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(f"case_type {case_type} is not supported")
  
imports: import warnings
  import numpy
  import pandas
  from pandas.api.types import is_bool_dtype, is_categorical_dtype, is_datetime64_any_dtype, is_numeric_dtype, is_object_dtype, is_string_dtype, is_timedelta64_dtype
  from sklearn import preprocessing, tree
  from sklearn.metrics import f1_score, mean_absolute_error
  from sklearn.model_selection import cross_val_score
  from deepchecks.utils.typing import Hashable
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