code: 
  
  
  
  
  from typing import TYPE_CHECKING
  
  from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
  
  
  SCREAMING_SNAKE_CASE__    :    int								=					{
      "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__    :    Tuple								=					["MarkupLMTokenizerFast"]
  
  try:
  				if not is_torch_available():
  								raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  				pass
  else:
  				SCREAMING_SNAKE_CASE__    :    Optional[int]								=					[
  				    "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__    :    Optional[Any]								=					_LazyModule(__name__, globals()["__file__"], _import_structure)
  
style_context: 
  
  
  
  
  SCREAMING_SNAKE_CASE__    :    List[str]								=					"\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n"
  
  SCREAMING_SNAKE_CASE__    :    List[str]								=					[{"type": "code", "content": INSTALL_CONTENT}]
  SCREAMING_SNAKE_CASE__    :    List[Any]								=					{
      "{processor_class}": "FakeProcessorClass",
      "{model_class}": "FakeModelClass",
      "{object_class}": "FakeObjectClass",
  }
  