translator = Translator(tr_config)
print('training started:')
EPOCH_NUM = int(conf['epoch size'])
BATCH_SIZE = int(conf['batch size'])
PRINT_PER = int(conf['print period'])
SAVE_PER = int(conf['save period'])
data_so_far = 0
data_size = int(sum([len(x) for x in en_corpus.datas]))
batch_index = 0
while data_so_far < EPOCH_NUM * data_size:
try:
x = en_corpus.next_batch(BATCH_SIZE)
y = fa_corpus.next_batch(BATCH_SIZE)
loss = translator.train_model(x, y)
if batch_index % PRINT_PER == 0:
assert en_corpus.indexes == fa_corpus.indexes
assert en_corpus.div_index == fa_corpus.div_index
print(batch_index, ': ', loss)
if batch_index % SAVE_PER == SAVE_PER - 1:
print('saving...')
en_corpus.save_corpus_state()
fa_corpus.save_corpus_state()
translator.save_model()
print('finished')
batch_index += 1
data_so_far += x.shape[1]
except KeyboardInterrupt:
break
print('finished')
