code: def testing_pipeline(seed, save_model):
      conf = dsl.get_pipeline_conf()
      conf.add_op_transformer(add_wandb_env_variables)
  
      setup_data_task = setup_data()
      setup_dataloaders_task = setup_dataloaders(
          setup_data_task.outputs["train_dataset"],
          setup_data_task.outputs["test_dataset"],
          batch_size=32,
      )
      train_model_task = train_model(  # noqa: F841
          setup_dataloaders_task.outputs["train_dataloader"],
          setup_dataloaders_task.outputs["test_dataloader"],
          save_model=save_model,
      )
  
file_path: wandb/tests/functional_tests/t0_main/kfp/kfp-pipeline-pytorch.py
imports: import os
  import random
  import kfp
  import kfp.dsl
  import wandb
  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, save_model) without return types