




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
		lowercase__							:	Tuple											=		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")
		lowercase__						,			lowercase__							:	List[str]											=		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")
				lowercase__							:	Dict											=		rh.cluster(
				    name="rh-cluster", ips=[args.host], ssh_creds={"ssh_user": args.user, "ssh_private_key": args.key_path}
				)
		else:
				lowercase__							:	Any											=		rh.cluster(
				    name="rh-cluster", instance_type=args.instance, provider=args.provider, use_spot=args.use_spot
				)
		lowercase__							:	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)






from abc import ABC, abstractmethod
from argparse import ArgumentParser
class 						UpperCAmelCase  (							UpperCAmelCase__     ):







						'''simple docstring'''





						@staticmethod
						@abstractmethod
						def 			snake_case__		(		__lowercase				:	ArgumentParser		):






							"""simple docstring"""






							raise NotImplementedError()






						@abstractmethod
						def 			snake_case__		(		self				:	Optional[Any]		):






							"""simple docstring"""






							raise NotImplementedError()
