


'''simple docstring'''



def     UpperCAmelCase__      (			UpperCAmelCase_					:       Dict							)  ->	list:
     __lowerCamelCase     :			str              =	1.3
     __lowerCamelCase     :			int              =	len(UpperCAmelCase_							)
     __lowerCamelCase     :			Tuple              =	False

     while not completed:
          # Update the gap value for a next comb
          __lowerCamelCase     :			int              =	int(gap / shrink_factor							)
          if gap <= 1:
               __lowerCamelCase     :			Tuple              =	True

          __lowerCamelCase     :			List[Any]              =	0
          while index + gap < len(UpperCAmelCase_							):
               if data[index] > data[index + gap]:
                    # Swap values
                    __lowerCamelCase       , __lowerCamelCase     :			List[str]              =	data[index + gap], data[index]
                    __lowerCamelCase     :			Any              =	False
               index += 1

     return data


if __name__ == "__main__":
      import doctest

      doctest.testmod()

      A__	:      Dict				=						input("""Enter numbers separated by a comma:\n""").strip()
      A__	:      Optional[Any]				=						[int(item) for item in user_input.split(""",""")]
      print(comb_sort(unsorted))





'''simple docstring'''



from typing import Callable, Optional, Union

from ...configuration_utils import PretrainedConfig
from ...utils import logging


A__	:      Any				=						logging.get_logger(__name__)

A__	:      str				=						{
    """microsoft/prophetnet-large-uncased""": (
        """https://huggingface.co/microsoft/prophetnet-large-uncased/resolve/main/config.json"""
    ),
}





class      UpperCAmelCase_						(_UpperCAmelCase						):





    """simple docstring"""






    lowerCamelCase						:      Dict							  =    'prophetnet'
    lowerCamelCase						:      List[str]							  =    ['past_key_values']
    lowerCamelCase						:      List[str]							  =    {
        'num_attention_heads': 'num_encoder_attention_heads',
    }







    def __init__(							self    ,  SCREAMING_SNAKE_CASE_ = 0.1    ,  SCREAMING_SNAKE_CASE_ = "gelu"    ,  SCREAMING_SNAKE_CASE_ = 3_05_22    ,  SCREAMING_SNAKE_CASE_ = 10_24    ,  SCREAMING_SNAKE_CASE_ = 40_96    ,  SCREAMING_SNAKE_CASE_ = 12    ,  SCREAMING_SNAKE_CASE_ = 16    ,  SCREAMING_SNAKE_CASE_ = 40_96    ,  SCREAMING_SNAKE_CASE_ = 12    ,  SCREAMING_SNAKE_CASE_ = 16    ,  SCREAMING_SNAKE_CASE_ = 0.1    ,  SCREAMING_SNAKE_CASE_ = 0.1    ,  SCREAMING_SNAKE_CASE_ = 5_12    ,  SCREAMING_SNAKE_CASE_ = 0.0_2    ,  SCREAMING_SNAKE_CASE_ = True    ,  SCREAMING_SNAKE_CASE_ = True    ,  SCREAMING_SNAKE_CASE_ = 0    ,  SCREAMING_SNAKE_CASE_ = 2    ,  SCREAMING_SNAKE_CASE_ = 32    ,  SCREAMING_SNAKE_CASE_ = 1_28    ,  SCREAMING_SNAKE_CASE_ = False    ,  SCREAMING_SNAKE_CASE_ = 0.0    ,  SCREAMING_SNAKE_CASE_ = True    ,  SCREAMING_SNAKE_CASE_ = 0    ,  SCREAMING_SNAKE_CASE_ = 1    ,  SCREAMING_SNAKE_CASE_ = 2    ,  **SCREAMING_SNAKE_CASE_    ,  )       ->  List[Any]:
         __lowerCamelCase     :			List[Any]              =	vocab_size
         __lowerCamelCase     :			Union[str, Any]              =	hidden_size
         __lowerCamelCase     :			Tuple              =	encoder_ffn_dim
         __lowerCamelCase     :			Any              =	num_encoder_layers
         __lowerCamelCase     :			int              =	num_encoder_attention_heads
         __lowerCamelCase     :			Optional[Any]              =	decoder_ffn_dim
         __lowerCamelCase     :			str              =	num_decoder_layers
         __lowerCamelCase     :			int              =	num_decoder_attention_heads
         __lowerCamelCase     :			Union[str, Any]              =	max_position_embeddings
         __lowerCamelCase     :			Optional[Any]              =	init_std  # Normal(0, this parameter)
         __lowerCamelCase     :			Union[str, Any]              =	activation_function

         # parameters for prophetnet
         __lowerCamelCase     :			int              =	ngram
         __lowerCamelCase     :			Optional[int]              =	num_buckets
         __lowerCamelCase     :			str              =	relative_max_distance
         __lowerCamelCase     :			Optional[Any]              =	disable_ngram_loss
         __lowerCamelCase     :			str              =	eps

         # 3 Types of Dropout
         __lowerCamelCase     :			Optional[Any]              =	attention_dropout
         __lowerCamelCase     :			str              =	activation_dropout
         __lowerCamelCase     :			Optional[Any]              =	dropout

         __lowerCamelCase     :			Optional[Any]              =	use_cache

         super().__init__(
             pad_token_id=SCREAMING_SNAKE_CASE_    ,  bos_token_id=SCREAMING_SNAKE_CASE_    ,  eos_token_id=SCREAMING_SNAKE_CASE_    ,  is_encoder_decoder=SCREAMING_SNAKE_CASE_    ,  add_cross_attention=SCREAMING_SNAKE_CASE_    ,  decoder_start_token_id=SCREAMING_SNAKE_CASE_    ,  **SCREAMING_SNAKE_CASE_    ,  )







    @property
    def    lowercase_       (							self			)       ->  int:
         return self.num_encoder_layers + self.num_decoder_layers







    @num_hidden_layers.setter
    def    lowercase_       (							self    ,  SCREAMING_SNAKE_CASE_			)       ->  Union[str, Any]:
         raise NotImplementedError(
             'This model does not support the setting of `num_hidden_layers`. Please set `num_encoder_layers` and'
             ' `num_decoder_layers`.'			)






