def getTrainModel(self, data_x, data_y, data_sm):
self.ngram_start_index = T.lscalar()
self.ngram_end_index = T.lscalar()
self.sm_start_index = T.lscalar()
self.sm_end_index = T.lscalar()
self.learning_rate = T.scalar()
# TRAIN_MODEL
self.train_outputs = [self.cost, self.grad_norm]
self.train_set_x, self.train_set_y, self.train_set_sm = io_read_ngram.shared_dataset(
[data_x, data_y, data_sm])
self.int_train_set_y = T.cast(self.train_set_y, 'int32')
self.train_model = theano.function(
inputs=[
self.ngram_start_index, self.ngram_end_index,
self.sm_start_index, self.sm_end_index, self.learning_rate
],
outputs=self.train_outputs,
updates=self.updates,
givens={
self.x:
self.train_set_x[self.ngram_start_index:self.ngram_end_index],
self.y:
self.int_train_set_y[self.ngram_start_index:self.
ngram_end_index],
self.sm:
self.train_set_sm[self.sm_start_index:self.sm_end_index],
self.lr:
self.learning_rate
})
return self.train_model
def getTrainModel(self, data_x, data_y, data_sm):
self.ngram_start_index = T.lscalar()
self.ngram_end_index = T.lscalar()
self.sm_start_index = T.lscalar()
self.sm_end_index = T.lscalar()
self.learning_rate = T.scalar()
# TRAIN_MODEL
self.train_outputs = [self.cost, self.grad_norm]
self.train_set_x, self.train_set_y, self.train_set_sm = io_read_ngram.shared_dataset([data_x, data_y, data_sm])
self.int_train_set_y = T.cast(self.train_set_y, "int32")
self.train_model = theano.function(
inputs=[
self.ngram_start_index,
self.ngram_end_index,
self.sm_start_index,
self.sm_end_index,
self.learning_rate,
],
outputs=self.train_outputs,
updates=self.updates,
givens={
self.x: self.train_set_x[self.ngram_start_index : self.ngram_end_index],
self.y: self.int_train_set_y[self.ngram_start_index : self.ngram_end_index],
self.sm: self.train_set_sm[self.sm_start_index : self.sm_end_index],
self.lr: self.learning_rate,
},
)
return self.train_model
def loadTestSet(self, test_data_package):
self.test_set_x, self.test_set_y, self.test_set_sm = test_data_package
self.shared_test_set_x, self.shared_test_set_y, self.shared_test_set_sm = io_read_ngram.shared_dataset(test_data_package)
self.shared_test_set_y = T.cast(self.shared_test_set_y, 'int32')
self.test_set_loaded = True
def loadValidSet(self, valid_data_package):
self.valid_set_x, self.valid_set_y, self.valid_set_sm = valid_data_package
self.shared_valid_set_x, self.shared_valid_set_y, self.shared_valid_set_sm = io_read_ngram.shared_dataset(valid_data_package)
self.shared_valid_set_y = T.cast(self.shared_valid_set_y, 'int32')
self.valid_set_loaded = True
