






"""simple docstring"""
from __future__ import annotations

def        snake_case   (     A__			,A__		):
			print(F"""Vertex\tShortest Distance from vertex {src}"""		)
			for i, d in enumerate(A__		):
						print(F"""{i}\t\t{d}"""		)

def        snake_case   (     A__			,A__			,A__		):
			for j in range(A__		):
						UpperCAmelCase_  ,			UpperCAmelCase_  ,			UpperCAmelCase_  :				Any      =      (graph[j][k] for k in ["src", "dst", "weight"])
						if distance[u] != float("inf"		) and distance[u] + w < distance[v]:
									return True
			return False

def        snake_case   (     A__			,A__			,A__			,A__		):
			UpperCAmelCase_  :				Optional[Any]      =      [float("inf"		)] * vertex_count
			UpperCAmelCase_  :				Any      =      0.0

			for _ in range(vertex_count - 1		):
						for j in range(A__		):
									UpperCAmelCase_  ,			UpperCAmelCase_  ,			UpperCAmelCase_  :				Tuple      =      (graph[j][k] for k in ["src", "dst", "weight"])

									if distance[u] != float("inf"		) and distance[u] + w < distance[v]:
												UpperCAmelCase_  :				List[Any]      =      distance[u] + w

			UpperCAmelCase_  :				Any      =      check_negative_cycle(A__			,A__			,A__		)
			if negative_cycle_exists:
						raise Exception("Negative cycle found"		)

			return distance


if __name__ == "__main__":
			import doctest

			doctest.testmod()

			lowerCamelCase_       			=   int(input('''Enter number of vertices: ''').strip())
			lowerCamelCase_       			=   int(input('''Enter number of edges: ''').strip())

			lowerCamelCase_       			=   [{} for _ in range(E)]

			for i in range(E):
						print('''Edge ''', i + 1)
						lowerCamelCase_			,	lowerCamelCase_			,	lowerCamelCase_       			=   (
						    int(x)
						    for x in input('''Enter source, destination, weight: ''').strip().split(''' ''')
						)
						lowerCamelCase_       			=   {'''src''': src, '''dst''': dest, '''weight''': weight}

			lowerCamelCase_       			=   int(input('''\nEnter shortest path source:''').strip())
			lowerCamelCase_       			=   bellman_ford(graph, V, E, source)
			print_distance(shortest_distance, 0)











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



