Download tools/prepare_codec.py from czyhust/west_gstar: direct link, hf CLI and curl.
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https://huggingface.co/czyhust/west_gstar/resolve/main/tools/prepare_codec.py
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| #!/usr/bin/env python3 | |
| # -*- coding: utf-8 -*- | |
| # Copyright 2025 Hao Yin(1049755192@qq.com) | |
| # prepare the codec.jsonl file for the tts flow inference | |
| import json | |
| import re | |
| import sys | |
| result_jsonl = sys.argv[1] | |
| test_jsonl = sys.argv[2] | |
| codec_jsonl = sys.argv[3] | |
| # extract llm_token from the result.jsonl | |
| llm_token_list = [] | |
| with open(result_jsonl) as f: | |
| for line in f: | |
| arr = line.strip() | |
| numbers = re.findall(r"speech_(\d+)", arr) | |
| result = " ".join(numbers) | |
| llm_token_list.append(result) | |
| # load the test jsonl file | |
| json_lines = open(test_jsonl).readlines() | |
| assert len(llm_token_list) == len( | |
| json_lines | |
| ), "llm_token_list and json_lines length mismatch" | |
| data = [] | |
| for i, line in enumerate(json_lines): | |
| item = json.loads(line) | |
| # add the llm_token to the item | |
| item["llm_token"] = llm_token_list[i] | |
| data.append(item) | |
| # save the data to the codec.jsonl file | |
| with open(codec_jsonl, "w") as f: | |
| for x in data: | |
| f.write(json.dumps(x, ensure_ascii=False) + "\n") | |