class_docstr: Base sampler class.
  Sampler is an object which generates examples similar to a given example.
class_docstr_tok: ["Base","sampler","class",".","Sampler","is","an","object","which","generates","examples","similar","to","a","given","example","."]
code: def fit(self, X=None, y=None):
      return self
  
imports: from __future__ import absolute_import
  import abc
  from functools import partial
  from typing import List, Tuple, Any, Union, Dict, Optional
  import six
  import numpy
  from scipy.stats import itemfreq
  from sklearn.base import BaseEstimator, clone
  from sklearn.neighbors import KernelDensity
  from sklearn.metrics import pairwise_distances
  from sklearn.model_selection import GridSearchCV, KFold
  from sklearn.utils import check_random_state
  from eli5.utils import vstack
  from eli5.lime.utils import rbf
  from .textutils import generate_samples, DEFAULT_TOKEN_PATTERN, TokenizedText
label_desc: Use image node_id 2 for calling the BaseSampler obj's underlying member method code with example usage: obj.fit(X, y) and returns: self