def METHOD_NAME(self) -> Tuple[torch.Tensor]:
    self.model.METHOD_NAME()
    with torch.no_grad():
        for idx in range(self.NUM_BATCHES):
            out = self.model(self.example_inputs[idx])
    # retrieve output tensors
    outputs = []
    for item in out:
        fields = list(map(lambda x: list(x.get_fields().values()), item.values()))
        for boxes in fields:
            tensor_box = list(filter(lambda x: isinstance(x, torch.Tensor), boxes))
            outputs.extend(tensor_box)
    return tuple(outputs)