def __init__()

in models_all.py [0:0]

• 19 lines of code
• 4 McCabe index (conditional complexity)

    def __init__(
        self,
        dlatent_size=512,  # Disentangled latent (W) dimensionality.
        num_channels=3,  # Number of output color channels.
        resolution=1024,  # Output resolution.
        fmap_base=8192,  # Overall multiplier for the number of feature maps.
        fmap_decay=1.0,  # log2 feature map reduction when doubling the resolution.
        fmap_max=512,  # Maximum number of feature maps in any layer.
        use_styles=True,  # Enable style inputs?
        const_input_layer=True,  # First layer is a learned constant?
        use_noise=True,  # Enable noise inputs?
        randomize_noise=True,  # True = randomize noise inputs every time (non-deterministic), False = read noise inputs from variables.  # noqa
        nonlinearity="lrelu",  # Activation function: 'relu', 'lrelu'
        use_wscale=True,  # Enable equalized learning rate?
        use_pixel_norm=False,  # Enable pixelwise feature vector normalization?
        use_instance_norm=True,  # Enable instance normalization?
        dtype=torch.float32,  # Data type to use for activations and outputs.
        blur_filter=None,  # Low-pass filter to apply when resampling activations. None = no filtering.  # noqa
        use_random_initial_noise=True,  # Whether to use randomized initial noise in noise layer