class_docstr: A wrapper around `shap.KernelExplainer` that supports:
  
      - fixing the seed when instantiating the KernelExplainer in a separate process.
  
      - passing a batch index to the explainer so that a parallel explainer pool can return batches in         arbitrary order.
class_docstr_tok: ["A","wrapper","around","`","shap.KernelExplainer","`","that","supports",":","-","fixing","the","seed","when","instantiating","the","KernelExplainer","in","a","separate","process",".","-","passing","a","batch","index","to","the","explainer","so","that","a","parallel","explainer","pool","can","return","batches","in","arbitrary","order","."]
docstr: Parameters
  -----------
  *args, **kwargs
      Arguments and keyword arguments for `shap.KernelExplainer` constructor.
code: def __init__(self, *args, **kwargs):
      """
      Parameters
      -----------
      *args, **kwargs
          Arguments and keyword arguments for `shap.KernelExplainer` constructor.
      """
  
      if "seed" in kwargs:
          seed = kwargs.pop("seed")
          np.random.seed(seed)
      super().__init__(*args, **kwargs)
  
imports: import copy
  import logging
  from functools import partial
  from typing import TYPE_CHECKING, Any, Callable, Dict, List, Optional, Sequence, Tuple, Union
  import numpy
  import pandas
  import shap
  import shap.utils._legacy
  from scipy import sparse
  from scipy.special import expit
  from shap import KernelExplainer
  from alibi.api.defaults import DEFAULT_DATA_KERNEL_SHAP, DEFAULT_DATA_TREE_SHAP, DEFAULT_META_KERNEL_SHAP, DEFAULT_META_TREE_SHAP
  from alibi.api.interfaces import Explainer, Explanation, FitMixin
  from alibi.utils.wrappers import methdispatch
label_desc: Use image node_id 1 to create a new KernelExplainerWrapper object from inherited base classes: KernelExplainer with example: obj = KernelExplainerWrapper()