
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__lowerCAmelCase      :					Dict   	=       {'configuration_qdqbert': ['QDQBERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'QDQBertConfig']}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __lowerCAmelCase      :					List[str]   	=       [
        'QDQBERT_PRETRAINED_MODEL_ARCHIVE_LIST',
        'QDQBertForMaskedLM',
        'QDQBertForMultipleChoice',
        'QDQBertForNextSentencePrediction',
        'QDQBertForQuestionAnswering',
        'QDQBertForSequenceClassification',
        'QDQBertForTokenClassification',
        'QDQBertLayer',
        'QDQBertLMHeadModel',
        'QDQBertModel',
        'QDQBertPreTrainedModel',
        'load_tf_weights_in_qdqbert',
    ]


if TYPE_CHECKING:
    from .configuration_qdqbert import QDQBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, QDQBertConfig

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_qdqbert import (
            QDQBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
            QDQBertForMaskedLM,
            QDQBertForMultipleChoice,
            QDQBertForNextSentencePrediction,
            QDQBertForQuestionAnswering,
            QDQBertForSequenceClassification,
            QDQBertForTokenClassification,
            QDQBertLayer,
            QDQBertLMHeadModel,
            QDQBertModel,
            QDQBertPreTrainedModel,
            load_tf_weights_in_qdqbert,
        )


else:
    import sys

    __lowerCAmelCase      :					List[Any]   	=       _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)



import sys

sys.set_int_max_str_digits(0)  # type: ignore

def a__   (	A_ ):






  '''simple docstring'''





  __magic_name__    					=	[0] * 11
  __magic_name__    					=	[0] * 11

  # mark last 9 numbers
  for _ in range(9 ):
    __magic_name__    					=	1
    __magic_name__    					=	number // 10
  # flag
  __magic_name__    					=	True

  # check last 9 numbers for pandigitality

  for x in range(9 ):
    if not check_last[x + 1]:
      __magic_name__    					=	False
  if not f:
    return f

  # mark first 9 numbers
  __magic_name__    					=	int(str(A_ )[:9] )

  for _ in range(9 ):
    __magic_name__    					=	1
    __magic_name__    					=	number // 10

  # check first 9 numbers for pandigitality

  for x in range(9 ):
    if not check_front[x + 1]:
      __magic_name__    					=	False
  return f

def a__   (	A_ ):






  '''simple docstring'''





  __magic_name__    					=	[0] * 11

  # mark last 9 numbers
  for _ in range(9 ):
    __magic_name__    					=	1
    __magic_name__    					=	number // 10
  # flag
  __magic_name__    					=	True

  # check last 9 numbers for pandigitality

  for x in range(9 ):
    if not check_last[x + 1]:
      __magic_name__    					=	False
  return f

def a__   (	):






  '''simple docstring'''





  __magic_name__    					=	1
  __magic_name__    					=	1
  __magic_name__    					=	2
  # temporary Fibonacci numbers

  __magic_name__    					=	1
  __magic_name__    					=	1
  __magic_name__    					=	2
  # temporary Fibonacci numbers mod 1e9

  # mod m=1e9, done for fast optimisation
  __magic_name__    					=	[0] * 1000000
  __magic_name__    					=	1000000000

  for x in range(1000000 ):
    __magic_name__    					=	(aa + ba) % m
    __magic_name__    					=	ba % m
    __magic_name__    					=	ca % m
    if checka(A_ ):
      __magic_name__    					=	1

  for x in range(1000000 ):
    __magic_name__    					=	a + b
    __magic_name__    					=	b
    __magic_name__    					=	c
    # perform check only if in tocheck
    if tocheck[x + 3] and check(A_ ):
      return x + 3  # first 2 already done
  return -1


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

