    def _extract_exec_path(self, dynamic_profiling_strategy=DynamicProfileStrategy.MAX):
        """Extract execution key, i.e. input arguments for the profiler.

        Parameters
        ----------
        dynamic_profiling_strategy: DynamicProfileStrategy, optional
            A dynamic profiling strategy. By default MAX is used, i.e. to profile
            a dynamic range, an upper bound will be used.
        """
        assert (
            len(self._attrs["normalized_shape"]) == 1
        ), "For profiling, normalized_shape must be 1D"

        m_max = 1
        m_min = 1
        for dim in self._attrs["inputs"][0]._attrs["shape"][:-1]:
            m_max *= max(dim._attrs["values"])
            m_min *= min(dim._attrs["values"])

        n = self._attrs["inputs"][0]._attrs["shape"][-1].value()

        shape_values_dict = {
            "M": [m_min, m_max],
            "N": [n],
        }

        self._attrs["exec_path"] = OrderedDict()
        if dynamic_profiling_strategy == DynamicProfileStrategy.MAX:
            max_values = {"M": [m_max], "N": [n]}

            exec_item = ExecItem(
                profiling_key=self._gen_exec_key(max_values),
                exec_cond=self._gen_exec_key(shape_values_dict),
                algo="",
            )
            self._attrs["exec_path"][exec_item.profiling_key] = exec_item
        elif dynamic_profiling_strategy == DynamicProfileStrategy.MIN:
            min_values = {"M": [m_min], "N": [n]}
            exec_item = ExecItem(
                profiling_key=self._gen_exec_key(min_values),
                exec_cond=self._gen_exec_key(shape_values_dict),
                algo="",
            )
            self._attrs["exec_path"][exec_item.profiling_key] = exec_item
Extract execution key, i.e. input arguments for the profiler.

Parameters
----------
dynamic_profiling_strategy: DynamicProfileStrategy, optional
A dynamic profiling strategy. By default MAX is used, i.e. to profile
a dynamic range, an upper bound will be used.
python/aitemplate/compiler/ops/layernorm/layernorm.py