code: from typing import TYPE_CHECKING
  
  from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
  
  
  _SCREAMING_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:
       _SCREAMING_SNAKE_CASE   						=    ["""MarkupLMTokenizerFast"""]
  
  try:
       if not is_torch_available():
            raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
       pass
  else:
       _SCREAMING_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
  
       _SCREAMING_SNAKE_CASE   						=    _LazyModule(__name__, globals()["""__file__"""], _import_structure)
  
  
style_context: _SCREAMING_SNAKE_CASE   						=    [0.485, 0.456, 0.406]
  _SCREAMING_SNAKE_CASE   						=    [0.229, 0.224, 0.225]
  _SCREAMING_SNAKE_CASE   						=    [0.5, 0.5, 0.5]
  _SCREAMING_SNAKE_CASE   						=    [0.5, 0.5, 0.5]
  _SCREAMING_SNAKE_CASE   						=    [0.48145466, 0.4578275, 0.40821073]
  _SCREAMING_SNAKE_CASE   						=    [0.26862954, 0.26130258, 0.27577711]
  
  