code: def _get_task(case_type, invalid_score):
      if case_type in VALID_CALCULATIONS.keys():
          return VALID_CALCULATIONS[case_type]
      elif case_type in INVALID_CALCULATIONS:
          return {
              "type": case_type,
              "is_valid_score": False,
              "model_score": invalid_score,
              "baseline_score": invalid_score,
              "ppscore": invalid_score,
              "metric_name": None,
              "metric_key": None,
              "model": None,
              "score_normalizer": None,
          }
      raise Exception("case_type {} is not supported".format(case_type))
  
imports: import numpy
  from sklearn import tree
  from sklearn import preprocessing
  from sklearn.model_selection import cross_val_score
  from sklearn.metrics import mean_absolute_error, f1_score
  import pandas
  from pandas.api.types import is_numeric_dtype, is_bool_dtype, is_object_dtype, is_categorical_dtype, is_string_dtype, is_datetime64_any_dtype, is_timedelta64_dtype
label_desc: Use image node_id 13 for calling a global function with example usage: _get_task(case_type, invalid_score) and returns: VALID_CALCULATIONS, dict