code: def load_data(y_name="Species"):
      """Returns the iris dataset as (train_x, train_y), (test_x, test_y)."""
      train_path, test_path = maybe_download()
  
      train = pd.read_csv(train_path, names=CSV_COLUMN_NAMES, header=0)
      train_x, train_y = train, train.pop(y_name)
  
      test = pd.read_csv(test_path, names=CSV_COLUMN_NAMES, header=0)
      test_x, test_y = test, test.pop(y_name)
  
      return (train_x, train_y), (test_x, test_y)
  
file_path: auptimizer/Examples/tf_iris_diff_opt/iris_data.py
imports: import pandas
  import tensorflow
label_desc: Use image node_id 2 for calling a global function with example usage: load_data(y_name) and returns: train_x,  train_y,  test_x,  test_y