def main(args):
"""Main function which runs worker."""
title = '## Starting evaluation of round {0} ##'.format(args.round_name)
logging.info('\n'
+ '#' * len(title) + '\n'
+ '#' * len(title) + '\n'
+ '##' + ' ' * (len(title)-2) + '##' + '\n'
+ title + '\n'
+ '#' * len(title) + '\n'
+ '#' * len(title) + '\n'
+ '##' + ' ' * (len(title)-2) + '##' + '\n')
if args.blacklisted_submissions:
logging.warning('BLACKLISTED SUBMISSIONS: %s',
args.blacklisted_submissions)
random.seed()
logging.info('Running nvidia-docker to ensure that GPU works')
shell_call(['docker', 'run', '--runtime=nvidia',
'--rm', 'nvidia/cuda', 'nvidia-smi'])
eval_worker = EvaluationWorker(
worker_id=args.worker_id,
storage_client=eval_lib.CompetitionStorageClient(
args.project_id, args.storage_bucket),
datastore_client=eval_lib.CompetitionDatastoreClient(
args.project_id, args.round_name),
storage_bucket=args.storage_bucket,
round_name=args.round_name,
dataset_name=args.dataset_name,
blacklisted_submissions=args.blacklisted_submissions,
num_defense_shards=args.num_defense_shards)
eval_worker.run_work()
def main(args):
"""Main function which runs worker."""
title = "## Starting evaluation of round {0} ##".format(args.round_name)
logging.info("\n" + "#" * len(title) + "\n" + "#" * len(title) + "\n" +
"##" + " " * (len(title) - 2) + "##" + "\n" + title + "\n" +
"#" * len(title) + "\n" + "#" * len(title) + "\n" + "##" +
" " * (len(title) - 2) + "##" + "\n")
if args.blacklisted_submissions:
logging.warning("BLACKLISTED SUBMISSIONS: %s",
args.blacklisted_submissions)
random.seed()
logging.info("Running nvidia-docker to ensure that GPU works")
shell_call([
"docker", "run", "--runtime=nvidia", "--rm", "nvidia/cuda",
"nvidia-smi"
])
eval_worker = EvaluationWorker(
worker_id=args.worker_id,
storage_client=eval_lib.CompetitionStorageClient(
args.project_id, args.storage_bucket),
datastore_client=eval_lib.CompetitionDatastoreClient(
args.project_id, args.round_name),
storage_bucket=args.storage_bucket,
round_name=args.round_name,
dataset_name=args.dataset_name,
blacklisted_submissions=args.blacklisted_submissions,
num_defense_shards=args.num_defense_shards,
)
eval_worker.run_work()
def main(args):
"""Main function which runs master."""
if args.blacklisted_submissions:
logging.warning("BLACKLISTED SUBMISSIONS: %s",
args.blacklisted_submissions)
if args.limited_dataset:
logging.info("Using limited dataset: 3 batches * 10 images")
max_dataset_num_images = 30
batch_size = 10
else:
logging.info("Using full dataset. Batch size: %d", DEFAULT_BATCH_SIZE)
max_dataset_num_images = None
batch_size = DEFAULT_BATCH_SIZE
random.seed()
print("\nRound: {0}\n".format(args.round_name))
eval_master = EvaluationMaster(
storage_client=eval_lib.CompetitionStorageClient(
args.project_id, args.storage_bucket),
datastore_client=eval_lib.CompetitionDatastoreClient(
args.project_id, args.round_name),
round_name=args.round_name,
dataset_name=args.dataset_name,
blacklisted_submissions=args.blacklisted_submissions,
results_dir=args.results_dir,
num_defense_shards=args.num_defense_shards,
verbose=args.verbose,
batch_size=batch_size,
max_dataset_num_images=max_dataset_num_images,
)
if args.command == "attack":
eval_master.prepare_attacks()
elif args.command == "defense":
eval_master.prepare_defenses()
elif args.command == "cleanup_defenses":
eval_master.cleanup_defenses()
elif args.command == "results":
eval_master.compute_results()
elif args.command == "status":
eval_master.show_status()
elif args.command == "cleanup_datastore":
eval_master.cleanup_datastore()
elif args.command == "cleanup_failed_attacks":
eval_master.cleanup_failed_attacks()
elif args.command == "cleanup_attacks_with_zero_images":
eval_master.cleanup_attacks_with_zero_images()
else:
print("Invalid command: ", args.command)
print("")
print(USAGE)
