


from typing import TYPE_CHECKING

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


_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:
   _snake_case					=					['''MarkupLMTokenizerFast''']

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _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

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







def 		lowercase_(  SCREAMING_SNAKE_CASE_				,						SCREAMING_SNAKE_CASE_     ):


  '''simple docstring'''

  sequence.append(SCREAMING_SNAKE_CASE_     )

  lowerCamelCase			: str   =    0
  while sequence[index] != target:
    index += 1

  sequence.pop()

  if index == len(SCREAMING_SNAKE_CASE_     ):
    return None

  return index


if __name__ == "__main__":
   _snake_case					=					input('''Enter numbers separated by comma:\n''').strip()
   _snake_case					=					[int(item) for item in user_input.split(''',''')]

   _snake_case					=					input('''Enter a single number to be found in the list:\n''')
   _snake_case					=					int(target_input)
   _snake_case					=					sentinel_linear_search(sequence, target)
   if result is not None:
      print(f'''{target} found at positions: {result}''')
   else:
      print('''Not found''')



