def METHOD_NAME(self, target : torch.fx.node.Target, args : Tuple[Argument, ...], kwargs : Dict[str, Any]):
    attr_proxy = super().METHOD_NAME(target, args, kwargs)
    if self.annotate_get_attrs:
        module_itr = self.module
        assert isinstance(target, str)
        atoms = target.split('.')
        for i, atom in enumerate(atoms):
            if not hasattr(module_itr, atom):
                raise RuntimeError(f'Node referenced nonextent target {".".join(atoms[:i])}!')
            module_itr = getattr(module_itr, atom)
        maybe_inferred_ts_type = torch._C._jit_try_infer_type(module_itr)
        if maybe_inferred_ts_type.success():
            python_type = _torchscript_type_to_python_type(maybe_inferred_ts_type.type())
            attr_proxy.node.type = python_type if not attr_proxy.node.type else attr_proxy.node.type
    return attr_proxy