



'''simple docstring'''




from collections import OrderedDict
from typing import Mapping

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


UpperCamelCase__       :	Dict    = logging.get_logger(__name__)

UpperCamelCase__       :	List[Any]    = {
    '''roberta-base''': '''https://huggingface.co/roberta-base/resolve/main/config.json''',
    '''roberta-large''': '''https://huggingface.co/roberta-large/resolve/main/config.json''',
    '''roberta-large-mnli''': '''https://huggingface.co/roberta-large-mnli/resolve/main/config.json''',
    '''distilroberta-base''': '''https://huggingface.co/distilroberta-base/resolve/main/config.json''',
    '''roberta-base-openai-detector''': '''https://huggingface.co/roberta-base-openai-detector/resolve/main/config.json''',
    '''roberta-large-openai-detector''': '''https://huggingface.co/roberta-large-openai-detector/resolve/main/config.json''',
}






class 						_UpperCamelCase  (							lowerCamelCase__    ):


			'''simple docstring'''

			_A      :		Tuple			    =		'''roberta'''

			def __init__(							self     : Dict							,     lowerCAmelCase__     : Optional[int]=5_0_2_6_5							,     lowerCAmelCase__     : Any=7_6_8							,     lowerCAmelCase__     : Any=1_2							,     lowerCAmelCase__     : int=1_2							,     lowerCAmelCase__     : List[Any]=3_0_7_2							,     lowerCAmelCase__     : Any="gelu"							,     lowerCAmelCase__     : Tuple=0.1							,     lowerCAmelCase__     : List[str]=0.1							,     lowerCAmelCase__     : List[Any]=5_1_2							,     lowerCAmelCase__     : Tuple=2							,     lowerCAmelCase__     : str=0.02							,     lowerCAmelCase__     : List[str]=1E-12							,     lowerCAmelCase__     : Union[str, Any]=1							,     lowerCAmelCase__     : Dict=0							,     lowerCAmelCase__     : Optional[Any]=2							,     lowerCAmelCase__     : int="absolute"							,     lowerCAmelCase__     : str=True							,     lowerCAmelCase__     : Optional[int]=None							,     **lowerCAmelCase__     : Tuple							,     ):





					"""simple docstring"""






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

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






class 						_UpperCamelCase  (							lowerCamelCase__    ):


			'''simple docstring'''

			@property
			def UpperCamelCase__					(							self     : Any						):





					"""simple docstring"""






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




'''simple docstring'''




from __future__ import annotations


def 				lowerCAmelCase_   (	_lowerCamelCase:   list[int]       ,      _lowerCamelCase:   list[int]       ,      _lowerCamelCase:   int					):
		__SCREAMING_SNAKE_CASE       :		List[Any]           =		list(range(len(_lowerCamelCase					)					)					)
		__SCREAMING_SNAKE_CASE       :		Optional[Any]           =		[v / w for v, w in zip(_lowerCamelCase       ,      _lowerCamelCase					)]
		index.sort(key=lambda _lowerCamelCase					: ratio[i]       ,      reverse=_lowerCamelCase					)

		__SCREAMING_SNAKE_CASE       :		float           =		0
		__SCREAMING_SNAKE_CASE       :		list[float]           =		[0] * len(_lowerCamelCase					)
		for i in index:
				if weight[i] <= capacity:
						__SCREAMING_SNAKE_CASE       :		str           =		1
						max_value += value[i]
						capacity -= weight[i]
				else:
						__SCREAMING_SNAKE_CASE       :		int           =		capacity / weight[i]
						max_value += value[i] * capacity / weight[i]
						break

		return max_value, fractions


if __name__ == "__main__":
						import doctest

						doctest.testmod()