


"""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
       UpperCAmelCase__					=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")
       UpperCAmelCase__				,   UpperCAmelCase__					=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")
              UpperCAmelCase__					=rh.cluster(
                  name="rh-cluster", ips=[args.host], ssh_creds={"ssh_user": args.user, "ssh_private_key": args.key_path}
              )
       else:
              UpperCAmelCase__					=rh.cluster(
                  name="rh-cluster", instance_type=args.instance, provider=args.provider, use_spot=args.use_spot
              )
       UpperCAmelCase__					=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 lowerCAmelCase_   (					UpperCamelCase__						:			Union[str, Any]					, UpperCamelCase__						:			Union[str, Any]					, UpperCamelCase__						:			int			):






 """simple docstring"""







 if n == 0:
  return 1

 elif n % 2 == 1:
  return (binary_exponentiation(UpperCamelCase__					, n - 1					, UpperCamelCase__			) * a) % mod

 else:
  __lowercase						=						binary_exponentiation(UpperCamelCase__					, n / 2					, UpperCamelCase__			)
  return (b * b) % mod


# a prime number
UpperCAmelCase__					=701

UpperCAmelCase__					=10_0000_0000
UpperCAmelCase__					=10

# using binary exponentiation function, O(log(p)):
print((a / b) % p == (a * binary_exponentiation(b, p - 2, p)) % p)

print((a / b) % p == (a * b ** (p - 2)) % p)
