def getBatchData(self):
src_lang = self.src_lang
tgt_lang = self.tgt_lang
tgt_vocab_size = self.tgt_vocab_size
ngram_size = self.ngram_size
is_shuffle = self.is_shuffle
chunk_size = self.chunk_size
src_window = self.src_window
opt = self.opt
(data_x, data_y) = io_read_ngram.get_joint_ngrams(self.src_f, self.tgt_f, self.align_f, \
tgt_vocab_size, ngram_size, src_window, opt, num_read_lines=chunk_size)
return (data_x, data_y)
def getBatchData(self):
src_lang = self.src_lang
tgt_lang = self.tgt_lang
tgt_vocab_size = self.tgt_vocab_size
ngram_size = self.ngram_size
is_shuffle = self.is_shuffle
chunk_size = self.chunk_size
src_window = self.src_window
opt = self.opt
(data_x, data_y) = io_read_ngram.get_joint_ngrams(self.src_f, self.tgt_f, self.align_f, \
tgt_vocab_size, ngram_size, src_window, opt, num_read_lines=chunk_size)
return (data_x, data_y)
def loadBatchData(self, isInitialLoad=False):
src_lang = self.src_lang
tgt_lang = self.tgt_lang
tgt_vocab_size = self.tgt_vocab_size
ngram_size = self.ngram_size
chunk_size = self.chunk_size
src_window = self.src_window
opt = self.opt
(self.data_x, self.data_y) = io_read_ngram.get_joint_ngrams(self.src_f, self.tgt_f, self.align_f, \
tgt_vocab_size, ngram_size, src_window, opt, num_read_lines=chunk_size)
if isInitialLoad == False:
assert (type(self.model) == model_nnlm.ModelNNLM)
return self.model.updateTrainModelInput(self.data_x, self.data_y)
def loadBatchData(self, isInitialLoad=False):
src_lang = self.src_lang
tgt_lang = self.tgt_lang
tgt_vocab_size = self.tgt_vocab_size
ngram_size = self.ngram_size
chunk_size = self.chunk_size
src_window = self.src_window
opt = self.opt
(self.data_x, self.data_y) = io_read_ngram.get_joint_ngrams(self.src_f, self.tgt_f, self.align_f, \
tgt_vocab_size, ngram_size, src_window, opt, num_read_lines=chunk_size)
if isInitialLoad == False:
assert(type(self.model) == model_nnlm.ModelNNLM)
return self.model.updateTrainModelInput(self.data_x, self.data_y)
