code: def get_name_from_model(model):
      if isinstance(model, LogisticRegression):
          return "LogisticRegression"
      if isinstance(model, RandomForestClassifier):
          return "RandomForestClassifier"
      if isinstance(model, RidgeClassifier):
          return "RidgeClassifier"
      if isinstance(model, GradientBoostingClassifier):
          return "GradientBoostingClassifier"
      if isinstance(model, ExtraTreesClassifier):
          return "ExtraTreesClassifier"
      if isinstance(model, AdaBoostClassifier):
          return "AdaBoostClassifier"
      if isinstance(model, SGDClassifier):
          return "SGDClassifier"
      if isinstance(model, Perceptron):
          return "Perceptron"
      if isinstance(model, PassiveAggressiveClassifier):
          return "PassiveAggressiveClassifier"
      if isinstance(model, LinearRegression):
          return "LinearRegression"
      if isinstance(model, RandomForestRegressor):
          return "RandomForestRegressor"
      if isinstance(model, Ridge):
          return "Ridge"
      if isinstance(model, ExtraTreesRegressor):
          return "ExtraTreesRegressor"
      if isinstance(model, AdaBoostRegressor):
          return "AdaBoostRegressor"
      if isinstance(model, RANSACRegressor):
          return "RANSACRegressor"
      if isinstance(model, GradientBoostingRegressor):
          return "GradientBoostingRegressor"
      if isinstance(model, Lasso):
          return "Lasso"
      if isinstance(model, ElasticNet):
          return "ElasticNet"
      if isinstance(model, LassoLars):
          return "LassoLars"
      if isinstance(model, OrthogonalMatchingPursuit):
          return "OrthogonalMatchingPursuit"
      if isinstance(model, BayesianRidge):
          return "BayesianRidge"
      if isinstance(model, ARDRegression):
          return "ARDRegression"
      if isinstance(model, SGDRegressor):
          return "SGDRegressor"
      if isinstance(model, PassiveAggressiveRegressor):
          return "PassiveAggressiveRegressor"
      if isinstance(model, MiniBatchKMeans):
          return "MiniBatchKMeans"
      if isinstance(model, LinearSVR):
          return "LinearSVR"
      if isinstance(model, LinearSVC):
          return "LinearSVC"
  
      if xgb_installed:
          if isinstance(model, XGBClassifier):
              return "XGBClassifier"
          if isinstance(model, XGBRegressor):
              return "XGBRegressor"
  
      if keras_imported:
          if isinstance(model, KerasRegressor):
              return "DeepLearningRegressor"
          if isinstance(model, KerasClassifier):
              return "DeepLearningClassifier"
  
      if lgb_installed:
          if isinstance(model, LGBMClassifier):
              return "LGBMClassifier"
          if isinstance(model, LGBMRegressor):
              return "LGBMRegressor"
  
      if catboost_installed:
          if isinstance(model, CatBoostClassifier):
              return "CatBoostClassifier"
          if isinstance(model, CatBoostRegressor):
              return "CatBoostRegressor"
  
file_path: auto_ml/auto_ml/utils_models.py
imports: import dill
  import os
  import random
  import sys
  from auto_ml import utils
  from auto_ml import utils_categorical_ensembling
  from sklearn.ensemble import RandomForestClassifier, RandomForestRegressor, ExtraTreesRegressor, AdaBoostRegressor, GradientBoostingRegressor, GradientBoostingClassifier, ExtraTreesClassifier, AdaBoostClassifier
  from sklearn.linear_model import RANSACRegressor, LinearRegression, Ridge, Lasso, ElasticNet, LassoLars, OrthogonalMatchingPursuit, BayesianRidge, ARDRegression, SGDRegressor, PassiveAggressiveRegressor, LogisticRegression, RidgeClassifier, SGDClassifier, Perceptron, PassiveAggressiveClassifier
  from sklearn.svm import LinearSVC, LinearSVR
  from sklearn.cluster import MiniBatchKMeans
label_desc: Use image node_id 2 for calling a global function with example usage: get_name_from_model(model) and returns: str, str, str, str, str, str, str, str, str, str, str, str, str, str, str, str, str, str, str, str, str, str, str, str, str, str, str, str, str, str, str, str, str, str, str