

from collections import OrderedDict
from typing import Mapping

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


A_ :				Union[str, Any]						 =    logging.get_logger(__name__)

A_ :				Optional[Any]						 =    {
    '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 					_a		(__magic_name__       ):


					'''simple docstring'''






					UpperCAmelCase__:     Tuple													= '''xlm-roberta'''






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



class 					_a		(__magic_name__       ):


					'''simple docstring'''






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






def 		UpperCamelCase      (lowercase_:				int					,   lowercase_:				int      )  ->   int:
	while second != 0:
		A__							:					int       =	first & second
		first ^= second
		A__							:					int       =	c << 1
	return first


if __name__ == "__main__":
	import doctest

	doctest.testmod()

	A_ :				Optional[Any]						 =    int(input('Enter the first number: ').strip())
	A_ :				List[str]						 =    int(input('Enter the second number: ').strip())
	print(f'''{add(first, second) = }''')



