






'''simple docstring'''



from typing import TYPE_CHECKING

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


SCREAMING_SNAKE_CASE						=	{
    '''configuration_squeezebert''': [
        '''SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''SqueezeBertConfig''',
        '''SqueezeBertOnnxConfig''',
    ],
    '''tokenization_squeezebert''': ['''SqueezeBertTokenizer'''],
}

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

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						SCREAMING_SNAKE_CASE						=	[
						    '''SQUEEZEBERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
						    '''SqueezeBertForMaskedLM''',
						    '''SqueezeBertForMultipleChoice''',
						    '''SqueezeBertForQuestionAnswering''',
						    '''SqueezeBertForSequenceClassification''',
						    '''SqueezeBertForTokenClassification''',
						    '''SqueezeBertModel''',
						    '''SqueezeBertModule''',
						    '''SqueezeBertPreTrainedModel''',
						]


if TYPE_CHECKING:
						from .configuration_squeezebert import (
						    SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
						    SqueezeBertConfig,
						    SqueezeBertOnnxConfig,
						)
						from .tokenization_squeezebert import SqueezeBertTokenizer

						try:
												if not is_tokenizers_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .tokenization_squeezebert_fast import SqueezeBertTokenizerFast

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_squeezebert import (
												    SQUEEZEBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
												    SqueezeBertForMaskedLM,
												    SqueezeBertForMultipleChoice,
												    SqueezeBertForQuestionAnswering,
												    SqueezeBertForSequenceClassification,
												    SqueezeBertForTokenClassification,
												    SqueezeBertModel,
												    SqueezeBertModule,
												    SqueezeBertPreTrainedModel,
												)

else:
						import sys

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











'''simple docstring'''



def 							lowercase_				(    __A :       float					,      __A :       int			)       ->      float:



 """simple docstring"""




 if digit_amount > 0:
  return round(number - int(__A			)					,      __A			)
 return number - int(__A			)


if __name__ == "__main__":
      print(decimal_isolate(1.53, 0))
      print(decimal_isolate(35.345, 1))
      print(decimal_isolate(35.345, 2))
      print(decimal_isolate(35.345, 3))
      print(decimal_isolate(-14.789, 3))
      print(decimal_isolate(0, 2))
      print(decimal_isolate(-14.123, 1))
      print(decimal_isolate(-14.123, 2))
      print(decimal_isolate(-14.123, 3))



