""" MALT-style dependency parser """ from __future__ import unicode_literals cimport cython from libc.stdint cimport uint32_t, uint64_t import random import os.path from os import path import shutil import json from cymem.cymem cimport Pool, Address from murmurhash.mrmr cimport hash64 from thinc.typedefs cimport weight_t, class_t, feat_t, atom_t from util import Config from thinc.features cimport Extractor from thinc.features cimport Feature from thinc.features cimport count_feats from thinc.learner cimport LinearModel from thinc.search cimport Beam from thinc.search cimport MaxViolation from ..tokens cimport Tokens, TokenC from ..strings cimport StringStore from .arc_eager cimport TransitionSystem, Transition from .transition_system import OracleError from ._state cimport State, new_state, copy_state, is_final, push_stack from ..gold cimport GoldParse from . import _parse_features from ._parse_features cimport fill_context, CONTEXT_SIZE DEBUG = False def set_debug(val): global DEBUG DEBUG = val cdef unicode print_state(State* s, list words): words = list(words) + ['EOL'] top = words[s.stack[0]] + '_%d' % s.sent[s.stack[0]].head second = words[s.stack[-1]] + '_%d' % s.sent[s.stack[-1]].head third = words[s.stack[-2]] + '_%d' % s.sent[s.stack[-2]].head n0 = words[s.i] if s.i < len(words) else 'EOL' n1 = words[s.i + 1] if s.i+1 < len(words) else 'EOL' if s.ents_len: ent = '%s %d-%d' % (s.ent.label, s.ent.start, s.ent.end) else: ent = '-' return ' '.join((ent, str(s.stack_len), third, second, top, '|', n0, n1)) def get_templates(name): pf = _parse_features if name == 'ner': return pf.ner elif name == 'debug': return pf.unigrams else: return (pf.unigrams + pf.s0_n0 + pf.s1_n0 + pf.s0_n1 + pf.n0_n1 + \ pf.tree_shape + pf.trigrams) cdef class Parser: def __init__(self, StringStore strings, model_dir, transition_system): assert os.path.exists(model_dir) and os.path.isdir(model_dir) self.cfg = Config.read(model_dir, 'config') self.moves = transition_system(strings, self.cfg.labels) templates = get_templates(self.cfg.features) self.model = Model(self.moves.n_moves, templates, model_dir) def __call__(self, Tokens tokens): if tokens.length == 0: return 0 if self.cfg.beam_width == 1: self._greedy_parse(tokens) else: self._beam_parse(tokens) def train(self, Tokens tokens, GoldParse gold): self.moves.preprocess_gold(gold) if self.cfg.beam_width == 1: return self._greedy_train(tokens, gold) else: return self._beam_train(tokens, gold) cdef int _greedy_parse(self, Tokens tokens) except -1: cdef atom_t[CONTEXT_SIZE] context cdef int n_feats cdef Pool mem = Pool() cdef State* state = new_state(mem, tokens.data, tokens.length) self.moves.initialize_state(state) cdef Transition guess while not is_final(state): fill_context(context, state) scores = self.model.score(context) guess = self.moves.best_valid(scores, state) guess.do(&guess, state) self.moves.finalize_state(state) tokens.set_parse(state.sent) cdef int _beam_parse(self, Tokens tokens) except -1: cdef Beam beam = Beam(self.model.n_classes, self.cfg.beam_width) beam.initialize(_init_state, tokens.length, tokens.data) while not beam.is_done: self._advance_beam(beam, None, False) state = beam.at(0) self.moves.finalize_state(state) tokens.set_parse(state.sent) def _greedy_train(self, Tokens tokens, GoldParse gold): cdef Pool mem = Pool() cdef State* state = new_state(mem, tokens.data, tokens.length) self.moves.initialize_state(state) cdef int cost cdef const Feature* feats cdef const weight_t* scores cdef Transition guess cdef Transition best cdef atom_t[CONTEXT_SIZE] context loss = 0 while not is_final(state): fill_context(context, state) scores = self.model.score(context) guess = self.moves.best_valid(scores, state) best = self.moves.best_gold(scores, state, gold) cost = guess.get_cost(&guess, state, gold) self.model.update(context, guess.clas, best.clas, cost) guess.do(&guess, state) loss += cost return loss def _beam_train(self, Tokens tokens, GoldParse gold_parse): cdef Beam pred = Beam(self.model.n_classes, self.cfg.beam_width) pred.initialize(_init_state, tokens.length, tokens.data) cdef Beam gold = Beam(self.model.n_classes, self.cfg.beam_width) gold.initialize(_init_state, tokens.length, tokens.data) violn = MaxViolation() while not pred.is_done and not gold.is_done: self._advance_beam(pred, gold_parse, False) self._advance_beam(gold, gold_parse, True) violn.check(pred, gold) counts = {} if pred._states[0].loss >= 1: self._count_feats(counts, tokens, violn.g_hist, 1) self._count_feats(counts, tokens, violn.p_hist, -1) self.model._model.update(counts) return pred._states[0].loss def _advance_beam(self, Beam beam, GoldParse gold, bint follow_gold): cdef atom_t[CONTEXT_SIZE] context cdef State* state cdef int i, j, cost cdef bint is_valid cdef const Transition* move for i in range(beam.size): state = beam.at(i) fill_context(context, state) scores = self.model.score(context) validities = self.moves.get_valid(state) if gold is None: for j in range(self.model.n_clases): beam.set_cell(i, j, scores[j], 0, validities[j]) elif not follow_gold: for j in range(self.model.n_classes): move = &self.moves.c[j] cost = move.get_cost(move, state, gold) beam.set_cell(i, j, scores[j], cost, validities[j]) else: for j in range(self.model.n_classes): move = &self.moves.c[j] cost = move.get_cost(move, state, gold) beam.set_cell(i, j, scores[j], cost, cost == 0) beam.advance(_transition_state, self.moves.c) beam.check_done(_check_final_state, NULL) def _count_feats(self, dict counts, Tokens tokens, list hist, int inc): cdef atom_t[CONTEXT_SIZE] context cdef Pool mem = Pool() cdef State* state = new_state(mem, tokens.data, tokens.length) self.moves.initialize_state(state) cdef class_t clas cdef int n_feats for clas in hist: if is_final(state): break fill_context(context, state) feats = self.model._extractor.get_feats(context, &n_feats) count_feats(counts.setdefault(clas, {}), feats, n_feats, inc) self.moves.c[clas].do(&self.moves.c[clas], state) # These are passed as callbacks to thinc.search.Beam cdef int _transition_state(void* _dest, void* _src, class_t clas, void* _moves) except -1: dest = _dest src = _src moves = _moves copy_state(dest, src) moves[clas].do(&moves[clas], dest) cdef void* _init_state(Pool mem, int length, void* tokens) except NULL: state = new_state(mem, tokens, length) push_stack(state) return state cdef int _check_final_state(void* state, void* extra_args) except -1: return is_final(state)