class_docstr: Counterfactual Reinforcement Learning Tabular. 
class_docstr_tok: ["Counterfactual","Reinforcement","Learning","Tabular","."]
docstr: Selects the backend according to the `backend` flag.
  
  Parameters
  ----------
  backend
      Deep learning backend. ``'tensorflow'`` | ``'pytorch'``. Default ``'tensorflow'``.
docstr_tok: ["Selects","the","backend","according","to","the","`","backend","`","flag",".","Parameters","--","--","--","--","--","backend","Deep","learning","backend",".","``","'tensorflow","'","``","|","``","'pytorch","'","``",".","Default","``","'tensorflow","'","``","."]
code: def _select_backend(self, backend, **kwargs):
      """
      Selects the backend according to the `backend` flag.
  
      Parameters
      ----------
      backend
          Deep learning backend. ``'tensorflow'`` | ``'pytorch'``. Default ``'tensorflow'``.
      """
      return (
          tensorflow_tabular_backend
          if backend == "tensorflow"
          else pytorch_tabular_backend
      )
  
imports: from functools import partial
  from itertools import count
  from typing import TYPE_CHECKING, Callable, Dict, List, Optional, Tuple, Union, cast
  import numpy
  from tqdm import tqdm
  from alibi.api.interfaces import Explainer, Explanation
  from alibi.explainers.backends.cfrl_tabular import get_conditional_vector, get_statistics, sample
  from alibi.explainers.cfrl_base import _PARAM_TYPES, CounterfactualRL, Postprocessing
  from alibi.utils.frameworks import has_pytorch, has_tensorflow
label_desc: Use image node_id 2 for calling the CounterfactualRLTabular obj's underlying member method code with example usage: obj._select_backend(backend) and returns: unknown