tensorflow/inference/docker/build_artifacts/sagemaker/python_service.py [97:120]:
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            self.model_handlers = {}
        else:
            self._tfs_grpc_ports = self._parse_concat_ports(TFS_GRPC_PORTS)
            self._tfs_rest_ports = self._parse_concat_ports(TFS_REST_PORTS)

            self._channels = {}
            for grpc_port in self._tfs_grpc_ports:
                # Initialize grpc channel here so gunicorn worker could have mapping
                # between each grpc port and channel
                self._setup_channel(grpc_port)

        self._default_handlers_enabled = False
        if os.path.exists(INFERENCE_SCRIPT_PATH):
            # Single-Model Mode & Multi-Model Mode both use one inference.py
            self._handler, self._input_handler, self._output_handler = self._import_handlers()
            self._handlers = self._make_handler(
                self._handler, self._input_handler, self._output_handler
            )
        else:
            self._handlers = default_handler
            self._default_handlers_enabled = True

        self._tfs_enable_batching = SAGEMAKER_BATCHING_ENABLED == "true"
        self._tfs_default_model_name = os.environ.get("TFS_DEFAULT_MODEL_NAME", "None")
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tensorflow/inference/docker/build_artifacts/sagemaker_neuron/python_service.py [71:94]:
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            self.model_handlers = {}
        else:
            self._tfs_grpc_ports = self._parse_concat_ports(TFS_GRPC_PORTS)
            self._tfs_rest_ports = self._parse_concat_ports(TFS_REST_PORTS)

            self._channels = {}
            for grpc_port in self._tfs_grpc_ports:
                # Initialize grpc channel here so gunicorn worker could have mapping
                # between each grpc port and channel
                self._setup_channel(grpc_port)

        self._default_handlers_enabled = False
        if os.path.exists(INFERENCE_SCRIPT_PATH):
            # Single-Model Mode & Multi-Model Mode both use one inference.py
            self._handler, self._input_handler, self._output_handler = self._import_handlers()
            self._handlers = self._make_handler(
                self._handler, self._input_handler, self._output_handler
            )
        else:
            self._handlers = default_handler
            self._default_handlers_enabled = True

        self._tfs_enable_batching = SAGEMAKER_BATCHING_ENABLED == "true"
        self._tfs_default_model_name = os.environ.get("TFS_DEFAULT_MODEL_NAME", "None")
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