code: def record_ppo_config(directory):
      # Start recording traces after 80 episodes -- by then, the environment is solved
      runner = Runner(
          agent=dict(
              agent="benchmarks/configs/ppo.json",
              recorder=dict(directory=directory, start=80),
          ),
          environment="benchmarks/configs/cartpole.json",
      )
      runner.run(num_episodes=100)
      runner.close()
  
imports: import os
  import numpy
  from tensorforce import Agent, Environment, Runner
label_desc: Use image node_id 2 for calling a global function with example usage: record_ppo_config(directory) without return types