code: def evaluate(self, X: np.ndarray) -> np.ndarray:
      return np.exp(X)
  
imports: from abc import abstractmethod
  from typing import Any
  import numpy
  import sklearn
  from packaging import version
  from sklearn.pipeline import make_pipeline
  from sklearn.preprocessing import PolynomialFeatures
  from sklearn.ensemble import AdaBoostRegressor, ExtraTreesRegressor, HistGradientBoostingRegressor, RandomForestRegressor
  from sklearn.gaussian_process import GaussianProcessRegressor
  from sklearn.linear_model import ElasticNetCV, LassoCV, LassoLarsIC, LinearRegression, RidgeCV
  from sklearn.neighbors import KNeighborsRegressor
  from sklearn.svm import SVR
  from dowhy.gcm.ml.prediction_model import PredictionModel
  from dowhy.gcm.util.general import auto_apply_encoders, auto_fit_encoders, shape_into_2d
label_desc: Use image node_id 1 for calling the InvertibleExponentialFunction obj's underlying member method code with example usage: obj.evaluate(X) and returns: np