




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'''
import unittest

from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script




@require_cpu
class 			lowerCamelCase_   (	unittest.TestCase      ):






      def lowercase_							(					self				:    Tuple ):


          '''simple docstring'''


          debug_launcher(test_script.main )






      def lowercase_							(					self				:    List[str] ):


          '''simple docstring'''


          debug_launcher(test_ops.main )
