code: def log_transform(all_targets):
      all_targets = np.log1p(all_targets)
      return all_targets, np.expm1
  
file_path: hyperparameter_hunter/examples/feature_engineering_examples/target_transform_inverse_example.py
imports: from hyperparameter_hunter import Environment, CVExperiment, FeatureEngineer
  from hyperparameter_hunter import DummyOptPro, Categorical
  from hyperparameter_hunter.utils.learning_utils import get_boston_data
  import numpy
  from sklearn.linear_model import Ridge
  from sklearn.model_selection import train_test_split
  from sklearn.preprocessing import QuantileTransformer, StandardScaler
label_desc: Use image node_id 3 for calling a global function with example usage: log_transform(all_targets) and returns: all_targets,  np