Finished implementation of wanvideowrapper nodes, updated example workflows, added some benchmarking files for reference.

Author: pollockjj

assets/flux1_dev_Q8_0_benchmark.png

@@ -830,29 +830,37 @@ def loadmodel(self, model, base_precision, load_device, device):
         original_loader = NODE_CLASS_MAPPINGS["DownloadAndLoadWav2VecModel"]()
         return original_loader.loadmodel(model, base_precision, load_device)
 
-class WanVideoControlnetLoader:
+class WanVideoUni3C_ControlnetLoader:
     @classmethod
     def INPUT_TYPES(s):
+        devices = get_device_list()
+        default_device = devices[1] if len(devices) > 1 else devices[0]
         return {
             "required": {
                 "model": (folder_paths.get_filename_list("controlnet"), {"tooltip": "These models are loaded from the 'ComfyUI/models/controlnet' -folder",}),
-
-            "base_precision": (["fp32", "bf16", "fp16"], {"default": "bf16"}),
-            "quantization": (['disabled', 'fp8_e4m3fn', 'fp8_e4m3fn_fast', 'fp8_e5m2', 'fp8_e4m3fn_fast_no_ffn'], {"default": 'disabled', "tooltip": "optional quantization method"}),
-            "load_device": (["main_device", "offload_device"], {"default": "main_device", "tooltip": "Initial device to load the model to, NOT recommended with the larger models unless you have 48GB+ VRAM"}),
+                "base_precision": (["fp32", "bf16", "fp16"], {"default": "fp16"}),
+                "quantization": (['disabled', 'fp8_e4m3fn', 'fp8_e5m2'], {"default": 'disabled', "tooltip": "optional quantization method"}),
+                "load_device": (["main_device", "offload_device"], {"default": "main_device", "tooltip": "Initial device to load the model to, NOT recommended with the larger models unless you have 48GB+ VRAM"}),
+                "device": (devices, {"default": default_device}),
+                "attention_mode": ([
+                        "sdpa",
+                        "sageattn",
+                        ], {"default": "sdpa"}),
             },
+            "optional": {
+                "compile_args": ("WANCOMPILEARGS", ),
+            }
         }
 
     RETURN_TYPES = ("WANVIDEOCONTROLNET",)
     RETURN_NAMES = ("controlnet", )
     FUNCTION = "loadmodel"
-    CATEGORY = "WanVideoWrapper"
-    DESCRIPTION = "Loads ControlNet model from 'https://huggingface.co/collections/TheDenk/wan21-controlnets-68302b430411dafc0d74d2fc'"
+    CATEGORY = "multigpu/WanVideoWrapper"
 
-    def loadmodel(self, model, base_precision, load_device, quantization):
+    def loadmodel(self, model, base_precision, load_device, quantization, attention_mode, compile_args=None):
         from . import set_current_device
 
         set_current_device(device)
-
-        original_loader = NODE_CLASS_MAPPINGS["WanVideoControlnetLoader"]()
-        return original_loader.loadmodel(model, base_precision, load_device, quantization)
+        
+        original_loader = NODE_CLASS_MAPPINGS["WanVideoUni3C_ControlnetLoader"]()
+        return original_loader.loadmodel(model, base_precision, load_device, quantization, attention_mode, compile_args)