mirror of
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149 lines
4.9 KiB
Cython
149 lines
4.9 KiB
Cython
# cython: infer_types=True
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# coding: utf-8
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from __future__ import unicode_literals
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from cpython.ref cimport PyObject, Py_INCREF, Py_XDECREF
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from cymem.cymem cimport Pool
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from thinc.typedefs cimport weight_t
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from collections import defaultdict, OrderedDict
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from ..structs cimport TokenC
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from .stateclass cimport StateClass
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from ..attrs cimport TAG, HEAD, DEP, ENT_TYPE, ENT_IOB
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cdef weight_t MIN_SCORE = -90000
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class OracleError(Exception):
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pass
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cdef void* _init_state(Pool mem, int length, void* tokens) except NULL:
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cdef StateClass st = StateClass.init(<const TokenC*>tokens, length)
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Py_INCREF(st)
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return <void*>st
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cdef class TransitionSystem:
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def __init__(self, StringStore string_table, labels_by_action):
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self.mem = Pool()
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self.strings = string_table
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self.n_moves = 0
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self._size = 100
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self.c = <Transition*>self.mem.alloc(self._size, sizeof(Transition))
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for action, label_strs in labels_by_action.items():
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for label_str in label_strs:
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self.add_action(int(action), label_str)
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self.root_label = self.strings['ROOT']
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self.init_beam_state = _init_state
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def __reduce__(self):
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labels_by_action = OrderedDict()
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cdef Transition t
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for trans in self.c[:self.n_moves]:
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label_str = self.strings[trans.label]
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labels_by_action.setdefault(trans.move, []).append(label_str)
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return (self.__class__,
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(self.strings, labels_by_action),
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None, None)
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def init_batch(self, docs):
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cdef StateClass state
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states = []
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offset = 0
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for doc in docs:
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state = StateClass(doc, offset=offset)
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self.initialize_state(state.c)
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states.append(state)
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offset += len(doc)
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return states
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def get_oracle_sequence(self, doc, GoldParse gold):
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cdef Pool mem = Pool()
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costs = <float*>mem.alloc(self.n_moves, sizeof(float))
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is_valid = <int*>mem.alloc(self.n_moves, sizeof(int))
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cdef StateClass state = StateClass(doc, offset=0)
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self.initialize_state(state.c)
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history = []
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while not state.is_final():
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self.set_costs(is_valid, costs, state, gold)
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for i in range(self.n_moves):
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if is_valid[i] and costs[i] <= 0:
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action = self.c[i]
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history.append(i)
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action.do(state.c, action.label)
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break
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else:
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print(gold.words)
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print(gold.ner)
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print(history)
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raise ValueError("Could not find gold move")
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return history
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cdef int initialize_state(self, StateC* state) nogil:
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pass
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cdef int finalize_state(self, StateC* state) nogil:
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pass
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def finalize_doc(self, doc):
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pass
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def preprocess_gold(self, GoldParse gold):
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raise NotImplementedError
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cdef Transition lookup_transition(self, object name) except *:
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raise NotImplementedError
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cdef Transition init_transition(self, int clas, int move, int label) except *:
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raise NotImplementedError
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def is_valid(self, StateClass stcls, move_name):
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action = self.lookup_transition(move_name)
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return action.is_valid(stcls.c, action.label)
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cdef int set_valid(self, int* is_valid, const StateC* st) nogil:
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cdef int i
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for i in range(self.n_moves):
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is_valid[i] = self.c[i].is_valid(st, self.c[i].label)
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cdef int set_costs(self, int* is_valid, weight_t* costs,
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StateClass stcls, GoldParse gold) except -1:
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cdef int i
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self.set_valid(is_valid, stcls.c)
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cdef int n_gold = 0
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for i in range(self.n_moves):
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if is_valid[i]:
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costs[i] = self.c[i].get_cost(stcls, &gold.c, self.c[i].label)
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n_gold += costs[i] <= 0
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else:
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costs[i] = 9000
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if n_gold <= 0:
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print(gold.words)
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print(gold.ner)
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raise ValueError(
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"Could not find a gold-standard action to supervise "
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"the entity recognizer\n"
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"The transition system has %d actions.\n"
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"%s" % (self.n_moves))
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def add_action(self, int action, label):
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if not isinstance(label, int):
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label = self.strings[label]
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# Check we're not creating a move we already have, so that this is
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# idempotent
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for trans in self.c[:self.n_moves]:
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if trans.move == action and trans.label == label:
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return 0
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if self.n_moves >= self._size:
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self._size *= 2
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self.c = <Transition*>self.mem.realloc(self.c, self._size * sizeof(self.c[0]))
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self.c[self.n_moves] = self.init_transition(self.n_moves, action, label)
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self.n_moves += 1
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return 1
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