更新 NV A100 Patched 镜像合并/fix_tokenizer.py

NV A100 Patched 镜像合并/fix_tokenizer.py

@@ -1,6 +1,8 @@
 import os 
 import shutil
 import json
+import transformers
+import inspect
 from detect_tokenizer import detect
 
 MODEL_DIR = os.environ.get("MODEL_DIR", "/model")
@@ -33,18 +35,28 @@ if os.path.exists(cfg_path):
 else:
     cfg = {}
 
-if typ == "fast":
-    cfg["tokenizer_class"] = "PreTrainedTokenizerFast"
-elif typ == "sentencepiece":
-    cfg["tokenizer_class"] = "LlamaTokenizer"
-elif typ == "bpe":
-    cfg["tokenizer_class"] = "GPT2TokenizerFast"
-else:
-    cfg["tokenizer_class"] = "PreTrainedTokenizerFast"
+VALID_CLASSES = {
+    name for name, obj in inspect.getmembers(transformers)
+    if inspect.isclass(obj) and "Tokenizer" in name
+}
 
-bad_classes = ["TokenizersBackend", "TiktokenTokenizer"]
-if orig_cls in bad_classes:
-    print(f"[fix] override bad tokenizer_class: {orig_cls} → {cfg['tokenizer_class']}")        
+BAD_CLASSES = {"TokenizersBackend", "TiktokenTokenizer"}
+
+FALLBACK = {
+    "fast": "PreTrainedTokenizerFast",
+    "sentencepiece": "LlamaTokenizer",
+    "bpe": "GPT2TokenizerFast",
+}
+
+if orig_cls and orig_cls in VALID_CLASSES and orig_cls not in BAD_CLASSES:
+    print(f"[fix_tokenizer] tokenizer_class '{orig_cls}' is valid, skip override")
+else:
+    fallback = FALLBACK.get(typ, "PreTrainedTokenizerFast")
+    if orig_cls:
+        print(f"[fix] override bad tokenizer_class: {orig_cls} → {fallback}")
+    else:
+        print(f"[fix] tokenizer_class missing, set to: {fallback}")
+    cfg["tokenizer_class"] = fallback
 
 with open(cfg_path, "w") as f:
     json.dump(cfg, f)