67 lines
1.5 KiB
Python
67 lines
1.5 KiB
Python
from .common import *
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import comfy
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import comfy.model_patcher
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import comfy.sd
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from .vulkan_monkeypatch import *
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def load_ModelPatcher(device, mp):
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assert isinstance(mp.model, torch.nn.Module)
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# move the model to the device
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mp.model.to(device)
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# overwrite load device
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mp.load_device = device
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# this will at least function, I hope
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class TorchVulkanLoader:
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def __init__(self):
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pass
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@classmethod
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def INPUT_TYPES(self):
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devices = [i for i in range(torchvulkan.device_count())]
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return {
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"required": {
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"device": (devices, {"default": 0})
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},
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"optional": {
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"model": ("MODEL",),
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"clip": ("CLIP",),
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"vae": ("VAE",)
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}
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}
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RETURN_TYPES = ("MODEL", "CLIP", "VAE")
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FUNCTION = "load_to_torchvulkan"
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CATEGORY = "Backends"
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def load_to_torchvulkan(self, device, model = None, clip = None, vae = None):
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# only do monkeypatching if node is invoked or whatever
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comfy.model_management.get_torch_device = get_torch_device_patched
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comfy.model_management.get_free_memory = get_free_memory_patched
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device = torch.device(f"vulkan:{device}")
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if not model is None:
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if isinstance(model, comfy.model_patcher.ModelPatcher):
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load_ModelPatcher(device, model)
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else:
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raise NotImplementedError
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if not clip is None:
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if isinstance(clip, comfy.sd.CLIP):
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load_ModelPatcher(device, clip.patcher)
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else:
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raise NotImplementedError
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if not vae is None:
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if isinstance(vae, comfy.sd.VAE):
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load_ModelPatcher(device, vae.patcher)
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else:
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raise NotImplementedError
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return model, clip, vae
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