def initialize_models_all()

in one_shot_domain_adaptation.py [0:0]

• 29 lines of code
• 2 McCabe index (conditional complexity)

def initialize_models_all(opt):
    """Initialize the model and load the pre-trained weights. Note that we only
    build the synthesis network which takes styles as input (no mapping network
    is necessary for our task)."""
    # load mapping network
    g_all = nn.Sequential(
        OrderedDict(
            [
                ("g_mapping", G_mapping()),
                # ('truncation', Truncation(avg_latent)),
                (
                    "g_synthesis",
                    G_synthesis(
                        randomize_noise=False,
                        resolution=opt.resolution,
                        use_random_initial_noise=opt.use_random_initial_noise,
                    ),
                ),
            ]
        )
    )
    g_all.load_state_dict(
        torch.load(
            "./karras2019stylegan-ffhq-1024x1024.for_g_all.pt"  # noqa
        )
    )
    state = g_all.g_synthesis.state_dict()
    state.update(torch.load(syn_pt_path))
    loaded_dict = {k: state[k] for k in g_all.g_synthesis.state_dict()}
    g_all.g_synthesis.load_state_dict(loaded_dict)
    g_all.eval()
    g_mapping = g_all.g_mapping.cuda()
    g_synthesis = g_all.g_synthesis.cuda()
    return g_mapping, g_synthesis