




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


_lowerCamelCase     :		List[Any]								=	logging.get_logger(__name__)

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


class     UpperCamelCase_   (			SCREAMING_SNAKE_CASE__					):

    '''simple docstring'''






    UpperCAmelCase__							  =				'''roc_bert'''


    def __init__(      self				:     Any ,			UpperCAmelCase__				:     List[str]=30_522 ,			UpperCAmelCase__				:     int=768 ,			UpperCAmelCase__				:     List[str]=12 ,			UpperCAmelCase__				:     int=12 ,			UpperCAmelCase__				:     List[Any]=3_072 ,			UpperCAmelCase__				:     List[str]="gelu" ,			UpperCAmelCase__				:     List[Any]=0.1 ,			UpperCAmelCase__				:     int=0.1 ,			UpperCAmelCase__				:     Optional[Any]=512 ,			UpperCAmelCase__				:     int=2 ,			UpperCAmelCase__				:     Any=0.02 ,			UpperCAmelCase__				:     Union[str, Any]=1e-12 ,			UpperCAmelCase__				:     str=True ,			UpperCAmelCase__				:     int=0 ,			UpperCAmelCase__				:     List[Any]="absolute" ,			UpperCAmelCase__				:     List[str]=None ,			UpperCAmelCase__				:     Tuple=True ,			UpperCAmelCase__				:     Dict=True ,			UpperCAmelCase__				:     Dict=768 ,			UpperCAmelCase__				:     List[str]=910 ,			UpperCAmelCase__				:     Any=512 ,			UpperCAmelCase__				:     Optional[int]=24_858 ,			UpperCAmelCase__				:     Any=True ,			**UpperCAmelCase__				:     Tuple ,			)						->int:





           '''simple docstring'''

           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=UpperCAmelCase__ ,			**UpperCAmelCase__)








_lowerCamelCase     :		dict[str, float]								=       {
    "km/h": 1.0,
    "m/s": 3.6,
    "mph": 1.609_344,
    "knot": 1.852,
}

_lowerCamelCase     :		dict[str, float]								=       {
    "km/h": 1.0,
    "m/s": 0.277_777_778,
    "mph": 0.621_371_192,
    "knot": 0.539_956_803,
}







def SCREAMING_SNAKE_CASE    (	lowercase_			,    lowercase_			,    lowercase_						)       ->	float:



       """simple docstring"""

       if unit_to not in speed_chart or unit_from not in speed_chart_inverse:
              A__							=   (
                  f"""Incorrect 'from_type' or 'to_type' value: {unit_from!r}, {unit_to!r}\n"""
                  f"""Valid values are: {", ".join(lowercase_						)}"""
              )
              raise ValueError(lowercase_						)
       return round(speed * speed_chart[unit_from] * speed_chart_inverse[unit_to]			,    3						)


if __name__ == "__main__":
  import doctest

  doctest.testmod()


