    def benchmark(
        self,
        inputs: Union[Dict[str, AITData], List[AITData]],
        outputs: Union[Dict[str, AITData], List[AITData]],
        stream_ptr: Optional[int] = None,
        graph_mode: bool = False,
        count: int = 10,
        repeat: int = 1,
        num_threads: int = 1,
        use_unique_stream_per_thread: bool = False,
    ) -> Tuple[float, float, Dict[str, AITData]]:
        """
        Benchmark the model. See run() for information on most parameters.
        """
        if isinstance(inputs, dict):
            inputs = self._dict_to_ordered_list(inputs, is_inputs=True)
        if isinstance(outputs, dict):
            outputs = self._dict_to_ordered_list(outputs, is_inputs=False)
        (
            c_inputs,
            c_outputs,
            c_stream,
            c_output_shapes_out,
        ) = self._prepare_run(
            inputs,
            outputs,
            stream_ptr,
        )
        time_ms = []
        runtime_ms = ctypes.c_float()
        for _ in range(repeat):
            self.DLL.AITemplateModelContainerBenchmark(
                self.handle,
                c_inputs,
                ctypes.c_size_t(len(inputs)),
                c_outputs,
                ctypes.c_size_t(len(outputs)),
                c_stream,
                ctypes.c_bool(graph_mode),
                ctypes.c_size_t(count),
                ctypes.c_size_t(num_threads),
                ctypes.c_bool(use_unique_stream_per_thread),
                ctypes.byref(runtime_ms),
                c_output_shapes_out,
            )
            time_ms.append(runtime_ms.value)
        mean = np.mean(time_ms)
        std = np.std(time_ms)

        return (mean, std, self._make_ait_outputs(outputs, c_output_shapes_out))
Benchmark the model. See run() for information on most parameters.
python/aitemplate/compiler/model.py