[Core] Unified quantization framework (#1764)

vllm_omni/diffusion/model_loader/diffusers_loader.py

@@ -260,7 +260,7 @@ class DiffusersPipelineLoader:
     ) -> nn.Module:
         """Load a model with the given configurations."""
         # CPU offload + FP8: load weights on device for FP8 quantization
-        if load_device == "cpu" and od_config.quantization and od_config.quantization.lower() != "none":
+        if load_device == "cpu" and od_config.quantization_config is not None:
             load_device = device.type
             logger.info(f"Quantization enabled with CPU offload, using {load_device} for weight loading")
 
@@ -342,28 +342,35 @@ class DiffusersPipelineLoader:
         quant_config = od_config.quantization_config
         if quant_config is None:
             return False
-        # Fast path: mapping-style config (e.g., DictConfig)
-        if isinstance(quant_config, dict):
-            method = str(quant_config.get("method", "")).lower()
-            if method != "gguf":
-                return False
-            gguf_model = quant_config.get("gguf_model")
-            if not gguf_model:
-                raise ValueError("GGUF quantization requires quantization_config.gguf_model")
+
+        # New API: DiffusionGGUFConfig (QuantizationConfig subclass)
+        from vllm_omni.quantization.gguf_config import DiffusionGGUFConfig
+
+        if isinstance(quant_config, DiffusionGGUFConfig):
+            if quant_config.gguf_model is None:
+                raise ValueError("GGUF quantization requires gguf_model")
             return True
 
-        # Normal path: DiffusionQuantizationConfig
-        if not hasattr(quant_config, "get_name"):
-            # Fallback: if it carries gguf_model, treat as GGUF
-            gguf_model = getattr(quant_config, "gguf_model", None)
-            return bool(gguf_model)
-        is_gguf = quant_config.get_name() == "gguf"
-        if not is_gguf:
+        # Dict-style config: {"method": "gguf", "gguf_model": "..."}
+        if isinstance(quant_config, dict):
+            if quant_config.get("method") == "gguf":
+                if not quant_config.get("gguf_model"):
+                    raise ValueError("GGUF quantization requires gguf_model")
+                return True
             return False
-        gguf_model = getattr(quant_config, "gguf_model", None)
-        if gguf_model is None:
-            raise ValueError("GGUF quantization requires quantization_config.gguf_model")
-        return True
+
+        # Check by name for any config that reports as "gguf"
+        if hasattr(quant_config, "get_name") and quant_config.get_name() == "gguf":
+            gguf_model = getattr(quant_config, "gguf_model", None)
+            if gguf_model is None:
+                raise ValueError("GGUF quantization requires gguf_model")
+            return True
+
+        # Fallback: object with gguf_model attribute but no get_name
+        if hasattr(quant_config, "gguf_model") and quant_config.gguf_model:
+            return True
+
+        return False
 
     def _is_transformer_source(self, source: "ComponentSource") -> bool:
         if source.subfolder == "transformer":