


'''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,
)


A   :  int       		=				{'''configuration_t5''': ['''T5_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''T5Config''', '''T5OnnxConfig''']}

try:
   if not is_sentencepiece_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   A   :  Tuple       		=				['''T5Tokenizer''']

try:
   if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   A   :  int       		=				['''T5TokenizerFast''']

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   A   :  Any       		=				[
       '''T5_PRETRAINED_MODEL_ARCHIVE_LIST''',
       '''T5EncoderModel''',
       '''T5ForConditionalGeneration''',
       '''T5Model''',
       '''T5PreTrainedModel''',
       '''load_tf_weights_in_t5''',
       '''T5ForQuestionAnswering''',
   ]

try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   A   :  Dict       		=				[
       '''TF_T5_PRETRAINED_MODEL_ARCHIVE_LIST''',
       '''TFT5EncoderModel''',
       '''TFT5ForConditionalGeneration''',
       '''TFT5Model''',
       '''TFT5PreTrainedModel''',
   ]

try:
   if not is_flax_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   A   :  str       		=				[
       '''FlaxT5EncoderModel''',
       '''FlaxT5ForConditionalGeneration''',
       '''FlaxT5Model''',
       '''FlaxT5PreTrainedModel''',
   ]


if TYPE_CHECKING:
   from .configuration_ta import T5_PRETRAINED_CONFIG_ARCHIVE_MAP, TaConfig, TaOnnxConfig

   try:
      if not is_sentencepiece_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_ta import TaTokenizer

   try:
      if not is_tokenizers_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_ta_fast import TaTokenizerFast

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_ta import (
          T5_PRETRAINED_MODEL_ARCHIVE_LIST,
          TaEncoderModel,
          TaForConditionalGeneration,
          TaForQuestionAnswering,
          TaModel,
          TaPreTrainedModel,
          load_tf_weights_in_ta,
      )

   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_ta import (
          TF_T5_PRETRAINED_MODEL_ARCHIVE_LIST,
          TFTaEncoderModel,
          TFTaForConditionalGeneration,
          TFTaModel,
          TFTaPreTrainedModel,
      )

   try:
      if not is_flax_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_flax_ta import (
          FlaxTaEncoderModel,
          FlaxTaForConditionalGeneration,
          FlaxTaModel,
          FlaxTaPreTrainedModel,
      )


else:
   import sys

   A   :  List[Any]       		=				_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)










'''simple docstring'''







A   :  Optional[Any]       		=				{
    '''0000''': '''0''',
    '''0001''': '''1''',
    '''0010''': '''2''',
    '''0011''': '''3''',
    '''0100''': '''4''',
    '''0101''': '''5''',
    '''0110''': '''6''',
    '''0111''': '''7''',
    '''1000''': '''8''',
    '''1001''': '''9''',
    '''1010''': '''a''',
    '''1011''': '''b''',
    '''1100''': '''c''',
    '''1101''': '''d''',
    '''1110''': '''e''',
    '''1111''': '''f''',
}






def    lowerCAmelCase__ (       lowerCamelCase  :    str     ):
       _A  :			Union[str, Any]											=      str(lowerCamelCase     ).strip()

       # Exceptions
       if not binary_str:
              raise ValueError('Empty string was passed to the function'     )
       _A  :			Any											=      binary_str[0] == '-'
       _A  :			str											=      binary_str[1:] if is_negative else binary_str
       if not all(char in '01' for char in binary_str     ):
              raise ValueError('Non-binary value was passed to the function'     )

       _A  :			Optional[Any]											=      (
           '0' * (4 * (divmod(len(lowerCamelCase     )						,4     )[0] + 1) - len(lowerCamelCase     )) + binary_str
       )

       _A  :			Optional[int]											=      []
       for x in range(0						,len(lowerCamelCase     )						,4     ):
              hexadecimal.append(BITS_TO_HEX[binary_str[x : x + 4]]     )
       _A  :			int											=      '0x' + ''.join(lowerCamelCase     )

       return "-" + hexadecimal_str if is_negative else hexadecimal_str


if __name__ == "__main__":
   from doctest import testmod

   testmod()






