def METHOD_NAME(self, input: torch.Tensor, target_is_real: bool) -> torch.Tensor:
    """
    Gets the ground truth tensor for the discriminator depending on whether the input is real or fake.
    Args:
        input: input tensor from the discriminator (output of discriminator, or output of one of the multi-scale
        discriminator). This is used to match the shape.
        target_is_real: whether the input is real or wannabe-real (1s) or fake (0s).
    Returns:
    """
    filling_label = self.real_label if target_is_real else self.fake_label
    label_tensor = torch.tensor(1).fill_(filling_label).type(input.type()).to(input[0].device)
    label_tensor.requires_grad_(False)
    return label_tensor.expand_as(input)