
from __future__ import annotations

from collections import Counter
from random import random






class     UpperCAmelCase						:



   def __init__(self						:   int					)						->      Dict:


          '''simple docstring'''


          snake_case			:  Union[str, Any]     							= {}



   def 							_SCREAMING_SNAKE_CASE  (self						:   List[Any]       ,		snake_case__						:   str					)						->      None:


          '''simple docstring'''


          snake_case			:  Tuple     							= {}



   def 							_SCREAMING_SNAKE_CASE  (self						:   Any       ,		snake_case__						:   str       ,		snake_case__						:   str       ,		snake_case__						:   float					)						->      None:


          '''simple docstring'''


          if nodea not in self.connections:
                 self.add_node(snake_case__					)
          if nodea not in self.connections:
                 self.add_node(snake_case__					)
          snake_case			:  str     							= probability



   def 							_SCREAMING_SNAKE_CASE  (self						:   str					)						->      list[str]:


          '''simple docstring'''


          return list(self.connections					)



   def 							_SCREAMING_SNAKE_CASE  (self						:   Optional[int]       ,		snake_case__						:   str					)						->      str:


          '''simple docstring'''


          snake_case			:  int     							= 0
          snake_case			:  Dict     							= random()

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



def      UpperCamelCase   (       __lowerCamelCase	:					str							,   __lowerCamelCase	:					list[tuple[str, str, float]]							,   __lowerCamelCase	:					int       ):
       snake_case			:  int     							= MarkovChainGraphUndirectedUnweighted()

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

       snake_case			:  Dict     							= Counter(graph.get_nodes()       )
       snake_case			:  Tuple     							= start

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

       return visited


if __name__ == "__main__":
   import doctest

   doctest.testmod()







from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


__lowerCamelCase				=			logging.get_logger(__name__)

__lowerCamelCase				=			{
    """kssteven/ibert-roberta-base""": """https://huggingface.co/kssteven/ibert-roberta-base/resolve/main/config.json""",
    """kssteven/ibert-roberta-large""": """https://huggingface.co/kssteven/ibert-roberta-large/resolve/main/config.json""",
    """kssteven/ibert-roberta-large-mnli""": (
        """https://huggingface.co/kssteven/ibert-roberta-large-mnli/resolve/main/config.json"""
    ),
}






class     UpperCAmelCase						(		A_					):
   A__   :						Optional[int]			=	"ibert"



   def __init__(self						:   List[Any]       ,		snake_case__						:   int=3_05_22       ,		snake_case__						:   int=7_68       ,		snake_case__						:   Any=12       ,		snake_case__						:   str=12       ,		snake_case__						:   Optional[int]=30_72       ,		snake_case__						:   Union[str, Any]="gelu"       ,		snake_case__						:   Any=0.1       ,		snake_case__						:   List[Any]=0.1       ,		snake_case__						:   str=5_12       ,		snake_case__						:   Optional[int]=2       ,		snake_case__						:   Any=0.02       ,		snake_case__						:   List[Any]=1e-12       ,		snake_case__						:   Optional[Any]=1       ,		snake_case__						:   List[Any]=0       ,		snake_case__						:   str=2       ,		snake_case__						:   Tuple="absolute"       ,		snake_case__						:   List[str]=False       ,		snake_case__						:   Tuple="none"       ,		**snake_case__						:   Tuple       ,		)						->      Union[str, Any]:


          '''simple docstring'''


          super().__init__(pad_token_id=snake_case__       ,		bos_token_id=snake_case__       ,		eos_token_id=snake_case__       ,		**snake_case__					)

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






class     UpperCAmelCase						(		A_					):



   @property
   def 							_SCREAMING_SNAKE_CASE  (self						:   Tuple					)						->      Mapping[str, Mapping[int, str]]:


          '''simple docstring'''


          if self.task == "multiple-choice":
                 snake_case			:  Optional[Any]     							= {0: "batch", 1: "choice", 2: "sequence"}
          else:
                 snake_case			:  List[Any]     							= {0: "batch", 1: "sequence"}
          return OrderedDict(
              [
                  ("input_ids", dynamic_axis),
                  ("attention_mask", dynamic_axis),
              ]					)





