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778d47d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 | from datasets import load_from_disk
import argparse
import datasets
import numpy as np
from datasets import Dataset
# add arguments data/llm_alignment/spider-p1
parser = argparse.ArgumentParser()
parser.add_argument("--data_dir", type=str, help="path to the data directory")
args = parser.parse_args()
# read all train data from the data directory, including
# dpo-llama-3-end2end-spider_train_fixed_sql
# dpo-llama-3-end2end-spider_train_planner
# dpo-llama-3-end2end-spider_train_validator_condition
# dpo-llama-3-end2end-spider_train_validator_join
# dpo-llama-3-end2end-spider_train_validator_select
# dpo-llama-3-end2end-spider_train_validator_order
import glob
import os
data_dirs = glob.glob(args.data_dir + "/*train*")
data_dirs = [x for x in data_dirs if os.path.isdir(x)]
print(data_dirs)
for data_dir in data_dirs:
dataset_train = load_from_disk(data_dir)
# load dev data
dev_file = data_dir.replace("train", "dev")
if os.path.exists(dev_file):
dataset_dev = load_from_disk(dev_file)
dataset_dev = list(dataset_dev['train_dpo'])
dataset_dev = np.random.permutation(dataset_dev)[:2000].tolist()
dataset_train['test_dpo'] = Dataset.from_list(dataset_dev)
print(data_dir)
print(dataset_train)
# save the merged data to other directory
dataset_train.save_to_disk(data_dir.replace("train", "train_dev"))
print(data_dir.replace("train", "train_dev"))
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