
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,
)


lowercase__						:Tuple					    =       {
    "configuration_big_bird": ["BIG_BIRD_PRETRAINED_CONFIG_ARCHIVE_MAP", "BigBirdConfig", "BigBirdOnnxConfig"],
}

try:
							if not is_sentencepiece_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowercase__						:Dict					    =       ["BigBirdTokenizer"]

try:
							if not is_tokenizers_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowercase__						:int					    =       ["BigBirdTokenizerFast"]

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowercase__						:Any					    =       [
							    "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:
							lowercase__						:Any					    =       [
							    "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

							lowercase__						:Optional[int]					    =       _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)





'''simple docstring'''

from hashlib import mda, shaaaa

lowerCAmelCase_			:			Union[str, Any]    	=   (shaaaa, mda)





class 				lowercase    :


   def __init__( self					:						Optional[Any] ,		__lowerCAmelCase					:						int = 8)   ->       None:
         lowercase_     			=   0B0
         lowercase_     			=   size


   def __UpperCAmelCase							( self					:						Dict ,		__lowerCAmelCase					:						str)   ->       None:
         lowercase_     			=   self.hash_(__lowerCAmelCase)
         self.bitarray |= h


   def __UpperCAmelCase							( self					:						Union[str, Any] ,		__lowerCAmelCase					:						str)   ->       bool:
         lowercase_     			=   self.hash_(__lowerCAmelCase)
         return (h & self.bitarray) == h


   def __contains__( self					:						str ,		__lowerCAmelCase					:						str)   ->       bool:
         return self.exists(__lowerCAmelCase)


   def __UpperCAmelCase							( self					:						Union[str, Any] ,		__lowerCAmelCase					:						int)   ->       str:
         lowercase_     			=   bin(__lowerCAmelCase)[2:]
         return res.zfill(self.size)


   @property
   def __UpperCAmelCase							( self					:						Dict)   ->       str:
         return self.format_bin(self.bitarray)


   def __UpperCAmelCase							( self					:						Any ,		__lowerCAmelCase					:						str)   ->       int:
         lowercase_     			=   0B0
         for func in HASH_FUNCTIONS:
               lowercase_     			=   (
                   int.from_bytes(func(value.encode()).digest() ,		"little") % self.size
               )
               res |= 2**position
         return res


   def __UpperCAmelCase							( self					:						Union[str, Any] ,		__lowerCAmelCase					:						str)   ->       str:
         return self.format_bin(self.hash_(__lowerCAmelCase))


   @property
   def __UpperCAmelCase							( self					:						str)   ->       float:
         lowercase_     			=   bin(self.bitarray).count("1")
         return (n_ones / self.size) ** len(__lowerCAmelCase)






