





"""simple docstring"""




from typing import TYPE_CHECKING

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


lowerCamelCase_	:		int         =   {
    'configuration_deberta_v2': ['DEBERTA_V2_PRETRAINED_CONFIG_ARCHIVE_MAP', 'DebertaV2Config', 'DebertaV2OnnxConfig'],
    'tokenization_deberta_v2': ['DebertaV2Tokenizer'],
}

try:
   if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowerCamelCase_	:		Any         =   ['DebertaV2TokenizerFast']

try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowerCamelCase_	:		Any         =   [
       'TF_DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST',
       'TFDebertaV2ForMaskedLM',
       'TFDebertaV2ForQuestionAnswering',
       'TFDebertaV2ForSequenceClassification',
       'TFDebertaV2ForTokenClassification',
       'TFDebertaV2Model',
       'TFDebertaV2PreTrainedModel',
   ]

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowerCamelCase_	:		Optional[Any]         =   [
       'DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST',
       'DebertaV2ForMaskedLM',
       'DebertaV2ForMultipleChoice',
       'DebertaV2ForQuestionAnswering',
       'DebertaV2ForSequenceClassification',
       'DebertaV2ForTokenClassification',
       'DebertaV2Model',
       'DebertaV2PreTrainedModel',
   ]


if TYPE_CHECKING:
   from .configuration_deberta_va import (
       DEBERTA_V2_PRETRAINED_CONFIG_ARCHIVE_MAP,
       DebertaVaConfig,
       DebertaVaOnnxConfig,
   )
   from .tokenization_deberta_va import DebertaVaTokenizer

   try:
      if not is_tokenizers_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_deberta_va_fast import DebertaVaTokenizerFast

   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_deberta_va import (
          TF_DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST,
          TFDebertaVaForMaskedLM,
          TFDebertaVaForQuestionAnswering,
          TFDebertaVaForSequenceClassification,
          TFDebertaVaForTokenClassification,
          TFDebertaVaModel,
          TFDebertaVaPreTrainedModel,
      )

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_deberta_va import (
          DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST,
          DebertaVaForMaskedLM,
          DebertaVaForMultipleChoice,
          DebertaVaForQuestionAnswering,
          DebertaVaForSequenceClassification,
          DebertaVaForTokenClassification,
          DebertaVaModel,
          DebertaVaPreTrainedModel,
      )

else:
   import sys

   lowerCamelCase_	:		Union[str, Any]         =   _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




"""simple docstring"""




from __future__ import annotations


def 	lowercase__  (      _UpperCAmelCase					)  ->      list[int]:






      '''simple docstring'''


      lowercase	:   Optional[Any]											= [0] * max_one

      for i in range(0						,   _UpperCAmelCase					):
            lowercase	:   List[Any]											= i

      for i in range(2						,   _UpperCAmelCase					):
            if totients[i] == i:
                  for j in range(_UpperCAmelCase						,   _UpperCAmelCase						,   _UpperCAmelCase					):
                        totients[j] -= totients[j] // i

      return totients


def 	lowercase__  (      _UpperCAmelCase						,   _UpperCAmelCase					)  ->      bool:






      '''simple docstring'''


      return sorted(str(_UpperCAmelCase					)					) == sorted(str(_UpperCAmelCase					)					)


def 	lowercase__  (      _UpperCAmelCase = 10_00_00_00					)  ->      int:






      '''simple docstring'''


      lowercase	:   Union[str, Any]											= 1  # i
      lowercase	:   Any											= 0  # φ(i)
      lowercase	:   int											= get_totients(max_n + 1					)

      for i in range(2						,   max_n + 1					):
            lowercase	:   Any											= totients[i]

            if i * min_denominator < min_numerator * t and has_same_digits(_UpperCAmelCase						,   _UpperCAmelCase					):
                  lowercase	:   List[Any]											= i
                  lowercase	:   Optional[Any]											= t

      return min_numerator


if __name__ == "__main__":
     print(f'''{solution() = }''')
