code: def check_label_dict(label_dict, case, classes=None):
      """
      Check if label_dict and model _classes match
  
      Parameters
      ----------
      label_dict: dict
          Dictionary mapping integer labels to domain names (classification - target values).
      case: string
          String that informs if the model used is for classification or regression problem.
      classes: list, None
          List of labels if the model used is for classification problem, None otherwise.
      """
      if label_dict is not None and case == "classification":
          if set(classes) != set(list(label_dict.keys())):
              raise ValueError(
                  "label_dict and don't match: \n"
                  + f"label_dict keys: {str(list(label_dict.keys()))}\n"
                  + f"Classes model values {str(classes)}"
              )
  
imports: import copy
  import numpy
  import pandas
  from shapash.utils.category_encoder_backend import no_dummies_category_encoder, supported_category_encoder, dummies_category_encoder
  from shapash.utils.columntransformer_backend import no_dummies_sklearn, supported_sklearn
  from shapash.utils.model import extract_features_model
  from shapash.utils.model_synoptic import dict_model_feature
  from shapash.utils.transform import preprocessing_tolist, check_transformers
  from shapash.utils.columntransformer_backend import columntransformer, get_feature_names, get_list_features_names
label_desc: Use image node_id 3 for calling a global function with example usage: check_label_dict(label_dict, case, classes) without return types