
'''simple docstring'''





from __future__ import annotations


def 							__A(lowerCAmelCase						,  lowerCAmelCase )		->				Optional[Any]:

		"""simple docstring"""






		print(F'Vertex\tShortest Distance from vertex {src}' )
		for i, d in enumerate(lowerCAmelCase ):
				print(F'{i}\t\t{d}' )


def 							__A(lowerCAmelCase						,  lowerCAmelCase						,  lowerCAmelCase )		->				Optional[Any]:

		"""simple docstring"""






		for j in range(lowerCAmelCase ):
				_UpperCamelCase						    =	(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 							__A(lowerCAmelCase						,  lowerCAmelCase						,  lowerCAmelCase						,  lowerCAmelCase )		->				list[float]:

		"""simple docstring"""






		_UpperCamelCase						    =	[float("""inf""" )] * vertex_count
		_UpperCamelCase						    =	0.0

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

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

		_UpperCamelCase						    =	check_negative_cycle(lowerCAmelCase						,  lowerCAmelCase						,  lowerCAmelCase )
		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)





import platform
from argparse import ArgumentParser

import huggingface_hub

from .. import __version__ as version
from ..utils import is_accelerate_available, is_torch_available, is_transformers_available, is_xformers_available
from . import BaseDiffusersCLICommand


def 							__A(lowerCAmelCase )		->				Optional[int]:

		"""simple docstring"""






		return EnvironmentCommand()







class        lowerCAmelCase__      (   __lowercase	):

						@staticmethod
						def  A_				(			a				)					->      List[str]:


								'''simple docstring'''

								_UpperCamelCase						    =	parser.add_parser("""env"""				)
								download_parser.set_defaults(func=a				)

						def  A_				(			self				)					->      List[str]:


								'''simple docstring'''

								_UpperCamelCase						    =	huggingface_hub.__version__

								_UpperCamelCase						    =	"""not installed"""
								_UpperCamelCase						    =	"""NA"""
								if is_torch_available():
										import torch

										_UpperCamelCase						    =	torch.__version__
										_UpperCamelCase						    =	torch.cuda.is_available()

								_UpperCamelCase						    =	"""not installed"""
								if is_transformers_available():
										import transformers

										_UpperCamelCase						    =	transformers.__version__

								_UpperCamelCase						    =	"""not installed"""
								if is_accelerate_available():
										import accelerate

										_UpperCamelCase						    =	accelerate.__version__

								_UpperCamelCase						    =	"""not installed"""
								if is_xformers_available():
										import xformers

										_UpperCamelCase						    =	xformers.__version__

								_UpperCamelCase						    =	{
								    """`diffusers` version""": version,
								    """Platform""": platform.platform(),
								    """Python version""": platform.python_version(),
								    """PyTorch version (GPU?)""": F'{pt_version} ({pt_cuda_available})',
								    """Huggingface_hub version""": hub_version,
								    """Transformers version""": transformers_version,
								    """Accelerate version""": accelerate_version,
								    """xFormers version""": xformers_version,
								    """Using GPU in script?""": """<fill in>""",
								    """Using distributed or parallel set-up in script?""": """<fill in>""",
								}

								print("""\nCopy-and-paste the text below in your GitHub issue and FILL OUT the two last points.\n"""				)
								print(self.format_dict(a				)				)

								return info







						@staticmethod
						def  A_				(			a				)					->      Dict:


								'''simple docstring'''

								return "\n".join([F'- {prop}: {val}' for prop, val in d.items()]				) + "\n"



