




"""simple docstring"""


from collections import OrderedDict
from typing import Mapping

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


A_						=				logging.get_logger(__name__)

A_						=				{
    '''distilbert-base-uncased''': '''https://huggingface.co/distilbert-base-uncased/resolve/main/config.json''',
    '''distilbert-base-uncased-distilled-squad''': (
        '''https://huggingface.co/distilbert-base-uncased-distilled-squad/resolve/main/config.json'''
    ),
    '''distilbert-base-cased''': '''https://huggingface.co/distilbert-base-cased/resolve/main/config.json''',
    '''distilbert-base-cased-distilled-squad''': (
        '''https://huggingface.co/distilbert-base-cased-distilled-squad/resolve/main/config.json'''
    ),
    '''distilbert-base-german-cased''': '''https://huggingface.co/distilbert-base-german-cased/resolve/main/config.json''',
    '''distilbert-base-multilingual-cased''': (
        '''https://huggingface.co/distilbert-base-multilingual-cased/resolve/main/config.json'''
    ),
    '''distilbert-base-uncased-finetuned-sst-2-english''': (
        '''https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english/resolve/main/config.json'''
    ),
}






class 					lowercase(     __a ):







 '''simple docstring'''





 lowercase__ 					=					"distilbert"
 lowercase__ 					=					{
     "hidden_size": "dim",
     "num_attention_heads": "n_heads",
     "num_hidden_layers": "n_layers",
 }


 def __init__(				self:		Any,      a_:		List[str]=30_522,      a_:		List[str]=512,      a_:		List[str]=False,      a_:		Any=6,      a_:		Optional[int]=12,      a_:		List[str]=768,      a_:		List[Any]=4 * 768,      a_:		List[str]=0.1,      a_:		Any=0.1,      a_:		Optional[int]="gelu",      a_:		Optional[Any]=0.02,      a_:		int=0.1,      a_:		Optional[int]=0.2,      a_:		Optional[int]=0,      **a_:		Optional[int],      ):




   '''simple docstring'''



   _snake_case							:		int								=  vocab_size
   _snake_case							:		Any								=  max_position_embeddings
   _snake_case							:		Tuple								=  sinusoidal_pos_embds
   _snake_case							:		int								=  n_layers
   _snake_case							:		int								=  n_heads
   _snake_case							:		Tuple								=  dim
   _snake_case							:		Dict								=  hidden_dim
   _snake_case							:		Optional[Any]								=  dropout
   _snake_case							:		Optional[Any]								=  attention_dropout
   _snake_case							:		Optional[int]								=  activation
   _snake_case							:		Dict								=  initializer_range
   _snake_case							:		Optional[Any]								=  qa_dropout
   _snake_case							:		Dict								=  seq_classif_dropout
   super().__init__(**a_,      pad_token_id=a_		)







class 					lowercase(     __a ):







 '''simple docstring'''





 @property
 def  UpperCamelCase_   (				self:		Union[str, Any]		):




   '''simple docstring'''



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







"""simple docstring"""






from __future__ import annotations

_lowercase : Dict      						=						1.6_021E-19  # units = C






def      snake_case__   (		__lowerCamelCase				:    float							,		__lowerCamelCase				:    float							,		__lowerCamelCase				:    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()




