(source, dest, force_fp16)
Convert legacy network pickle into the native PyTorch format.

    The tool is able to load the main network configurations exported using the TensorFlow version of StyleGAN2 or StyleGAN2-ADA.
    It does not support e.g. StyleGAN2-ADA comparison methods, StyleGAN2 configs A-D, or StyleGAN1 networks.

    Example:

    \b
    python legacy.py \\
        --source=https://nvlabs-fi-cdn.nvidia.com/stylegan2/networks/stylegan2-cat-config-f.pkl \\
        --dest=stylegan2-cat-config-f.pkl
Convert legacy network pickle into the native PyTorch format.
Convert legacy network pickle into the native PyTorch format .
def convert_network_pickle(source, dest, force_fp16):
    """Convert legacy network pickle into the native PyTorch format.

    The tool is able to load the main network configurations exported using the TensorFlow version of StyleGAN2 or StyleGAN2-ADA.
    It does not support e.g. StyleGAN2-ADA comparison methods, StyleGAN2 configs A-D, or StyleGAN1 networks.

    Example:

    \b
    python legacy.py \\
        --source=https://nvlabs-fi-cdn.nvidia.com/stylegan2/networks/stylegan2-cat-config-f.pkl \\
        --dest=stylegan2-cat-config-f.pkl
    """
    print(f'Loading "{source}"...')
    with dnnlib.util.open_url(source) as f:
        data = load_network_pkl(f, force_fp16=force_fp16)
    print(f'Saving "{dest}"...')
    with open(dest, 'wb') as f:
        pickle.dump(data, f)
    print('Done.')
def convert_network_pickle ( source , dest , force_fp16 ) : print ( f'Loading "{source}"...' ) with dnnlib . util . open_url ( source ) as f : data = load_network_pkl ( f , force_fp16 = force_fp16 ) print ( f'Saving "{dest}"...' ) with open ( dest , 'wb' ) as f : pickle . dump ( data , f ) print ( 'Done.' )