class_docstr: Metaclass for ``DependentBackend``.
  To ensure the backend config is unique in diverse threads for multiprocessing runtime,
  the backend config is instantiated in the metaclass during interpretation phase.
class_docstr_tok: ["Metaclass","for","``","DependentBackend","``",".","To","ensure","the","backend","config","is","unique","in","diverse","threads","for","multiprocessing","runtime",",","the","backend","config","is","instantiated","in","the","metaclass","during","interpretation","phase","."]
code: def __init__(
      cls,
      name: str,
      bases: _typing.Tuple[type, ...],
      namespace: _typing.Dict[str, _typing.Any],
  ):
      super(_DependentBackendMetaclass, cls).__init__(
          name, bases, namespace
      )
      cls._backend_config: _BackendConfig = _generate_backend_config()
      _backend_logger.info(
          "Adopted backend: %s" % str(cls._backend_config)
      )
  
imports: import os
  import logging
  import typing
label_desc: Use image node_id 2 to create a new _DependentBackendMetaclass object from inherited base classes: type with example: obj = _DependentBackendMetaclass(cls, name, bases, namespace)