code: def test_default_sparse(input_data_imputation):
      X, mask = input_data_imputation
      X = sparse.csr_matrix(X)
      Y = CategoricalImputation().fit_transform(X)
      Y = Y.todense()
  
      np.testing.assert_equal(Y == 0, mask)
      np.testing.assert_equal(Y != 0, ~mask)
  
file_path: auto-sklearn/test/test_pipeline/components/data_preprocessing/test_categorical_imputation.py
imports: import numpy
  import pandas
  from scipy import sparse
  from autosklearn.pipeline.components.data_preprocessing.imputation.categorical_imputation import CategoricalImputation
  import pytest
label_desc: Use image node_id 4 for calling a global function with example usage: test_default_sparse(input_data_imputation) without return types