code: def create_scikit_model_weights():
      master_seed(1234)
  
      model_list = {
          "decisionTreeClassifier": DecisionTreeClassifier(),
          "extraTreeClassifier": ExtraTreeClassifier(),
          "adaBoostClassifier": AdaBoostClassifier(),
          "baggingClassifier": BaggingClassifier(),
          "extraTreesClassifier": ExtraTreesClassifier(n_estimators=10),
          "gradientBoostingClassifier": GradientBoostingClassifier(
              n_estimators=10
          ),
          "randomForestClassifier": RandomForestClassifier(
              n_estimators=10
          ),
          "logisticRegression": LogisticRegression(
              solver="lbfgs", multi_class="auto"
          ),
          "svc": SVC(gamma="auto"),
          "linearSVC": LinearSVC(),
      }
  
      clipped_models = {
          model_name: model for model_name, model in model_list.items()
      }
      unclipped_models = {
          model_name: model for model_name, model in model_list.items()
      }
  
      (x_train_iris, y_train_iris), (_, _), _, _ = load_dataset("iris")
  
      y_train_iris = np.argmax(y_train_iris, axis=1)
  
      for model_name, model in clipped_models.items():
          model.fit(X=x_train_iris, y=y_train_iris)
          pickle.dump(
              model,
              open(
                  os.path.join(
                      os.path.dirname(os.path.dirname(__file__)),
                      "resources/models/scikit/",
                      "scikit-"
                      + model_name
                      + "-iris-clipped-ge-1.3.0.pickle",
                  ),
                  "wb",
              ),
          )
  
      for model_name, model in unclipped_models.items():
          model.fit(X=x_train_iris, y=y_train_iris)
          pickle.dump(
              model,
              open(
                  os.path.join(
                      os.path.dirname(os.path.dirname(__file__)),
                      "resources/models/scikit/",
                      "scikit-"
                      + model_name
                      + "-iris-unclipped-ge-1.3.0.pickle",
                  ),
                  "wb",
              ),
          )
  
file_path: adversarial-robustness-toolbox/utils/resources/create_model_weights.py
imports: import os
  import pickle
  import tensorflow
  from tensorflow.keras.models import Sequential
  from tensorflow.keras.layers import Dense, Flatten, Conv2D, MaxPooling2D
  from sklearn.linear_model import LogisticRegression
  from sklearn.svm import SVC, LinearSVC
  from sklearn.tree import DecisionTreeClassifier, ExtraTreeClassifier
  from sklearn.ensemble import AdaBoostClassifier, BaggingClassifier, ExtraTreesClassifier
  from sklearn.ensemble import GradientBoostingClassifier, RandomForestClassifier
  import numpy
  from tests.utils import load_dataset, master_seed
label_desc: Use image node_id 3 for calling a global function with example usage: create_scikit_model_weights() without return types