class_docstr: Base class for parallel objects
  
  Parameters
  ----------
  name : str
      name of instance. Should be unique.
  
  backend : str or object (default = 'threading')
      backend infrastructure to use during call to
      :class:`mlens.externals.joblib.Parallel`. See Joblib for further
      documentation. To set global backend,
      see :func:`~mlens.config.set_backend`.
  
  raise_on_exception : bool (default = True)
      whether to issue warnings on soft exceptions or raise error.
      Examples include lack of layers, bad inputs, and failed fit of an
      estimator in a layer. If set to ``False``, warnings are issued instead
      but estimation continues unless exception is fatal. Note that this
      can result in unexpected behavior unless the exception is anticipated.
  
  verbose : int or bool (default = False)
      level of verbosity.
  
  n_jobs : int (default = -1)
      Degree of concurrency in estimation. Set to -1 to maximize,
      1 runs on a single process (or thread).
  
  dtype : obj (default = np.float32)
      data type to use, must be compatible with a numpy array dtype.
code: def __init__(self, name, *args, **kwargs):
      super(BaseParallel, self).__init__(*args, **kwargs)
      self.name = name
      self.__no_output__ = False
  
imports: import warnings
  from abc import abstractmethod
  import numpy
  from ._base_functions import check_stack, check_params
  from ..None import config
  from ..utils.exceptions import ParallelProcessingError
  from ..externals.sklearn.base import clone, BaseEstimator
label_desc: Use image node_id 1 to create a new BaseParallel object from inherited base classes: BaseBackend with example: obj = BaseParallel(name)