class_docstr: Splitter that subsamples a given fraction of the dataset
class_docstr_tok: ["Splitter","that","subsamples","a","given","fraction","of","the","dataset"]
code: def split(self, X, y, groups=None):
      for train_idx, test_idx in self.base_cv.split(X, y, groups):
          train_idx = resample(
              train_idx,
              replace=False,
              random_state=self.random_state,
              n_samples=int(self.fraction * train_idx.shape[0]),
          )
          if self.subsample_test:
              test_idx = resample(
                  test_idx,
                  replace=False,
                  random_state=self.random_state,
                  n_samples=int(self.fraction * test_idx.shape[0]),
              )
          yield train_idx, test_idx
  
imports: from abc import abstractmethod
  from copy import deepcopy
  from math import ceil, floor, log
  from numbers import Integral, Real
  import numpy
  from ..base import _fit_context, is_classifier
  from ..metrics._scorer import get_scorer_names
  from ..utils import resample
  from ..utils._param_validation import Interval, StrOptions
  from ..utils.multiclass import check_classification_targets
  from ..utils.validation import _num_samples
  from .None import ParameterGrid, ParameterSampler
  from ._search import BaseSearchCV
  from ._split import _yields_constant_splits, check_cv
label_desc: Use image node_id 2 for calling the _SubsampleMetaSplitter obj's underlying member method code with example usage: obj.split(X, y, groups) without return types