from __future__ import unicode_literals from ._state cimport State from ._state cimport has_head, get_idx, get_s0, get_n0 from ._state cimport is_final, at_eol, pop_stack, push_stack, add_dep from ._state cimport head_in_buffer, children_in_buffer from ._state cimport head_in_stack, children_in_stack from ..structs cimport TokenC DEF NON_MONOTONIC = True cdef enum: SHIFT REDUCE LEFT RIGHT N_MOVES cdef inline bint _can_shift(const State* s) nogil: return not at_eol(s) cdef inline bint _can_right(const State* s) nogil: return s.stack_len >= 1 and not at_eol(s) cdef inline bint _can_left(const State* s) nogil: if NON_MONOTONIC: return s.stack_len >= 1 else: return s.stack_len >= 1 and not has_head(get_s0(s)) cdef inline bint _can_reduce(const State* s) nogil: if NON_MONOTONIC: return s.stack_len >= 2 else: return s.stack_len >= 2 and has_head(get_s0(s)) cdef int _shift_cost(const State* s, const int* gold) except -1: assert not at_eol(s) cost = 0 cost += head_in_stack(s, s.i, gold) cost += children_in_stack(s, s.i, gold) if NON_MONOTONIC: cost += gold[s.stack[0]] == s.i return cost cdef int _right_cost(const State* s, const int* gold) except -1: assert s.stack_len >= 1 cost = 0 if gold[s.i] == s.stack[0]: return cost cost += head_in_buffer(s, s.i, gold) cost += children_in_stack(s, s.i, gold) cost += head_in_stack(s, s.i, gold) if NON_MONOTONIC: cost += gold[s.stack[0]] == s.i return cost cdef int _left_cost(const State* s, const int* gold) except -1: assert s.stack_len >= 1 cost = 0 if gold[s.stack[0]] == s.i: return cost cost += head_in_buffer(s, s.stack[0], gold) cost += children_in_buffer(s, s.stack[0], gold) if NON_MONOTONIC and s.stack_len >= 2: cost += gold[s.stack[0]] == s.stack[-1] return cost cdef int _reduce_cost(const State* s, const int* gold) except -1: cdef int cost = 0 cost += children_in_buffer(s, s.stack[0], gold) if NON_MONOTONIC: cost += head_in_buffer(s, s.stack[0], gold) return cost cdef class TransitionSystem: def __init__(self, list left_labels, list right_labels): self.mem = Pool() left_labels.sort() right_labels.sort() if 'ROOT' in right_labels: right_labels.pop(right_labels.index('ROOT')) if 'ROOT' in left_labels: left_labels.pop(left_labels.index('ROOT')) self.n_moves = 2 + len(left_labels) + len(right_labels) moves = self.mem.alloc(self.n_moves, sizeof(Transition)) cdef int i = 0 moves[i].move = SHIFT moves[i].label = 0 moves[i].clas = i i += 1 moves[i].move = REDUCE moves[i].label = 0 moves[i].clas = i i += 1 self.label_ids = {'ROOT': 0} cdef int label_id for label_str in left_labels: label_str = unicode(label_str) label_id = self.label_ids.setdefault(label_str, len(self.label_ids)) moves[i].move = LEFT moves[i].label = label_id moves[i].clas = i i += 1 for label_str in right_labels: label_str = unicode(label_str) label_id = self.label_ids.setdefault(label_str, len(self.label_ids)) moves[i].move = RIGHT moves[i].label = label_id moves[i].clas = i i += 1 self._moves = moves cdef int transition(self, State *s, const Transition* t) except -1: if t.move == SHIFT: # Set the dep label, in case we need it after we reduce if NON_MONOTONIC: get_s0(s).dep = t.label push_stack(s) elif t.move == LEFT: add_dep(s, s.i, s.stack[0], t.label) pop_stack(s) elif t.move == RIGHT: add_dep(s, s.stack[0], s.i, t.label) push_stack(s) elif t.move == REDUCE: add_dep(s, s.stack[-1], s.stack[0], get_s0(s).dep) pop_stack(s) else: raise Exception(t.move) cdef Transition best_valid(self, const weight_t* scores, const State* s) except *: cdef bint[N_MOVES] valid valid[SHIFT] = _can_shift(s) valid[LEFT] = _can_left(s) valid[RIGHT] = _can_right(s) valid[REDUCE] = _can_reduce(s) cdef int best = -1 cdef weight_t score = 0 cdef weight_t best_r_score = -9000 cdef int best_r_label = -1 cdef int i for i in range(self.n_moves): if valid[self._moves[i].move] and (best == -1 or scores[i] > score): best = i score = scores[i] if self._moves[i].move == RIGHT and scores[i] > best_r_score: best_r_label = self._moves[i].label assert best >= 0 cdef Transition t = self._moves[best] t.score = score if t.move == SHIFT: t.label = best_r_label return t cdef Transition best_gold(self, Transition* guess, const weight_t* scores, const State* s, const int* gold_heads, const int* gold_labels) except *: # If we can create a gold dependency, only one action can be correct cdef int[N_MOVES] unl_costs unl_costs[SHIFT] = _shift_cost(s, gold_heads) if _can_shift(s) else -1 unl_costs[LEFT] = _left_cost(s, gold_heads) if _can_left(s) else -1 unl_costs[RIGHT] = _right_cost(s, gold_heads) if _can_right(s) else -1 unl_costs[REDUCE] = _reduce_cost(s, gold_heads) if _can_reduce(s) else -1 guess.cost = unl_costs[guess.move] cdef Transition t cdef int target_label cdef int i if gold_heads[s.stack[0]] == s.i: target_label = gold_labels[s.stack[0]] if guess.move == LEFT: guess.cost += guess.label != target_label for i in range(self.n_moves): t = self._moves[i] if t.move == LEFT and t.label == target_label: return t elif gold_heads[s.i] == s.stack[0]: target_label = gold_labels[s.i] if guess.move == RIGHT: guess.cost += guess.label != target_label for i in range(self.n_moves): t = self._moves[i] if t.move == RIGHT and t.label == target_label: return t cdef int best = -1 cdef weight_t score = -9000 for i in range(self.n_moves): t = self._moves[i] if unl_costs[t.move] == 0 and (best == -1 or scores[i] > score): best = i score = scores[i] t = self._moves[best] t.score = score assert best >= 0 return t