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import os
import pandas as pd
import json
from tqdm import tqdm
from glob import glob
from collections import defaultdict
# root_path = '/etc/ssd1/jiangzhongtao/baai_embedding_tune/data/all_collect/mteb-classification'
# fnames = os.listdir(root_path)
# dataset2size = defaultdict(int)
# for fname in fnames:
# _, name, lang = fname.split('_')
# fname = os.path.join(root_path, fname)
# with open(fname, 'r') as f:
# for line in f:
# dataset2size[name] += 1
src = 'mteb-Clustering'
# postfix = '_hn'
with open(f'/etc/ssd1/jiangzhongtao/baai_embedding_tune/data/all_collect/instructions/{src}_instructions.json') as f:
instructions = json.load(f)
# src += postfix
root_path = f'/etc/ssd1/jiangzhongtao/baai_embedding_tune/data/all_collect/{src}'
fnames = os.listdir(root_path)
pbar = tqdm()
for fname in tqdm(fnames):
_, name, lang = fname[:-6].split('_')
instruction = instructions[name]
f_in = open(os.path.join(root_path, fname), 'r')
f_out = open(os.path.join(root_path, fname) + '.inst', 'w')
for line in f_in:
line = json.loads(line)
line['instruction'] = instruction
line = json.dumps(line, ensure_ascii=False)
f_out.write(line + '\n')
pbar.update(1)
f_in.close()
f_out.close()
for fname in tqdm(glob(f'/etc/ssd1/jiangzhongtao/baai_embedding_tune/data/all_collect/{src}/*.jsonl')):
os.remove(fname)
for fname in tqdm(glob(f'/etc/ssd1/jiangzhongtao/baai_embedding_tune/data/all_collect/{src}/*.jsonl.inst')):
os.rename(fname, fname.replace('.inst', ''))
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