
def     a__			(    snake_case   ,	snake_case   ,	snake_case   ,	snake_case    ):





  """simple docstring"""
  if start == end:
    return start if lst[start] > item else start + 1
  if start > end:
    return start

  __SCREAMING_SNAKE_CASE     :					List[Any]			=						(start + end) // 2
  if lst[mid] < item:
    return binary_search(snake_case   ,	snake_case   ,	mid + 1   ,	snake_case    )
  elif lst[mid] > item:
    return binary_search(snake_case   ,	snake_case   ,	snake_case   ,	mid - 1    )
  else:
    return mid


def     a__			(    snake_case    ):





  """simple docstring"""
  __SCREAMING_SNAKE_CASE     :					Optional[int]			=						len(snake_case    )

  for index in range(1   ,	snake_case    ):
    __SCREAMING_SNAKE_CASE     :					Union[str, Any]			=						lst[index]
    __SCREAMING_SNAKE_CASE     :					int			=						binary_search(snake_case   ,	snake_case   ,	0   ,	index - 1    )
    __SCREAMING_SNAKE_CASE     :					Union[str, Any]			=						lst[:pos] + [value] + lst[pos:index] + lst[index + 1 :]

  return lst


def     a__			(    snake_case   ,	snake_case    ):





  """simple docstring"""
  if not left:
    return right

  if not right:
    return left

  if left[0] < right[0]:
    return [left[0], *merge(left[1:]   ,	snake_case    )]

  return [right[0], *merge(snake_case   ,	right[1:]    )]


def     a__			(    snake_case    ):





  """simple docstring"""
  __SCREAMING_SNAKE_CASE     :					Tuple			=						len(snake_case    )
  __SCREAMING_SNAKE_CASE     :					Any			=						[], []
  __SCREAMING_SNAKE_CASE     :					str			=						[lst[0]]
  __SCREAMING_SNAKE_CASE     :					Optional[int]			=						[]
  __SCREAMING_SNAKE_CASE     :					Optional[int]			=						1
  while i < length:
    if lst[i] < lst[i - 1]:
      runs.append(snake_case    )
      __SCREAMING_SNAKE_CASE     :					int			=						[lst[i]]
    else:
      new_run.append(lst[i]    )
    i += 1
  runs.append(snake_case    )

  for run in runs:
    sorted_runs.append(insertion_sort(snake_case    )    )
  for run in sorted_runs:
    __SCREAMING_SNAKE_CASE     :					int			=						merge(snake_case   ,	snake_case    )

  return sorted_array


def     a__			(    ):





  """simple docstring"""
  __SCREAMING_SNAKE_CASE     :					str			=						[5, 9, 10, 3, -4, 5, 178, 92, 46, -18, 0, 7]
  __SCREAMING_SNAKE_CASE     :					int			=						tim_sort(snake_case    )
  print(snake_case    )


if __name__ == "__main__":
   main()


from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


lowercase_											=	{
    """configuration_led""": ["""LED_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LEDConfig"""],
    """tokenization_led""": ["""LEDTokenizer"""],
}

try:
   if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowercase_											=	["""LEDTokenizerFast"""]

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowercase_											=	[
       """LED_PRETRAINED_MODEL_ARCHIVE_LIST""",
       """LEDForConditionalGeneration""",
       """LEDForQuestionAnswering""",
       """LEDForSequenceClassification""",
       """LEDModel""",
       """LEDPreTrainedModel""",
   ]


try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowercase_											=	["""TFLEDForConditionalGeneration""", """TFLEDModel""", """TFLEDPreTrainedModel"""]


if TYPE_CHECKING:
   from .configuration_led import LED_PRETRAINED_CONFIG_ARCHIVE_MAP, LEDConfig
   from .tokenization_led import LEDTokenizer

   try:
      if not is_tokenizers_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_led_fast import LEDTokenizerFast

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_led import (
          LED_PRETRAINED_MODEL_ARCHIVE_LIST,
          LEDForConditionalGeneration,
          LEDForQuestionAnswering,
          LEDForSequenceClassification,
          LEDModel,
          LEDPreTrainedModel,
      )

   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_led import TFLEDForConditionalGeneration, TFLEDModel, TFLEDPreTrainedModel

else:
   import sys

   lowercase_											=	_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)
