class_docstr: Temporary class
  
  Wrapper to get full estimator on no-args instantiation. For compatibility
  with older Scikit-learn versions.
code: def fit_transform(self, X, y, *args, **kwargs):
      X, y = check_X_y(X, y)
      return super(Tmp, self).fit_transform(X, y, *args, **kwargs)
  
imports: import numpy
  from mlens.index import FullIndex, FoldIndex
  from mlens.testing import Data
  from mlens.testing.dummy import ESTIMATORS, PREPROCESSING
  from mlens.utils.dummy import OLS, Scale
  from mlens.utils.exceptions import NotFittedError, ParameterChangeWarning
  from mlens.parallel import make_group
  from mlens.estimators import LearnerEstimator, TransformerEstimator, LayerEnsemble
  from mlens.externals.sklearn.base import clone
label_desc: Use image node_id 3 for calling the Tmp obj's underlying member method code with example usage: obj.fit_transform(X, y) and returns: super