[Bugfix] Fix handling of Tensorizer arguments for LoadConfig (#20643)

Signed-off-by: Sanger Steel <sangersteel@gmail.com>

vllm/engine/arg_utils.py

@@ -1003,41 +1003,27 @@ class EngineArgs:
             override_attention_dtype=self.override_attention_dtype,
         )
 
-    def valid_tensorizer_config_provided(self) -> bool:
-        """
-        Checks if a parseable TensorizerConfig was passed to
-        self.model_loader_extra_config. It first checks if the config passed
-        is a dict or a TensorizerConfig object directly, and if the latter is
-        true (by checking that the object has TensorizerConfig's
-        .to_serializable() method), converts it in to a serializable dict
-        format
-        """
-        if self.model_loader_extra_config:
-            if hasattr(self.model_loader_extra_config, "to_serializable"):
-                self.model_loader_extra_config = (
-                    self.model_loader_extra_config.to_serializable())
-            for allowed_to_pass in ["tensorizer_uri", "tensorizer_dir"]:
-                try:
-                    self.model_loader_extra_config[allowed_to_pass]
-                    return False
-                except KeyError:
-                    pass
-        return True
+    def validate_tensorizer_args(self):
+        from vllm.model_executor.model_loader.tensorizer import (
+            TensorizerConfig)
+        for key in self.model_loader_extra_config:
+            if key in TensorizerConfig._fields:
+                self.model_loader_extra_config["tensorizer_config"][
+                    key] = self.model_loader_extra_config[key]
 
     def create_load_config(self) -> LoadConfig:
 
         if self.quantization == "bitsandbytes":
             self.load_format = "bitsandbytes"
 
-        if (self.load_format == "tensorizer"
-                and self.valid_tensorizer_config_provided()):
-            logger.info("Inferring Tensorizer args from %s", self.model)
-            self.model_loader_extra_config = {"tensorizer_dir": self.model}
-        else:
-            logger.info(
-                "Using Tensorizer args from --model-loader-extra-config. "
-                "Note that you can now simply pass the S3 directory in the "
-                "model tag instead of providing the JSON string.")
+        if self.load_format == "tensorizer":
+            if hasattr(self.model_loader_extra_config, "to_serializable"):
+                self.model_loader_extra_config = (
+                    self.model_loader_extra_config.to_serializable())
+            self.model_loader_extra_config["tensorizer_config"] = {}
+            self.model_loader_extra_config["tensorizer_config"][
+                "tensorizer_dir"] = self.model
+            self.validate_tensorizer_args()
 
         return LoadConfig(
             load_format=self.load_format,