


'''simple docstring'''







from __future__ import annotations


def 	SCREAMING_SNAKE_CASE_					(  _UpperCAmelCase	:	list    ,_UpperCAmelCase	:	int    ,_UpperCAmelCase	:	int    ,_UpperCAmelCase	:	int  )  ->			list:
       _a    : Union[str, Any]     					=[]
       _a					,    _a    : Any     					=input_list[low:mid], input_list[mid : high + 1]
       while left and right:
              result.append((left if left[0] <= right[0] else right).pop(0  )  )
       _a    : Any     					=result + left + right
       return input_list


def 	SCREAMING_SNAKE_CASE_					(  _UpperCAmelCase	:	list  )  ->			list:
       if len(_UpperCAmelCase  ) <= 1:
              return input_list
       _a    : Union[str, Any]     					=list(_UpperCAmelCase  )

       # iteration for two-way merging
       _a    : List[Any]     					=2
       while p <= len(_UpperCAmelCase  ):
              # getting low, high and middle value for merge-sort of single list
              for i in range(0    ,len(_UpperCAmelCase  )    ,_UpperCAmelCase  ):
                     _a    : Tuple     					=i
                     _a    : List[Any]     					=i + p - 1
                     _a    : List[str]     					=(low + high + 1) // 2
                     _a    : Dict     					=merge(_UpperCAmelCase    ,_UpperCAmelCase    ,_UpperCAmelCase    ,_UpperCAmelCase  )
              # final merge of last two parts
              if p * 2 >= len(_UpperCAmelCase  ):
                     _a    : str     					=i
                     _a    : Dict     					=merge(_UpperCAmelCase    ,0    ,_UpperCAmelCase    ,len(_UpperCAmelCase  ) - 1  )
                     break
              p *= 2

       return input_list


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






'''simple docstring'''







from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


A__:    List[str]					    =       logging.get_logger(__name__)

A__:    Union[str, Any]					    =       {
    '''facebook/data2vec-text-base''': '''https://huggingface.co/data2vec/resolve/main/config.json''',
}







class A__       (						UpperCAmelCase__      ):
      __UpperCamelCase       :  int	       =							"data2vec-text"






      def __init__( self			:str     ,						SCREAMING_SNAKE_CASE			:Optional[Any]=3_0_5_2_2     ,						SCREAMING_SNAKE_CASE			:Any=7_6_8     ,						SCREAMING_SNAKE_CASE			:List[Any]=1_2     ,						SCREAMING_SNAKE_CASE			:List[str]=1_2     ,						SCREAMING_SNAKE_CASE			:Dict=3_0_7_2     ,						SCREAMING_SNAKE_CASE			:List[str]="gelu"     ,						SCREAMING_SNAKE_CASE			:Any=0.1     ,						SCREAMING_SNAKE_CASE			:List[str]=0.1     ,						SCREAMING_SNAKE_CASE			:int=5_1_2     ,						SCREAMING_SNAKE_CASE			:int=2     ,						SCREAMING_SNAKE_CASE			:Union[str, Any]=0.02     ,						SCREAMING_SNAKE_CASE			:Dict=1e-12     ,						SCREAMING_SNAKE_CASE			:int=1     ,						SCREAMING_SNAKE_CASE			:Dict=0     ,						SCREAMING_SNAKE_CASE			:List[Any]=2     ,						SCREAMING_SNAKE_CASE			:str="absolute"     ,						SCREAMING_SNAKE_CASE			:Tuple=True     ,						SCREAMING_SNAKE_CASE			:Union[str, Any]=None     ,						**SCREAMING_SNAKE_CASE			:Union[str, Any]     ,						)       ->					List[str]:




             '''simple docstring'''
             super().__init__(pad_token_id=SCREAMING_SNAKE_CASE     ,						bos_token_id=SCREAMING_SNAKE_CASE     ,						eos_token_id=SCREAMING_SNAKE_CASE     ,						**SCREAMING_SNAKE_CASE	)

             _a    : Optional[Any]     					=vocab_size
             _a    : Optional[Any]     					=hidden_size
             _a    : Any     					=num_hidden_layers
             _a    : List[str]     					=num_attention_heads
             _a    : Union[str, Any]     					=hidden_act
             _a    : Any     					=intermediate_size
             _a    : str     					=hidden_dropout_prob
             _a    : Optional[Any]     					=attention_probs_dropout_prob
             _a    : Optional[Any]     					=max_position_embeddings
             _a    : Union[str, Any]     					=type_vocab_size
             _a    : Tuple     					=initializer_range
             _a    : Optional[int]     					=layer_norm_eps
             _a    : Tuple     					=position_embedding_type
             _a    : int     					=use_cache
             _a    : List[str]     					=classifier_dropout







class A__       (						UpperCAmelCase__      ):






      @property
      def __UpperCAmelCase       ( self			:int	)       ->					Mapping[str, Mapping[int, str]]:




             '''simple docstring'''
             if self.task == "multiple-choice":
                    _a    : Tuple     					={0: """batch""", 1: """choice""", 2: """sequence"""}
             else:
                    _a    : List[Any]     					={0: """batch""", 1: """sequence"""}
             return OrderedDict(
                 [
                     ("""input_ids""", dynamic_axis),
                     ("""attention_mask""", dynamic_axis),
                 ]	)


