code: 
  
  
  from typing import TYPE_CHECKING
  
  from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
  
  
  SCREAMING_SNAKE_CASE : Optional[Any]          =    {
      "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:
   SCREAMING_SNAKE_CASE : Optional[Any]          =    ["MarkupLMTokenizerFast"]
  
  try:
   if not is_torch_available():
    raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
   pass
  else:
   SCREAMING_SNAKE_CASE : List[Any]          =    [
       "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
  
   SCREAMING_SNAKE_CASE : str          =    _LazyModule(__name__, globals()["__file__"], _import_structure)
  
  
  
style_context: 
  
  
  from __future__ import annotations
  
  
  
  
  
  def 						_lowerCamelCase		(							SCREAMING_SNAKE_CASE_				: list      ):
  
  
  
  
  
  
  							"""simple docstring"""
  
  
  
  							a_       :   Tuple			=	sorted(SCREAMING_SNAKE_CASE_      )
  							a_       :   Tuple			=	len(SCREAMING_SNAKE_CASE_      )
  							a_       :   Tuple			=	length >> 1
  							return (
  							    (sorted_list[mid_index] + sorted_list[mid_index - 1]) / 2
  							    if length % 2 == 0
  							    else sorted_list[mid_index]
  							)
  
  
  
  
  
  def 						_lowerCamelCase		(							):
  
  
  
  
  
  
  							"""simple docstring"""
  
  
  
  							import doctest
  
  							doctest.testmod()
  
  
  if __name__ == "__main__":
  	main()
  
  
  