

"""simple docstring"""





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


_a       =							logging.get_logger(__name__)

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




class 					_lowerCAmelCase  (	lowercase   ):







 """simple docstring"""







 __UpperCAmelCase	:					Any   		=	"nllb-moe"
 __UpperCAmelCase	:					str   		=	["past_key_values"]
 __UpperCAmelCase	:					Any   		=	{"num_attention_heads": "encoder_attention_heads", "hidden_size": "d_model"}


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









"""simple docstring"""
from __future__ import annotations

__a      =				10
def    A_  (			_lowercase	):







						'''simple docstring'''


						snake_case_ :Union[str, Any]						=			1
						snake_case_ :List[str]						=			max(_lowercase	)
						while placement <= max_digit:
												# declare and initialize empty buckets
												snake_case_ :list[list]						=			[[] for _ in range(_lowercase	)]
												# split list_of_ints between the buckets
												for i in list_of_ints:
																		snake_case_ :Any						=			int((i / placement) % RADIX	)
																		buckets[tmp].append(_lowercase	)
												# put each buckets' contents into list_of_ints
												snake_case_ :Optional[Any]						=			0
												for b in range(_lowercase	):
																		for i in buckets[b]:
																								snake_case_ :Union[str, Any]						=			i
																								a += 1
        # move to next
												placement *= RADIX
						return list_of_ints


if __name__ == "__main__":
						import doctest

						doctest.testmod()
