code: def forecast(self, X):
      return np.array([random.random() for _ in range(len(X))])
  
imports: import json
  import random
  import ssl
  import numpy
  import pandas
  import pytest
  from dice_ml.utils import helpers
  from sklearn.model_selection import train_test_split
  from rai_test_utils.datasets.tabular import create_iris_data
  from raiutils.common.retries import retry_function
label_desc: Use image node_id 1 for calling the RandomForecastingModel obj's underlying member method code with example usage: obj.forecast(X) and returns: np