class_docstr: Counterfactual Reinforcement Learning. 
class_docstr_tok: ["Counterfactual","Reinforcement","Learning","."]
docstr: Verifies if the backend is supported.
  
  Parameters
  ----------
  backend
      Backend to be checked.
code: def _verify_backend(backend: str):
      """
      Verifies if the backend is supported.
  
      Parameters
      ----------
      backend
          Backend to be checked.
      """
  
      # Check if pytorch/tensorflow backend supported.
      if (backend == Framework.PYTORCH and not has_pytorch) or (
          backend == Framework.TENSORFLOW and not has_tensorflow
      ):
          raise ImportError(
              f"{backend} not installed. Cannot initialize and run the CounterfactualRL"
              f" with {backend} backend."
          )
  
      # Allow only pytorch and tensorflow.
      elif backend not in [Framework.PYTORCH, Framework.TENSORFLOW]:
          raise NotImplementedError(
              f"{backend} not implemented. Use `tensorflow` or `pytorch` instead."
          )
  
imports: import logging
  import os
  from abc import ABC, abstractmethod
  from copy import deepcopy
  from typing import TYPE_CHECKING, Any, Callable, Dict, Optional, Tuple, Union, cast
  import numpy
  from tqdm import tqdm
  from alibi.api.defaults import DEFAULT_DATA_CFRL, DEFAULT_META_CFRL
  from alibi.api.interfaces import Explainer, Explanation, FitMixin
  from alibi.explainers.backends.cfrl_base import generate_empty_condition, get_classification_reward, get_hard_distribution, identity_function
  from alibi.utils.frameworks import Framework, has_pytorch, has_tensorflow
label_desc: Use image node_id 4 for calling the CounterfactualRL obj's underlying member method code with example usage: obj._verify_backend(backend) without return types