update openvino backend

comfy/cli_args.py

@@ -83,6 +83,7 @@ fpte_group.add_argument("--fp32-text-enc", action="store_true", help="Store text
 parser.add_argument("--force-channels-last", action="store_true", help="Force channels last format when inferencing the models.")
 
 parser.add_argument("--directml", type=int, nargs="?", metavar="DIRECTML_DEVICE", const=-1, help="Use torch-directml.")
+parser.add_argument("--openvino", type=str, default="GPU", help="Run OpenVINO inference engine on the specified device.")
 
 parser.add_argument("--oneapi-device-selector", type=str, default=None, metavar="SELECTOR_STRING", help="Sets the oneAPI device(s) this instance will use.")
 parser.add_argument("--disable-ipex-optimize", action="store_true", help="Disables ipex.optimize default when loading models with Intel's Extension for Pytorch.")

comfy/model_management.py

@@ -93,7 +93,7 @@ try:
 except:
     npu_available = False
 
-if args.cpu:
+if args.cpu or args.openvino:
     cpu_state = CPUState.CPU
 
 def is_intel_xpu():

comfy/model_patcher.py

@@ -469,6 +469,15 @@ class ModelPatcher:
                     current_patches = self.patches.get(key, [])
                     current_patches.append((strength_patch, patches[k], strength_model, offset, function))
                     self.patches[key] = current_patches
+                else:
+                    new_key=key.replace("diffusion_model","diffusion_model._orig_mod")
+                    if new_key in model_sd:
+                        p.add(k)
+                        if key in self.patches:
+                            self.patches.pop(key)
+                        current_patches = self.patches.get(new_key, [])
+                        current_patches.append((strength_patch, patches[k], strength_model, offset, function))
+                        self.patches[new_key] = current_patches
 
             self.patches_uuid = uuid.uuid4()
             return list(p)

comfy/sampler_helpers.py

@@ -1,4 +1,5 @@
 from __future__ import annotations
+from comfy.cli_args import args
 import uuid
 import comfy.model_management
 import comfy.conds
@@ -114,7 +115,11 @@ def prepare_sampling(model: ModelPatcher, noise_shape, conds, model_options=None
     minimum_memory_required = model.memory_required([noise_shape[0]] + list(noise_shape[1:])) + inference_memory
     comfy.model_management.load_models_gpu([model] + models, memory_required=memory_required, minimum_memory_required=minimum_memory_required)
     real_model = model.model
-
+    if args.openvino and real_model.diffusion_model.__class__.__name__=="UNetModel":
+        import openvino.torch
+        import torch
+        print("Unet is being compiled using OpenVINO")
+        real_model.diffusion_model = torch.compile(real_model.diffusion_model, backend="openvino", options = {"device" : args.openvino, "model_caching" : False, "cache_dir": "./model_cache"})
     return real_model, conds, models
 
 def cleanup_models(conds, models):