My similar solution to fix this was:
model = some_Network()
sd = model.state_dict()
sd.update(torch.load(some_Network_model_path))

model.load_state_dict(sd)
model.moduleFeatures.moduleOne = torch.nn.Sequential(
                    torch.nn.Conv2d(in_channels=1, out_channels=32, kernel_size=7, stride=1, padding=3),
                    torch.nn.LeakyReLU(inplace=False, negative_slope=0.1)
                )

Where I change the first layer of the model from a 3-channel input convolution layer to a 1-channel input convolution layer to handle grayscale images as input