




'''simple docstring'''







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available


lowerCAmelCase_    	=							{
    '''configuration_flaubert''': ['''FLAUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''FlaubertConfig''', '''FlaubertOnnxConfig'''],
    '''tokenization_flaubert''': ['''FlaubertTokenizer'''],
}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCAmelCase_    	=							[
        '''FLAUBERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
        '''FlaubertForMultipleChoice''',
        '''FlaubertForQuestionAnswering''',
        '''FlaubertForQuestionAnsweringSimple''',
        '''FlaubertForSequenceClassification''',
        '''FlaubertForTokenClassification''',
        '''FlaubertModel''',
        '''FlaubertWithLMHeadModel''',
        '''FlaubertPreTrainedModel''',
    ]

try:
    if not is_tf_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCAmelCase_    	=							[
        '''TF_FLAUBERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
        '''TFFlaubertForMultipleChoice''',
        '''TFFlaubertForQuestionAnsweringSimple''',
        '''TFFlaubertForSequenceClassification''',
        '''TFFlaubertForTokenClassification''',
        '''TFFlaubertModel''',
        '''TFFlaubertPreTrainedModel''',
        '''TFFlaubertWithLMHeadModel''',
    ]


if TYPE_CHECKING:
    from .configuration_flaubert import FLAUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, FlaubertConfig, FlaubertOnnxConfig
    from .tokenization_flaubert import FlaubertTokenizer

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_flaubert import (
            FLAUBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
            FlaubertForMultipleChoice,
            FlaubertForQuestionAnswering,
            FlaubertForQuestionAnsweringSimple,
            FlaubertForSequenceClassification,
            FlaubertForTokenClassification,
            FlaubertModel,
            FlaubertPreTrainedModel,
            FlaubertWithLMHeadModel,
        )

    try:
        if not is_tf_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_tf_flaubert import (
            TF_FLAUBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
            TFFlaubertForMultipleChoice,
            TFFlaubertForQuestionAnsweringSimple,
            TFFlaubertForSequenceClassification,
            TFFlaubertForTokenClassification,
            TFFlaubertModel,
            TFFlaubertPreTrainedModel,
            TFFlaubertWithLMHeadModel,
        )

else:
    import sys

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










'''simple docstring'''







from __future__ import annotations

from enum import Enum, unique
from typing import TypeVar

# Create a generic variable that can be 'Enum', or any subclass.
lowerCAmelCase_    	=							TypeVar('''T''', bound='''Enum''')

@unique
class   _snake_case( UpperCAmelCase			):
 __snake_case:       List[Any]									=				80
 __snake_case:       Optional[int]									=				70
 __snake_case:       Optional[int]									=				60
 __snake_case:       int									=				50
 __snake_case:       Dict									=				40
 __snake_case:       Dict									=				30
 __snake_case:       str									=				20
 __snake_case:       Optional[int]									=				10




@unique
class   _snake_case( UpperCAmelCase			):
 __snake_case:       List[Any]									=				24
 __snake_case:       Union[str, Any]									=				21
 __snake_case:       Dict									=				18
 __snake_case:       List[str]									=				15
 __snake_case:       Union[str, Any]									=				12
 __snake_case:       Tuple									=				9
 __snake_case:       int									=				6
 __snake_case:       Tuple									=				3
 __snake_case:       List[Any]									=				2
 __snake_case:       int									=				1
 __snake_case:       List[str]									=				-1
 __snake_case:       Union[str, Any]									=				-2
 __snake_case:       List[str]									=				-3
 __snake_case:       Any									=				-6
 __snake_case:       Tuple									=				-9
 __snake_case:       List[str]									=				-12
 __snake_case:       Dict									=				-15
 __snake_case:       Optional[int]									=				-18
 __snake_case:       str									=				-21
 __snake_case:       Any									=				-24






 @classmethod
 def 	_UpperCamelCase   (cls					:     type[T]						)					->      dict:






    """simple docstring"""


    return {unit.name: unit.value for unit in cls if unit.value > 0}






 @classmethod
 def 	_UpperCamelCase   (cls					:     type[T]						)					->      dict:






    """simple docstring"""


    return {unit.name: unit.value for unit in cls if unit.value < 0}







def 	_A			(   UpperCAmelCase	):






   '''simple docstring'''







   A__         =    SIUnit.get_positive() if value > 0 else SIUnit.get_negative()
   for name_prefix, value_prefix in prefixes.items():
      A__         =    value / (10**value_prefix)
      if numerical_part > 1:
         return F"""{numerical_part!s} {name_prefix}"""
   return str(UpperCAmelCase	)







def 	_A			(   UpperCAmelCase	):






   '''simple docstring'''







   for prefix in BinaryUnit:
      A__         =    value / (2**prefix.value)
      if numerical_part > 1:
         return F"""{numerical_part!s} {prefix.name}"""
   return str(UpperCAmelCase	)


if __name__ == "__main__":
    import doctest

    doctest.testmod()


