code: def get_column_type(output_type):
      """Get column type to use in drift functions."""
      # TODO smarter mapping based on data?
      # NOTE/TODO: this function is kept only for backward compatibility, remove it later
      mapper = {
          "continuous": "numerical",
          "discrete": "categorical",
          "class_id": "categorical",
          "numerical": "numerical",
          "categorical": "categorical",
      }
      return mapper[output_type]
  
file_path: deepchecks/deepchecks/vision/utils/label_prediction_properties.py
imports: from typing import List, Sequence, Union
  import numpy
label_desc: Use image node_id 14 for calling a global function with example usage: get_column_type(output_type) and returns: mapper