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


UpperCAmelCase_			    =							logging.get_logger(__name__)

UpperCAmelCase_			    =							{
    '''uw-madison/mra-base-512-4''': '''https://huggingface.co/uw-madison/mra-base-512-4/resolve/main/config.json''',
}




class  __magic_name__  (		__a    ):





   """simple docstring"""




   lowerCAmelCase      :    List[str]  			=   '''mra'''



   def __init__(	self					:  Tuple		,  _lowercase					:  Any=50_265		,  _lowercase					:  List[Any]=768		,  _lowercase					:  Optional[int]=12		,  _lowercase					:  Any=12		,  _lowercase					:  Any=3_072		,  _lowercase					:  Optional[int]="gelu"		,  _lowercase					:  Any=0.1		,  _lowercase					:  Union[str, Any]=0.1		,  _lowercase					:  Union[str, Any]=512		,  _lowercase					:  List[Any]=1		,  _lowercase					:  int=0.02		,  _lowercase					:  Optional[int]=1E-5		,  _lowercase					:  int="absolute"		,  _lowercase					:  Optional[Any]=4		,  _lowercase					:  Optional[int]="full"		,  _lowercase					:  Dict=0		,  _lowercase					:  Dict=0		,  _lowercase					:  Union[str, Any]=1		,  _lowercase					:  Any=0		,  _lowercase					:  Any=2		,  **_lowercase					:  List[str]		,  ):



    """simple docstring"""



    super().__init__(pad_token_id=_lowercase		,  bos_token_id=_lowercase		,  eos_token_id=_lowercase		,  **_lowercase							)

    _UpperCamelCase:     str							= vocab_size
    _UpperCamelCase:     Tuple							= max_position_embeddings
    _UpperCamelCase:     Optional[int]							= hidden_size
    _UpperCamelCase:     Dict							= num_hidden_layers
    _UpperCamelCase:     Union[str, Any]							= num_attention_heads
    _UpperCamelCase:     List[Any]							= intermediate_size
    _UpperCamelCase:     int							= hidden_act
    _UpperCamelCase:     List[Any]							= hidden_dropout_prob
    _UpperCamelCase:     List[str]							= attention_probs_dropout_prob
    _UpperCamelCase:     Any							= initializer_range
    _UpperCamelCase:     Dict							= type_vocab_size
    _UpperCamelCase:     Optional[Any]							= layer_norm_eps
    _UpperCamelCase:     str							= position_embedding_type
    _UpperCamelCase:     int							= block_per_row
    _UpperCamelCase:     Tuple							= approx_mode
    _UpperCamelCase:     List[Any]							= initial_prior_first_n_blocks
    _UpperCamelCase:     List[str]							= initial_prior_diagonal_n_blocks
from __future__ import annotations

UpperCAmelCase_			    =							1.6_0_2_1E-1_9  # units = C




def       lowerCAmelCase_     (		lowercase:							float  ,					lowercase:							float  ,					lowercase:							float  ,					)    ->				tuple[str, float]:







 '''simple docstring'''
 if (conductivity, electron_conc, mobility).count(0		) != 1:
  raise ValueError('''You cannot supply more or less than 2 values'''		)
 elif conductivity < 0:
  raise ValueError('''Conductivity cannot be negative'''		)
 elif electron_conc < 0:
  raise ValueError('''Electron concentration cannot be negative'''		)
 elif mobility < 0:
  raise ValueError('''mobility cannot be negative'''		)
 elif conductivity == 0:
  return (
      "conductivity",
      mobility * electron_conc * ELECTRON_CHARGE,
  )
 elif electron_conc == 0:
  return (
      "electron_conc",
      conductivity / (mobility * ELECTRON_CHARGE),
  )
 else:
  return (
      "mobility",
      conductivity / (electron_conc * ELECTRON_CHARGE),
  )


if __name__ == "__main__":
  import doctest

  doctest.testmod()