




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


UpperCAmelCase__				     = logging.get_logger(__name__)

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







class a (     __SCREAMING_SNAKE_CASE  ):
						"""simple docstring"""

						UpperCamelCase_	:       List[str]       	=		'nllb-moe'
						UpperCamelCase_	:       Union[str, Any]       	=		['past_key_values']
						UpperCamelCase_	:       Optional[Any]       	=		{'num_attention_heads': 'encoder_attention_heads', 'hidden_size': 'd_model'}






						def __init__( self :     List[str]				,							lowerCamelCase__ :     Tuple=128_112				,							lowerCamelCase__ :     Optional[int]=1_024				,							lowerCamelCase__ :     Any=12				,							lowerCamelCase__ :     List[str]=4_096				,							lowerCamelCase__ :     Optional[int]=16				,							lowerCamelCase__ :     Dict=12				,							lowerCamelCase__ :     Any=4_096				,							lowerCamelCase__ :     Optional[Any]=16				,							lowerCamelCase__ :     List[str]=0.0_5				,							lowerCamelCase__ :     Optional[int]=0.0_5				,							lowerCamelCase__ :     Any=True				,							lowerCamelCase__ :     int=True				,							lowerCamelCase__ :     int="relu"				,							lowerCamelCase__ :     Optional[Any]=1_024				,							lowerCamelCase__ :     Any=0.1				,							lowerCamelCase__ :     Union[str, Any]=0.1				,							lowerCamelCase__ :     int=0.0				,							lowerCamelCase__ :     Dict=0.0_2				,							lowerCamelCase__ :     Tuple=2				,							lowerCamelCase__ :     Optional[Any]=True				,							lowerCamelCase__ :     int=False				,							lowerCamelCase__ :     int="float32"				,							lowerCamelCase__ :     Dict=False				,							lowerCamelCase__ :     Any=128				,							lowerCamelCase__ :     str=64				,							lowerCamelCase__ :     Any=4				,							lowerCamelCase__ :     Any=4				,							lowerCamelCase__ :     Any=0.0_0_1				,							lowerCamelCase__ :     Union[str, Any]=0.0_0_1				,							lowerCamelCase__ :     int="all"				,							lowerCamelCase__ :     Any=False				,							lowerCamelCase__ :     Optional[Any]=False				,							lowerCamelCase__ :     Dict=1.0				,							lowerCamelCase__ :     Tuple=0.2				,							lowerCamelCase__ :     Optional[int]=1				,							lowerCamelCase__ :     Union[str, Any]=0				,							lowerCamelCase__ :     Optional[Any]=2				,							lowerCamelCase__ :     Dict=False				,							**lowerCamelCase__ :     Tuple				,							)    ->						int:
													"""simple docstring"""


													__lowercase      =    vocab_size
													__lowercase      =    max_position_embeddings
													__lowercase      =    d_model
													__lowercase      =    encoder_ffn_dim
													__lowercase      =    encoder_layers
													__lowercase      =    encoder_attention_heads
													__lowercase      =    decoder_ffn_dim
													__lowercase      =    decoder_layers
													__lowercase      =    decoder_attention_heads
													__lowercase      =    dropout
													__lowercase      =    attention_dropout
													__lowercase      =    activation_dropout
													__lowercase      =    activation_function
													__lowercase      =    init_std
													__lowercase      =    encoder_layerdrop
													__lowercase      =    decoder_layerdrop
													__lowercase      =    use_cache
													__lowercase      =    encoder_layers
													__lowercase      =    scale_embedding  # scale factor will be sqrt(d_model) if True
													__lowercase      =    router_z_loss_coef
													__lowercase      =    router_aux_loss_coef
													__lowercase      =    decoder_sparse_step
													__lowercase      =    encoder_sparse_step
													__lowercase      =    num_experts
													__lowercase      =    expert_capacity
													__lowercase      =    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}'				)
													__lowercase      =    router_dtype

													__lowercase      =    router_ignore_padding_tokens
													__lowercase      =    batch_prioritized_routing
													__lowercase      =    second_expert_policy
													__lowercase      =    normalize_router_prob_before_dropping
													__lowercase      =    moe_eval_capacity_token_fraction
													__lowercase      =    moe_token_dropout
													__lowercase      =    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__				,							)












from __future__ import annotations







def 		_A(       UpperCamelCase__							:			list[int]				,       UpperCamelCase__							:			list[int]				,       UpperCamelCase__							:			int				)    -> tuple[float, list[float]]:
							'''simple docstring'''


							__lowercase      =    list(range(len(UpperCamelCase__				)				)				)
							__lowercase      =    [v / w for v, w in zip(UpperCamelCase__				,       UpperCamelCase__				)]
							index.sort(key=lambda UpperCamelCase__				: ratio[i]				,       reverse=UpperCamelCase__				)

							__lowercase      =    0
							__lowercase      =    [0] * len(UpperCamelCase__				)
							for i in index:
														if weight[i] <= capacity:
																					__lowercase      =    1
																					max_value += value[i]
																					capacity -= weight[i]
														else:
																					__lowercase      =    capacity / weight[i]
																					max_value += value[i] * capacity / weight[i]
																					break

							return max_value, fractions


if __name__ == "__main__":
			import doctest

			doctest.testmod()






