code: 
  
  
  
  
  
  def 		UpperCamelCase       (							_lowerCamelCase      :      Optional[Any]		, _lowerCamelCase      :      int		, _lowerCamelCase      :      Dict		, _lowerCamelCase      :      Any ):
      if start == end:
          return start if lst[start] > item else start + 1
      if start > end:
          return start
  
      A__       =    (start + end) // 2
      if lst[mid] < item:
          return binary_search(_lowerCamelCase		, _lowerCamelCase		, mid + 1		, _lowerCamelCase )
      elif lst[mid] > item:
          return binary_search(_lowerCamelCase		, _lowerCamelCase		, _lowerCamelCase		, mid - 1 )
      else:
          return mid
  
  
  
  
  
  def 		UpperCamelCase       (							_lowerCamelCase      :      int ):
      A__       =    len(_lowerCamelCase )
  
      for index in range(1		, _lowerCamelCase ):
          A__       =    lst[index]
          A__       =    binary_search(_lowerCamelCase		, _lowerCamelCase		, 0		, index - 1 )
          A__       =    lst[:pos] + [value] + lst[pos:index] + lst[index + 1 :]
  
      return lst
  
  
  
  
  
  def 		UpperCamelCase       (							_lowerCamelCase      :      Dict		, _lowerCamelCase      :      List[Any] ):
      if not left:
          return right
  
      if not right:
          return left
  
      if left[0] < right[0]:
          return [left[0], *merge(left[1:]		, _lowerCamelCase )]
  
      return [right[0], *merge(_lowerCamelCase		, right[1:] )]
  
  
  
  
  
  def 		UpperCamelCase       (							_lowerCamelCase      :      Any ):
      A__       =    len(_lowerCamelCase )
      A__,			A__       =    [], []
      A__       =    [lst[0]]
      A__       =    []
      A__       =    1
      while i < length:
          if lst[i] < lst[i - 1]:
              runs.append(_lowerCamelCase )
              A__       =    [lst[i]]
          else:
              new_run.append(lst[i] )
          i += 1
      runs.append(_lowerCamelCase )
  
      for run in runs:
          sorted_runs.append(insertion_sort(_lowerCamelCase ) )
      for run in sorted_runs:
          A__       =    merge(_lowerCamelCase		, _lowerCamelCase )
  
      return sorted_array
  
  
  
  
  
  def 		UpperCamelCase       (							):
      A__       =    [5, 9, 10, 3, -4, 5, 1_78, 92, 46, -18, 0, 7]
      A__       =    tim_sort(_lowerCamelCase )
      print(_lowerCamelCase )
  
  
  if __name__ == "__main__":
    main()
  
  
  
  
style_context: 
  
  
  
  
  
  '''simple docstring'''
  
  from typing import TYPE_CHECKING
  
  from ...utils import (
      OptionalDependencyNotAvailable,
      _LazyModule,
      is_tf_available,
      is_tokenizers_available,
      is_torch_available,
  )
  
  
  __lowerCAmelCase							:			int				={
      "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							:			Any				=["LayoutLMTokenizerFast"]
  
  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    __lowerCAmelCase							:			Dict				=[
        "LAYOUTLM_PRETRAINED_MODEL_ARCHIVE_LIST",
        "LayoutLMForMaskedLM",
        "LayoutLMForSequenceClassification",
        "LayoutLMForTokenClassification",
        "LayoutLMForQuestionAnswering",
        "LayoutLMModel",
        "LayoutLMPreTrainedModel",
    ]
  
  try:
    if not is_tf_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    __lowerCAmelCase							:			str				=[
        "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							:			int				=_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
  
  
  
  