code: def testing_pipeline(seed: int):
      conf = dsl.get_pipeline_conf()
      conf.add_op_transformer(add_wandb_env_variables)
  
      preprocess_data_task = preprocess_data(seed)
      train_model_task = train_model(
          preprocess_data_task.outputs["X_train"],
          preprocess_data_task.outputs["y_train"],
      )
      test_model_task = test_model(  # noqa: F841
          preprocess_data_task.outputs["X_test"],
          preprocess_data_task.outputs["y_test"],
          train_model_task.output,
      )
  
file_path: wandb/tests/functional_tests/t0_main/kfp/kfp-pipeline-sklearn.py
imports: import os
  import random
  from typing import NamedTuple
  import kfp
  import kfp.dsl
  from kfp import components
  from kubernetes.client.models import V1EnvVar
  from wandb.integration.kfp import wandb_log
  from wandb_probe import wandb_probe_package
label_desc: Use image node_id 5 for calling a global function with example usage: testing_pipeline(seed) without return types