





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


A       :   Any					= logging.get_logger(__name__)

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


class     A     (SCREAMING_SNAKE_CASE       ):
			'''simple docstring'''




			__lowerCamelCase      :			Union[str, Any]							     =       '''nllb-moe'''
			__lowerCamelCase      :			int							     =       ['''past_key_values''']
			__lowerCamelCase      :			str							     =       {'''num_attention_heads''': '''encoder_attention_heads''', '''hidden_size''': '''d_model'''}






			def __init__(     self  :       Optional[int]				,      __lowerCAmelCase  :       List[str]=12_81_12				,      __lowerCAmelCase  :       List[Any]=10_24				,      __lowerCAmelCase  :       List[Any]=12				,      __lowerCAmelCase  :       List[Any]=40_96				,      __lowerCAmelCase  :       str=16				,      __lowerCAmelCase  :       List[str]=12				,      __lowerCAmelCase  :       List[Any]=40_96				,      __lowerCAmelCase  :       Any=16				,      __lowerCAmelCase  :       Optional[Any]=0.0_5				,      __lowerCAmelCase  :       Dict=0.0_5				,      __lowerCAmelCase  :       int=True				,      __lowerCAmelCase  :       Union[str, Any]=True				,      __lowerCAmelCase  :       Any="relu"				,      __lowerCAmelCase  :       Tuple=10_24				,      __lowerCAmelCase  :       Optional[int]=0.1				,      __lowerCAmelCase  :       int=0.1				,      __lowerCAmelCase  :       Union[str, Any]=0.0				,      __lowerCAmelCase  :       List[str]=0.0_2				,      __lowerCAmelCase  :       List[Any]=2				,      __lowerCAmelCase  :       Optional[Any]=True				,      __lowerCAmelCase  :       Tuple=False				,      __lowerCAmelCase  :       Tuple="float32"				,      __lowerCAmelCase  :       Dict=False				,      __lowerCAmelCase  :       List[Any]=1_28				,      __lowerCAmelCase  :       Union[str, Any]=64				,      __lowerCAmelCase  :       Optional[int]=4				,      __lowerCAmelCase  :       int=4				,      __lowerCAmelCase  :       int=0.0_0_1				,      __lowerCAmelCase  :       Dict=0.0_0_1				,      __lowerCAmelCase  :       Optional[Any]="all"				,      __lowerCAmelCase  :       Tuple=False				,      __lowerCAmelCase  :       List[str]=False				,      __lowerCAmelCase  :       Tuple=1.0				,      __lowerCAmelCase  :       Optional[int]=0.2				,      __lowerCAmelCase  :       int=1				,      __lowerCAmelCase  :       Optional[Any]=0				,      __lowerCAmelCase  :       List[str]=2				,      __lowerCAmelCase  :       Optional[int]=False				,      **__lowerCAmelCase  :       List[str]				,      )      ->      Union[str, Any]:







					"""simple docstring"""






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

					A__     =  router_ignore_padding_tokens
					A__     =  batch_prioritized_routing
					A__     =  second_expert_policy
					A__     =  normalize_router_prob_before_dropping
					A__     =  moe_eval_capacity_token_fraction
					A__     =  moe_token_dropout
					A__     =  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				,      )










def   __lowerCamelCase   (				__a  :int       )						->							Dict:






		"""simple docstring"""

		A__     =  len(__a       )
		A__     =  sum(__a       )

		A__     =  [[False for x in range(s + 1       )] for y in range(n + 1       )]

		for i in range(1       ,	n + 1       ):
				A__     =  True

		for i in range(1       ,	s + 1       ):
				A__     =  False

		for i in range(1       ,	n + 1       ):
				for j in range(1       ,	s + 1       ):
						A__     =  dp[i][j - 1]

						if arr[i - 1] <= j:
								A__     =  dp[i][j] or dp[i - 1][j - arr[i - 1]]

		for j in range(int(s / 2       )       ,	-1       ,	-1       ):
				if dp[n][j] is True:
						A__     =  s - 2 * j
						break

		return diff



