


from __future__ import annotations






def 		lowercase_(  SCREAMING_SNAKE_CASE_				,						SCREAMING_SNAKE_CASE_     ):


  '''simple docstring'''

  lowerCamelCase			: int   =    0
  lowerCamelCase			: str   =    len(_UpperCAmelCase     ) - 1
  while left <= right:
    lowerCamelCase			: Any   =    (left + right) // 2
    if left == right:
      if sorted_list[middle] < item:
        lowerCamelCase			: Optional[Any]   =    middle + 1
      break
    elif sorted_list[middle] < item:
      lowerCamelCase			: Tuple   =    middle + 1
    else:
      lowerCamelCase			: List[Any]   =    middle - 1
  sorted_list.insert(_UpperCAmelCase				,						_UpperCAmelCase     )
  return sorted_list






def 		lowercase_(  SCREAMING_SNAKE_CASE_				,						SCREAMING_SNAKE_CASE_     ):


  '''simple docstring'''

  lowerCamelCase			: str   =    []
  while left and right:
    if left[0][0] < right[0][0]:
      result.append(left.pop(0     )     )
    else:
      result.append(right.pop(0     )     )
  return result + left + right






def 		lowercase_(  SCREAMING_SNAKE_CASE_     ):


  '''simple docstring'''

  lowerCamelCase			: Union[str, Any]   =    len(_UpperCAmelCase     )
  if length <= 1:
    return list_ad
  lowerCamelCase			: int   =    length // 2
  return merge(sortlist_ad(list_ad[:middle]     )				,						sortlist_ad(list_ad[middle:]     )     )






def 		lowercase_(  SCREAMING_SNAKE_CASE_     ):


  '''simple docstring'''

  if len(_UpperCAmelCase     ) <= 1:
    return collection
  lowerCamelCase			: Optional[int]   =    []
  lowerCamelCase			: int   =    False
  for i in range(0				,						len(_UpperCAmelCase     )				,						2     ):
    if i == len(_UpperCAmelCase     ) - 1:
      lowerCamelCase			: str   =    True
    else:
      if collection[i] < collection[i + 1]:
        two_paired_list.append([collection[i], collection[i + 1]]     )
      else:
        two_paired_list.append([collection[i + 1], collection[i]]     )
  lowerCamelCase			: Union[str, Any]   =    sortlist_ad(_UpperCAmelCase     )
  lowerCamelCase			: List[Any]   =    [i[0] for i in sorted_list_ad]
  result.append(sorted_list_ad[-1][1]     )
  if has_last_odd_item:
    lowerCamelCase			: Tuple   =    collection[-1]
    lowerCamelCase			: Optional[Any]   =    binary_search_insertion(_UpperCAmelCase				,						_UpperCAmelCase     )
  lowerCamelCase			: Optional[int]   =    False
  for i in range(len(_UpperCAmelCase     ) - 1     ):
    if result[i] == collection[-1] and has_last_odd_item:
      lowerCamelCase			: Any   =    True
    lowerCamelCase			: List[str]   =    sorted_list_ad[i][1]
    # If last_odd_item is inserted before the item's index,
    # you should forward index one more.
    if is_last_odd_item_inserted_before_this_index:
      lowerCamelCase			: Dict   =    result[: i + 2] + binary_search_insertion(result[i + 2 :]				,						_UpperCAmelCase     )
    else:
      lowerCamelCase			: str   =    result[: i + 1] + binary_search_insertion(result[i + 1 :]				,						_UpperCAmelCase     )

  return result


if __name__ == "__main__":
     _snake_case					=					input('''Enter numbers separated by a comma:\n''').strip()
     _snake_case					=					[int(item) for item in user_input.split(''',''')]
     print(merge_insertion_sort(unsorted))







from typing import Optional, Union

from ...file_utils import TensorType
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, TruncationStrategy
class      UpperCAmelCase_ ( UpperCamelCase   ):

   '''simple docstring'''




   __A			:				Union[str, Any]							=		"MarkupLMFeatureExtractor"
   __A			:				List[str]							=		("MarkupLMTokenizer", "MarkupLMTokenizerFast")
   __A			:				str							=		True






   def __call__(		self						,    __A=None						,    __A=None						,    __A=None						,    __A=None						,    __A=None						,    __A = True						,    __A = False						,    __A = None						,    __A = None						,    __A = 0						,    __A = None						,    __A = None						,    __A = None						,    __A = False						,    __A = False						,    __A = False						,    __A = False						,    __A = True						,    __A = None						,    **__A						,    ):






     """simple docstring"""





     if self.parse_html:
       if html_strings is None:
         raise ValueError("Make sure to pass HTML strings in case `parse_html` is set to `True`"			)

       if nodes is not None or xpaths is not None or node_labels is not None:
         raise ValueError(
             "Please don't pass nodes, xpaths nor node labels in case `parse_html` is set to `True`"			)

       lowerCamelCase			: Any   =    self.feature_extractor(__A			)
       lowerCamelCase			: Optional[int]   =    features["nodes"]
       lowerCamelCase			: Any   =    features["xpaths"]
     else:
       if html_strings is not None:
         raise ValueError("You have passed HTML strings but `parse_html` is set to `False`."			)
       if nodes is None or xpaths is None:
         raise ValueError("Make sure to pass nodes and xpaths in case `parse_html` is set to `False`"			)

        # # second, apply the tokenizer
     if questions is not None and self.parse_html:
       if isinstance(__A						,    __A			):
         lowerCamelCase			: Tuple   =    [questions]  # add batch dimension (as the feature extractor always adds a batch dimension)

     lowerCamelCase			: Tuple   =    self.tokenizer(
         text=questions if questions is not None else nodes						,    text_pair=nodes if questions is not None else None						,    xpaths=__A						,    node_labels=__A						,    add_special_tokens=__A						,    padding=__A						,    truncation=__A						,    max_length=__A						,    stride=__A						,    pad_to_multiple_of=__A						,    return_token_type_ids=__A						,    return_attention_mask=__A						,    return_overflowing_tokens=__A						,    return_special_tokens_mask=__A						,    return_offsets_mapping=__A						,    return_length=__A						,    verbose=__A						,    return_tensors=__A						,    **__A						,    )

     return encoded_inputs






   def _snake_case   (		self						,    *__A						,    **__A			):






     """simple docstring"""





     return self.tokenizer.batch_decode(*__A						,    **__A			)






   def _snake_case   (		self						,    *__A						,    **__A			):






     """simple docstring"""





     return self.tokenizer.decode(*__A						,    **__A			)






   @property
   def _snake_case   (		self			):






     """simple docstring"""





     lowerCamelCase			: Dict   =    self.tokenizer.model_input_names
     return tokenizer_input_names



