| """ | |
| Split the dataset into training and test set. | |
| Usage: python3 -m fastchat.data.split_train_test --in sharegpt.json | |
| """ | |
| import argparse | |
| import json | |
| import numpy as np | |
| if __name__ == "__main__": | |
| parser = argparse.ArgumentParser() | |
| parser.add_argument("--in-file", type=str, required=True) | |
| parser.add_argument("--begin", type=int, default=0) | |
| parser.add_argument("--end", type=int, default=100) | |
| parser.add_argument("--ratio", type=float, default=0.9) | |
| args = parser.parse_args() | |
| content = json.load(open(args.in_file, "r")) | |
| np.random.seed(0) | |
| perm = np.random.permutation(len(content)) | |
| content = [content[i] for i in perm] | |
| split = int(args.ratio * len(content)) | |
| train_set = content[:split] | |
| test_set = content[split:] | |
| print(f"#train: {len(train_set)}, #test: {len(test_set)}") | |
| train_name = args.in_file.replace(".json", "_train.json") | |
| test_name = args.in_file.replace(".json", "_test.json") | |
| json.dump(train_set, open(train_name, "w"), indent=2, ensure_ascii=False) | |
| json.dump(test_set, open(test_name, "w"), indent=2, ensure_ascii=False) | |