




from ...configuration_utils import PretrainedConfig
from ...utils import logging


a_      						=   logging.get_logger(__name__)

a_      						=   {
    "google/pegasus-x-base": "https://huggingface.co/google/pegasus-x-base/resolve/main/config.json",
    "google/pegasus-x-large": "https://huggingface.co/google/pegasus-x-large/resolve/main/config.json",
    # See all PEGASUS-X models at https://huggingface.co/models?filter=pegasus-x
}

class        _lowerCamelCase  (	_SCREAMING_SNAKE_CASE      ):

      """simple docstring"""

      lowerCAmelCase__	:       Dict			=    "pegasus_x"
      lowerCAmelCase__	:       Tuple			=    ["past_key_values"]
      lowerCAmelCase__	:       Any			=    {"num_attention_heads": "encoder_attention_heads", "hidden_size": "d_model"}







      def __init__(   self    :       str       ,				snake_case    :       int=96103       ,				snake_case    :       List[Any]=16384       ,				snake_case    :       Any=16       ,				snake_case    :       int=4096       ,				snake_case    :       List[Any]=16       ,				snake_case    :       List[Any]=16       ,				snake_case    :       List[Any]=4096       ,				snake_case    :       List[str]=16       ,				snake_case    :       List[Any]=0.0       ,				snake_case    :       List[Any]=0.0       ,				snake_case    :       Tuple=True       ,				snake_case    :       List[str]=True       ,				snake_case    :       List[str]="gelu"       ,				snake_case    :       Optional[Any]=1024       ,				snake_case    :       Any=0.1       ,				snake_case    :       int=0.0       ,				snake_case    :       str=0.0       ,				snake_case    :       Optional[int]=0.02       ,				snake_case    :       Optional[Any]=0       ,				snake_case    :       int=True       ,				snake_case    :       Union[str, Any]=0       ,				snake_case    :       List[str]=1       ,				snake_case    :       Tuple=1       ,				snake_case    :       str=32       ,				snake_case    :       Union[str, Any]=512       ,				snake_case    :       List[Any]=True       ,				**snake_case    :       Optional[int]       ,				):
          __UpperCamelCase     						=  vocab_size
          __UpperCamelCase     						=  max_position_embeddings
          __UpperCamelCase     						=  d_model
          __UpperCamelCase     						=  encoder_ffn_dim
          __UpperCamelCase     						=  encoder_layers
          __UpperCamelCase     						=  encoder_attention_heads
          __UpperCamelCase     						=  decoder_ffn_dim
          __UpperCamelCase     						=  decoder_layers
          __UpperCamelCase     						=  decoder_attention_heads
          __UpperCamelCase     						=  dropout
          __UpperCamelCase     						=  attention_dropout
          __UpperCamelCase     						=  activation_dropout
          __UpperCamelCase     						=  activation_function
          __UpperCamelCase     						=  init_std
          __UpperCamelCase     						=  encoder_layerdrop
          __UpperCamelCase     						=  decoder_layerdrop
          __UpperCamelCase     						=  use_cache
          __UpperCamelCase     						=  encoder_layers
          __UpperCamelCase     						=  scale_embedding  # scale factor will be sqrt(d_model) if True

          __UpperCamelCase     						=  num_global_tokens
          __UpperCamelCase     						=  block_size
          __UpperCamelCase     						=  stagger_local_blocks

          super().__init__(
              pad_token_id=snake_case       ,				eos_token_id=snake_case       ,				is_encoder_decoder=snake_case       ,				decoder_start_token_id=snake_case       ,				forced_eos_token_id=snake_case       ,				**snake_case       ,				)







      @property
      def 					snake_case		(   self    :       Optional[int] ):
          return self.encoder_attention_heads







      @property
      def 					snake_case		(   self    :       str ):
          return self.d_model












'''simple docstring'''
from __future__ import annotations

A							:      List[str] 	=       {1: 1}
def 				snake_case_  (   a__		:	int			):



    """simple docstring"""




    if n in COLLATZ_SEQUENCE_LENGTHS:
        return COLLATZ_SEQUENCE_LENGTHS[n]
    __lowercase							=						n // 2 if n % 2 == 0 else 3 * n + 1
    __lowercase							=						collatz_sequence_length(a__			) + 1
    __lowercase							=						sequence_length
    return sequence_length
def 				snake_case_  (   a__		:	int = 1_00_00_00			):



    """simple docstring"""




    __lowercase							=						max((collatz_sequence_length(a__			), i) for i in range(1    ,a__			)			)
    return result[1]


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




