code: def generate_classification_data(
      f,
      num_example,
      num_features,
      classify_func,
      seed=random.randint(0, 100),
      bounds=None,
  ):
      random.seed(seed)
      classify_func_obj = get_function_object(
          "classification.classification_functions",
          classify_func["name"],
      )
      if not bounds:
          bounds = [[0, 1] for _ in range(num_features)]
      for _ in range(num_example):
          x = [
              random.uniform(bounds[index][0], bounds[index][1])
              for index in range(num_features)
          ]
          y = classify_func_obj(x, **classify_func["params"])
          f.write(
              f"{y} |f {' '.join([f'x{i}:{x[i]}' for i in range(num_features)])}\n"
          )
  
label_desc: Use image node_id 1 for calling a global function with example usage: generate_classification_data(f, num_example, num_features, classify_func, seed, bounds) without return types