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Add fix_tokenizer.py, vllm_wrapper.sh, Dockerfile, and README for automatic tokenizer_config.json repair on Iluvatar BI-100 vLLM images.
96 lines
3.1 KiB
Python
96 lines
3.1 KiB
Python
#!/usr/bin/env python3
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"""
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检测并修复 tokenizer_config.json 中的两类问题：
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1. tokenizer_class 在 transformers 中不存在（如 TokenizersBackend）
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2. extra_special_tokens 为 list 格式（transformers 要求 dict）
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若存在问题，将 tokenizer 文件复制到 /tmp/fixed_tokenizer/ 并修复，
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最后将修复目录路径输出到 stdout。若无需修复，输出为空。
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"""
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import os
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import sys
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import json
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import shutil
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MODEL_DIR = sys.argv[1] if len(sys.argv) > 1 else os.environ.get("MODEL_DIR", "/model")
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OUT_DIR = "/tmp/fixed_tokenizer"
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def main():
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cfg_path = os.path.join(MODEL_DIR, "tokenizer_config.json")
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if not os.path.exists(cfg_path):
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return
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with open(cfg_path) as f:
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cfg = json.load(f)
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fixes = []
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# --- 检测 1：tokenizer_class 是否在 transformers 中存在 ---
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tokenizer_class = cfg.get("tokenizer_class", "")
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bad_tokenizer_class = False
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if tokenizer_class:
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import transformers
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if getattr(transformers, tokenizer_class, None) is None:
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bad_tokenizer_class = True
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fixes.append(f"tokenizer_class '{tokenizer_class}' not found in transformers")
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# --- 检测 2：extra_special_tokens 是否为 list 格式 ---
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bad_extra_special_tokens = (
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"extra_special_tokens" in cfg
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and isinstance(cfg["extra_special_tokens"], list)
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)
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if bad_extra_special_tokens:
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fixes.append("extra_special_tokens is a list, expected dict")
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if not fixes:
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return # 无需修复
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# 复制 tokenizer 文件到临时目录
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os.makedirs(OUT_DIR, exist_ok=True)
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for fname in [
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"tokenizer.json",
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"tokenizer_config.json",
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"special_tokens_map.json",
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"vocab.json",
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"merges.txt",
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"tokenizer.model",
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]:
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src = os.path.join(MODEL_DIR, fname)
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if os.path.exists(src):
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shutil.copy(src, OUT_DIR)
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# --- 修复 1：替换 tokenizer_class ---
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if bad_tokenizer_class:
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files = os.listdir(MODEL_DIR)
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if "tokenizer.json" in files:
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fixed_class = "PreTrainedTokenizerFast"
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elif "tokenizer.model" in files:
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fixed_class = "LlamaTokenizer"
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elif "vocab.json" in files and "merges.txt" in files:
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fixed_class = "GPT2TokenizerFast"
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else:
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fixed_class = "PreTrainedTokenizerFast"
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cfg["tokenizer_class"] = fixed_class
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print(
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f"[fix_tokenizer] tokenizer_class: '{tokenizer_class}' → '{fixed_class}'",
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file=sys.stderr,
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)
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# --- 修复 2：extra_special_tokens list → dict ---
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if bad_extra_special_tokens:
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orig_list = cfg["extra_special_tokens"]
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cfg["extra_special_tokens"] = {token: token for token in orig_list}
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print(
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f"[fix_tokenizer] extra_special_tokens: list({len(orig_list)}) → dict",
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file=sys.stderr,
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)
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with open(os.path.join(OUT_DIR, "tokenizer_config.json"), "w") as f:
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json.dump(cfg, f, indent=2)
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print(OUT_DIR) # 输出修复目录，供 entrypoint.sh 捕获
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main()
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