56 lines
1.8 KiB
Python
56 lines
1.8 KiB
Python
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class ModelMergeSimple:
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@classmethod
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def INPUT_TYPES(s):
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return {"required": { "model1": ("MODEL",),
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"model2": ("MODEL",),
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"ratio": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01}),
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}}
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RETURN_TYPES = ("MODEL",)
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FUNCTION = "merge"
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CATEGORY = "_for_testing/model_merging"
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def merge(self, model1, model2, ratio):
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m = model1.clone()
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sd = model2.model_state_dict("diffusion_model.")
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for k in sd:
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m.add_patches({k: (sd[k], )}, 1.0 - ratio, ratio)
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return (m, )
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class ModelMergeBlocks:
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@classmethod
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def INPUT_TYPES(s):
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return {"required": { "model1": ("MODEL",),
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"model2": ("MODEL",),
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"input": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01}),
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"middle": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01}),
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"out": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01})
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}}
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RETURN_TYPES = ("MODEL",)
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FUNCTION = "merge"
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CATEGORY = "_for_testing/model_merging"
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def merge(self, model1, model2, **kwargs):
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m = model1.clone()
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sd = model2.model_state_dict("diffusion_model.")
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default_ratio = next(iter(kwargs.values()))
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for k in sd:
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ratio = default_ratio
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k_unet = k[len("diffusion_model."):]
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for arg in kwargs:
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if k_unet.startswith(arg):
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ratio = kwargs[arg]
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m.add_patches({k: (sd[k], )}, 1.0 - ratio, ratio)
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return (m, )
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NODE_CLASS_MAPPINGS = {
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"ModelMergeSimple": ModelMergeSimple,
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"ModelMergeBlocks": ModelMergeBlocks
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}
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