flagged the loader as not implemented, for now

__init__.py

@@ -1,7 +1,6 @@
 from .common import *
 from .torchvulkan_loader import *
 
-
 #  Map all your custom nodes classes with the names that will be displayed in the UI.
 NODE_CLASS_MAPPINGS = {
 	"Torchvulkan Loader": TorchVulkanLoader

prestartup_script.py

@@ -0,0 +1,7 @@
+import comfy
+import torchvulkan
+import torch
+
+global cpu_state
+cpu_state = None
+

torchvulkan_loader.py

@@ -25,6 +25,7 @@ class TorchVulkanLoader:
 	CATEGORY = "Backends"
 	
 	def load_to_torchvulkan(self, device, model = None, clip = None, vae = None):
+		raise NotImplementedError
 		device = torch.device(f"vulkan:{device}")
 		if model: model.to(device)
 		if clip: clip.to(device)

vulkan_monkeypatch.py

@@ -0,0 +1,28 @@
+import comfy
+import comfy.model_management
+
+# Patched version of comfy.model_management.get_torch_device that allows vulkan devices to be treated as default
+def get_torch_device_patched():
+	global directml_enabled
+	global cpu_state
+	if directml_enabled:
+		global directml_device
+		return directml_device
+	if cpu_state == CPUState.MPS:
+		return torch.device("mps")
+	if cpu_state == CPUState.CPU:
+		return torch.device("cpu")
+	else:
+		if True:
+			# for now, just see if this works c:
+			return torch.device(f"vulkan:0")
+		else:
+			if is_intel_xpu():
+				return torch.device("xpu", torch.xpu.current_device())
+			elif is_ascend_npu():
+				return torch.device("npu", torch.npu.current_device())
+			elif is_mlu():
+				return torch.device("mlu", torch.mlu.current_device())
+			else:
+				return torch.device(torch.cuda.current_device())
+comfy.model_management.get_torch_device = get_torch_device_patched