def _handle_load_model_post()

in tensorflow/inference/docker/build_artifacts/sagemaker/python_service.py [0:0]

• 40 lines of code
• 8 McCabe index (conditional complexity)

    def _handle_load_model_post(self, res, data):  # noqa: C901
        with lock():
            model_name = data["model_name"]
            base_path = data["url"]

            # sync sync_local_mme_instance_status & update available ports
            self._sync_local_mme_instance_status()
            self._update_ports_available()
            self._sync_model_handlers()

            # model is already loaded
            if model_name in self._mme_tfs_instances_status:
                res.status = falcon.HTTP_409
                res.body = json.dumps({"error": "Model {} is already loaded.".format(model_name)})
                return

            is_load_successful = True
            response = {}
            for i in range(self._tfs_instance_count):
                # check if there are available ports
                if not self._ports_available():
                    is_load_successful = False
                    response["status"] = falcon.HTTP_507
                    response["body"] = json.dumps(
                        {"error": "Memory exhausted: no available ports to load the model."}
                    )
                    break
                tfs_rest_port = self._tfs_available_ports["rest_port"].pop()
                tfs_grpc_port = self._tfs_available_ports["grpc_port"].pop()

                response = self._load_model(model_name, base_path, tfs_rest_port, tfs_grpc_port, i)

                if "pid" in response:
                    self._mme_tfs_instances_status.setdefault(model_name, []).append(
                        TfsInstanceStatus(tfs_rest_port, tfs_grpc_port, response["pid"])
                    )

                if response["status"] != falcon.HTTP_200:
                    log.info(f"Failed to load model : {model_name}")
                    is_load_successful = False
                    break

            if not is_load_successful:
                log.info(f"Failed to load model : {model_name}, Starting to cleanup...")
                self._delete_model(model_name)
                self._remove_model_config(model_name)
            else:
                self._upload_mme_instance_status()

            res.status = response["status"]
            res.body = response["body"]