


'''simple docstring'''

from typing import TYPE_CHECKING

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


lowerCamelCase							:     List[str]								=			{
    """configuration_layoutlm""": ["""LAYOUTLM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LayoutLMConfig""", """LayoutLMOnnxConfig"""],
    """tokenization_layoutlm""": ["""LayoutLMTokenizer"""],
}

try:
 if not is_tokenizers_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCamelCase							:     int								=			["""LayoutLMTokenizerFast"""]

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCamelCase							:     List[str]								=			[
     """LAYOUTLM_PRETRAINED_MODEL_ARCHIVE_LIST""",
     """LayoutLMForMaskedLM""",
     """LayoutLMForSequenceClassification""",
     """LayoutLMForTokenClassification""",
     """LayoutLMForQuestionAnswering""",
     """LayoutLMModel""",
     """LayoutLMPreTrainedModel""",
 ]

try:
 if not is_tf_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCamelCase							:     Any								=			[
     """TF_LAYOUTLM_PRETRAINED_MODEL_ARCHIVE_LIST""",
     """TFLayoutLMForMaskedLM""",
     """TFLayoutLMForSequenceClassification""",
     """TFLayoutLMForTokenClassification""",
     """TFLayoutLMForQuestionAnswering""",
     """TFLayoutLMMainLayer""",
     """TFLayoutLMModel""",
     """TFLayoutLMPreTrainedModel""",
 ]


if TYPE_CHECKING:
 from .configuration_layoutlm import LAYOUTLM_PRETRAINED_CONFIG_ARCHIVE_MAP, LayoutLMConfig, LayoutLMOnnxConfig
 from .tokenization_layoutlm import LayoutLMTokenizer

 try:
  if not is_tokenizers_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .tokenization_layoutlm_fast import LayoutLMTokenizerFast

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_layoutlm import (
      LAYOUTLM_PRETRAINED_MODEL_ARCHIVE_LIST,
      LayoutLMForMaskedLM,
      LayoutLMForQuestionAnswering,
      LayoutLMForSequenceClassification,
      LayoutLMForTokenClassification,
      LayoutLMModel,
      LayoutLMPreTrainedModel,
  )
 try:
  if not is_tf_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_tf_layoutlm import (
      TF_LAYOUTLM_PRETRAINED_MODEL_ARCHIVE_LIST,
      TFLayoutLMForMaskedLM,
      TFLayoutLMForQuestionAnswering,
      TFLayoutLMForSequenceClassification,
      TFLayoutLMForTokenClassification,
      TFLayoutLMMainLayer,
      TFLayoutLMModel,
      TFLayoutLMPreTrainedModel,
  )

else:
 import sys

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








'''simple docstring'''

from __future__ import annotations

from collections import Counter

def _SCREAMING_SNAKE_CASE   (A ) -> list[int]:






       """simple docstring"""







       lowercase__       =				[True] * n
       lowercase__       =				False
       lowercase__       =				False
       lowercase__       =				True

       for i in range(3						,				int(n**0.5 + 1 )						,				2 ):
              lowercase__       =				i * 2
              while index < n:
                     lowercase__       =				False
                     lowercase__       =				index + i

       lowercase__       =				[2]

       for i in range(3						,				A						,				2 ):
              if is_prime[i]:
                     primes.append(A )

       return primes

def _SCREAMING_SNAKE_CASE   (A ) -> list[list[int]]:






       """simple docstring"""







       lowercase__       =				str(A )
       lowercase__       =				[]
       lowercase__       =				['''0''', '''1''', '''2''', '''3''', '''4''', '''5''', '''6''', '''7''', '''8''', '''9''']

       for duplicate in Counter(A ) - Counter(set(A ) ):
              lowercase__       =				[int(number_str.replace(A						,				A ) ) for digit in digits]
              replacements.append(A )

       return replacements

def _SCREAMING_SNAKE_CASE   (A = 8 ) -> int:






       """simple docstring"""







       lowercase__       =				set()

       # Filter primes with less than 3 replaceable digits
       lowercase__       =				{
           x for x in set(prime_sieve(1_000_000 ) ) if len(str(A ) ) - len(set(str(A ) ) ) >= 3
       }

       for prime in primes:
              if prime in numbers_checked:
                     continue

              lowercase__       =				digit_replacements(A )

              for family in replacements:
                     numbers_checked.update(A )
                     lowercase__       =				primes.intersection(A )

                     if len(A ) != family_length:
                            continue

                     return min(A )

       return -1


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




