spaCy/spacy/syntax/transition_system.pyx

# cython: infer_types=True
# coding: utf-8
from __future__ import unicode_literals

from cpython.ref cimport PyObject, Py_INCREF, Py_XDECREF
from cymem.cymem cimport Pool
from thinc.typedefs cimport weight_t
from collections import defaultdict, OrderedDict

from ..structs cimport TokenC
from .stateclass cimport StateClass
from ..attrs cimport TAG, HEAD, DEP, ENT_TYPE, ENT_IOB
from ..typedefs cimport attr_t


cdef weight_t MIN_SCORE = -90000


class OracleError(Exception):
    pass


cdef void* _init_state(Pool mem, int length, void* tokens) except NULL:
    cdef StateClass st = StateClass.init(<const TokenC*>tokens, length)
    Py_INCREF(st)
    return <void*>st


cdef class TransitionSystem:
    def __init__(self, StringStore string_table, labels_by_action):
        self.mem = Pool()
        self.strings = string_table
        self.n_moves = 0
        self._size = 100

        self.c = <Transition*>self.mem.alloc(self._size, sizeof(Transition))

        for action, label_strs in labels_by_action.items():
            for label_str in label_strs:
                self.add_action(int(action), label_str)
        self.root_label = self.strings.add('ROOT')
        self.init_beam_state = _init_state

    def __reduce__(self):
        labels_by_action = OrderedDict()
        cdef Transition t
        for trans in self.c[:self.n_moves]:
            label_str = self.strings[trans.label]
            labels_by_action.setdefault(trans.move, []).append(label_str)
        return (self.__class__,
                (self.strings, labels_by_action),
                None, None)

    def init_batch(self, docs):
        cdef StateClass state
        states = []
        offset = 0
        for doc in docs:
            state = StateClass(doc, offset=offset)
            self.initialize_state(state.c)
            states.append(state)
            offset += len(doc)
        return states

    def get_oracle_sequence(self, doc, GoldParse gold):
        cdef Pool mem = Pool()
        costs = <float*>mem.alloc(self.n_moves, sizeof(float))
        is_valid = <int*>mem.alloc(self.n_moves, sizeof(int))

        cdef StateClass state = StateClass(doc, offset=0)
        self.initialize_state(state.c)
        history = []
        while not state.is_final():
            self.set_costs(is_valid, costs, state, gold)
            for i in range(self.n_moves):
                if is_valid[i] and costs[i] <= 0:
                    action = self.c[i]
                    history.append(i)
                    action.do(state.c, action.label)
                    break
            else:
                print(gold.words)
                print(gold.ner)
                print(history)
                raise ValueError("Could not find gold move")
        return history

    cdef int initialize_state(self, StateC* state) nogil:
        pass

    cdef int finalize_state(self, StateC* state) nogil:
        pass

    def finalize_doc(self, doc):
        pass

    def preprocess_gold(self, GoldParse gold):
        raise NotImplementedError

    cdef Transition lookup_transition(self, object name) except *:
        raise NotImplementedError

    cdef Transition init_transition(self, int clas, int move, attr_t label) except *:
        raise NotImplementedError

    def is_valid(self, StateClass stcls, move_name):
        action = self.lookup_transition(move_name)
        return action.is_valid(stcls.c, action.label)

    cdef int set_valid(self, int* is_valid, const StateC* st) nogil:
        cdef int i
        for i in range(self.n_moves):
            is_valid[i] = self.c[i].is_valid(st, self.c[i].label)

    cdef int set_costs(self, int* is_valid, weight_t* costs,
                       StateClass stcls, GoldParse gold) except -1:
        cdef int i
        self.set_valid(is_valid, stcls.c)
        cdef int n_gold = 0
        for i in range(self.n_moves):
            if is_valid[i]:
                costs[i] = self.c[i].get_cost(stcls, &gold.c, self.c[i].label)
                n_gold += costs[i] <= 0
            else:
                costs[i] = 9000
        if n_gold <= 0:
            print(gold.words)
            print(gold.ner)
            print([gold.c.ner[i].clas for i in range(gold.length)])
            print([gold.c.ner[i].move for i in range(gold.length)])
            print([gold.c.ner[i].label for i in range(gold.length)])
            print("Self labels", [self.c[i].label for i in range(self.n_moves)])
            raise ValueError(
                "Could not find a gold-standard action to supervise "
                "the entity recognizer\n"
                "The transition system has %d actions." % (self.n_moves))

    def add_action(self, int action, label_name):
        cdef attr_t label_id
        if not isinstance(label_name, int):
            label_id = self.strings.add(label_name)
        else:
            label_id = label_name
        # Check we're not creating a move we already have, so that this is
        # idempotent
        for trans in self.c[:self.n_moves]:
            if trans.move == action and trans.label == label_id:
                return 0
        if self.n_moves >= self._size:
            self._size *= 2
            self.c = <Transition*>self.mem.realloc(self.c, self._size * sizeof(self.c[0]))
        self.c[self.n_moves] = self.init_transition(self.n_moves, action, label_id)
        assert self.c[self.n_moves].label == label_id
        self.n_moves += 1
        return 1