

from collections import OrderedDict
from typing import Mapping

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


A_	:			Tuple  	=      logging.get_logger(__name__)

A_	:			Any  	=      {
    'camembert-base': 'https://huggingface.co/camembert-base/resolve/main/config.json',
    'umberto-commoncrawl-cased-v1': (
        'https://huggingface.co/Musixmatch/umberto-commoncrawl-cased-v1/resolve/main/config.json'
    ),
    'umberto-wikipedia-uncased-v1': (
        'https://huggingface.co/Musixmatch/umberto-wikipedia-uncased-v1/resolve/main/config.json'
    ),
}



class    _a						(__magic_name__    ):


					'''simple docstring'''






					UpperCAmelCase__:       List[Any]  							=	'''camembert'''






					def __init__(			self   ,	A__=3_0522   ,	A__=768   ,	A__=12   ,	A__=12   ,	A__=3072   ,	A__="gelu"   ,	A__=0.1   ,	A__=0.1   ,	A__=512   ,	A__=2   ,	A__=0.0_2   ,	A__=1e-12   ,	A__=1   ,	A__=0   ,	A__=2   ,	A__="absolute"   ,	A__=True   ,	A__=None   ,	**A__   ,	):
						super().__init__(pad_token_id=A__   ,	bos_token_id=A__   ,	eos_token_id=A__   ,	**A__      )

						A__							:   str					       =		vocab_size
						A__							:   List[Any]					       =		hidden_size
						A__							:   str					       =		num_hidden_layers
						A__							:   Optional[Any]					       =		num_attention_heads
						A__							:   List[Any]					       =		hidden_act
						A__							:   int					       =		intermediate_size
						A__							:   Tuple					       =		hidden_dropout_prob
						A__							:   List[str]					       =		attention_probs_dropout_prob
						A__							:   Tuple					       =		max_position_embeddings
						A__							:   Optional[int]					       =		type_vocab_size
						A__							:   Any					       =		initializer_range
						A__							:   Optional[int]					       =		layer_norm_eps
						A__							:   Optional[int]					       =		position_embedding_type
						A__							:   List[Any]					       =		use_cache
						A__							:   List[Any]					       =		classifier_dropout



class    _a						(__magic_name__    ):


					'''simple docstring'''






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






from __future__ import annotations

def 						UpperCamelCase (lowercase_:			float   ,				lowercase_:			float   ,				lowercase_:			float )					->				dict[str, float]:
	if (voltage, current, resistance).count(0 ) != 1:
		raise ValueError("""One and only one argument must be 0""" )
	if resistance < 0:
		raise ValueError("""Resistance cannot be negative""" )
	if voltage == 0:
		return {"voltage": float(current * resistance )}
	elif current == 0:
		return {"current": voltage / resistance}
	elif resistance == 0:
		return {"resistance": voltage / current}
	else:
		raise ValueError("""Exactly one argument must be 0""" )


if __name__ == "__main__":
	import doctest

	doctest.testmod()



