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Update nodes.py

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kijai 2024-05-09 01:48:53 +03:00
parent 4f9d3f4142
commit 928e5cc778
1 changed files with 15 additions and 0 deletions
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nodes/nodes.py
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@ -1654,6 +1654,21 @@ class LoadICLightUnet:
print("LoadICLightUnet: Loading LoadICLightUnet weights") print("LoadICLightUnet: Loading LoadICLightUnet weights")
from comfy.utils import load_torch_file from comfy.utils import load_torch_file
model_clone = model.clone() model_clone = model.clone()
conv_layer = model_clone.model.diffusion_model.input_blocks[0][0]
print(f"Current number of input channels: {conv_layer.in_channels}")
# Create a new Conv2d layer with 8 input channels
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)
new_conv_layer.weight.zero_()
new_conv_layer.weight[:, :4, :, :].copy_(conv_layer.weight)
new_conv_layer.bias = conv_layer.bias
new_conv_layer = new_conv_layer.to(torch.float16)
conv_layer.conv_in = new_conv_layer
# Replace the old layer with the new one
model_clone.model.diffusion_model.input_blocks[0][0] = new_conv_layer
# Verify the change
print(f"New number of input channels: {model_clone.model.diffusion_model.input_blocks[0][0].in_channels}")
new_state_dict = load_torch_file(model_full_path) new_state_dict = load_torch_file(model_full_path)
prefix_to_remove = 'model.' prefix_to_remove = 'model.'
new_keys_dict = {key[len(prefix_to_remove):]: new_state_dict[key] for key in new_state_dict if key.startswith(prefix_to_remove)} new_keys_dict = {key[len(prefix_to_remove):]: new_state_dict[key] for key in new_state_dict if key.startswith(prefix_to_remove)}