



"""simple docstring"""

from typing import Callable, Optional, Union

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


a_			   =					logging.get_logger(__name__)

a_			   =					{
    '''microsoft/xprophetnet-large-wiki100-cased''': (
        '''https://huggingface.co/microsoft/xprophetnet-large-wiki100-cased/resolve/main/config.json'''
    ),
}







class    __lowercase     (					_UpperCAmelCase):







						"""simple docstring"""







						_A		:							Any							       =		"""xlm-prophetnet"""
						_A		:							Union[str, Any]							       =		["""past_key_values"""]
						_A		:							Optional[int]							       =		{
						    """num_attention_heads""": """num_encoder_attention_heads""",
						}







						def __init__(self   ,		lowercase__ = 0.1   ,		lowercase__ = "gelu"   ,		lowercase__ = 3_05_22   ,		lowercase__ = 10_24   ,		lowercase__ = 40_96   ,		lowercase__ = 12   ,		lowercase__ = 16   ,		lowercase__ = 40_96   ,		lowercase__ = 12   ,		lowercase__ = 16   ,		lowercase__ = 0.1   ,		lowercase__ = 0.1   ,		lowercase__ = 5_12   ,		lowercase__ = 0.02   ,		lowercase__ = True   ,		lowercase__ = True   ,		lowercase__ = 0   ,		lowercase__ = 2   ,		lowercase__ = 32   ,		lowercase__ = 1_28   ,		lowercase__ = False   ,		lowercase__ = 0.0   ,		lowercase__ = True   ,		lowercase__ = 0   ,		lowercase__ = 1   ,		lowercase__ = 2   ,		**lowercase__   ,		):
											snake_case_					:		Dict 					=					vocab_size
											snake_case_					:		Optional[int] 					=					hidden_size
											snake_case_					:		Tuple 					=					encoder_ffn_dim
											snake_case_					:		Optional[Any] 					=					num_encoder_layers
											snake_case_					:		Dict 					=					num_encoder_attention_heads
											snake_case_					:		Dict 					=					decoder_ffn_dim
											snake_case_					:		Union[str, Any] 					=					num_decoder_layers
											snake_case_					:		Tuple 					=					num_decoder_attention_heads
											snake_case_					:		Optional[int] 					=					max_position_embeddings
											snake_case_					:		str 					=					init_std  # Normal(0, this parameter)
											snake_case_					:		Optional[Any] 					=					activation_function

											# parameters for xlmprophetnet
											snake_case_					:		Dict 					=					ngram
											snake_case_					:		List[Any] 					=					num_buckets
											snake_case_					:		Union[str, Any] 					=					relative_max_distance
											snake_case_					:		Optional[int] 					=					disable_ngram_loss
											snake_case_					:		Optional[int] 					=					eps

											# 3 Types of Dropout
											snake_case_					:		Optional[Any] 					=					attention_dropout
											snake_case_					:		Optional[int] 					=					activation_dropout
											snake_case_					:		Any 					=					dropout

											snake_case_					:		Tuple 					=					use_cache

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







						@property
						def 						__UpperCamelCase							(self       ):
											return self.num_encoder_layers + self.num_decoder_layers







						@num_hidden_layers.setter
						def 						__UpperCamelCase							(self   ,		lowercase__       ):
											raise NotImplementedError(
											    """This model does not support the setting of `num_hidden_layers`. Please set `num_encoder_layers` and"""
											    """ `num_decoder_layers`."""       )









"""simple docstring"""

def 							SCREAMING_SNAKE_CASE__      (		SCREAMING_SNAKE_CASE__ :  list			):



					"""simple docstring"""





					snake_case_					:		Optional[int] 					=					len(SCREAMING_SNAKE_CASE__			)
					for i in range(1				,    SCREAMING_SNAKE_CASE__			):
										snake_case_					:		Tuple 					=					collection[i]
										snake_case_					:		Tuple 					=					0
										snake_case_					:		str 					=					i - 1

										while low <= high:
															snake_case_					:		Optional[int] 					=					(low + high) // 2
															if val < collection[mid]:
																				snake_case_					:		List[str] 					=					mid - 1
															else:
																				snake_case_					:		str 					=					mid + 1
										for j in range(SCREAMING_SNAKE_CASE__				,    SCREAMING_SNAKE_CASE__				,    -1			):
															snake_case_					:		List[str] 					=					collection[j - 1]
										snake_case_					:		Any 					=					val
					return collection


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




