code: 
  
  from __future__ import annotations
  
  
  
  
  def     UpperCAmelCase__       (    _A   :				int							):
  
  
  
  
  
    '''simple docstring'''
  
  
  
  
  
  
  
    a__						=[0] * max_one
  
    for i in range(0			,   _A							):
      a__						=i
  
    for i in range(2			,   _A							):
      if totients[i] == i:
        for j in range(_A			,   _A			,   _A							):
          totients[j] -= totients[j] // i
  
    return totients
  
  
  
  
  def     UpperCAmelCase__       (    _A   :				int			,   _A   :				int							):
  
  
  
  
  
    '''simple docstring'''
  
  
  
  
  
  
  
    return sorted(str(_A							)							) == sorted(str(_A							)							)
  
  
  
  
  def     UpperCAmelCase__       (    _A   :				int = 10_00_00_00							):
  
  
  
  
  
    '''simple docstring'''
  
  
  
  
  
  
  
    a__						=1  # i
    a__						=0  # φ(i)
    a__						=get_totients(max_n + 1							)
  
    for i in range(2			,   max_n + 1							):
      a__						=totients[i]
  
      if i * min_denominator < min_numerator * t and has_same_digits(_A			,   _A							):
        a__						=i
        a__						=t
  
    return min_numerator
  
  
  if __name__ == "__main__":
         print(f"""{solution() = }""")
  
style_context: 
  
  from typing import TYPE_CHECKING
  
  from ...utils import (
      OptionalDependencyNotAvailable,
      _LazyModule,
      is_tf_available,
      is_tokenizers_available,
      is_torch_available,
  )
  
  
  lowerCamelCase     =      {
      '''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     =      ['''DebertaV2TokenizerFast''']
  
  try:
         if not is_tf_available():
                raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
         pass
  else:
         lowerCamelCase     =      [
             '''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     =      [
             '''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     =      _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
  