


'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging


UpperCAmelCase_			:  Optional[int]										=   logging.get_logger(__name__)

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

class     _lowerCamelCase       (     __lowerCAmelCase					):




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


 def __init__(   self   ,   __lowercase=128_112   ,   __lowercase=1_024   ,   __lowercase=12   ,   __lowercase=4_096   ,   __lowercase=16   ,   __lowercase=12   ,   __lowercase=4_096   ,   __lowercase=16   ,   __lowercase=0.0_5   ,   __lowercase=0.0_5   ,   __lowercase=True   ,   __lowercase=True   ,   __lowercase="relu"   ,   __lowercase=1_024   ,   __lowercase=0.1   ,   __lowercase=0.1   ,   __lowercase=0.0   ,   __lowercase=0.0_2   ,   __lowercase=2   ,   __lowercase=True   ,   __lowercase=False   ,   __lowercase="float32"   ,   __lowercase=False   ,   __lowercase=128   ,   __lowercase=64   ,   __lowercase=4   ,   __lowercase=4   ,   __lowercase=0.0_0_1   ,   __lowercase=0.0_0_1   ,   __lowercase="all"   ,   __lowercase=False   ,   __lowercase=False   ,   __lowercase=1.0   ,   __lowercase=0.2   ,   __lowercase=1   ,   __lowercase=0   ,   __lowercase=2   ,   __lowercase=False   ,   **__lowercase   ,   ):

  """simple docstring"""







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

  __A	:		Any	  =      router_ignore_padding_tokens
  __A	:		Optional[int]	  =      batch_prioritized_routing
  __A	:		Union[str, Any]	  =      second_expert_policy
  __A	:		List[Any]	  =      normalize_router_prob_before_dropping
  __A	:		int	  =      moe_eval_capacity_token_fraction
  __A	:		List[Any]	  =      moe_token_dropout
  __A	:		Tuple	  =      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 .configuration_bert_masked import MaskedBertConfig
from .modeling_bert_masked import (
    MaskedBertForMultipleChoice,
    MaskedBertForQuestionAnswering,
    MaskedBertForSequenceClassification,
    MaskedBertForTokenClassification,
    MaskedBertModel,
)
from .modules import *

