






import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging


A        =			logging.get_logger(__name__)


class 							__a							(  __A						):





						'''simple docstring'''



						UpperCAmelCase__      :				Optional[int]				    =						"""encoder-decoder"""
						UpperCAmelCase__      :				List[Any]				    =						True


						def __init__(						self ,    **UpperCamelCase__       ):
										super().__init__(**UpperCamelCase__       )
										assert (
										    "encoder" in kwargs and "decoder" in kwargs
										), "Config has to be initialized with encoder and decoder config"
										SCREAMING_SNAKE_CASE_   :	Any													=   kwargs.pop('encoder'       )
										SCREAMING_SNAKE_CASE_   :	Optional[int]													=   encoder_config.pop('model_type'       )
										SCREAMING_SNAKE_CASE_   :	Tuple													=   kwargs.pop('decoder'       )
										SCREAMING_SNAKE_CASE_   :	Tuple													=   decoder_config.pop('model_type'       )

										from ..auto.configuration_auto import AutoConfig

										SCREAMING_SNAKE_CASE_   :	List[Any]													=   AutoConfig.for_model(UpperCamelCase__ ,    **UpperCamelCase__       )
										SCREAMING_SNAKE_CASE_   :	Union[str, Any]													=   AutoConfig.for_model(UpperCamelCase__ ,    **UpperCamelCase__       )
										SCREAMING_SNAKE_CASE_   :	Union[str, Any]													=   True


						@classmethod
						def   __snake_case			(						cls ,    UpperCamelCase__ ,    UpperCamelCase__ ,    **UpperCamelCase__       ):
										logger.info('Set `config.is_decoder=True` and `config.add_cross_attention=True` for decoder_config'       )
										SCREAMING_SNAKE_CASE_   :	Optional[Any]													=   True
										SCREAMING_SNAKE_CASE_   :	List[str]													=   True

										return cls(encoder=encoder_config.to_dict() ,    decoder=decoder_config.to_dict() ,    **UpperCamelCase__       )






						def   __snake_case			(						self       ):
										SCREAMING_SNAKE_CASE_   :	List[str]													=   copy.deepcopy(self.__dict__       )
										SCREAMING_SNAKE_CASE_   :	Union[str, Any]													=   self.encoder.to_dict()
										SCREAMING_SNAKE_CASE_   :	List[str]													=   self.decoder.to_dict()
										SCREAMING_SNAKE_CASE_   :	Dict													=   self.__class__.model_type
										return output







from __future__ import annotations

from collections import Counter
from random import random


class 							__a							:





		'''simple docstring'''



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


		def   __snake_case			(						self ,    UpperCamelCase__       ):
						SCREAMING_SNAKE_CASE_   :	int													=   {}


		def   __snake_case			(						self ,    UpperCamelCase__ ,    UpperCamelCase__ ,    UpperCamelCase__       ):
						if nodea not in self.connections:
										self.add_node(UpperCamelCase__       )
						if nodea not in self.connections:
										self.add_node(UpperCamelCase__       )
						SCREAMING_SNAKE_CASE_   :	Tuple													=   probability


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






		def   __snake_case			(						self ,    UpperCamelCase__       ):
						SCREAMING_SNAKE_CASE_   :	Dict													=   0
						SCREAMING_SNAKE_CASE_   :	List[Any]													=   random()

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






def 					_lowerCamelCase(			lowerCAmelCase__				:		str    ,    lowerCAmelCase__				:		list[tuple[str, str, float]]    ,    lowerCAmelCase__				:		int      ):





				'''simple docstring'''







				SCREAMING_SNAKE_CASE_   :	Union[str, Any]													=   MarkovChainGraphUndirectedUnweighted()

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

				SCREAMING_SNAKE_CASE_   :	List[str]													=   Counter(graph.get_nodes()      )
				SCREAMING_SNAKE_CASE_   :	Optional[Any]													=   start

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

				return visited


if __name__ == "__main__":
				import doctest

				doctest.testmod()