code: def main(bucket):
      secrets_file = os.path.join(
          os.path.dirname(__file__), "..", "aws_secrets.txt"
      )
      if os.path.isfile(secrets_file):
          print(f"Loading AWS secrets from file {secrets_file}")
  
          from configparser import ConfigParser
  
          config = ConfigParser()
          config.read(secrets_file)
  
          for k, v in config.items():
              for x, y in v.items():
                  var = str(x).upper()
                  os.environ[var] = str(y)
      else:
          print("No AWS secrets file found. Loading from boto.")
          try:
              from boto3 import Session
  
              session = Session()
              credentials = session.get_credentials()
              current_credentials = credentials.get_frozen_credentials()
  
              os.environ[
                  "AWS_ACCESS_KEY_ID"
              ] = current_credentials.access_key
              os.environ[
                  "AWS_SECRET_ACCESS_KEY"
              ] = current_credentials.secret_key
              os.environ[
                  "AWS_SESSION_TOKEN"
              ] = current_credentials.token
          except Exception:
              print(
                  "Cannot setup AWS credentials (is this running on GCE?)"
              )
  
      if all(
          os.getenv(k, "")
          for k in [
              "AWS_ACCESS_KEY_ID",
              "AWS_SECRET_ACCESS_KEY",
              "AWS_SESSION_TOKEN",
          ]
      ):
          print("AWS secrets found in env.")
      else:
          print("Warning: No AWS secrets found in env!")
  
      ray.init(address="auto")
  
      num_samples = 16
      results_per_second = (
          5 / 60
      )  # 5 results per minute = 1 every 12 seconds
      trial_length_s = 300
  
      max_runtime = 650
  
      timed_tune_run(
          name="durable trainable",
          num_samples=num_samples,
          results_per_second=results_per_second,
          trial_length_s=trial_length_s,
          max_runtime=max_runtime,
          checkpoint_freq_s=12,  # Once every 12 seconds (once per result)
          checkpoint_size_b=int(10 * 1000**2),  # 10 MB
          keep_checkpoints_num=2,
          resources_per_trial={"cpu": 2},
          storage_path=bucket,
      )
  
imports: import argparse
  import os
  import ray
  from ray.tune.utils.release_test_util import timed_tune_run
label_desc: Use image node_id 1 for calling a global function with example usage: main(bucket) without return types