


"""simple docstring"""






from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional, Union

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


if TYPE_CHECKING:
   from ...onnx.config import PatchingSpec
   from ...tokenization_utils_base import PreTrainedTokenizerBase


__snake_case		=       logging.get_logger(__name__)

__snake_case		=       {
    '''allenai/longformer-base-4096''': '''https://huggingface.co/allenai/longformer-base-4096/resolve/main/config.json''',
    '''allenai/longformer-large-4096''': '''https://huggingface.co/allenai/longformer-large-4096/resolve/main/config.json''',
    '''allenai/longformer-large-4096-finetuned-triviaqa''': (
        '''https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/config.json'''
    ),
    '''allenai/longformer-base-4096-extra.pos.embd.only''': (
        '''https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/config.json'''
    ),
    '''allenai/longformer-large-4096-extra.pos.embd.only''': (
        '''https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/config.json'''
    ),
}


class     __lowerCamelCase  (					a__				):

     '''simple docstring'''
     A_       :	Any    =		'longformer'


     def __init__(      self    ,				__UpperCAmelCase = 512    ,				__UpperCAmelCase = 2    ,				__UpperCAmelCase = 1    ,				__UpperCAmelCase = 0    ,				__UpperCAmelCase = 2    ,				__UpperCAmelCase = 30522    ,				__UpperCAmelCase = 768    ,				__UpperCAmelCase = 12    ,				__UpperCAmelCase = 12    ,				__UpperCAmelCase = 3072    ,				__UpperCAmelCase = "gelu"    ,				__UpperCAmelCase = 0.1    ,				__UpperCAmelCase = 0.1    ,				__UpperCAmelCase = 512    ,				__UpperCAmelCase = 2    ,				__UpperCAmelCase = 0.02    ,				__UpperCAmelCase = 1e-1_2    ,				__UpperCAmelCase = False    ,				**__UpperCAmelCase    ,				)       ->							str:
          super().__init__(pad_token_id=__UpperCAmelCase    ,				**__UpperCAmelCase							)

          _a    	=				attention_window
          _a    	=				sep_token_id
          _a    	=				bos_token_id
          _a    	=				eos_token_id
          _a    	=				vocab_size
          _a    	=				hidden_size
          _a    	=				num_hidden_layers
          _a    	=				num_attention_heads
          _a    	=				hidden_act
          _a    	=				intermediate_size
          _a    	=				hidden_dropout_prob
          _a    	=				attention_probs_dropout_prob
          _a    	=				max_position_embeddings
          _a    	=				type_vocab_size
          _a    	=				initializer_range
          _a    	=				layer_norm_eps
          _a    	=				onnx_export







class     __lowerCamelCase  (					a__				):

     '''simple docstring'''


     def __init__(      self    ,				__UpperCAmelCase    ,				__UpperCAmelCase = "default"    ,				__UpperCAmelCase = None							)       ->							Any:
          super().__init__(__UpperCAmelCase    ,				__UpperCAmelCase    ,				__UpperCAmelCase							)
          _a    	=				True


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


     @property
     def 							_UpperCAmelCase      (      self							)       ->							Mapping[str, Mapping[int, str]]:
          _a    	=				super().outputs
          if self.task == "default":
               _a    	=				{0: '''batch'''}
          return outputs


     @property
     def 							_UpperCAmelCase      (      self							)       ->							float:
          return 1e-4


     @property
     def 							_UpperCAmelCase      (      self							)       ->							int:
          # needs to be >= 14 to support tril operator
          return max(super().default_onnx_opset    ,				14							)





     def 							_UpperCAmelCase      (      self    ,				__UpperCAmelCase    ,				__UpperCAmelCase = -1    ,				__UpperCAmelCase = -1    ,				__UpperCAmelCase = False    ,				__UpperCAmelCase = None    ,				)       ->							Mapping[str, Any]:
          _a    	=				super().generate_dummy_inputs(
              preprocessor=__UpperCAmelCase    ,				batch_size=__UpperCAmelCase    ,				seq_length=__UpperCAmelCase    ,				is_pair=__UpperCAmelCase    ,				framework=__UpperCAmelCase							)
          import torch

          # for some reason, replacing this code by inputs["global_attention_mask"] = torch.randint(2, inputs["input_ids"].shape, dtype=torch.int64)
          # makes the export fail randomly
          _a    	=				torch.zeros_like(inputs['''input_ids''']							)
          # make every second token global
          _a    	=				1

          return inputs



"""simple docstring"""






def       A_   (   _lowerCAmelCase     :					int = 10_00       ):






     """simple docstring"""

     _a	,      _a    	=				1, 1
     _a    	=				2
     while True:
          _a    	=				0
          _a    	=				fa + fa
          _a	,      _a    	=				fa, f
          index += 1
          for _ in str(_lowerCAmelCase       ):
               i += 1
          if i == n:
               break
     return index


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