
"""simple docstring"""

from typing import TYPE_CHECKING

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


SCREAMING_SNAKE_CASE_			    =  {
    '''configuration_markuplm''': ['''MARKUPLM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MarkupLMConfig'''],
    '''feature_extraction_markuplm''': ['''MarkupLMFeatureExtractor'''],
    '''processing_markuplm''': ['''MarkupLMProcessor'''],
    '''tokenization_markuplm''': ['''MarkupLMTokenizer'''],
}

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

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   SCREAMING_SNAKE_CASE_			    =  [
       '''MARKUPLM_PRETRAINED_MODEL_ARCHIVE_LIST''',
       '''MarkupLMForQuestionAnswering''',
       '''MarkupLMForSequenceClassification''',
       '''MarkupLMForTokenClassification''',
       '''MarkupLMModel''',
       '''MarkupLMPreTrainedModel''',
   ]


if TYPE_CHECKING:
   from .configuration_markuplm import MARKUPLM_PRETRAINED_CONFIG_ARCHIVE_MAP, MarkupLMConfig
   from .feature_extraction_markuplm import MarkupLMFeatureExtractor
   from .processing_markuplm import MarkupLMProcessor
   from .tokenization_markuplm import MarkupLMTokenizer

   try:
      if not is_tokenizers_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_markuplm_fast import MarkupLMTokenizerFast

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_markuplm import (
          MARKUPLM_PRETRAINED_MODEL_ARCHIVE_LIST,
          MarkupLMForQuestionAnswering,
          MarkupLMForSequenceClassification,
          MarkupLMForTokenClassification,
          MarkupLMModel,
          MarkupLMPreTrainedModel,
      )


else:
   import sys

   SCREAMING_SNAKE_CASE_			    =  _LazyModule(__name__, globals()['''__file__'''], _import_structure)










"""simple docstring"""




def        a_				(							_lowercase = 10**6   ):

						if n <= 0:
												raise ValueError('''Please enter an integer greater than 0'''   )

						_UpperCamelCase			:					Any     =    list(range(n + 1   )   )
						for number in range(2       ,						n + 1   ):
												if phi[number] == number:
																		phi[number] -= 1
																		for multiple in range(number * 2       ,						n + 1       ,						_lowercase   ):
																								_UpperCamelCase			:					List[str]     =    (phi[multiple] // number) * (number - 1)

						_UpperCamelCase			:					Union[str, Any]     =    1
						for number in range(1       ,						n + 1   ):
												if (answer / phi[answer]) < (number / phi[number]):
																		_UpperCamelCase			:					List[str]     =    number

						return answer


if __name__ == "__main__":
						print(solution())



