code: 
  
  
  from typing import TYPE_CHECKING
  
  from ...utils import (
      OptionalDependencyNotAvailable,
      _LazyModule,
      is_tf_available,
      is_tokenizers_available,
      is_torch_available,
  )
  
  
  lowerCAmelCase					 =	{
      '''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					 =	['''LayoutLMTokenizerFast''']
  
  try:
  	if not is_torch_available():
  		raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  	pass
  else:
  	lowerCAmelCase					 =	[
  	    '''LAYOUTLM_PRETRAINED_MODEL_ARCHIVE_LIST''',
  	    '''LayoutLMForMaskedLM''',
  	    '''LayoutLMForSequenceClassification''',
  	    '''LayoutLMForTokenClassification''',
  	    '''LayoutLMForQuestionAnswering''',
  	    '''LayoutLMModel''',
  	    '''LayoutLMPreTrainedModel''',
  	]
  
  try:
  	if not is_tf_available():
  		raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  	pass
  else:
  	lowerCAmelCase					 =	[
  	    '''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					 =	_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
  
  
  
  
  
  
  
style_context: 
  
  
  def  _lowerCamelCase(			lowercase__			)		->			str:
  
  		'''simple docstring'''
  
  
  
  
  
  
  
  		return " ".join([word[::-1] for word in input_str.split()]			)
  
  
  if __name__ == "__main__":
  	import doctest
  
  	doctest.testmod()
  
  
  
  
  
  
  