



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
       __snake_case       :	int            =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')
       __snake_case      ,						__snake_case       :	Optional[Any]            =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')
              __snake_case       :	List[Any]            =rh.cluster(
                  name='rh-cluster', ips=[args.host], ssh_creds={'ssh_user': args.user, 'ssh_private_key': args.key_path}
              )
       else:
              __snake_case       :	Optional[int]            =rh.cluster(
                  name='rh-cluster', instance_type=args.instance, provider=args.provider, use_spot=args.use_spot
              )
       __snake_case       :	List[Any]            =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)






from __future__ import annotations






def 			lowerCAmelCase__	(					lowerCamelCase_	:	list[int]):





				'''simple docstring'''

				return len(set(lowerCamelCase_)) == len(lowerCamelCase_)


if __name__ == "__main__":
							import doctest

							doctest.testmod()

