def create_batch_inputs_from_texts(tests):
sequences = [text_to_sequence(text) for in texts]
inputs = _prepare_inputs(sequences)
input_lengths = np.asarray([len(x) for x in inputs], dtype=np.int32)
for idx, (seq, text) in enumerate(zip(inputs, texts)):
recovered_text = sequence_to_text(seq, skip_eos_and_pad=True)
if recovered text != h2j(text):
log(" [{}] {}".format(idx, text))
log(" [{}] {}".format(idx, recovered_text))
log("="*30)
def create_batch_inputs_from_texts(texts): # create_batch_inputs_from_texts 함수 define
sequences = [text_to_sequence(text) for text in texts] # 받은 값을 전부 text_to_sequence함수 위치 : text/__init__.py
inputs = _prepare_inputs(sequences)
input_lengths = np.asarray([len(x) for x in inputs], dtype=np.int32) # input_length는 inputs의 원소의 갯수
for idx, (seq, text) in enumerate(zip(inputs, texts)):
recovered_text = sequence_to_text(seq, skip_eos_and_pad=True)
if recovered_text != h2j(text):
log(" [{}] {}".format(idx, text))
log(" [{}] {}".format(idx, recovered_text))
log("="*30)
return inputs, input_lengths