mirror of
https://github.com/explosion/spaCy.git
synced 2024-09-21 19:39:13 +03:00
45 lines
1.5 KiB
Cython
45 lines
1.5 KiB
Cython
|
from thinc.example cimport Example
|
||
|
|
|
||
|
|
|
||
|
|
cdef class TheanoModel(Model):
|
||
|
|
def __init__(self, n_classes, input_layer, train_func, predict_func, 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
|
||
|
|
|
||
|
|
tables = []
|
||
|
|
lengths = []
|
||
|
|
for window_size, n_dims, vocab_size in input_structure:
|
||
|
|
tables.append(EmbeddingTable(n_dims, vocab_size, initializer))
|
||
|
|
lengths.append(window_size)
|
||
|
|
|
||
|
|
self.input_layer = InputLayer(lengths, tables)
|
||
|
|
|
||
|
|
self.train_func = train_func
|
||
|
|
self.predict_func = predict_func
|
||
|
|
|
||
|
|
self.model_loc = model_loc
|
||
|
|
if self.model_loc and path.exists(self.model_loc):
|
||
|
|
self._model.load(self.model_loc, freq_thresh=0)
|
||
|
|
|
||
|
|
def train(self, Instance eg):
|
||
|
|
pass
|
||
|
|
|
||
|
|
def predict(self, Instance eg):
|
||
|
|
|
||
|
|
cdef const weight_t* score(self, atom_t* context) except NULL:
|
||
|
|
self.set_scores(self._scores, context)
|
||
|
|
return self._scores
|
||
|
|
|
||
|
|
cdef int set_scores(self, weight_t* scores, atom_t* context) except -1:
|
||
|
|
# TODO f(context) --> Values
|
||
|
|
self._input_layer.fill(self._x, self._values, use_avg=False)
|
||
|
|
theano_scores = self._predict(self._x)
|
||
|
|
for i in range(self.n_classes):
|
||
|
|
output[i] = theano_scores[i]
|
||
|
|
|
||
|
|
cdef int update(self, atom_t* context, class_t guess, class_t gold, int cost) except -1:
|
||
|
|
# TODO f(context) --> Values
|
||
|
|
self._input_layer.fill(self._x, self._values, use_avg=False)
|
||
|
|
|