class_docstr: Temporary class
  
  Wrapper to get full estimator on no-args instantiation. For compatibility
  with older Scikit-learn versions.
class_docstr_tok: ["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)
      y = np.asarray(y, X.dtype)
      return super(Tmp, self).fit_transform(X, y, *args, **kwargs)
  
imports: import numpy
  from mlens.index import FoldIndex, FullIndex
  from mlens.utils.dummy import OLS, Scale
  from mlens.utils.exceptions import NotFittedError, ParameterChangeWarning
  from mlens.testing import Data
  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