def Run(self, inputs):
        """
        Args:
            inputs: list, Each value corresponds to an input name of self._input_names
        Returns:
            results: dict, {name : numpy.array}
        """
        infer_inputs = []
        for idx, data in enumerate(inputs):
            infer_input = InferInput(self._input_names[idx], data.shape,
                                     "UINT8")
            infer_input.set_data_from_numpy(data)
            infer_inputs.append(infer_input)

        results = self._client.infer(
            model_name=self._model_name,
            model_version=self._model_version,
            inputs=infer_inputs,
            outputs=self._outputs_req,
            client_timeout=self._response_wait_t, )
        results = {name: results.as_numpy(name) for name in self._output_names}
        return results

        Args:
            inputs: list, Each value corresponds to an input name of self._input_names
        Returns:
            results: dict, {name : numpy.array}
        
deploy/fastdeploy/semantic_segmentation/serving/fastdeploy_serving/paddleseg_grpc_client.py