code: def mixin_worker_runtime_parser(parser):
      """Mixing in arguments required by :class:`WorkerRuntime` into the given parser.
      :param parser: the parser instance to which we add arguments
      """
  
      gp = add_arg_group(parser, title="WorkerRuntime")
      from jina.constants import __default_executor__
  
      gp.add_argument(
          "--uses",
          type=str,
          default=__default_executor__,
          help="""
          The config of the executor, it could be one of the followings:
          * the string literal of an Executor class name
          * an Executor YAML file (.yml, .yaml, .jaml)
          * a Jina Hub Executor (must start with `jinahub://` or `jinahub+docker://`)
          * a docker image (must start with `docker://`)
          * the string literal of a YAML config (must start with `!` or `jtype: `)
          * the string literal of a JSON config
  
          When use it under Python, one can use the following values additionally:
          - a Python dict that represents the config
          - a text file stream has `.read()` interface
          """,
      )
      gp.add_argument(
          "--uses-with",
          action=KVAppendAction,
          metavar="KEY: VALUE",
          nargs="*",
          help="""
      Dictionary of keyword arguments that will override the `with` configuration in `uses`
      """,
      )
      gp.add_argument(
          "--uses-metas",
          action=KVAppendAction,
          metavar="KEY: VALUE",
          nargs="*",
          help="""
      Dictionary of keyword arguments that will override the `metas` configuration in `uses`
      """,
      )
      gp.add_argument(
          "--uses-requests",
          action=KVAppendAction,
          metavar="KEY: VALUE",
          nargs="*",
          help="""
          Dictionary of keyword arguments that will override the `requests` configuration in `uses`
          """,
      )
      gp.add_argument(
          "--uses-dynamic-batching",
          action=KVAppendAction,
          metavar="KEY: VALUE",
          nargs="*",
          help="""
          Dictionary of keyword arguments that will override the `dynamic_batching` configuration in `uses`
          """,
      )
      gp.add_argument(
          "--py-modules",
          type=str,
          nargs="*",
          metavar="PATH",
          help="""
  The customized python modules need to be imported before loading the executor
  
  Note that the recommended way is to only import a single module - a simple python file, if your
  executor can be defined in a single file, or an ``__init__.py`` file if you have multiple files,
  which should be structured as a python package. For more details, please see the
  `Executor cookbook <https://docs.jina.ai/concepts/executor/executor-files/>`__
  """,
      )
  
      gp.add_argument(
          "--output-array-type",
          type=str,
          default=None,
          help="""
  The type of array `tensor` and `embedding` will be serialized to.
  
  Supports the same types as `docarray.to_protobuf(.., ndarray_type=...)`, which can be found 
  `here <https://docarray.jina.ai/fundamentals/document/serialization/#from-to-protobuf>`.
  Defaults to retaining whatever type is returned by the Executor.
  """,
      )
  
      gp.add_argument(
          "--exit-on-exceptions",
          type=str,
          default=[],
          nargs="*",
          help="List of exceptions that will cause the Executor to shut down.",
      )
  
      gp.add_argument(
          "--no-reduce",
          "--disable-reduce",
          action="store_true",
          default=False,
          help="Disable the built-in reduction mechanism. Set this if the reduction is to be handled by the Executor "
          "itself by operating on a `docs_matrix` or `docs_map`",
      )
  
      gp.add_argument(
          "--allow-concurrent",
          action="store_true",
          default=False,
          help="Allow concurrent requests to be processed by the Executor. This is only recommended if the Executor is thread-safe.",
      )
  
      mixin_base_runtime_parser(gp)
      mixin_raft_parser(gp)
      mixin_grpc_channel_options_parser(gp)
  
label_desc: Use image node_id 1 for calling a global function with example usage: mixin_worker_runtime_parser(parser) without return types