





import warnings

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


UpperCAmelCase_      							=     logging.get_logger(__name__)

UpperCAmelCase_      							=     {
    """RUCAIBox/mvp""": """https://huggingface.co/RUCAIBox/mvp/resolve/main/config.json""",
}
class 			UpperCamelCase_		(  _lowerCamelCase					):
					lowerCAmelCase_							=	'''mvp'''
					lowerCAmelCase_							=	['''past_key_values''']
					lowerCAmelCase_							=	{'''num_attention_heads''': '''encoder_attention_heads''', '''hidden_size''': '''d_model'''}




					def __init__(		self				,						lowerCAmelCase_=5_0267				,						lowerCAmelCase_=1024				,						lowerCAmelCase_=12				,						lowerCAmelCase_=4096				,						lowerCAmelCase_=16				,						lowerCAmelCase_=12				,						lowerCAmelCase_=4096				,						lowerCAmelCase_=16				,						lowerCAmelCase_=0.0				,						lowerCAmelCase_=0.0				,						lowerCAmelCase_="gelu"				,						lowerCAmelCase_=1024				,						lowerCAmelCase_=0.1				,						lowerCAmelCase_=0.0				,						lowerCAmelCase_=0.0				,						lowerCAmelCase_=0.02				,						lowerCAmelCase_=0.0				,						lowerCAmelCase_=False				,						lowerCAmelCase_=True				,						lowerCAmelCase_=1				,						lowerCAmelCase_=0				,						lowerCAmelCase_=2				,						lowerCAmelCase_=True				,						lowerCAmelCase_=2				,						lowerCAmelCase_=2				,						lowerCAmelCase_=False				,						lowerCAmelCase_=100				,						lowerCAmelCase_=800				,						**lowerCAmelCase_				,						)		->							int:
										_snake_case									=				vocab_size
										_snake_case									=				max_position_embeddings
										_snake_case									=				d_model
										_snake_case									=				encoder_ffn_dim
										_snake_case									=				encoder_layers
										_snake_case									=				encoder_attention_heads
										_snake_case									=				decoder_ffn_dim
										_snake_case									=				decoder_layers
										_snake_case									=				decoder_attention_heads
										_snake_case									=				dropout
										_snake_case									=				attention_dropout
										_snake_case									=				activation_dropout
										_snake_case									=				activation_function
										_snake_case									=				init_std
										_snake_case									=				encoder_layerdrop
										_snake_case									=				decoder_layerdrop
										_snake_case									=				classifier_dropout
										_snake_case									=				use_cache
										_snake_case									=				encoder_layers
										_snake_case									=				scale_embedding  # scale factor will be sqrt(d_model) if True
										_snake_case									=				use_prompt
										_snake_case									=				prompt_length
										_snake_case									=				prompt_mid_dim

										super().__init__(
										    pad_token_id=lowerCAmelCase_				,						bos_token_id=lowerCAmelCase_				,						eos_token_id=lowerCAmelCase_				,						is_encoder_decoder=lowerCAmelCase_				,						decoder_start_token_id=lowerCAmelCase_				,						forced_eos_token_id=lowerCAmelCase_				,						**lowerCAmelCase_				,						)

										if self.forced_bos_token_id is None and kwargs.get('force_bos_token_to_be_generated'				,						lowerCAmelCase_  ):
															_snake_case									=				self.bos_token_id
															warnings.warn(
															    F'''Please make sure the config includes `forced_bos_token_id={self.bos_token_id}` in future versions. '''
															    'The config can simply be saved and uploaded again to be fixed.'  )










def 						lowerCamelCase__     (     UpperCamelCase__			:       list						)			-> list:



					'''simple docstring'''




					_snake_case									=				len(UpperCamelCase__						)
					for i in range(1       ,    UpperCamelCase__						):
										_snake_case									=				collection[i]
										_snake_case									=				0
										_snake_case									=				i - 1

										while low <= high:
															_snake_case									=				(low + high) // 2
															if val < collection[mid]:
																				_snake_case									=				mid - 1
															else:
																				_snake_case									=				mid + 1
										for j in range(UpperCamelCase__       ,    UpperCamelCase__       ,    -1						):
															_snake_case									=				collection[j - 1]
										_snake_case									=				val
					return collection


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



