


def   _UpperCAmelCase       (     UpperCAmelCase      :			int      ):
      """simple docstring"""




      __lowerCamelCase     :      Any       						=						[1]

      __lowerCamelCase     :      Optional[Any]       						=						0, 0, 0
      __lowerCamelCase     :      Tuple       						=						ugly_nums[ia] * 2
      __lowerCamelCase     :      Union[str, Any]       						=						ugly_nums[ia] * 3
      __lowerCamelCase     :      Tuple       						=						ugly_nums[ia] * 5

      for _ in range(1						,	UpperCAmelCase      ):
            __lowerCamelCase     :      str       						=						min(UpperCAmelCase						,	UpperCAmelCase						,	UpperCAmelCase      )
            ugly_nums.append(UpperCAmelCase      )
            if next_num == next_a:
                  ia += 1
                  __lowerCamelCase     :      Any       						=						ugly_nums[ia] * 2
            if next_num == next_a:
                  ia += 1
                  __lowerCamelCase     :      List[Any]       						=						ugly_nums[ia] * 3
            if next_num == next_a:
                  ia += 1
                  __lowerCamelCase     :      Optional[int]       						=						ugly_nums[ia] * 5
      return ugly_nums[-1]


if __name__ == "__main__":
    from doctest import testmod

    testmod(verbose=True)
    print(F'''{ugly_numbers(200) = }''')







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


__UpperCamelCase    :						Tuple     =							logging.get_logger(__name__)

__UpperCamelCase    :						Any     =							{
    'facebook/nllb-moe-54B': 'https://huggingface.co/facebook/nllb-moe-54b/resolve/main/config.json',
}



class 							_UpperCamelCase (						A						):

   '''simple docstring'''







   a_				:							int    = "nllb-moe"
   a_				:							Optional[int]    = ["past_key_values"]
   a_				:							Optional[Any]    = {"num_attention_heads": "encoder_attention_heads", "hidden_size": "d_model"}

   def __init__(  self  : int       ,  _lowerCamelCase  : Union[str, Any]=1_2_8_1_1_2       ,  _lowerCamelCase  : List[str]=1_0_2_4       ,  _lowerCamelCase  : Optional[int]=1_2       ,  _lowerCamelCase  : int=4_0_9_6       ,  _lowerCamelCase  : Union[str, Any]=1_6       ,  _lowerCamelCase  : int=1_2       ,  _lowerCamelCase  : Optional[int]=4_0_9_6       ,  _lowerCamelCase  : Any=1_6       ,  _lowerCamelCase  : Any=0.05       ,  _lowerCamelCase  : List[Any]=0.05       ,  _lowerCamelCase  : Tuple=True       ,  _lowerCamelCase  : Any=True       ,  _lowerCamelCase  : Optional[int]="relu"       ,  _lowerCamelCase  : Dict=1_0_2_4       ,  _lowerCamelCase  : Optional[int]=0.1       ,  _lowerCamelCase  : Optional[int]=0.1       ,  _lowerCamelCase  : Optional[int]=0.0       ,  _lowerCamelCase  : List[Any]=0.02       ,  _lowerCamelCase  : List[str]=2       ,  _lowerCamelCase  : List[str]=True       ,  _lowerCamelCase  : Union[str, Any]=False       ,  _lowerCamelCase  : Optional[Any]="float32"       ,  _lowerCamelCase  : Union[str, Any]=False       ,  _lowerCamelCase  : Tuple=1_2_8       ,  _lowerCamelCase  : Dict=6_4       ,  _lowerCamelCase  : Any=4       ,  _lowerCamelCase  : List[Any]=4       ,  _lowerCamelCase  : str=0.001       ,  _lowerCamelCase  : Dict=0.001       ,  _lowerCamelCase  : Any="all"       ,  _lowerCamelCase  : Optional[Any]=False       ,  _lowerCamelCase  : List[Any]=False       ,  _lowerCamelCase  : Optional[Any]=1.0       ,  _lowerCamelCase  : List[str]=0.2       ,  _lowerCamelCase  : List[Any]=1       ,  _lowerCamelCase  : str=0       ,  _lowerCamelCase  : int=2       ,  _lowerCamelCase  : int=False       ,  **_lowerCamelCase  : List[str]       ,  ):






         '''simple docstring'''



         __lowerCamelCase     :      Optional[Any]       						=						vocab_size
         __lowerCamelCase     :      str       						=						max_position_embeddings
         __lowerCamelCase     :      int       						=						d_model
         __lowerCamelCase     :      Optional[Any]       						=						encoder_ffn_dim
         __lowerCamelCase     :      str       						=						encoder_layers
         __lowerCamelCase     :      Tuple       						=						encoder_attention_heads
         __lowerCamelCase     :      Union[str, Any]       						=						decoder_ffn_dim
         __lowerCamelCase     :      Dict       						=						decoder_layers
         __lowerCamelCase     :      Any       						=						decoder_attention_heads
         __lowerCamelCase     :      Union[str, Any]       						=						dropout
         __lowerCamelCase     :      Dict       						=						attention_dropout
         __lowerCamelCase     :      int       						=						activation_dropout
         __lowerCamelCase     :      Union[str, Any]       						=						activation_function
         __lowerCamelCase     :      Optional[int]       						=						init_std
         __lowerCamelCase     :      Union[str, Any]       						=						encoder_layerdrop
         __lowerCamelCase     :      Dict       						=						decoder_layerdrop
         __lowerCamelCase     :      List[str]       						=						use_cache
         __lowerCamelCase     :      Any       						=						encoder_layers
         __lowerCamelCase     :      List[Any]       						=						scale_embedding  # scale factor will be sqrt(d_model) if True
         __lowerCamelCase     :      Optional[Any]       						=						router_z_loss_coef
         __lowerCamelCase     :      Union[str, Any]       						=						router_aux_loss_coef
         __lowerCamelCase     :      Dict       						=						decoder_sparse_step
         __lowerCamelCase     :      Optional[int]       						=						encoder_sparse_step
         __lowerCamelCase     :      Any       						=						num_experts
         __lowerCamelCase     :      int       						=						expert_capacity
         __lowerCamelCase     :      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}"""							)
         __lowerCamelCase     :      Tuple       						=						router_dtype

         __lowerCamelCase     :      Dict       						=						router_ignore_padding_tokens
         __lowerCamelCase     :      str       						=						batch_prioritized_routing
         __lowerCamelCase     :      List[str]       						=						second_expert_policy
         __lowerCamelCase     :      Tuple       						=						normalize_router_prob_before_dropping
         __lowerCamelCase     :      Dict       						=						moe_eval_capacity_token_fraction
         __lowerCamelCase     :      Optional[int]       						=						moe_token_dropout
         __lowerCamelCase     :      Dict       						=						output_router_logits
         super().__init__(
             pad_token_id=_lowerCamelCase       ,  bos_token_id=_lowerCamelCase       ,  eos_token_id=_lowerCamelCase       ,  is_encoder_decoder=_lowerCamelCase       ,  decoder_start_token_id=_lowerCamelCase       ,  **_lowerCamelCase       ,  )



