
from collections import OrderedDict
from typing import Mapping

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


_lowercase											=    logging.get_logger(__name__)

_lowercase											=    {
    """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 			lowercase_		(      A       ):
       __lowerCamelCase				       =						"xlm-roberta"


       def __init__(    self						,       __A=30_522						,       __A=768						,       __A=12						,       __A=12						,       __A=3_072						,       __A="gelu"						,       __A=0.1						,       __A=0.1						,       __A=512						,       __A=2						,       __A=0.02						,       __A=1e-1_2						,       __A=1						,       __A=0						,       __A=2						,       __A="absolute"						,       __A=True						,       __A=None						,       **__A						,       )						->    Any:
              super().__init__(pad_token_id=__A						,       bos_token_id=__A						,       eos_token_id=__A						,       **__A				)

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






class 			lowercase_		(      A       ):


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


def 							SCREAMING_SNAKE_CASE_	(					UpperCAmelCase_	:     int = 1_0_0_0				)			->						int:
       SCREAMING_SNAKE_CASE_							:				int		=2**power
       SCREAMING_SNAKE_CASE_							:				Tuple		=0
       while n:
              SCREAMING_SNAKE_CASE_	,     SCREAMING_SNAKE_CASE_							:				Union[str, Any]		=r + n % 1_0, n // 1_0
       return r


if __name__ == "__main__":
 print(solution(int(str(input()).strip())))
