from __future__ import annotations

from collections import Counter
from random import random


class _a  :

	'''simple docstring'''



	def __init__(  self       ):
			__A				:       List[str]			    = {}

	def 	__UpperCAmelCase(  self				,					__UpperCAmelCase       ):
			__A				:       List[Any]			    = {}

	def 	__UpperCAmelCase(  self				,					__UpperCAmelCase				,					__UpperCAmelCase				,					__UpperCAmelCase       ):







			if nodea not in self.connections:
					self.add_node(__UpperCAmelCase       )
			if nodea not in self.connections:
					self.add_node(__UpperCAmelCase       )
			__A				:       Union[str, Any]			    = probability

	def 	__UpperCAmelCase(  self       ):
			return list(self.connections       )







	def 	__UpperCAmelCase(  self				,					__UpperCAmelCase       ):
			__A				:       str			    = 0
			__A				:       str			    = random()

			for dest in self.connections[node]:
					current_probability += self.connections[node][dest]
					if current_probability > random_value:
							return dest
			return ""



def        lowerCamelCase_       (    _lowercase   ,      _lowercase   ,      _lowercase							)				->			dict[str, int]:
		__A				:       Optional[Any]			    = MarkovChainGraphUndirectedUnweighted()

		for nodea, nodea, probability in transitions:
				graph.add_transition_probability(_lowercase   ,      _lowercase   ,      _lowercase							)

		__A				:       Optional[int]			    = Counter(graph.get_nodes()							)
		__A				:       Optional[Any]			    = start

		for _ in range(_lowercase							):
				__A				:       Dict			    = graph.transition(_lowercase							)
				visited[node] += 1

		return visited


if __name__ == "__main__":
					import doctest

					doctest.testmod()









'''simple docstring'''

from argparse import ArgumentParser

from .add_new_model import AddNewModelCommand
from .add_new_model_like import AddNewModelLikeCommand
from .convert import ConvertCommand
from .download import DownloadCommand
from .env import EnvironmentCommand
from .lfs import LfsCommands
from .pt_to_tf import PTtoTFCommand
from .run import RunCommand
from .serving import ServeCommand
from .user import UserCommands

def _SCREAMING_SNAKE_CASE ()			->			Dict:






       """simple docstring"""







       lowercase__      =					ArgumentParser('''Transformers CLI tool'''    ,					usage='''transformers-cli <command> [<args>]'''			)
       lowercase__      =					parser.add_subparsers(help='''transformers-cli command helpers'''			)

       # Register commands
       ConvertCommand.register_subcommand(A			)
       DownloadCommand.register_subcommand(A			)
       EnvironmentCommand.register_subcommand(A			)
       RunCommand.register_subcommand(A			)
       ServeCommand.register_subcommand(A			)
       UserCommands.register_subcommand(A			)
       AddNewModelCommand.register_subcommand(A			)
       AddNewModelLikeCommand.register_subcommand(A			)
       LfsCommands.register_subcommand(A			)
       PTtoTFCommand.register_subcommand(A			)

       # Let's go
       lowercase__      =					parser.parse_args()

       if not hasattr(A    ,					'''func'''			):
              parser.print_help()
              exit(1			)

       # Run
       lowercase__      =					args.func(A			)
       service.run()


if __name__ == "__main__":
 main()




