mirror of https://github.com/explosion/spaCy.git
45 lines
1.5 KiB
Cython
45 lines
1.5 KiB
Cython
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from thinc.example cimport Example
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cdef class TheanoModel(Model):
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def __init__(self, n_classes, input_layer, train_func, predict_func, model_loc=None):
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if model_loc is not None and path.isdir(model_loc):
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model_loc = path.join(model_loc, 'model')
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self.n_classes = n_classes
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tables = []
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lengths = []
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for window_size, n_dims, vocab_size in input_structure:
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tables.append(EmbeddingTable(n_dims, vocab_size, initializer))
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lengths.append(window_size)
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self.input_layer = InputLayer(lengths, tables)
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self.train_func = train_func
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self.predict_func = predict_func
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self.model_loc = model_loc
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if self.model_loc and path.exists(self.model_loc):
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self._model.load(self.model_loc, freq_thresh=0)
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def train(self, Instance eg):
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pass
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def predict(self, Instance eg):
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cdef const weight_t* score(self, atom_t* context) except NULL:
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self.set_scores(self._scores, context)
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return self._scores
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cdef int set_scores(self, weight_t* scores, atom_t* context) except -1:
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# TODO f(context) --> Values
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self._input_layer.fill(self._x, self._values, use_avg=False)
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theano_scores = self._predict(self._x)
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for i in range(self.n_classes):
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output[i] = theano_scores[i]
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cdef int update(self, atom_t* context, class_t guess, class_t gold, int cost) except -1:
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# TODO f(context) --> Values
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self._input_layer.fill(self._x, self._values, use_avg=False)
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