

from typing import TYPE_CHECKING

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


lowerCamelCase_    =					{
    '''configuration_mpnet''': ['''MPNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MPNetConfig'''],
    '''tokenization_mpnet''': ['''MPNetTokenizer'''],
}

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

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCamelCase_    =					[
        '''MPNET_PRETRAINED_MODEL_ARCHIVE_LIST''',
        '''MPNetForMaskedLM''',
        '''MPNetForMultipleChoice''',
        '''MPNetForQuestionAnswering''',
        '''MPNetForSequenceClassification''',
        '''MPNetForTokenClassification''',
        '''MPNetLayer''',
        '''MPNetModel''',
        '''MPNetPreTrainedModel''',
    ]

try:
    if not is_tf_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCamelCase_    =					[
        '''TF_MPNET_PRETRAINED_MODEL_ARCHIVE_LIST''',
        '''TFMPNetEmbeddings''',
        '''TFMPNetForMaskedLM''',
        '''TFMPNetForMultipleChoice''',
        '''TFMPNetForQuestionAnswering''',
        '''TFMPNetForSequenceClassification''',
        '''TFMPNetForTokenClassification''',
        '''TFMPNetMainLayer''',
        '''TFMPNetModel''',
        '''TFMPNetPreTrainedModel''',
    ]


if TYPE_CHECKING:
    from .configuration_mpnet import MPNET_PRETRAINED_CONFIG_ARCHIVE_MAP, MPNetConfig
    from .tokenization_mpnet import MPNetTokenizer

    try:
        if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .tokenization_mpnet_fast import MPNetTokenizerFast

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_mpnet import (
            MPNET_PRETRAINED_MODEL_ARCHIVE_LIST,
            MPNetForMaskedLM,
            MPNetForMultipleChoice,
            MPNetForQuestionAnswering,
            MPNetForSequenceClassification,
            MPNetForTokenClassification,
            MPNetLayer,
            MPNetModel,
            MPNetPreTrainedModel,
        )

    try:
        if not is_tf_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_tf_mpnet import (
            TF_MPNET_PRETRAINED_MODEL_ARCHIVE_LIST,
            TFMPNetEmbeddings,
            TFMPNetForMaskedLM,
            TFMPNetForMultipleChoice,
            TFMPNetForQuestionAnswering,
            TFMPNetForSequenceClassification,
            TFMPNetForTokenClassification,
            TFMPNetMainLayer,
            TFMPNetModel,
            TFMPNetPreTrainedModel,
        )

else:
    import sys

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







"""simple docstring"""







import unittest
from timeit import timeit






def 					_lowerCAmelCase				(					lowerCAmelCase		,					lowerCAmelCase						):







       '''simple docstring'''
       UpperCAmelCase					=	first_num if first_num >= second_num else second_num
       UpperCAmelCase					=	max_num
       while (common_mult % first_num > 0) or (common_mult % second_num > 0):
              common_mult += max_num
       return common_mult






def 					_lowerCAmelCase				(					lowerCAmelCase		,					lowerCAmelCase						):







       '''simple docstring'''
       return b if a == 0 else greatest_common_divisor(b % a		,					lowerCAmelCase						)






def 					_lowerCAmelCase				(					lowerCAmelCase		,					lowerCAmelCase						):







       '''simple docstring'''
       return first_num // greatest_common_divisor(lowerCAmelCase		,					lowerCAmelCase						) * second_num






def 					_lowerCAmelCase				(					):







       '''simple docstring'''
       UpperCAmelCase					=	(
           """from __main__ import least_common_multiple_slow, least_common_multiple_fast"""
       )
       print(
           """least_common_multiple_slow():"""		,					timeit("""least_common_multiple_slow(1000, 999)"""		,					setup=lowerCAmelCase						)		,					)
       print(
           """least_common_multiple_fast():"""		,					timeit("""least_common_multiple_fast(1000, 999)"""		,					setup=lowerCAmelCase						)		,					)





class      UpperCamelCase_       (				unittest.TestCase     ):
  _A				:    List[str] =		(
      (10, 20),
      (13, 15),
      (4, 31),
      (10, 42),
      (43, 34),
      (5, 12),
      (12, 25),
      (10, 25),
      (6, 9),
  )
  _A				:    int =		(20, 195, 124, 210, 1462, 60, 300, 50, 18)



  def 						UpperCamelCase_ (					self )	->	Any:



         """simple docstring"""





         for i, (first_num, second_num) in enumerate(self.test_inputs ):
                UpperCAmelCase					=	least_common_multiple_slow(snake_case__       ,						snake_case__ )
                UpperCAmelCase					=	least_common_multiple_fast(snake_case__       ,						snake_case__ )
                with self.subTest(i=snake_case__ ):
                       self.assertEqual(snake_case__       ,						self.expected_results[i] )
                       self.assertEqual(snake_case__       ,						self.expected_results[i] )


if __name__ == "__main__":
 benchmark()
 unittest.main()
