




'''simple docstring'''


from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_sentencepiece_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


UpperCamelCase			     =					{
    '''configuration_big_bird''': ['''BIG_BIRD_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''BigBirdConfig''', '''BigBirdOnnxConfig'''],
}

try:
     if not is_sentencepiece_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     UpperCamelCase			     =					['''BigBirdTokenizer''']

try:
     if not is_tokenizers_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     UpperCamelCase			     =					['''BigBirdTokenizerFast''']

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     UpperCamelCase			     =					[
         '''BIG_BIRD_PRETRAINED_MODEL_ARCHIVE_LIST''',
         '''BigBirdForCausalLM''',
         '''BigBirdForMaskedLM''',
         '''BigBirdForMultipleChoice''',
         '''BigBirdForPreTraining''',
         '''BigBirdForQuestionAnswering''',
         '''BigBirdForSequenceClassification''',
         '''BigBirdForTokenClassification''',
         '''BigBirdLayer''',
         '''BigBirdModel''',
         '''BigBirdPreTrainedModel''',
         '''load_tf_weights_in_big_bird''',
     ]

try:
     if not is_flax_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     UpperCamelCase			     =					[
         '''FlaxBigBirdForCausalLM''',
         '''FlaxBigBirdForMaskedLM''',
         '''FlaxBigBirdForMultipleChoice''',
         '''FlaxBigBirdForPreTraining''',
         '''FlaxBigBirdForQuestionAnswering''',
         '''FlaxBigBirdForSequenceClassification''',
         '''FlaxBigBirdForTokenClassification''',
         '''FlaxBigBirdModel''',
         '''FlaxBigBirdPreTrainedModel''',
     ]

if TYPE_CHECKING:
     from .configuration_big_bird import BIG_BIRD_PRETRAINED_CONFIG_ARCHIVE_MAP, BigBirdConfig, BigBirdOnnxConfig

     try:
          if not is_sentencepiece_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .tokenization_big_bird import BigBirdTokenizer

     try:
          if not is_tokenizers_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .tokenization_big_bird_fast import BigBirdTokenizerFast

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_big_bird import (
              BIG_BIRD_PRETRAINED_MODEL_ARCHIVE_LIST,
              BigBirdForCausalLM,
              BigBirdForMaskedLM,
              BigBirdForMultipleChoice,
              BigBirdForPreTraining,
              BigBirdForQuestionAnswering,
              BigBirdForSequenceClassification,
              BigBirdForTokenClassification,
              BigBirdLayer,
              BigBirdModel,
              BigBirdPreTrainedModel,
              load_tf_weights_in_big_bird,
          )

     try:
          if not is_flax_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_flax_big_bird import (
              FlaxBigBirdForCausalLM,
              FlaxBigBirdForMaskedLM,
              FlaxBigBirdForMultipleChoice,
              FlaxBigBirdForPreTraining,
              FlaxBigBirdForQuestionAnswering,
              FlaxBigBirdForSequenceClassification,
              FlaxBigBirdForTokenClassification,
              FlaxBigBirdModel,
              FlaxBigBirdPreTrainedModel,
          )

else:
     import sys

     UpperCamelCase			     =					_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)












'''simple docstring'''


from __future__ import annotations

import random






class 						lowerCAmelCase_	:







  '''simple docstring'''

  UpperCamelCase_			:      Optional[int]										=				6



  def __init__( self				:							Dict	)			->		Dict:







       '''simple docstring'''



       A:		Union[str, Any]          =		list(range(1					,  Dice.NUM_SIDES + 1	)	)




  def 					_snake_case     ( self				:							Optional[Any]	)			->		Any:







       '''simple docstring'''



       return random.choice(self.sides	)






def 					SCREAMING_SNAKE_CASE(   __lowercase		,				__lowercase = 2	)			-> list[float]:
     A:		Union[str, Any]          =		[Dice() for i in range(__lowercase	)]
     A:		Union[str, Any]          =		[0] * (len(__lowercase	) * Dice.NUM_SIDES + 1)
     for _ in range(__lowercase	):
          count_of_sum[sum(dice.roll() for dice in dices	)] += 1
     A:		Dict          =		[round((count * 1_0_0) / num_throws		,				2	) for count in count_of_sum]
     return probability[num_dice:]  # remove probability of sums that never appear


if __name__ == "__main__":
     import doctest

     doctest.testmod()






