



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









def 					__lowerCAmelCase		(  __lowerCamelCase	:    int = 3				,   __lowerCamelCase	:    int = 7				,   __lowerCamelCase	:    int = 1000000	)  ->						int:
					__lowerCAmelCase	   =0
					__lowerCAmelCase	   =1

					for current_denominator in range(1				,   limit + 1	):
										__lowerCAmelCase	   =current_denominator * numerator // denominator
										if current_denominator % denominator == 0:
															current_numerator -= 1
										if current_numerator * max_denominator > current_denominator * max_numerator:
															__lowerCAmelCase	   =current_numerator
															__lowerCAmelCase	   =current_denominator
					return max_numerator


if __name__ == "__main__":
				print(solution(numerator=3, denominator=7, limit=1_00_00_00))




