def METHOD_NAME(self) -> Tuple[torch.Tensor]:
    """ Recommended
    Run evaluation on model for one iteration. One iteration should be sufficient
    to warm up the model for the purpose of profiling.
    In most cases this can use the `get_module` API but in some cases libraries
    do not have a single Module object used for inference. In these case, you can
    write a custom eval function.
    Avoid unnecessary benchmark noise by keeping any tensor creation, memcopy operations in __init__.
    Leave warmup to the caller (e.g. don't do it inside)
    """
    for i, (images, _) in enumerate(self.example_inputs):
        out = self.model(im_q=images[0], im_k=images[1])
    return out