code: def _check_model(model, n_classes, pred_func):
      """
      Check input model, return class information and predict function.
  
      Parameters
      ----------
      model : object
          The input model object.
          It should have either `predict_proba` or `predict` method if pred_func is not provided.
          It should have `n_classes_` attribute if n_classes is not provided or it's a regression model.
      n_classes : int, optional
          The number of classes in the target variable. If not provided, it will try to obtain the value from the model.
      pred_func : callable, optional
          The prediction function to be used. If not provided, it will try to obtain the function from the model.
  
      Returns
      -------
      int
          The number of classes in the target variable.
      callable
          The prediction function to be used.
      bool
          Flag indicating if the prediction function was obtained from the model or was provided as input.
  
      Raises
      ------
      AssertionError
          If `n_classes` is not provided and cannot be accessed through `model.n_classes_`,
          or if `pred_func` is not provided and neither `model.predict_proba` nor `model.predict` exist.
      """
  
      n_classes_ = None
      if hasattr(model, "n_classes_"):
          n_classes_ = model.n_classes_
  
      if n_classes_ is None:
          assert (
              n_classes is not None
          ), "n_classes is required when it can't be accessed through model.n_classes_."
      else:
          n_classes = n_classes_
  
      if pred_func is None:
          pred_func_ = None
          from_model = True
          if hasattr(model, "predict_proba"):
              pred_func_ = model.predict_proba
          elif hasattr(model, "predict"):
              pred_func_ = model.predict
          assert (
              pred_func_ is not None
          ), "pred_func is required when model.predict_proba or model.predict doesn't exist."
          pred_func = pred_func_
          print("obtain pred_func from the provided model.")
      else:
          print("using provided pred_func.")
          from_model = False
  
      return n_classes, pred_func, from_model
  
imports: import numpy
  import pandas
  import psutil
label_desc: Use image node_id 6 for calling a global function with example usage: _check_model(model, n_classes, pred_func) and returns: n_classes,  pred_func,  from_model