




UpperCAmelCase__						:       Any							=    {hex(i)[2:]: i for i in range(16)}  # Use [:2] to strip off the leading '0x'


def 		_lowerCamelCase				(					UpperCamelCase							)			->		int:





  """simple docstring"""





  _lowercase: List[str]						     =    hex_string.strip().lower()
  if not hex_string:
    raise ValueError('Empty string was passed to the function'							)
  _lowercase: Dict						     =    hex_string[0] == '-'
  if is_negative:
    _lowercase: Tuple						     =    hex_string[1:]
  if not all(char in hex_table for char in hex_string							):
    raise ValueError('Non-hexadecimal value was passed to the function'							)
  _lowercase: List[str]						     =    0
  for char in hex_string:
    _lowercase: Optional[int]						     =    16 * decimal_number + hex_table[char]
  return -decimal_number if is_negative else decimal_number


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

   testmod()






from typing import TYPE_CHECKING

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


UpperCAmelCase__						:       Union[str, Any]							=    {'configuration_bert_generation': ['BertGenerationConfig']}

try:
   if not is_sentencepiece_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   UpperCAmelCase__						:       str							=    ['BertGenerationTokenizer']

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   UpperCAmelCase__						:       Tuple							=    [
       'BertGenerationDecoder',
       'BertGenerationEncoder',
       'BertGenerationPreTrainedModel',
       'load_tf_weights_in_bert_generation',
   ]


if TYPE_CHECKING:
   from .configuration_bert_generation import BertGenerationConfig

   try:
      if not is_sentencepiece_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_bert_generation import BertGenerationTokenizer

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_bert_generation import (
          BertGenerationDecoder,
          BertGenerationEncoder,
          BertGenerationPreTrainedModel,
          load_tf_weights_in_bert_generation,
      )

else:
   import sys

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