




from typing import Callable, Optional, Union

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


a_ 		=  logging.get_logger(__name__)

a_ 		=  {
    "microsoft/prophetnet-large-uncased": (
        "https://huggingface.co/microsoft/prophetnet-large-uncased/resolve/main/config.json"
    ),
}

class 			_lowerCamelCase    (      lowerCamelCase_ ):

      """simple docstring"""

      lowerCAmelCase__      :			str     =       "prophetnet"
      lowerCAmelCase__      :			Any     =       ["past_key_values"]
      lowerCAmelCase__      :			Tuple     =       {
          "num_attention_heads": "num_encoder_attention_heads",
      }







      def __init__(  self       :			Tuple			,							snake_case       :			Optional[float] = 0.1			,							snake_case       :			Optional[Union[str, Callable]] = "gelu"			,							snake_case       :			Optional[int] = 30522			,							snake_case       :			Optional[int] = 1024			,							snake_case       :			Optional[int] = 4096			,							snake_case       :			Optional[int] = 12			,							snake_case       :			Optional[int] = 16			,							snake_case       :			Optional[int] = 4096			,							snake_case       :			Optional[int] = 12			,							snake_case       :			Optional[int] = 16			,							snake_case       :			Optional[float] = 0.1			,							snake_case       :			Optional[float] = 0.1			,							snake_case       :			Optional[int] = 512			,							snake_case       :			Optional[float] = 0.02			,							snake_case       :			Optional[bool] = True			,							snake_case       :			Optional[bool] = True			,							snake_case       :			Optional[int] = 0			,							snake_case       :			Optional[int] = 2			,							snake_case       :			Optional[int] = 32			,							snake_case       :			Optional[int] = 128			,							snake_case       :			Optional[bool] = False			,							snake_case       :			Optional[float] = 0.0			,							snake_case       :			Optional[bool] = True			,							snake_case       :			Optional[int] = 0			,							snake_case       :			Optional[int] = 1			,							snake_case       :			Optional[int] = 2			,							**snake_case       :			Dict			,							):
          __UpperCamelCase			=    vocab_size
          __UpperCamelCase			=    hidden_size
          __UpperCamelCase			=    encoder_ffn_dim
          __UpperCamelCase			=    num_encoder_layers
          __UpperCamelCase			=    num_encoder_attention_heads
          __UpperCamelCase			=    decoder_ffn_dim
          __UpperCamelCase			=    num_decoder_layers
          __UpperCamelCase			=    num_decoder_attention_heads
          __UpperCamelCase			=    max_position_embeddings
          __UpperCamelCase			=    init_std  # Normal(0, this parameter)
          __UpperCamelCase			=    activation_function

          # parameters for prophetnet
          __UpperCamelCase			=    ngram
          __UpperCamelCase			=    num_buckets
          __UpperCamelCase			=    relative_max_distance
          __UpperCamelCase			=    disable_ngram_loss
          __UpperCamelCase			=    eps

          # 3 Types of Dropout
          __UpperCamelCase			=    attention_dropout
          __UpperCamelCase			=    activation_dropout
          __UpperCamelCase			=    dropout

          __UpperCamelCase			=    use_cache

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







      @property
      def    snake_case						(  self       :			str					):
          return self.num_encoder_layers + self.num_decoder_layers







      @num_hidden_layers.setter
      def    snake_case						(  self       :			Any			,							snake_case       :			int					):
          raise NotImplementedError(
              '''This model does not support the setting of `num_hidden_layers`. Please set `num_encoder_layers` and'''
              ''' `num_decoder_layers`.'''					)









from __future__ import annotations

_lowerCamelCase							={1: 1}







def      snake_case__							(  lowerCAmelCase_     ):





     """simple docstring"""







     if n in COLLATZ_SEQUENCE_LENGTHS:
          return COLLATZ_SEQUENCE_LENGTHS[n]
     SCREAMING_SNAKE_CASE 		=n // 2 if n % 2 == 0 else 3 * n + 1
     SCREAMING_SNAKE_CASE 		=collatz_sequence_length(lowerCAmelCase_     ) + 1
     SCREAMING_SNAKE_CASE 		=sequence_length
     return sequence_length







def      snake_case__							(  lowerCAmelCase_ = 1000000     ):





     """simple docstring"""







     SCREAMING_SNAKE_CASE 		=max((collatz_sequence_length(lowerCAmelCase_     ), i) for i in range(1,       lowerCAmelCase_     )     )
     return result[1]


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

