code: def get_iris_data(test_size=0.2):
      iris_data = load_iris()
      x = iris_data.data
      y = iris_data.target.reshape(-1, 1)
      encoder = OneHotEncoder(sparse=False)
      y = encoder.fit_transform(y)
      train_x, test_x, train_y, test_y = train_test_split(x, y)
      return train_x, train_y, test_x, test_y
  
imports: import tensorflow
  from sklearn.datasets import load_iris
  from sklearn.model_selection import train_test_split
  from sklearn.preprocessing import OneHotEncoder
label_desc: Use image node_id 1 for calling a global function with example usage: get_iris_data(test_size) and returns: train_x,  train_y,  test_x,  test_y