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Update nodes.py
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@ -1646,7 +1646,7 @@ class LoadICLightUnet:
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CATEGORY = "KJNodes/experimental"
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def load(self, model, model_path):
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print("LoadICLightUnet: Checking ResAdapter path")
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print("LoadICLightUnet: Checking LoadICLightUnet path")
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model_full_path = folder_paths.get_full_path("unet", model_path)
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if not os.path.exists(model_full_path):
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raise Exception("Invalid model path")
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@ -1657,6 +1657,7 @@ class LoadICLightUnet:
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conv_layer = model_clone.model.diffusion_model.input_blocks[0][0]
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print(f"Current number of input channels: {conv_layer.in_channels}")
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# Create a new Conv2d layer with 8 input channels
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new_conv_layer = torch.nn.Conv2d(8, conv_layer.out_channels, kernel_size=conv_layer.kernel_size, stride=conv_layer.stride, padding=conv_layer.padding)
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new_conv_layer.weight.zero_()
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@ -1668,7 +1669,19 @@ class LoadICLightUnet:
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model_clone.model.diffusion_model.input_blocks[0][0] = new_conv_layer
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# Verify the change
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print(f"New number of input channels: {model_clone.model.diffusion_model.input_blocks[0][0].in_channels}")
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# Monkey patch because I don't know what I'm doing
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from comfy.model_base import IP2P
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import types
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base_model_instance = model_clone.model
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# Dynamically add the extra_conds method from IP2P to the instance of BaseModel
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def bound_extra_conds(self, **kwargs):
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return IP2P.extra_conds(self, **kwargs)
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base_model_instance.process_ip2p_image_in = lambda image: image
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base_model_instance.extra_conds = types.MethodType(bound_extra_conds, base_model_instance)
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# Some Proper patching
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new_state_dict = load_torch_file(model_full_path)
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prefix_to_remove = 'model.'
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new_keys_dict = {key[len(prefix_to_remove):]: new_state_dict[key] for key in new_state_dict if key.startswith(prefix_to_remove)}
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@ -1677,11 +1690,9 @@ class LoadICLightUnet:
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try:
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for key in new_keys_dict:
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model_clone.add_patches({key: (new_keys_dict[key],)}, 1.0, 1.0)
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#print(f"Added patch for: {key}")
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except:
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raise Exception("Could not patch model")
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print("LoadICLightUnet: Added LoadICLightUnet patches")
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#model_clone.model.diffusion_model.in_channels = 8
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return (model_clone, )
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