





from typing import TYPE_CHECKING

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


lowercase_					     =	{
    '''configuration_roc_bert''': ['''ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''RoCBertConfig'''],
    '''tokenization_roc_bert''': ['''RoCBertTokenizer'''],
}

try:
 if not is_tokenizers_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 pass

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowercase_					     =	[
     '''ROC_BERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''RoCBertForCausalLM''',
     '''RoCBertForMaskedLM''',
     '''RoCBertForMultipleChoice''',
     '''RoCBertForPreTraining''',
     '''RoCBertForQuestionAnswering''',
     '''RoCBertForSequenceClassification''',
     '''RoCBertForTokenClassification''',
     '''RoCBertLayer''',
     '''RoCBertModel''',
     '''RoCBertPreTrainedModel''',
     '''load_tf_weights_in_roc_bert''',
 ]

if TYPE_CHECKING:
 from .configuration_roc_bert import ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP, RoCBertConfig
 from .tokenization_roc_bert import RoCBertTokenizer

 try:
  if not is_tokenizers_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  raise OptionalDependencyNotAvailable()

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_roc_bert import (
      ROC_BERT_PRETRAINED_MODEL_ARCHIVE_LIST,
      RoCBertForCausalLM,
      RoCBertForMaskedLM,
      RoCBertForMultipleChoice,
      RoCBertForPreTraining,
      RoCBertForQuestionAnswering,
      RoCBertForSequenceClassification,
      RoCBertForTokenClassification,
      RoCBertLayer,
      RoCBertModel,
      RoCBertPreTrainedModel,
      load_tf_weights_in_roc_bert,
  )


else:
 import sys

 lowercase_					     =	_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)









from string import ascii_uppercase

lowercase_					     =	{str(ord(c) - 55): c for c in ascii_uppercase}




def     __UpperCamelCase						(_SCREAMING_SNAKE_CASE	,		_SCREAMING_SNAKE_CASE	)       ->     str:
  if isinstance(_SCREAMING_SNAKE_CASE	,		_SCREAMING_SNAKE_CASE	):
    raise TypeError('int() can\'t convert non-string with explicit base'	)
  if num < 0:
    raise ValueError('parameter must be positive int'	)
  if isinstance(_SCREAMING_SNAKE_CASE	,		_SCREAMING_SNAKE_CASE	):
    raise TypeError('\'str\' object cannot be interpreted as an integer'	)
  if isinstance(_SCREAMING_SNAKE_CASE	,		_SCREAMING_SNAKE_CASE	):
    raise TypeError('\'float\' object cannot be interpreted as an integer'	)
  if base in (0, 1):
    raise ValueError('base must be >= 2'	)
  if base > 36:
    raise ValueError('base must be <= 36'	)
  lowercase__			    =						''
  lowercase__			    =						0
  lowercase__			    =						0
  while div != 1:
    lowercase__    ,					lowercase__			    =						divmod(_SCREAMING_SNAKE_CASE	,		_SCREAMING_SNAKE_CASE	)
    if base >= 11 and 9 < mod < 36:
      lowercase__			    =						ALPHABET_VALUES[str(_SCREAMING_SNAKE_CASE	)]
    else:
      lowercase__			    =						str(_SCREAMING_SNAKE_CASE	)
    new_value += actual_value
    lowercase__			    =						num // base
    lowercase__			    =						div
    if div == 0:
      return str(new_value[::-1]	)
    elif div == 1:
      new_value += str(_SCREAMING_SNAKE_CASE	)
      return str(new_value[::-1]	)

  return new_value[::-1]


if __name__ == "__main__":
      import doctest

      doctest.testmod()

      for base in range(2, 37):
            for num in range(1_000):
                  assert int(decimal_to_any(num, base), base) == num, (
                      num,
                      base,
                      decimal_to_any(num, base),
                      int(decimal_to_any(num, base), base),
                  )


