
"""simple docstring"""




from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig


A__      :	Dict          =    {
    """albert-base-v1""": """https://huggingface.co/albert-base-v1/resolve/main/config.json""",
    """albert-large-v1""": """https://huggingface.co/albert-large-v1/resolve/main/config.json""",
    """albert-xlarge-v1""": """https://huggingface.co/albert-xlarge-v1/resolve/main/config.json""",
    """albert-xxlarge-v1""": """https://huggingface.co/albert-xxlarge-v1/resolve/main/config.json""",
    """albert-base-v2""": """https://huggingface.co/albert-base-v2/resolve/main/config.json""",
    """albert-large-v2""": """https://huggingface.co/albert-large-v2/resolve/main/config.json""",
    """albert-xlarge-v2""": """https://huggingface.co/albert-xlarge-v2/resolve/main/config.json""",
    """albert-xxlarge-v2""": """https://huggingface.co/albert-xxlarge-v2/resolve/main/config.json""",
}







class   _lowercase						(       lowerCAmelCase_				):


     '''simple docstring'''





     _A								=							'albert'



     def __init__(      self ,			__UpperCamelCase=3_00_00 ,			__UpperCamelCase=1_28 ,			__UpperCamelCase=40_96 ,			__UpperCamelCase=12 ,			__UpperCamelCase=1 ,			__UpperCamelCase=64 ,			__UpperCamelCase=1_63_84 ,			__UpperCamelCase=1 ,			__UpperCamelCase="gelu_new" ,			__UpperCamelCase=0 ,			__UpperCamelCase=0 ,			__UpperCamelCase=5_12 ,			__UpperCamelCase=2 ,			__UpperCamelCase=0.02 ,			__UpperCamelCase=1E-12 ,			__UpperCamelCase=0.1 ,			__UpperCamelCase="absolute" ,			__UpperCamelCase=0 ,			__UpperCamelCase=2 ,			__UpperCamelCase=3 ,			**__UpperCamelCase ,			)->					int:
          super().__init__(pad_token_id=__UpperCamelCase ,			bos_token_id=__UpperCamelCase ,			eos_token_id=__UpperCamelCase ,			**__UpperCamelCase  )

          UpperCAmelCase__							: List[Any] 							=						vocab_size
          UpperCAmelCase__							: Tuple 							=						embedding_size
          UpperCAmelCase__							: Optional[Any] 							=						hidden_size
          UpperCAmelCase__							: int 							=						num_hidden_layers
          UpperCAmelCase__							: Any 							=						num_hidden_groups
          UpperCAmelCase__							: int 							=						num_attention_heads
          UpperCAmelCase__							: str 							=						inner_group_num
          UpperCAmelCase__							: List[Any] 							=						hidden_act
          UpperCAmelCase__							: Optional[Any] 							=						intermediate_size
          UpperCAmelCase__							: Tuple 							=						hidden_dropout_prob
          UpperCAmelCase__							: Dict 							=						attention_probs_dropout_prob
          UpperCAmelCase__							: Optional[int] 							=						max_position_embeddings
          UpperCAmelCase__							: Dict 							=						type_vocab_size
          UpperCAmelCase__							: str 							=						initializer_range
          UpperCAmelCase__							: Dict 							=						layer_norm_eps
          UpperCAmelCase__							: Union[str, Any] 							=						classifier_dropout_prob
          UpperCAmelCase__							: int 							=						position_embedding_type







class   _lowercase						(       lowerCAmelCase_				):


     '''simple docstring'''





     @property
     def  lowerCAmelCase__       (      self  )->					Mapping[str, Mapping[int, str]]:
          if self.task == "multiple-choice":
               UpperCAmelCase__							: int 							=						{0: "batch", 1: "choice", 2: "sequence"}
          else:
               UpperCAmelCase__							: List[str] 							=						{0: "batch", 1: "sequence"}
          return OrderedDict(
              [
                  ("input_ids", dynamic_axis),
                  ("attention_mask", dynamic_axis),
                  ("token_type_ids", dynamic_axis),
              ]  )





"""simple docstring"""




def 							a__ (				lowerCAmelCase	:       list       ,    lowerCAmelCase	:       list		):






     '''simple docstring'''
     _validate_point(lowerCAmelCase		)
     _validate_point(lowerCAmelCase		)
     if len(lowerCAmelCase		) != len(lowerCAmelCase		):
          raise ValueError("Both points must be in the same n-dimensional space"		)

     return float(sum(abs(a - b		) for a, b in zip(lowerCAmelCase       ,    lowerCAmelCase		)		)		)



def 							a__ (				lowerCAmelCase	:       list[float]		):






     '''simple docstring'''
     if point:
          if isinstance(lowerCAmelCase       ,    lowerCAmelCase		):
               for item in point:
                    if not isinstance(lowerCAmelCase       ,    (int, float)		):
                         UpperCAmelCase__							: Tuple 							=						(
                             "Expected a list of numbers as input, found "
                             F"{type(lowerCAmelCase		).__name__}"
                         )
                         raise TypeError(lowerCAmelCase		)
          else:
               UpperCAmelCase__							: Dict 							=						F"Expected a list of numbers as input, found {type(lowerCAmelCase		).__name__}"
               raise TypeError(lowerCAmelCase		)
     else:
          raise ValueError("Missing an input"		)



def 							a__ (				lowerCAmelCase	:       list       ,    lowerCAmelCase	:       list		):






     '''simple docstring'''
     _validate_point(lowerCAmelCase		)
     _validate_point(lowerCAmelCase		)
     if len(lowerCAmelCase		) != len(lowerCAmelCase		):
          raise ValueError("Both points must be in the same n-dimensional space"		)

     return float(sum(abs(x - y		) for x, y in zip(lowerCAmelCase       ,    lowerCAmelCase		)		)		)


if __name__ == "__main__":
    import doctest

    doctest.testmod()



