def quaternion_apply(quaternion, point):
    """
    Apply the rotation given by a quaternion to a 3D point.
    Usual torch rules for broadcasting apply.

    Args:
        quaternion: Tensor of quaternions, real part first, of shape (..., 4).
        point: Tensor of 3D points of shape (..., 3).

    Returns:
        Tensor of rotated points of shape (..., 3).
    """
    if point.size(-1) != 3:
        raise ValueError(f"Points are not in 3D, f{point.shape}.")
    real_parts = point.new_zeros(point.shape[:-1] + (1,))
    point_as_quaternion = torch.cat((real_parts, point), -1)
    out = quaternion_raw_multiply(
        quaternion_raw_multiply(quaternion, point_as_quaternion),
        quaternion_invert(quaternion),
    )
    return out[..., 1:]

    Apply the rotation given by a quaternion to a 3D point.
    Usual torch rules for broadcasting apply.

    Args:
        quaternion: Tensor of quaternions, real part first, of shape (..., 4).
        point: Tensor of 3D points of shape (..., 3).

    Returns:
        Tensor of rotated points of shape (..., 3).
    
mGPT/utils/rotation_conversions.py