code: def transform(self, X):
      from scipy import sparse
  
      if sparse.issparse(X):
          return X.todense().getA()
      else:
          return X
  
file_path: auto-sklearn/autosklearn/pipeline/components/feature_preprocessing/densifier.py
imports: from typing import Optional
  from ConfigSpace.configuration_space import ConfigurationSpace
  from autosklearn.askl_typing import FEAT_TYPE_TYPE
  from autosklearn.pipeline.components.base import AutoSklearnPreprocessingAlgorithm
  from autosklearn.pipeline.constants import DENSE, INPUT, SPARSE, UNSIGNED_DATA
label_desc: Use image node_id 3 for calling the Densifier obj's underlying member method code with example usage: obj.transform(X) and returns: X, X