class_docstr: Sampler that would sample even with a single class.
class_docstr_tok: ["Sampler","that","would","sample","even","with","a","single","class","."]
code: def _fit_resample(self, X, y):
      return X, y
  
imports: import numpy
  import pytest
  from sklearn.base import BaseEstimator
  from sklearn.utils.multiclass import check_classification_targets
  from imblearn.base import BaseSampler
  from imblearn.over_sampling.base import BaseOverSampler
  from imblearn.utils import check_target_type
  from imblearn.utils.estimator_checks import check_samplers_fit, check_samplers_nan, check_samplers_one_label, check_samplers_preserve_dtype, check_samplers_sparse, check_samplers_string, check_target_type
label_desc: Use image node_id 2 for calling the SamplerSingleClass obj's underlying member method code with example usage: obj._fit_resample(X, y) and returns: X,  y