code: 
  
  from __future__ import annotations
  
  
  
  
  def     UpperCAmelCase__       (    _A   :				List[Any]			,   _A   :				List[Any]							):
  
  
  
  
  
    '''simple docstring'''
  
  
  
  
  
  
  
    a__						=0
    a__						=len(_A							) - 1
    while left <= right:
      a__						=(left + right) // 2
      if left == right:
        if sorted_list[middle] < item:
          a__						=middle + 1
        break
      elif sorted_list[middle] < item:
        a__						=middle + 1
      else:
        a__						=middle - 1
    sorted_list.insert(_A			,   _A							)
    return sorted_list
  
  
  
  
  def     UpperCAmelCase__       (    _A   :				Any			,   _A   :				Tuple							):
  
  
  
  
  
    '''simple docstring'''
  
  
  
  
  
  
  
    a__						=[]
    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     UpperCAmelCase__       (    _A   :				Optional[Any]							):
  
  
  
  
  
    '''simple docstring'''
  
  
  
  
  
  
  
    a__						=len(_A							)
    if length <= 1:
      return list_ad
    a__						=length // 2
    return merge(sortlist_ad(list_ad[:middle]							)			,   sortlist_ad(list_ad[middle:]							)							)
  
  
  
  
  def     UpperCAmelCase__       (    _A   :				list[int]							):
  
  
  
  
  
    '''simple docstring'''
  
  
  
  
  
  
  
    if len(_A							) <= 1:
      return collection
    a__						=[]
    a__						=False
    for i in range(0			,   len(_A							)			,   2							):
      if i == len(_A							) - 1:
        a__						=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]]							)
    a__						=sortlist_ad(_A							)
    a__						=[i[0] for i in sorted_list_ad]
    result.append(sorted_list_ad[-1][1]							)
    if has_last_odd_item:
      a__						=collection[-1]
      a__						=binary_search_insertion(_A			,   _A							)
    a__						=False
    for i in range(len(_A							) - 1							):
      if result[i] == collection[-1] and has_last_odd_item:
        a__						=True
      a__						=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:
        a__						=result[: i + 2] + binary_search_insertion(result[i + 2 :]			,   _A							)
      else:
        a__						=result[: i + 1] + binary_search_insertion(result[i + 1 :]			,   _A							)
  
    return result
  
  
  if __name__ == "__main__":
         lowerCamelCase         =      input('''Enter numbers separated by a comma:\n''').strip()
         lowerCamelCase         =      [int(item) for item in user_input.split(''',''')]
         print(merge_insertion_sort(unsorted))
  
style_context: 
  
  from typing import TYPE_CHECKING
  
  from ...utils import (
      OptionalDependencyNotAvailable,
      _LazyModule,
      is_tf_available,
      is_tokenizers_available,
      is_torch_available,
  )
  
  
  lowerCamelCase     =      {
      '''configuration_deberta_v2''': ['''DEBERTA_V2_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''DebertaV2Config''', '''DebertaV2OnnxConfig'''],
      '''tokenization_deberta_v2''': ['''DebertaV2Tokenizer'''],
  }
  
  try:
         if not is_tokenizers_available():
                raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
         pass
  else:
         lowerCamelCase     =      ['''DebertaV2TokenizerFast''']
  
  try:
         if not is_tf_available():
                raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
         pass
  else:
         lowerCamelCase     =      [
             '''TF_DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST''',
             '''TFDebertaV2ForMaskedLM''',
             '''TFDebertaV2ForQuestionAnswering''',
             '''TFDebertaV2ForSequenceClassification''',
             '''TFDebertaV2ForTokenClassification''',
             '''TFDebertaV2Model''',
             '''TFDebertaV2PreTrainedModel''',
         ]
  
  try:
         if not is_torch_available():
                raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
         pass
  else:
         lowerCamelCase     =      [
             '''DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST''',
             '''DebertaV2ForMaskedLM''',
             '''DebertaV2ForMultipleChoice''',
             '''DebertaV2ForQuestionAnswering''',
             '''DebertaV2ForSequenceClassification''',
             '''DebertaV2ForTokenClassification''',
             '''DebertaV2Model''',
             '''DebertaV2PreTrainedModel''',
         ]
  
  
  if TYPE_CHECKING:
         from .configuration_deberta_va import (
             DEBERTA_V2_PRETRAINED_CONFIG_ARCHIVE_MAP,
             DebertaVaConfig,
             DebertaVaOnnxConfig,
         )
         from .tokenization_deberta_va import DebertaVaTokenizer
  
         try:
                if not is_tokenizers_available():
                       raise OptionalDependencyNotAvailable()
         except OptionalDependencyNotAvailable:
                pass
         else:
                from .tokenization_deberta_va_fast import DebertaVaTokenizerFast
  
         try:
                if not is_tf_available():
                       raise OptionalDependencyNotAvailable()
         except OptionalDependencyNotAvailable:
                pass
         else:
                from .modeling_tf_deberta_va import (
                    TF_DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST,
                    TFDebertaVaForMaskedLM,
                    TFDebertaVaForQuestionAnswering,
                    TFDebertaVaForSequenceClassification,
                    TFDebertaVaForTokenClassification,
                    TFDebertaVaModel,
                    TFDebertaVaPreTrainedModel,
                )
  
         try:
                if not is_torch_available():
                       raise OptionalDependencyNotAvailable()
         except OptionalDependencyNotAvailable:
                pass
         else:
                from .modeling_deberta_va import (
                    DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST,
                    DebertaVaForMaskedLM,
                    DebertaVaForMultipleChoice,
                    DebertaVaForQuestionAnswering,
                    DebertaVaForSequenceClassification,
                    DebertaVaForTokenClassification,
                    DebertaVaModel,
                    DebertaVaPreTrainedModel,
                )
  
  else:
         import sys
  
         lowerCamelCase     =      _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
  