demo.py [33:45]:
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	builder = ModelBuilder()
	net_visual = builder.build_visual(weights=opt.weights_visual)
	net_audio = builder.build_audio(
	        ngf=opt.unet_ngf,
	        input_nc=opt.unet_input_nc,
	        output_nc=opt.unet_output_nc,
	        weights=opt.weights_audio)
	nets = (net_visual, net_audio)

	# construct our audio-visual model
	model = AudioVisualModel(nets, opt)
	model = torch.nn.DataParallel(model, device_ids=opt.gpu_ids)
	model.to(opt.device)
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train.py [76:88]:
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builder = ModelBuilder()
net_visual = builder.build_visual(weights=opt.weights_visual)
net_audio = builder.build_audio(
        ngf=opt.unet_ngf,
        input_nc=opt.unet_input_nc,
        output_nc=opt.unet_output_nc,
        weights=opt.weights_audio)
nets = (net_visual, net_audio)

# construct our audio-visual model
model = AudioVisualModel(nets, opt)
model = torch.nn.DataParallel(model, device_ids=opt.gpu_ids)
model.to(opt.device)
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