code: def explore(config):
      # Ensure we collect enough timesteps to do sgd.
      if config["train_batch_size"] < config["sgd_minibatch_size"] * 2:
          config["train_batch_size"] = config["sgd_minibatch_size"] * 2
      # Ensure we run at least one sgd iter.
      if config["lambda"] > 1:
          config["lambda"] = 1
      config["train_batch_size"] = int(config["train_batch_size"])
      return config
  
file_path: ray/python/ray/tune/examples/pb2_ppo_example.py
imports: import os
  import random
  import argparse
  import pandas
  from datetime import datetime
  from ray.tune import run, sample_from
  from ray.tune.schedulers import PopulationBasedTraining
  from ray.tune.schedulers.pb2 import PB2
label_desc: Use image node_id 1 for calling a global function with example usage: explore(config) and returns: config