def test(model_dir,
input_path,
output_path,
beam_size=4,
max_dec_len=60,
dec_alpha=0.6):
gpt2 = GPT2(config_path)
generator = beam_search_generator(gpt2,
beam_size=beam_size,
model_directory=model_dir,
max_dec_len=max_dec_len,
dec_alpha=dec_alpha)
sess = generator.build_graph_and_restore(
eos_id=gpt2.text_enc.encode('\n')[0])
lines = read_file_lines(input_path)
result = []
for line in lines:
result.append(generator.generate(sess, line))
sess.close()
write_file_lines(output_path, result)
def test(
config_path,
input_num,
model_dir='./models/ori_rule/formality_infer/',
input_path='../training_data/dif_models/eval.ori_rule',
output_path='../evaluate/gyafc_model_outputs/fr_out/formal.gpt.cat_ori_rule.old',
beam_size=4,
max_dec_len=60,
dec_alpha=0.6):
gpt2 = NMT_GPT(config_path=config_path, input_num=input_num)
generator = beam_search_generator(gpt2,
beam_size=beam_size,
model_directory=model_dir,
max_dec_len=max_dec_len,
dec_alpha=dec_alpha)
sess = generator.build_graph_and_restore(
eos_id=gpt2.text_enc.encode('\n')[0])
lines = read_file_lines(input_path)
result = []
for line in lines:
result.append(generator.generate(sess, line, multi_pls=True))
print(line + ' ||| ' + result[-1].strip())
sess.close()
write_file_lines(output_path, result)