Merge e14b8dfec5 into 22ad513c72

comfy/model_patcher.py

@@ -498,12 +498,20 @@ class ModelPatcher:
                     key = k[0]
                     if len(k) > 2:
                         function = k[2]
-
+                org_key=key.replace("diffusion_model", "diffusion_model._orig_mod")
                 if key in model_sd:
                     p.add(k)
                     current_patches = self.patches.get(key, [])
                     current_patches.append((strength_patch, patches[k], strength_model, offset, function))
                     self.patches[key] = current_patches
+                    self.patches[org_key] = current_patches
+                elif org_key in model_sd:
+                    if key in self.patches:
+                        self.patches.pop(key)
+                    p.add(k)
+                    current_patches = self.patches.get(org_key, [])
+                    current_patches.append((strength_patch, patches[k], strength_model, offset, function))
+                    self.patches[org_key] = current_patches
 
             self.patches_uuid = uuid.uuid4()
             return list(p)

comfy_extras/nodes_torch_compile.py

@@ -1,21 +1,64 @@
 import torch
+import importlib
+
 
 class TorchCompileModel:
     @classmethod
     def INPUT_TYPES(s):
-        return {"required": { "model": ("MODEL",),
+        if importlib.util.find_spec("openvino") is not None:
-                             "backend": (["inductor", "cudagraphs"],),
+            import openvino as ov
-                              }}
+
+            core = ov.Core()
+            available_devices = core.available_devices
+        else:
+            available_devices = []
+
+        return {
+            "required": {
+                "model": ("MODEL",),
+                "backend": (["inductor", "cudagraphs", "openvino"],),
+            },
+            "optional": {
+                "openvino_device": (available_devices,),
+            },
+        }
+
     RETURN_TYPES = ("MODEL",)
     FUNCTION = "patch"
 
     CATEGORY = "_for_testing"
     EXPERIMENTAL = True
 
-    def patch(self, model, backend):
+    def patch(self, model, backend, openvino_device):
+        print(model.__class__.__name__)
+        if backend == "openvino":
+            options = {"device": openvino_device}
+            try:
+                import openvino.torch
+            except ImportError:
+                raise ImportError(
+                    "Could not import openvino python package. "
+                    "Please install it with `pip install openvino`."
+                )
+            import openvino.frontend.pytorch.torchdynamo.execute as ov_ex
+
+            torch._dynamo.reset()
+            ov_ex.compiled_cache.clear()
+            ov_ex.req_cache.clear()
+            ov_ex.partitioned_modules.clear()
+        else:
+            options = None
         m = model.clone()
-        m.add_object_patch("diffusion_model", torch.compile(model=m.get_model_object("diffusion_model"), backend=backend))
+        m.add_object_patch(
-        return (m, )
+            "diffusion_model",
+            torch.compile(
+                model=m.get_model_object("diffusion_model"),
+                backend=backend,
+                options=options,
+            ),
+        )
+        return (m,)
+
 
 NODE_CLASS_MAPPINGS = {
     "TorchCompileModel": TorchCompileModel,