'''simple docstring'''






import argparse
import shlex

import runhouse as rh


if __name__ == "__main__":
    # Refer to https://runhouse-docs.readthedocs-hosted.com/en/latest/api/python/cluster.html#hardware-setup for cloud access
    # setup instructions, if using on-demand hardware

    # If user passes --user <user> --host <host> --key_path <key_path> <example> <args>, fill them in as BYO cluster
    # If user passes --instance <instance> --provider <provider> <example> <args>, fill them in as on-demand cluster
    # Throw an error if user passes both BYO and on-demand cluster args
    # Otherwise, use default values
    SCREAMING_SNAKE_CASE_	   =			argparse.ArgumentParser()
    parser.add_argument('--user', type=str, default='ubuntu')
    parser.add_argument('--host', type=str, default='localhost')
    parser.add_argument('--key_path', type=str, default=None)
    parser.add_argument('--instance', type=str, default='V100:1')
    parser.add_argument('--provider', type=str, default='cheapest')
    parser.add_argument('--use_spot', type=bool, default=False)
    parser.add_argument('--example', type=str, default='pytorch/text-generation/run_generation.py')
    SCREAMING_SNAKE_CASE_	   =			parser.parse_known_args()
    if args.host != "localhost":
        if args.instance != "V100:1" or args.provider != "cheapest":
            raise ValueError('Cannot specify both BYO and on-demand cluster args')
        SCREAMING_SNAKE_CASE_	   =			rh.cluster(
            name='rh-cluster', ips=[args.host], ssh_creds={'ssh_user': args.user, 'ssh_private_key': args.key_path}
        )
    else:
        SCREAMING_SNAKE_CASE_	   =			rh.cluster(
            name='rh-cluster', instance_type=args.instance, provider=args.provider, use_spot=args.use_spot
        )
    SCREAMING_SNAKE_CASE_	   =			args.example.rsplit('/', 1)[0]

    # Set up remote environment
    cluster.install_packages(['pip:./'])  # Installs transformers from local source
    # Note transformers is copied into the home directory on the remote machine, so we can install from there
    cluster.run([f"""pip install -r transformers/examples/{example_dir}/requirements.txt"""])
    cluster.run(['pip install torch --upgrade --extra-index-url https://download.pytorch.org/whl/cu117'])

    # Run example. You can bypass the CLI wrapper and paste your own code here.
    cluster.run([f"""python transformers/examples/{args.example} {" ".join(shlex.quote(arg) for arg in unknown)}"""])

    # Alternatively, we can just import and run a training function (especially if there's no wrapper CLI):
    # from my_script... import train
    # reqs = ['pip:./', 'torch', 'datasets', 'accelerate', 'evaluate', 'tqdm', 'scipy', 'scikit-learn', 'tensorboard']
    # launch_train_gpu = rh.function(fn=train,
    #                                system=gpu,
    #                                reqs=reqs,
    #                                name='train_bert_glue')
    #
    # We can pass in arguments just like we would to a function:
    # launch_train_gpu(num_epochs = 3, lr = 2e-5, seed = 42, batch_size = 16
    #                  stream_logs=True)
'''simple docstring'''






def  UpperCamelCase__					(					_lowercase    :				list     )							->	list:
  if len(_lowercase     ) <= 1:
    return lst

  __UpperCAmelCase:					List[str]		= 1

  while i < len(_lowercase     ):
    if lst[i - 1] <= lst[i]:
      i += 1
    else:
      __UpperCAmelCase, __UpperCAmelCase:					Tuple		= lst[i], lst[i - 1]
      i -= 1
      if i == 0:
        __UpperCAmelCase:					List[str]		= 1

  return lst


if __name__ == "__main__":
    SCREAMING_SNAKE_CASE_	   =			input('Enter numbers separated by a comma:\n').strip()
    SCREAMING_SNAKE_CASE_	   =			[int(item) for item in user_input.split(',')]
    print(gnome_sort(unsorted))