NeuralChat-LLAMA-POC / fastchat /data /optional_clean.py
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"""
Do optional cleaning (e.g., remove some languages).
Usage:
python3 -m fastchat.data.optional_clean --in input.json --out output.json --keep-lang en
python3 -m fastchat.data.optional_clean --in input.json --out output.json --skip-lang en
Requirement:
pip3 install polyglot icu pyicu pycld2 morfessor
"""
import argparse
import json
import re
import polyglot
from polyglot.detect import Detector
import pycld2
from tqdm import tqdm
def skip(conv, args):
# Remove certain languages
if args.keep_lang != "all" or args.skip_lang is not None:
text = "\n".join([x["value"] for x in conv["conversations"]])
try:
lang_code = Detector(text).language.code
except (pycld2.error, polyglot.detect.base.UnknownLanguage):
lang_code = "unknown"
if args.keep_lang != "all" and lang_code != args.keep_lang:
return True
if lang_code == args.skip_lang:
return True
# Remove repetitive numbers
if args.reduce_rep:
for sentence in conv["conversations"]:
val = sentence["value"]
sub = re.search(r"(\d)\1{8}", val)
if sub is not None:
return True
return False
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("--in-file", type=str, required=True)
parser.add_argument("--out-file", type=str)
parser.add_argument(
"--keep-lang",
type=str,
default="all",
choices=["all", "en"],
help="Only keep certain langauges.",
)
parser.add_argument("--skip-lang", type=str, help="Skip a specific language.")
# NOTE: Be careful about reduce_rep which may remove some good data.
# For example, addresses could have long consecutive 0's
parser.add_argument("--reduce-rep", action="store_true")
args = parser.parse_args()
in_file = args.in_file
out_file = args.out_file
keep_lang = args.keep_lang
skip_lang = args.skip_lang
reduce_rep = args.reduce_rep
assert keep_lang == "all" or skip_lang is None
if out_file is None:
out_file = "sharegpt_clean"
if keep_lang != "all":
out_file += "_" + keep_lang
if skip_lang is not None:
out_file += "_skip_" + skip_lang
if reduce_rep:
out_file += "_reduce_rep"
out_file += ".json"
content = json.load(open(in_file, "r"))
num_conv = len(content)
new_content = []
for conv in tqdm(content):
if not skip(conv, args):
new_content.append(conv)
print(f"return {len(new_content)} out of {len(content)}, start dump ...")
json.dump(new_content, open(out_file, "w"), indent=2)