code: def get_activation_layer(activation):
      if activation == "LeakyReLU":
          return LeakyReLU()
      if activation == "PReLU":
          return PReLU()
      if activation == "ELU":
          return ELU()
      if activation == "ThresholdedReLU":
          return ThresholdedReLU()
  
      return Activation(activation)
  
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 7 for calling a global function with example usage: get_activation_layer(activation) and returns: Activation, LeakyReLU, PReLU, ELU, ThresholdedReLU