code: def input_data_imputation(request):
      size = (50, 20)
      X = np.array(np.random.randint(3, 10, size=size), dtype=float)
      mask = np.logical_not(
          np.random.randint(0, 5, size=size), dtype=bool
      )
      X[mask] = np.nan
      if request.param == "numpy":
          pass
      elif request.param == "pandas":
          X = pd.DataFrame(X)
      return X, 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 1 for calling a global function with example usage: input_data_imputation(request) and returns: X,  mask