class_docstr: A sampler that uses an underlying training set to draw records that have a subset of features with
  values specified in an instance to be explained, `X`. 
class_docstr_tok: ["A","sampler","that","uses","an","underlying","training","set","to","draw","records","that","have","a","subset","of","features","with","values","specified","in","an","instance","to","be","explained",",","`","X","`","."]
docstr: Initialise the tabular sampler object with data, discretizer, feature statistics and
  build an index from feature values and bins to database rows for each feature.
  
  Parameters
  ----------
  train_data:
      Data from which samples are drawn. Can be a `numpy` array or a `ray` future.
  d_train_data:
      Discretized version for training data. Can be a `numpy` array or a `ray` future.
  
  Returns
  -------
  An initialised sampler.
code: def deferred_init(
      self,
      train_data: Union[np.ndarray, Any],
      d_train_data: Union[np.ndarray, Any],
  ) -> Any:
      """
      Initialise the tabular sampler object with data, discretizer, feature statistics and
      build an index from feature values and bins to database rows for each feature.
  
      Parameters
      ----------
      train_data:
          Data from which samples are drawn. Can be a `numpy` array or a `ray` future.
      d_train_data:
          Discretized version for training data. Can be a `numpy` array or a `ray` future.
  
      Returns
      -------
      An initialised sampler.
      """
  
      self._set_data(train_data, d_train_data)
      self._set_discretizer(self.disc_perc)
      self._set_numerical_feats_stats()
      self.val2idx = self._get_data_index()
  
      return self
  
imports: import copy
  from collections import OrderedDict, defaultdict
  from itertools import accumulate
  from typing import Any, Callable, DefaultDict, Dict, List, Optional, Set, Tuple, Type, Union
  import numpy
  from alibi.api.defaults import DEFAULT_DATA_ANCHOR, DEFAULT_META_ANCHOR
  from alibi.api.interfaces import Explainer, Explanation, FitMixin
  from alibi.exceptions import NotFittedError, PredictorCallError, PredictorReturnTypeError
  from alibi.utils.discretizer import Discretizer
  from alibi.utils.mapping import ohe_to_ord, ord_to_ohe
  from alibi.utils.wrappers import ArgmaxTransformer
  from .anchor_base import AnchorBaseBeam
  from .anchor_explanation import AnchorExplanation
label_desc: Use image node_id 2 for calling the TabularSampler obj's underlying member method code with example usage: obj.deferred_init(train_data, d_train_data) and returns: self