end(); ++it) { const Node& old_node = nodes_[it->first]; Node& new_node = out->nodes_[it->second]; new_node.cat_ = old_node.cat_; new_node.id_ = it->second; } for (int i = 0; i < vit_edges.size(); ++i) { const Edge& old_edge = *vit_edges[i]; Edge& new_edge = out->edges_[i]; new_edge = old_edge; new_edge.id_ = i; const int new_head_node = old2new_node[old_edge.head_node_]; new_edge.head_node_ = new_head_node; out->nodes_[new_head_node].in_edges_.push_back(i); for (int j = 0; j < old_edge.tail_nodes_.size(); ++j) { const int new_tail_node = old2new_node[old_edge.tail_nodes_[j]]; new_edge.tail_nodes_[j] = new_tail_node; out->nodes_[new_tail_node].out_edges_.push_back(i); } } return out; }