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


lowercase__          =logging.get_logger(__name__)

lowercase__          ={
    'abeja/gpt-neox-japanese-2.7b': 'https://huggingface.co/abeja/gpt-neox-japanese-2.7b/resolve/main/config.json',
}



class 		UpperCamelCase__  (	lowerCamelCase__   ):
			_SCREAMING_SNAKE_CASE				:							str     	=				"gpt_neox_japanese"
			def __init__(self			: str ,    snake_case_			: Tuple=3_2_0_0_0 ,    snake_case_			: Tuple=2_5_6_0 ,    snake_case_			: Union[str, Any]=3_2 ,    snake_case_			: str=3_2 ,    snake_case_			: int=4 ,    snake_case_			: str="gelu" ,    snake_case_			: Any=1.00 ,    snake_case_			: Dict=1_0_0_0_0 ,    snake_case_			: List[Any]=2_0_4_8 ,    snake_case_			: Union[str, Any]=0.02 ,    snake_case_			: Any=1E-5 ,    snake_case_			: Optional[int]=True ,    snake_case_			: str=3_1_9_9_6 ,    snake_case_			: Union[str, Any]=3_1_9_9_9 ,    snake_case_			: List[Any]=0.1 ,    snake_case_			: List[str]=0.0 ,    **snake_case_			: Any ,    ):
				super().__init__(bos_token_id=__lowerCamelCase ,    eos_token_id=__lowerCamelCase ,    **__lowerCamelCase       )
				__a			:  Dict		    =  vocab_size
				__a			:  List[Any]		    =  max_position_embeddings
				__a			:  List[Any]		    =  hidden_size
				__a			:  List[str]		    =  num_hidden_layers
				__a			:  List[Any]		    =  num_attention_heads
				__a			:  Optional[int]		    =  intermediate_multiple_size
				__a			:  int		    =  hidden_act
				__a			:  int		    =  rotary_pct
				__a			:  List[Any]		    =  rotary_emb_base
				__a			:  Optional[int]		    =  initializer_range
				__a			:  Dict		    =  layer_norm_eps
				__a			:  Optional[Any]		    =  use_cache
				__a			:  Dict		    =  attention_dropout
				__a			:  List[str]		    =  hidden_dropout


from transformers import BertTokenizerFast

from .custom_tokenization import CustomTokenizer



class 		UpperCamelCase__  (	__lowercase   ):
   _SCREAMING_SNAKE_CASE				:							Union[str, Any]     	=				CustomTokenizer
   pass
