




'''simple docstring'''



from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


lowerCamelCase_			=						logging.get_logger(__name__)

lowerCamelCase_			=						{
    'andreasmadsen/efficient_mlm_m0.40': (
        'https://huggingface.co/andreasmadsen/efficient_mlm_m0.40/resolve/main/config.json'
    ),
}







class 		lowercase_   (			A       ):


   """simple docstring"""

   lowerCamelCase_      =						'''roberta-prelayernorm'''



   def __init__(   self :     Tuple  ,				__lowerCamelCase :     Optional[int]=5_0_2_6_5  ,				__lowerCamelCase :     int=7_6_8  ,				__lowerCamelCase :     Any=1_2  ,				__lowerCamelCase :     int=1_2  ,				__lowerCamelCase :     Any=3_0_7_2  ,				__lowerCamelCase :     int="gelu"  ,				__lowerCamelCase :     Dict=0.1  ,				__lowerCamelCase :     Any=0.1  ,				__lowerCamelCase :     Optional[int]=5_1_2  ,				__lowerCamelCase :     Union[str, Any]=2  ,				__lowerCamelCase :     Any=0.0_2  ,				__lowerCamelCase :     List[str]=1e-12  ,				__lowerCamelCase :     Optional[Any]=1  ,				__lowerCamelCase :     List[Any]=0  ,				__lowerCamelCase :     List[Any]=2  ,				__lowerCamelCase :     List[str]="absolute"  ,				__lowerCamelCase :     Optional[Any]=True  ,				__lowerCamelCase :     List[Any]=None  ,				**__lowerCamelCase :     str  ,				):

      """simple docstring"""
      super().__init__(pad_token_id=__lowerCamelCase  ,				bos_token_id=__lowerCamelCase  ,				eos_token_id=__lowerCamelCase  ,				**__lowerCamelCase   )

      _SCREAMING_SNAKE_CASE	=				vocab_size
      _SCREAMING_SNAKE_CASE	=				hidden_size
      _SCREAMING_SNAKE_CASE	=				num_hidden_layers
      _SCREAMING_SNAKE_CASE	=				num_attention_heads
      _SCREAMING_SNAKE_CASE	=				hidden_act
      _SCREAMING_SNAKE_CASE	=				intermediate_size
      _SCREAMING_SNAKE_CASE	=				hidden_dropout_prob
      _SCREAMING_SNAKE_CASE	=				attention_probs_dropout_prob
      _SCREAMING_SNAKE_CASE	=				max_position_embeddings
      _SCREAMING_SNAKE_CASE	=				type_vocab_size
      _SCREAMING_SNAKE_CASE	=				initializer_range
      _SCREAMING_SNAKE_CASE	=				layer_norm_eps
      _SCREAMING_SNAKE_CASE	=				position_embedding_type
      _SCREAMING_SNAKE_CASE	=				use_cache
      _SCREAMING_SNAKE_CASE	=				classifier_dropout







class 		lowercase_   (			A       ):


   """simple docstring"""

   @property
   def 							lowerCAmelCase_      (   self :     int   ):

      """simple docstring"""
      if self.task == "multiple-choice":
         _SCREAMING_SNAKE_CASE	=				{0: "batch", 1: "choice", 2: "sequence"}
      else:
         _SCREAMING_SNAKE_CASE	=				{0: "batch", 1: "sequence"}
      return OrderedDict(
          [
              ("input_ids", dynamic_axis),
              ("attention_mask", dynamic_axis),
          ]   )







'''simple docstring'''



from __future__ import annotations
def 			SCREAMING_SNAKE_CASE_			(							__A    :			float	,					__A    :			float	,					__A    :			float	,					)			->			tuple:
   if (electron_conc, hole_conc, intrinsic_conc).count(0  ) != 1:
      raise ValueError("You cannot supply more or less than 2 values"  )
   elif electron_conc < 0:
      raise ValueError("Electron concentration cannot be negative in a semiconductor"  )
   elif hole_conc < 0:
      raise ValueError("Hole concentration cannot be negative in a semiconductor"  )
   elif intrinsic_conc < 0:
      raise ValueError(
          "Intrinsic concentration cannot be negative in a semiconductor"  )
   elif electron_conc == 0:
      return (
          "electron_conc",
          intrinsic_conc**2 / hole_conc,
      )
   elif hole_conc == 0:
      return (
          "hole_conc",
          intrinsic_conc**2 / electron_conc,
      )
   elif intrinsic_conc == 0:
      return (
          "intrinsic_conc",
          (electron_conc * hole_conc) ** 0.5,
      )
   else:
      return (-1, -1)


if __name__ == "__main__":
 import doctest

 doctest.testmod()

