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


UpperCAmelCase__		:     Dict     			=      logging.get_logger(__name__)

UpperCAmelCase__		:     Optional[Any]     			=      {
    'google/pegasus-large': 'https://huggingface.co/google/pegasus-large/resolve/main/config.json',
    # See all PEGASUS models at https://huggingface.co/models?filter=pegasus
}






class UpperCAmelCase   (						SCREAMING_SNAKE_CASE__   ):





   '''simple docstring'''
   __UpperCamelCase		:    Optional[int] 				=    '''pegasus'''
   __UpperCamelCase		:    Tuple 				=    ['''past_key_values''']
   __UpperCamelCase		:    Dict 				=    {'''num_attention_heads''': '''encoder_attention_heads''', '''hidden_size''': '''d_model'''}


   def __init__(					self     :							Tuple			,			lowerCAmelCase_     :							Optional[int]=5_0_2_6_5			,			lowerCAmelCase_     :							Optional[int]=1_0_2_4			,			lowerCAmelCase_     :							List[Any]=1_2			,			lowerCAmelCase_     :							int=4_0_9_6			,			lowerCAmelCase_     :							int=1_6			,			lowerCAmelCase_     :							Optional[int]=1_2			,			lowerCAmelCase_     :							Optional[Any]=4_0_9_6			,			lowerCAmelCase_     :							Union[str, Any]=1_6			,			lowerCAmelCase_     :							str=0.0			,			lowerCAmelCase_     :							Optional[Any]=0.0			,			lowerCAmelCase_     :							Optional[Any]=True			,			lowerCAmelCase_     :							Dict=True			,			lowerCAmelCase_     :							List[str]="gelu"			,			lowerCAmelCase_     :							int=1_0_2_4			,			lowerCAmelCase_     :							List[str]=0.1			,			lowerCAmelCase_     :							List[str]=0.0			,			lowerCAmelCase_     :							Union[str, Any]=0.0			,			lowerCAmelCase_     :							List[Any]=0.02			,			lowerCAmelCase_     :							int=0			,			lowerCAmelCase_     :							List[str]=False			,			lowerCAmelCase_     :							Any=0			,			lowerCAmelCase_     :							Union[str, Any]=1			,			lowerCAmelCase_     :							List[str]=1			,			**lowerCAmelCase_     :							str			,			):

      """simple docstring"""
      _A:  Optional[Any]					=       vocab_size
      _A:  Tuple					=       max_position_embeddings
      _A:  str					=       d_model
      _A:  int					=       encoder_ffn_dim
      _A:  Union[str, Any]					=       encoder_layers
      _A:  Union[str, Any]					=       encoder_attention_heads
      _A:  Union[str, Any]					=       decoder_ffn_dim
      _A:  Any					=       decoder_layers
      _A:  Tuple					=       decoder_attention_heads
      _A:  int					=       dropout
      _A:  List[str]					=       attention_dropout
      _A:  Tuple					=       activation_dropout
      _A:  Union[str, Any]					=       activation_function
      _A:  Any					=       init_std
      _A:  Tuple					=       encoder_layerdrop
      _A:  Tuple					=       decoder_layerdrop
      _A:  Optional[int]					=       use_cache
      _A:  Union[str, Any]					=       encoder_layers
      _A:  int					=       scale_embedding  # scale factor will be sqrt(d_model) if True
      super().__init__(
          pad_token_id=lowerCAmelCase_			,			eos_token_id=lowerCAmelCase_			,			is_encoder_decoder=lowerCAmelCase_			,			decoder_start_token_id=lowerCAmelCase_			,			forced_eos_token_id=lowerCAmelCase_			,			**lowerCAmelCase_			,			)


   @property
   def  __magic_name__				(					self     :							Optional[Any]     ):

      """simple docstring"""
      return self.encoder_attention_heads


   @property
   def  __magic_name__				(					self     :							str     ):

      """simple docstring"""
      return self.d_model





def   lowerCamelCase__							(					a      )      ->   bool:
   _A:  Dict					=       [int(a      ) for i in ip_va_address.split('''.'''      ) if i.isdigit()]
   return len(a      ) == 4 and all(0 <= int(a      ) <= 2_54 for octet in octets      )


if __name__ == "__main__":
   UpperCAmelCase__		:     str     			=      input().strip()
   UpperCAmelCase__		:     Any     			=      'valid' if is_ip_va_address_valid(ip) else 'invalid'
   print(F"""{ip} is a {valid_or_invalid} IP v4 address.""")



