





'''simple docstring'''






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


A   : int             =			logging.get_logger(__name__)

A   : int             =			{
    'weiweishi/roc-bert-base-zh': 'https://huggingface.co/weiweishi/roc-bert-base-zh/resolve/main/config.json',
}







class 			lowerCamelCase					(						__UpperCAmelCase  ):
					_SCREAMING_SNAKE_CASE							   =    "roc_bert"


					def __init__(					self	:  Optional[Any]       ,     __snake_case	:  List[Any]=3_05_22       ,     __snake_case	:  Tuple=7_68       ,     __snake_case	:  Dict=12       ,     __snake_case	:  str=12       ,     __snake_case	:  List[Any]=30_72       ,     __snake_case	:  Dict="gelu"       ,     __snake_case	:  List[Any]=0.1       ,     __snake_case	:  int=0.1       ,     __snake_case	:  Optional[int]=5_12       ,     __snake_case	:  str=2       ,     __snake_case	:  int=0.02       ,     __snake_case	:  Any=1e-12       ,     __snake_case	:  List[Any]=True       ,     __snake_case	:  int=0       ,     __snake_case	:  Any="absolute"       ,     __snake_case	:  List[Any]=None       ,     __snake_case	:  Tuple=True       ,     __snake_case	:  Any=True       ,     __snake_case	:  Optional[int]=7_68       ,     __snake_case	:  Optional[Any]=9_10       ,     __snake_case	:  Union[str, Any]=5_12       ,     __snake_case	:  Optional[int]=2_48_58       ,     __snake_case	:  List[Any]=True       ,     **__snake_case	:  Optional[int]       ,     ):





											'''simple docstring'''





											_snake_case:   str  					=		vocab_size
											_snake_case:   Union[str, Any]  					=		max_position_embeddings
											_snake_case:   Optional[Any]  					=		hidden_size
											_snake_case:   Dict  					=		num_hidden_layers
											_snake_case:   int  					=		num_attention_heads
											_snake_case:   Optional[Any]  					=		intermediate_size
											_snake_case:   Union[str, Any]  					=		hidden_act
											_snake_case:   List[str]  					=		hidden_dropout_prob
											_snake_case:   List[str]  					=		attention_probs_dropout_prob
											_snake_case:   Any  					=		initializer_range
											_snake_case:   str  					=		type_vocab_size
											_snake_case:   Tuple  					=		layer_norm_eps
											_snake_case:   List[Any]  					=		use_cache
											_snake_case:   Union[str, Any]  					=		enable_pronunciation
											_snake_case:   int  					=		enable_shape
											_snake_case:   Union[str, Any]  					=		pronunciation_embed_dim
											_snake_case:   Optional[int]  					=		pronunciation_vocab_size
											_snake_case:   str  					=		shape_embed_dim
											_snake_case:   Dict  					=		shape_vocab_size
											_snake_case:   List[str]  					=		concat_input
											_snake_case:   Dict  					=		position_embedding_type
											_snake_case:   str  					=		classifier_dropout
											super().__init__(pad_token_id=__snake_case       ,     **__snake_case       )












'''simple docstring'''






A   : List[str]             =			'\n# Transformers 설치 방법\n! pip install transformers datasets\n# 마지막 릴리스 대신 소스에서 설치하려면, 위 명령을 주석으로 바꾸고 아래 명령을 해제하세요.\n# ! pip install git+https://github.com/huggingface/transformers.git\n'

A   : List[str]             =			[{'type': 'code', 'content': INSTALL_CONTENT}]
A   : Dict             =			{
    '{processor_class}': 'FakeProcessorClass',
    '{model_class}': 'FakeModelClass',
    '{object_class}': 'FakeObjectClass',
}





