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import argparse
from fengshen import UbertPipelines
import os
import json
from tqdm import tqdm
def load_data(data_path):
with open(data_path, 'r', encoding='utf8') as f:
lines = f.readlines()
samples = [json.loads(line) for line in tqdm(lines)]
return samples
def main():
total_parser = argparse.ArgumentParser("TASK NAME")
total_parser.add_argument('--data_dir', default='./data', type=str)
total_parser.add_argument('--train_data', default='train.json', type=str)
total_parser.add_argument('--valid_data', default='dev.json', type=str)
total_parser.add_argument('--test_data', default='test.json', type=str)
total_parser.add_argument('--output_path',default='./predict.json', type=str)
total_parser = UbertPipelines.pipelines_args(total_parser)
args = total_parser.parse_args()
train_data = load_data(os.path.join(args.data_dir, args.train_data))
dev_data = load_data(os.path.join(args.data_dir, args.valid_data))
test_data = load_data(os.path.join(args.data_dir, args.test_data))
# test_data = test_data[:10]
model = UbertPipelines(args)
if args.train:
model.fit(train_data, dev_data)
result = model.predict(test_data)
for line in result[:20]:
print(line)
with open(args.output_path, 'w', encoding='utf8') as f:
for line in result:
json_data = json.dumps(line, ensure_ascii=False)
f.write(json_data+'\n')
if __name__ == "__main__":
main()
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