


'''simple docstring'''




from math import log

from scipy.constants import Boltzmann, physical_constants

_lowerCAmelCase  :		List[str]		     =	300  # TEMPERATURE (unit = K)

def 			__UpperCamelCase    (    _A    :				float					,   _A    :				float					,   _A    :				float					,   )    ->      float:




	"""simple docstring"""





	if donor_conc <= 0:
		raise ValueError('Donor concentration should be positive'				)
	elif acceptor_conc <= 0:
		raise ValueError('Acceptor concentration should be positive'				)
	elif intrinsic_conc <= 0:
		raise ValueError('Intrinsic concentration should be positive'				)
	elif donor_conc <= intrinsic_conc:
		raise ValueError(
		    'Donor concentration should be greater than intrinsic concentration'				)
	elif acceptor_conc <= intrinsic_conc:
		raise ValueError(
		    'Acceptor concentration should be greater than intrinsic concentration'				)
	else:
		return (
		    Boltzmann
		    * T
		    * log((donor_conc * acceptor_conc) / intrinsic_conc**2				)
		    / physical_constants["electron volt"][0]
		)


if __name__ == "__main__":
				import doctest

				doctest.testmod()




'''simple docstring'''




from collections import OrderedDict
from typing import Mapping

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


_lowerCAmelCase  :		Any		     =	logging.get_logger(__name__)

_lowerCAmelCase  :		List[str]		     =	{
    'xlm-roberta-base': 'https://huggingface.co/xlm-roberta-base/resolve/main/config.json',
    'xlm-roberta-large': 'https://huggingface.co/xlm-roberta-large/resolve/main/config.json',
    'xlm-roberta-large-finetuned-conll02-dutch': (
        'https://huggingface.co/xlm-roberta-large-finetuned-conll02-dutch/resolve/main/config.json'
    ),
    'xlm-roberta-large-finetuned-conll02-spanish': (
        'https://huggingface.co/xlm-roberta-large-finetuned-conll02-spanish/resolve/main/config.json'
    ),
    'xlm-roberta-large-finetuned-conll03-english': (
        'https://huggingface.co/xlm-roberta-large-finetuned-conll03-english/resolve/main/config.json'
    ),
    'xlm-roberta-large-finetuned-conll03-german': (
        'https://huggingface.co/xlm-roberta-large-finetuned-conll03-german/resolve/main/config.json'
    ),
}



class  lowerCAmelCase				(				a							):
	_lowerCamelCase   :					List[str]			      = """xlm-roberta"""



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

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



class  lowerCAmelCase				(				a							):



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