code: 
  from __future__ import annotations
  
  
  
  
  
  
  def 						lowerCAmelCase_		(      _snake_case   :						Optional[int]   ,     _snake_case   :						str     )       ->	Any:
  
  
  
  
  
  
  
  	'''simple docstring'''
  
  
  	__magic_name__	:	Union[str, Any]			     =  0
  	__magic_name__	:	List[str]			     =  len(_snake_case     ) - 1
  	while left <= right:
  		__magic_name__	:	Optional[int]			     =  (left + right) // 2
  		if left == right:
  			if sorted_list[middle] < item:
  				__magic_name__	:	Any			     =  middle + 1
  			break
  		elif sorted_list[middle] < item:
  			__magic_name__	:	Optional[Any]			     =  middle + 1
  		else:
  			__magic_name__	:	Tuple			     =  middle - 1
  	sorted_list.insert(_snake_case   ,     _snake_case     )
  	return sorted_list
  
  
  
  
  
  
  def 						lowerCAmelCase_		(      _snake_case   :						Tuple   ,     _snake_case   :						List[Any]     )       ->	Union[str, Any]:
  
  
  
  
  
  
  
  	'''simple docstring'''
  
  
  	__magic_name__	:	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 						lowerCAmelCase_		(      _snake_case   :						str     )       ->	Tuple:
  
  
  
  
  
  
  
  	'''simple docstring'''
  
  
  	__magic_name__	:	Dict			     =  len(_snake_case     )
  	if length <= 1:
  		return list_ad
  	__magic_name__	:	Optional[int]			     =  length // 2
  	return merge(sortlist_ad(list_ad[:middle]     )   ,     sortlist_ad(list_ad[middle:]     )     )
  
  
  
  
  
  
  def 						lowerCAmelCase_		(      _snake_case   :						list[int]     )       ->	list[int]:
  
  
  
  
  
  
  
  	'''simple docstring'''
  
  
  	if len(_snake_case     ) <= 1:
  		return collection
  	__magic_name__	:	Optional[Any]			     =  []
  	__magic_name__	:	Union[str, Any]			     =  False
  	for i in range(0   ,     len(_snake_case     )   ,     2     ):
  		if i == len(_snake_case     ) - 1:
  			__magic_name__	:	List[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]]     )
  	__magic_name__	:	List[Any]			     =  sortlist_ad(_snake_case     )
  	__magic_name__	:	List[Any]			     =  [i[0] for i in sorted_list_ad]
  	result.append(sorted_list_ad[-1][1]     )
  	if has_last_odd_item:
  		__magic_name__	:	Tuple			     =  collection[-1]
  		__magic_name__	:	Union[str, Any]			     =  binary_search_insertion(_snake_case   ,     _snake_case     )
  	__magic_name__	:	Union[str, Any]			     =  False
  	for i in range(len(_snake_case     ) - 1     ):
  		if result[i] == collection[-1] and has_last_odd_item:
  			__magic_name__	:	int			     =  True
  		__magic_name__	:	Tuple			     =  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:
  			__magic_name__	:	Optional[Any]			     =  result[: i + 2] + binary_search_insertion(result[i + 2 :]   ,     _snake_case     )
  		else:
  			__magic_name__	:	Dict			     =  result[: i + 1] + binary_search_insertion(result[i + 1 :]   ,     _snake_case     )
  
  	return result
  
  
  if __name__ == "__main__":
  				snake_case				:	str							   =						input("Enter numbers separated by a comma:\n").strip()
  				snake_case				:	str							   =						[int(item) for item in user_input.split(",")]
  				print(merge_insertion_sort(unsorted))
  
style_context: 
  import os
  from shutil import copyfile
  from typing import List, Optional, Tuple
  
  from ...tokenization_utils import AddedToken
  from ...tokenization_utils_fast import PreTrainedTokenizerFast
  from ...utils import is_sentencepiece_available, logging
  
  
  if is_sentencepiece_available():
  				from .tokenization_xlm_roberta import XLMRobertaTokenizer
  else:
  				snake_case				:	Any							   =						None
  
  
  snake_case				:	Union[str, Any]							   =						logging.get_logger(__name__)
  
  snake_case				:	Any							   =						{"vocab_file": "sentencepiece.bpe.model", "tokenizer_file": "tokenizer.json"}
  
  snake_case				:	Optional[Any]							   =						{
      "vocab_file": {
          "xlm-roberta-base": "https://huggingface.co/xlm-roberta-base/resolve/main/sentencepiece.bpe.model",
          "xlm-roberta-large": "https://huggingface.co/xlm-roberta-large/resolve/main/sentencepiece.bpe.model",
          "xlm-roberta-large-finetuned-conll02-dutch": (
              "https://huggingface.co/xlm-roberta-large-finetuned-conll02-dutch/resolve/main/sentencepiece.bpe.model"
          ),
          "xlm-roberta-large-finetuned-conll02-spanish": (
              "https://huggingface.co/xlm-roberta-large-finetuned-conll02-spanish/resolve/main/sentencepiece.bpe.model"
          ),
          "xlm-roberta-large-finetuned-conll03-english": (
              "https://huggingface.co/xlm-roberta-large-finetuned-conll03-english/resolve/main/sentencepiece.bpe.model"
          ),
          "xlm-roberta-large-finetuned-conll03-german": (
              "https://huggingface.co/xlm-roberta-large-finetuned-conll03-german/resolve/main/sentencepiece.bpe.model"
          ),
      },
      "tokenizer_file": {
          "xlm-roberta-base": "https://huggingface.co/xlm-roberta-base/resolve/main/tokenizer.json",
          "xlm-roberta-large": "https://huggingface.co/xlm-roberta-large/resolve/main/tokenizer.json",
          "xlm-roberta-large-finetuned-conll02-dutch": (
              "https://huggingface.co/xlm-roberta-large-finetuned-conll02-dutch/resolve/main/tokenizer.json"
          ),
          "xlm-roberta-large-finetuned-conll02-spanish": (
              "https://huggingface.co/xlm-roberta-large-finetuned-conll02-spanish/resolve/main/tokenizer.json"
          ),
          "xlm-roberta-large-finetuned-conll03-english": (
              "https://huggingface.co/xlm-roberta-large-finetuned-conll03-english/resolve/main/tokenizer.json"
          ),
          "xlm-roberta-large-finetuned-conll03-german": (
              "https://huggingface.co/xlm-roberta-large-finetuned-conll03-german/resolve/main/tokenizer.json"
          ),
      },
  }
  
  snake_case				:	Optional[int]							   =						{
      "xlm-roberta-base": 512,
      "xlm-roberta-large": 512,
      "xlm-roberta-large-finetuned-conll02-dutch": 512,
      "xlm-roberta-large-finetuned-conll02-spanish": 512,
      "xlm-roberta-large-finetuned-conll03-english": 512,
      "xlm-roberta-large-finetuned-conll03-german": 512,
  }
  
  
  
  
  
  class    _snake_case      (  snake_case       ):
  			UpperCamelCase__					   =					VOCAB_FILES_NAMES
  			UpperCamelCase__					   =					PRETRAINED_VOCAB_FILES_MAP
  			UpperCamelCase__					   =					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  			UpperCamelCase__					   =					['input_ids', 'attention_mask']
  			UpperCamelCase__					   =					XLMRobertaTokenizer
  
  
  
  
  
  
  
  			def __init__(       self		,     _a=None		,     _a=None		,     _a="<s>"		,     _a="</s>"		,     _a="</s>"		,     _a="<s>"		,     _a="<unk>"		,     _a="<pad>"		,     _a="<mask>"		,     **_a		,     ):
  				# Mask token behave like a normal word, i.e. include the space before it
  				__magic_name__	:	List[str]			     =  AddedToken(_a		,     lstrip=_a		,     rstrip=_a	) if isinstance(_a		,     _a	) else mask_token
  
  				super().__init__(
  				    _a		,     tokenizer_file=_a		,     bos_token=_a		,     eos_token=_a		,     sep_token=_a		,     cls_token=_a		,     unk_token=_a		,     pad_token=_a		,     mask_token=_a		,     **_a		,     )
  
  				__magic_name__	:	Optional[int]			     =  vocab_file
  				__magic_name__	:	List[str]			     =  False if not self.vocab_file else True
  
  
  
  
  
  
  
  			def     SCREAMING_SNAKE_CASE					(       self		,     _a		,     _a = None	):
  
  				if token_ids_a is None:
  					return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
  				__magic_name__	:	Union[str, Any]			     =  [self.cls_token_id]
  				__magic_name__	:	str			     =  [self.sep_token_id]
  				return cls + token_ids_a + sep + sep + token_ids_a + sep
  
  
  
  
  
  
  
  			def     SCREAMING_SNAKE_CASE					(       self		,     _a		,     _a = None	):
  				__magic_name__	:	List[str]			     =  [self.sep_token_id]
  				__magic_name__	:	List[str]			     =  [self.cls_token_id]
  
  				if token_ids_a is None:
  					return len(cls + token_ids_a + sep	) * [0]
  				return len(cls + token_ids_a + sep + sep + token_ids_a + sep	) * [0]
  
  
  
  
  
  
  
  			def     SCREAMING_SNAKE_CASE					(       self		,     _a		,     _a = None	):
  				if not self.can_save_slow_tokenizer:
  					raise ValueError(
  					    "Your fast tokenizer does not have the necessary information to save the vocabulary for a slow "
  					    "tokenizer."	)
  
  				if not os.path.isdir(_a	):
  					logger.error(f'''Vocabulary path ({save_directory}) should be a directory.'''	)
  					return
  				__magic_name__	:	Any			     =  os.path.join(
  				    _a		,     (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]	)
  
  				if os.path.abspath(self.vocab_file	) != os.path.abspath(_a	):
  					copyfile(self.vocab_file		,     _a	)
  
  				return (out_vocab_file,)
  