

'''simple docstring'''

def    lowercase__			(				__UpperCamelCase   )->			bool:
      UpperCamelCase      = 0
      for ch in input_str:
            UpperCamelCase      = ord(__UpperCamelCase   )
            UpperCamelCase      = pow(2		,						__UpperCamelCase   )

            # If we already turned on bit for current character's unicode
            if bitmap >> ch_unicode & 1 == 1:
                  return False
            bitmap |= ch_bit_index_on
      return True


if __name__ == "__main__":
     import doctest

     doctest.testmod()








'''simple docstring'''

from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


SCREAMING_SNAKE_CASE__     =       {
    'configuration_mobilebert': [
        'MOBILEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'MobileBertConfig',
        'MobileBertOnnxConfig',
    ],
    'tokenization_mobilebert': ['MobileBertTokenizer'],
}

try:
     if not is_tokenizers_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     SCREAMING_SNAKE_CASE__     =       ['MobileBertTokenizerFast']

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     SCREAMING_SNAKE_CASE__     =       [
         'MOBILEBERT_PRETRAINED_MODEL_ARCHIVE_LIST',
         'MobileBertForMaskedLM',
         'MobileBertForMultipleChoice',
         'MobileBertForNextSentencePrediction',
         'MobileBertForPreTraining',
         'MobileBertForQuestionAnswering',
         'MobileBertForSequenceClassification',
         'MobileBertForTokenClassification',
         'MobileBertLayer',
         'MobileBertModel',
         'MobileBertPreTrainedModel',
         'load_tf_weights_in_mobilebert',
     ]

try:
     if not is_tf_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     SCREAMING_SNAKE_CASE__     =       [
         'TF_MOBILEBERT_PRETRAINED_MODEL_ARCHIVE_LIST',
         'TFMobileBertForMaskedLM',
         'TFMobileBertForMultipleChoice',
         'TFMobileBertForNextSentencePrediction',
         'TFMobileBertForPreTraining',
         'TFMobileBertForQuestionAnswering',
         'TFMobileBertForSequenceClassification',
         'TFMobileBertForTokenClassification',
         'TFMobileBertMainLayer',
         'TFMobileBertModel',
         'TFMobileBertPreTrainedModel',
     ]


if TYPE_CHECKING:
     from .configuration_mobilebert import (
         MOBILEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
         MobileBertConfig,
         MobileBertOnnxConfig,
     )
     from .tokenization_mobilebert import MobileBertTokenizer

     try:
          if not is_tokenizers_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .tokenization_mobilebert_fast import MobileBertTokenizerFast

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_mobilebert import (
              MOBILEBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
              MobileBertForMaskedLM,
              MobileBertForMultipleChoice,
              MobileBertForNextSentencePrediction,
              MobileBertForPreTraining,
              MobileBertForQuestionAnswering,
              MobileBertForSequenceClassification,
              MobileBertForTokenClassification,
              MobileBertLayer,
              MobileBertModel,
              MobileBertPreTrainedModel,
              load_tf_weights_in_mobilebert,
          )

     try:
          if not is_tf_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_tf_mobilebert import (
              TF_MOBILEBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
              TFMobileBertForMaskedLM,
              TFMobileBertForMultipleChoice,
              TFMobileBertForNextSentencePrediction,
              TFMobileBertForPreTraining,
              TFMobileBertForQuestionAnswering,
              TFMobileBertForSequenceClassification,
              TFMobileBertForTokenClassification,
              TFMobileBertMainLayer,
              TFMobileBertModel,
              TFMobileBertPreTrainedModel,
          )

else:
     import sys

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