mirror of
https://github.com/explosion/spaCy.git
synced 2024-11-14 05:37:03 +03:00
61 lines
2.0 KiB
Cython
61 lines
2.0 KiB
Cython
# cython: profile=True
|
|
from __future__ import unicode_literals
|
|
from __future__ import division
|
|
|
|
from os import path
|
|
import os
|
|
import shutil
|
|
import json
|
|
import cython
|
|
import numpy.random
|
|
|
|
from thinc.features cimport Feature, count_feats
|
|
|
|
|
|
cdef int arg_max(const weight_t* scores, const int n_classes) nogil:
|
|
cdef int i
|
|
cdef int best = 0
|
|
cdef weight_t mode = scores[0]
|
|
for i in range(1, n_classes):
|
|
if scores[i] > mode:
|
|
mode = scores[i]
|
|
best = i
|
|
return best
|
|
|
|
|
|
cdef class Model:
|
|
def __init__(self, n_classes, templates, model_loc=None):
|
|
if model_loc is not None and path.isdir(model_loc):
|
|
model_loc = path.join(model_loc, 'model')
|
|
self.n_classes = n_classes
|
|
self._extractor = Extractor(templates)
|
|
self._model = LinearModel(n_classes, self._extractor.n_templ)
|
|
self.model_loc = model_loc
|
|
if self.model_loc and path.exists(self.model_loc):
|
|
self._model.load(self.model_loc, freq_thresh=0)
|
|
|
|
cdef const weight_t* score(self, atom_t* context) except NULL:
|
|
cdef int n_feats
|
|
feats = self._extractor.get_feats(context, &n_feats)
|
|
return self._model.get_scores(feats, n_feats)
|
|
|
|
cdef int set_scores(self, weight_t* scores, atom_t* context) except -1:
|
|
cdef int n_feats
|
|
feats = self._extractor.get_feats(context, &n_feats)
|
|
self._model.set_scores(scores, feats, n_feats)
|
|
|
|
cdef int update(self, atom_t* context, class_t guess, class_t gold, int cost) except -1:
|
|
cdef int n_feats
|
|
if cost == 0:
|
|
self._model.update({})
|
|
else:
|
|
feats = self._extractor.get_feats(context, &n_feats)
|
|
counts = {gold: {}, guess: {}}
|
|
count_feats(counts[gold], feats, n_feats, cost)
|
|
count_feats(counts[guess], feats, n_feats, -cost)
|
|
self._model.update(counts)
|
|
|
|
def end_training(self):
|
|
self._model.end_training()
|
|
self._model.dump(self.model_loc, freq_thresh=0)
|