45aac954cfe5ff814fe34492462d3c736fb8c36f,kornia/augmentation/functional.py,,apply_rotation,#Any#Any#Any#,488

Before Change

    if not torch.is_tensor(input):
        raise TypeError(f"Input type is not a torch.Tensor. Got {type(input)}")

    if not torch.is_tensor(degrees):
        if isinstance(degrees, float):
            if degrees < 0:
                raise ValueError(f"If Degrees is only one number it must be a positive number. Got{degrees}")
            degrees = torch.tensor([-degrees, degrees])

        elif isinstance(degrees, (tuple, list)):
            degrees = torch.tensor(degrees)

        else:
            raise TypeError(f"Degrees should be a float number a sequence or a tensor. Got {type(degrees)}")

    degrees = cast(torch.Tensor, degrees)

    if degrees.numel() != 2:
        raise ValueError("If degrees is a sequence it must be of length 2")

After Change

    input = input.unsqueeze(0)
    input = input.view((-1, (*input.shape[-3:])))
    angles: torch.Tensor = params["degrees"].to(device, dtype)

    transformed: torch.Tensor = rotate(input, angles).squeeze(0)

Instances