"""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
     _a   :	List[str] 					=     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')
     _a					,     _a   :	Dict 					=     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')
          _a   :	Any 					=     rh.cluster(
              name='rh-cluster', ips=[args.host], ssh_creds={'ssh_user': args.user, 'ssh_private_key': args.key_path}
          )
     else:
          _a   :	List[Any] 					=     rh.cluster(
              name='rh-cluster', instance_type=args.instance, provider=args.provider, use_spot=args.use_spot
          )
     _a   :	Optional[int] 					=     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 							SCREAMING_SNAKE_CASE  (    _lowerCamelCase		: int = 1000000			) ->   int:
  _lowerCAmelCase		: List[str]						    =  [i - 1 for i in range(limit + 1			)]

  for i in range(2    ,limit + 1			):
    if phi[i] == i - 1:
      for j in range(2 * i    ,limit + 1    ,_lowerCamelCase			):
        phi[j] -= phi[j] // i

  return sum(phi[2 : limit + 1]			)


if __name__ == "__main__":
     print(solution())




