






"""simple docstring"""



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


_lowerCAmelCase	:	Dict				=      logging.get_logger(__name__)

_lowerCAmelCase	:	Optional[Any]				=      {
    """facebook/nllb-moe-54B""": """https://huggingface.co/facebook/nllb-moe-54b/resolve/main/config.json""",
}




class 			lowerCAmelCase__			(    __magic_name__   ):
   SCREAMING_SNAKE_CASE_    ='''nllb-moe'''
   SCREAMING_SNAKE_CASE_    =['''past_key_values''']
   SCREAMING_SNAKE_CASE_    ={'''num_attention_heads''': '''encoder_attention_heads''', '''hidden_size''': '''d_model'''}
   def __init__(		self      :	int							,			snake_case__      :	Any=1_2_8_1_1_2							,			snake_case__      :	List[str]=1_0_2_4							,			snake_case__      :	Any=1_2							,			snake_case__      :	Dict=4_0_9_6							,			snake_case__      :	Any=1_6							,			snake_case__      :	str=1_2							,			snake_case__      :	Union[str, Any]=4_0_9_6							,			snake_case__      :	Tuple=1_6							,			snake_case__      :	Union[str, Any]=0.05							,			snake_case__      :	Tuple=0.05							,			snake_case__      :	Any=True							,			snake_case__      :	Tuple=True							,			snake_case__      :	Tuple="relu"							,			snake_case__      :	List[Any]=1_0_2_4							,			snake_case__      :	Union[str, Any]=0.1							,			snake_case__      :	Optional[int]=0.1							,			snake_case__      :	Union[str, Any]=0.0							,			snake_case__      :	int=0.02							,			snake_case__      :	Any=2							,			snake_case__      :	Tuple=True							,			snake_case__      :	Union[str, Any]=False							,			snake_case__      :	Any="float32"							,			snake_case__      :	Dict=False							,			snake_case__      :	List[str]=1_2_8							,			snake_case__      :	Dict=6_4							,			snake_case__      :	List[Any]=4							,			snake_case__      :	Tuple=4							,			snake_case__      :	Any=0.001							,			snake_case__      :	List[Any]=0.001							,			snake_case__      :	int="all"							,			snake_case__      :	int=False							,			snake_case__      :	Optional[Any]=False							,			snake_case__      :	Optional[Any]=1.0							,			snake_case__      :	List[Any]=0.2							,			snake_case__      :	Any=1							,			snake_case__      :	Union[str, Any]=0							,			snake_case__      :	int=2							,			snake_case__      :	List[str]=False							,			**snake_case__      :	str							,			):


        '''simple docstring'''
        UpperCAmelCase__						:    Any							=							vocab_size
        UpperCAmelCase__						:    Optional[Any]							=							max_position_embeddings
        UpperCAmelCase__						:    Any							=							d_model
        UpperCAmelCase__						:    List[Any]							=							encoder_ffn_dim
        UpperCAmelCase__						:    Union[str, Any]							=							encoder_layers
        UpperCAmelCase__						:    Optional[Any]							=							encoder_attention_heads
        UpperCAmelCase__						:    Tuple							=							decoder_ffn_dim
        UpperCAmelCase__						:    Optional[Any]							=							decoder_layers
        UpperCAmelCase__						:    str							=							decoder_attention_heads
        UpperCAmelCase__						:    Dict							=							dropout
        UpperCAmelCase__						:    Optional[int]							=							attention_dropout
        UpperCAmelCase__						:    List[str]							=							activation_dropout
        UpperCAmelCase__						:    Optional[int]							=							activation_function
        UpperCAmelCase__						:    Optional[Any]							=							init_std
        UpperCAmelCase__						:    int							=							encoder_layerdrop
        UpperCAmelCase__						:    int							=							decoder_layerdrop
        UpperCAmelCase__						:    Any							=							use_cache
        UpperCAmelCase__						:    Any							=							encoder_layers
        UpperCAmelCase__						:    Tuple							=							scale_embedding  # scale factor will be sqrt(d_model) if True
        UpperCAmelCase__						:    List[Any]							=							router_z_loss_coef
        UpperCAmelCase__						:    Any							=							router_aux_loss_coef
        UpperCAmelCase__						:    str							=							decoder_sparse_step
        UpperCAmelCase__						:    Tuple							=							encoder_sparse_step
        UpperCAmelCase__						:    Optional[int]							=							num_experts
        UpperCAmelCase__						:    Optional[Any]							=							expert_capacity
        UpperCAmelCase__						:    Dict							=							router_bias
        if router_dtype not in ["float32", "float16", "bfloat16"]:
             raise ValueError(f'`router_dtype` must be one of \'float32\', \'float16\' or \'bfloat16\', got {router_dtype}'							)
        UpperCAmelCase__						:    Dict							=							router_dtype

        UpperCAmelCase__						:    List[str]							=							router_ignore_padding_tokens
        UpperCAmelCase__						:    str							=							batch_prioritized_routing
        UpperCAmelCase__						:    Any							=							second_expert_policy
        UpperCAmelCase__						:    str							=							normalize_router_prob_before_dropping
        UpperCAmelCase__						:    Union[str, Any]							=							moe_eval_capacity_token_fraction
        UpperCAmelCase__						:    Tuple							=							moe_token_dropout
        UpperCAmelCase__						:    List[str]							=							output_router_logits
        super().__init__(
            pad_token_id=snake_case__							,			bos_token_id=snake_case__							,			eos_token_id=snake_case__							,			is_encoder_decoder=snake_case__							,			decoder_start_token_id=snake_case__							,			**snake_case__							,			)










"""simple docstring"""



def 	SCREAMING_SNAKE_CASE__       (  snake_case       : list				)->		list:






     '''simple docstring'''



     UpperCAmelCase__						:    List[str]							=							False
     while is_sorted is False:  # Until all the indices are traversed keep looping
          UpperCAmelCase__						:    List[Any]							=							True
          for i in range(0			,					len(snake_case				) - 1			,					2				):  # iterating over all even indices
               if input_list[i] > input_list[i + 1]:
                    UpperCAmelCase__							,				UpperCAmelCase__						:    Optional[int]							=							input_list[i + 1], input_list[i]
                    # swapping if elements not in order
                    UpperCAmelCase__						:    int							=							False

          for i in range(1			,					len(snake_case				) - 1			,					2				):  # iterating over all odd indices
               if input_list[i] > input_list[i + 1]:
                    UpperCAmelCase__							,				UpperCAmelCase__						:    Optional[int]							=							input_list[i + 1], input_list[i]
                    # swapping if elements not in order
                    UpperCAmelCase__						:    str							=							False
     return input_list


if __name__ == "__main__":
 print("""Enter list to be sorted""")
 _lowerCAmelCase	:	List[str]				=      [int(x) for x in input().split()]
 # inputing elements of the list in one line
 _lowerCAmelCase	:	Optional[int]				=      odd_even_sort(input_list)
 print("""The sorted list is""")
 print(sorted_list)


