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


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

SCREAMING_SNAKE_CASE							:Union[str, Any]										=    {
    'weiweishi/roc-bert-base-zh': 'https://huggingface.co/weiweishi/roc-bert-base-zh/resolve/main/config.json',
}





class 							UpperCAmelCase				(  _lowerCamelCase  ):




 '''simple docstring'''





 snake_case_    =					"roc_bert"






 def __init__(	self :			Union[str, Any]							,A :			str=3_05_22							,A :			int=7_68							,A :			Dict=12							,A :			int=12							,A :			Dict=30_72							,A :			Dict="gelu"							,A :			Optional[Any]=0.1							,A :			int=0.1							,A :			Dict=5_12							,A :			int=2							,A :			Union[str, Any]=0.02							,A :			str=1E-12							,A :			Any=True							,A :			Any=0							,A :			Optional[int]="absolute"							,A :			Dict=None							,A :			Tuple=True							,A :			Tuple=True							,A :			Tuple=7_68							,A :			str=9_10							,A :			Tuple=5_12							,A :			Tuple=2_48_58							,A :			List[str]=True							,**A :			int							,):
     __A             =			vocab_size
     __A             =			max_position_embeddings
     __A             =			hidden_size
     __A             =			num_hidden_layers
     __A             =			num_attention_heads
     __A             =			intermediate_size
     __A             =			hidden_act
     __A             =			hidden_dropout_prob
     __A             =			attention_probs_dropout_prob
     __A             =			initializer_range
     __A             =			type_vocab_size
     __A             =			layer_norm_eps
     __A             =			use_cache
     __A             =			enable_pronunciation
     __A             =			enable_shape
     __A             =			pronunciation_embed_dim
     __A             =			pronunciation_vocab_size
     __A             =			shape_embed_dim
     __A             =			shape_vocab_size
     __A             =			concat_input
     __A             =			position_embedding_type
     __A             =			classifier_dropout
     super().__init__(pad_token_id=A							,**A			)


import warnings

from ...utils import logging
from .image_processing_clip import CLIPImageProcessor


SCREAMING_SNAKE_CASE							:Any										=    logging.get_logger(__name__)





class 							UpperCAmelCase				(  __SCREAMING_SNAKE_CASE  ):




	'''simple docstring'''





	def __init__(	self :			int							,*A :			Dict							,**A :			Dict			):
					warnings.warn(
					    "The class CLIPFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please"
					    " use CLIPImageProcessor instead."							,A							,)
					super().__init__(*A							,**A			)
