



"""simple docstring"""

from __future__ import annotations

from collections import Counter
from random import random







class    __lowercase     :







						"""simple docstring"""







						def __init__(self       ):
											snake_case_					:		Tuple 					=					{}







						def 						__UpperCamelCase							(self   ,		lowercase__       ):
											snake_case_					:		Optional[int] 					=					{}







						def 						__UpperCamelCase							(self   ,		lowercase__   ,		lowercase__   ,		lowercase__       ):
											if nodea not in self.connections:
																self.add_node(lowercase__       )
											if nodea not in self.connections:
																self.add_node(lowercase__       )
											snake_case_					:		Optional[Any] 					=					probability







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







						def 						__UpperCamelCase							(self   ,		lowercase__       ):
											snake_case_					:		int 					=					0
											snake_case_					:		List[str] 					=					random()

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







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



					"""simple docstring"""





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

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

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

					for _ in range(SCREAMING_SNAKE_CASE__			):
										snake_case_					:		List[Any] 					=					graph.transition(SCREAMING_SNAKE_CASE__			)
										visited[node] += 1

					return visited


if __name__ == "__main__":
			import doctest

			doctest.testmod()









"""simple docstring"""

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


a_			   =					logging.get_logger(__name__)

a_			   =					{
    '''facebook/dpr-ctx_encoder-single-nq-base''': (
        '''https://huggingface.co/facebook/dpr-ctx_encoder-single-nq-base/resolve/main/config.json'''
    ),
    '''facebook/dpr-question_encoder-single-nq-base''': (
        '''https://huggingface.co/facebook/dpr-question_encoder-single-nq-base/resolve/main/config.json'''
    ),
    '''facebook/dpr-reader-single-nq-base''': (
        '''https://huggingface.co/facebook/dpr-reader-single-nq-base/resolve/main/config.json'''
    ),
    '''facebook/dpr-ctx_encoder-multiset-base''': (
        '''https://huggingface.co/facebook/dpr-ctx_encoder-multiset-base/resolve/main/config.json'''
    ),
    '''facebook/dpr-question_encoder-multiset-base''': (
        '''https://huggingface.co/facebook/dpr-question_encoder-multiset-base/resolve/main/config.json'''
    ),
    '''facebook/dpr-reader-multiset-base''': (
        '''https://huggingface.co/facebook/dpr-reader-multiset-base/resolve/main/config.json'''
    ),
}







class    __lowercase     (					_UpperCAmelCase):







						"""simple docstring"""







						_A		:							Optional[int]							       =		"""dpr"""







						def __init__(self   ,		lowercase__=3_05_22   ,		lowercase__=7_68   ,		lowercase__=12   ,		lowercase__=12   ,		lowercase__=30_72   ,		lowercase__="gelu"   ,		lowercase__=0.1   ,		lowercase__=0.1   ,		lowercase__=5_12   ,		lowercase__=2   ,		lowercase__=0.02   ,		lowercase__=1e-12   ,		lowercase__=0   ,		lowercase__="absolute"   ,		lowercase__ = 0   ,		**lowercase__   ,		):
											super().__init__(pad_token_id=lowercase__   ,		**lowercase__       )

											snake_case_					:		List[Any] 					=					vocab_size
											snake_case_					:		List[str] 					=					hidden_size
											snake_case_					:		Tuple 					=					num_hidden_layers
											snake_case_					:		List[Any] 					=					num_attention_heads
											snake_case_					:		int 					=					hidden_act
											snake_case_					:		Dict 					=					intermediate_size
											snake_case_					:		int 					=					hidden_dropout_prob
											snake_case_					:		Any 					=					attention_probs_dropout_prob
											snake_case_					:		str 					=					max_position_embeddings
											snake_case_					:		List[str] 					=					type_vocab_size
											snake_case_					:		List[str] 					=					initializer_range
											snake_case_					:		Optional[int] 					=					layer_norm_eps
											snake_case_					:		Union[str, Any] 					=					projection_dim
											snake_case_					:		str 					=					position_embedding_type




