



"""simple docstring"""






import functools
import operator

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


lowerCAmelCase__              =							logging.get_logger(__name__)

lowerCAmelCase__              =							{
    '''asapp/sew-tiny-100k''': '''https://huggingface.co/asapp/sew-tiny-100k/resolve/main/config.json''',
    # See all SEW models at https://huggingface.co/models?filter=sew
}






class 			__snake_case			(      _a):
  snake_case__							:  Optional[Any]         =		"""sew"""




  def __init__(					self	:		Dict		,   __lowerCAmelCase	:		Union[str, Any]=3_2		,   __lowerCAmelCase	:		Union[str, Any]=7_6_8		,   __lowerCAmelCase	:		List[Any]=1_2		,   __lowerCAmelCase	:		List[Any]=1_2		,   __lowerCAmelCase	:		Union[str, Any]=3_0_7_2		,   __lowerCAmelCase	:		Optional[int]=2		,   __lowerCAmelCase	:		Tuple="gelu"		,   __lowerCAmelCase	:		List[Any]=0.1		,   __lowerCAmelCase	:		List[str]=0.1		,   __lowerCAmelCase	:		Optional[int]=0.1		,   __lowerCAmelCase	:		Dict=0.0		,   __lowerCAmelCase	:		Optional[int]=0.1		,   __lowerCAmelCase	:		List[str]=0.1		,   __lowerCAmelCase	:		Optional[int]=0.02		,   __lowerCAmelCase	:		Optional[Any]=1E-5		,   __lowerCAmelCase	:		str="group"		,   __lowerCAmelCase	:		Any="gelu"		,   __lowerCAmelCase	:		Optional[int]=(6_4, 1_2_8, 1_2_8, 1_2_8, 1_2_8, 2_5_6, 2_5_6, 2_5_6, 2_5_6, 5_1_2, 5_1_2, 5_1_2, 5_1_2)		,   __lowerCAmelCase	:		List[str]=(5, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1)		,   __lowerCAmelCase	:		Dict=(1_0, 3, 1, 3, 1, 3, 1, 3, 1, 2, 1, 2, 1)		,   __lowerCAmelCase	:		Optional[int]=False		,   __lowerCAmelCase	:		int=1_2_8		,   __lowerCAmelCase	:		Any=1_6		,   __lowerCAmelCase	:		Dict=True		,   __lowerCAmelCase	:		Tuple=0.05		,   __lowerCAmelCase	:		Optional[int]=1_0		,   __lowerCAmelCase	:		Dict=2		,   __lowerCAmelCase	:		Any=0.0		,   __lowerCAmelCase	:		List[Any]=1_0		,   __lowerCAmelCase	:		Union[str, Any]=0		,   __lowerCAmelCase	:		Dict="mean"		,   __lowerCAmelCase	:		Optional[int]=False		,   __lowerCAmelCase	:		Optional[int]=False		,   __lowerCAmelCase	:		List[str]=2_5_6		,   __lowerCAmelCase	:		Dict=0		,   __lowerCAmelCase	:		Any=1		,   __lowerCAmelCase	:		int=2		,   **__lowerCAmelCase	:		int		,   ):






         """simple docstring"""






         super().__init__(**__lowerCAmelCase		,   pad_token_id=__lowerCAmelCase		,   bos_token_id=__lowerCAmelCase		,   eos_token_id=__lowerCAmelCase						)
         _lowerCamelCase		:							List[Any]            =					hidden_size
         _lowerCamelCase		:							List[str]            =					feat_extract_norm
         _lowerCamelCase		:							Optional[Any]            =					feat_extract_activation
         _lowerCamelCase		:							Dict            =					list(__lowerCAmelCase						)
         _lowerCamelCase		:							Tuple            =					list(__lowerCAmelCase						)
         _lowerCamelCase		:							Union[str, Any]            =					list(__lowerCAmelCase						)
         _lowerCamelCase		:							List[Any]            =					conv_bias
         _lowerCamelCase		:							Any            =					num_conv_pos_embeddings
         _lowerCamelCase		:							Optional[Any]            =					num_conv_pos_embedding_groups
         _lowerCamelCase		:							Tuple            =					len(self.conv_dim						)
         _lowerCamelCase		:							List[str]            =					num_hidden_layers
         _lowerCamelCase		:							List[str]            =					intermediate_size
         _lowerCamelCase		:							Union[str, Any]            =					squeeze_factor
         _lowerCamelCase		:							Tuple            =					hidden_act
         _lowerCamelCase		:							Any            =					num_attention_heads
         _lowerCamelCase		:							Any            =					hidden_dropout
         _lowerCamelCase		:							Optional[int]            =					attention_dropout
         _lowerCamelCase		:							Tuple            =					activation_dropout
         _lowerCamelCase		:							Dict            =					feat_proj_dropout
         _lowerCamelCase		:							List[str]            =					final_dropout
         _lowerCamelCase		:							Union[str, Any]            =					layerdrop
         _lowerCamelCase		:							Dict            =					layer_norm_eps
         _lowerCamelCase		:							List[Any]            =					initializer_range
         _lowerCamelCase		:							List[str]            =					vocab_size

         if (
             (len(self.conv_stride						) != self.num_feat_extract_layers)
             or (len(self.conv_kernel						) != self.num_feat_extract_layers)
             or (len(self.conv_dim						) != self.num_feat_extract_layers)
         ):
                raise ValueError(
                    '''Configuration for convolutional layers is incorrect.'''
                    '''It is required that `len(config.conv_dim)` == `len(config.conv_stride)` == `len(config.conv_kernel)`,'''
                    f'''but is `len(config.conv_dim) = {len(self.conv_dim						)}`, `len(config.conv_stride)'''
                    f'''= {len(self.conv_stride						)}`, `len(config.conv_kernel) = {len(self.conv_kernel						)}`.'''						)

         # fine-tuning config parameters for SpecAugment: https://arxiv.org/abs/1904.08779
         _lowerCamelCase		:							Any            =					apply_spec_augment
         _lowerCamelCase		:							Dict            =					mask_time_prob
         _lowerCamelCase		:							List[str]            =					mask_time_length
         _lowerCamelCase		:							str            =					mask_time_min_masks
         _lowerCamelCase		:							List[Any]            =					mask_feature_prob
         _lowerCamelCase		:							Union[str, Any]            =					mask_feature_length
         _lowerCamelCase		:							Dict            =					mask_feature_min_masks

         # ctc loss
         _lowerCamelCase		:							List[Any]            =					ctc_loss_reduction
         _lowerCamelCase		:							Union[str, Any]            =					ctc_zero_infinity

         # sequence classification
         _lowerCamelCase		:							Union[str, Any]            =					use_weighted_layer_sum
         _lowerCamelCase		:							int            =					classifier_proj_size




  @property
  def 		SCREAMING_SNAKE_CASE							(					self	:		Any						):






         """simple docstring"""






         return functools.reduce(operator.mul		,   self.conv_stride		,   1						)









def      _UpperCamelCase  (a__ :int = 1000							):






							"""simple docstring"""





							UpperCamelCase__					  =      2**power
							UpperCamelCase__					  =      0
							while n:
														UpperCamelCase__  ,  UpperCamelCase__					  =      r + n % 10, n // 10
							return r


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




