98 lines
3.3 KiB
Python
98 lines
3.3 KiB
Python
import comfy.sd
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import comfy.utils
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import folder_paths
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import json
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import os
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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 = "advanced/model_merging"
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def merge(self, model1, model2, ratio):
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m = model1.clone()
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kp = model2.get_key_patches("diffusion_model.")
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for k in kp:
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m.add_patches({k: kp[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 = "advanced/model_merging"
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def merge(self, model1, model2, **kwargs):
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m = model1.clone()
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kp = model2.get_key_patches("diffusion_model.")
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default_ratio = next(iter(kwargs.values()))
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for k in kp:
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ratio = default_ratio
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k_unet = k[len("diffusion_model."):]
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last_arg_size = 0
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for arg in kwargs:
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if k_unet.startswith(arg) and last_arg_size < len(arg):
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ratio = kwargs[arg]
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last_arg_size = len(arg)
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m.add_patches({k: kp[k]}, 1.0 - ratio, ratio)
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return (m, )
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class CheckpointSave:
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def __init__(self):
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self.output_dir = folder_paths.get_output_directory()
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@classmethod
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def INPUT_TYPES(s):
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return {"required": { "model": ("MODEL",),
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"clip": ("CLIP",),
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"vae": ("VAE",),
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"filename_prefix": ("STRING", {"default": "checkpoints/ComfyUI"}),},
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"hidden": {"prompt": "PROMPT", "extra_pnginfo": "EXTRA_PNGINFO"},}
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RETURN_TYPES = ()
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FUNCTION = "save"
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OUTPUT_NODE = True
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CATEGORY = "advanced/model_merging"
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def save(self, model, clip, vae, filename_prefix, prompt=None, extra_pnginfo=None):
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full_output_folder, filename, counter, subfolder, filename_prefix = folder_paths.get_save_image_path(filename_prefix, self.output_dir)
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prompt_info = ""
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if prompt is not None:
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prompt_info = json.dumps(prompt)
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metadata = {"prompt": prompt_info}
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if extra_pnginfo is not None:
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for x in extra_pnginfo:
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metadata[x] = json.dumps(extra_pnginfo[x])
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output_checkpoint = f"{filename}_{counter:05}_.safetensors"
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output_checkpoint = os.path.join(full_output_folder, output_checkpoint)
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comfy.sd.save_checkpoint(output_checkpoint, model, clip, vae, metadata=metadata)
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return {}
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NODE_CLASS_MAPPINGS = {
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"ModelMergeSimple": ModelMergeSimple,
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"ModelMergeBlocks": ModelMergeBlocks,
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"CheckpointSave": CheckpointSave,
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}
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