code: def check_model_class(model_class, model, verbose):
      model_info = get_model_info(model)
  
      if model_class is None:
          if hasattr(model, "_final_estimator"):
              model_class = str(type(model._final_estimator))
              model_info["Pipeline"] = True
          else:
              model_class = str(type(model))
              model_info["Pipeline"] = False
          from re import search
  
          model_class = search("(?<=<class ').*(?='>)", model_class)[0]
          model_info["model_class_default"] = True
  
          verbose_cat(
              "  -> model_class       : " + model_class + " (default)",
              verbose=verbose,
          )
  
      else:
          model_info["model_class_default"] = False
  
          verbose_cat(
              "  -> model_class       : " + model_class, verbose=verbose
          )
  
      return model_class, model_info
  
imports: import numpy
  import pandas
  from copy import deepcopy
  from warnings import warn
  from .helper import verbose_cat, is_y_in_data, get_model_info
  from .yhat import get_predict_function_and_model_type
label_desc: Use image node_id 7 for calling a global function with example usage: check_model_class(model_class, model, verbose) and returns: model_class,  model_info