



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


snake_case    :						List[Any]  =						logging.get_logger(__name__)

snake_case    :						int  =						{
    'tanreinama/GPTSAN-2.8B-spout_is_uniform': (
        'https://huggingface.co/tanreinama/GPTSAN-2.8B-spout_is_uniform/resolve/main/config.json'
    ),
}




class 							lowerCAmelCase__  (	UpperCamelCase						):
     __A     :    List[Any]           =						'gptsan-japanese'
     __A     :    Dict           =						[
         'past_key_values',
     ]
     __A     :    Optional[int]           =						{
         'hidden_size': 'd_model',
         'num_attention_heads': 'num_heads',
         'num_hidden_layers': 'num_layers',
     }







     def __init__(       self      :     Any			,		_A      :     Optional[Any]=3_6000			,		_A      :     List[str]=1280			,		_A      :     List[Any]=1024			,		_A      :     int=8192			,		_A      :     Optional[int]=4096			,		_A      :     int=128			,		_A      :     Optional[int]=10			,		_A      :     Any=0			,		_A      :     List[Any]=16			,		_A      :     Tuple=16			,		_A      :     Any=128			,		_A      :     Any=0.0			,		_A      :     Any=1e-5			,		_A      :     Union[str, Any]=False			,		_A      :     List[str]=0.0			,		_A      :     str="float32"			,		_A      :     Any=False			,		_A      :     Optional[int]=False			,		_A      :     str=False			,		_A      :     Tuple=0.0_02			,		_A      :     Tuple=False			,		_A      :     str=True			,		_A      :     Optional[Any]=3_5998			,		_A      :     Optional[Any]=3_5995			,		_A      :     Dict=3_5999			,		**_A      :     int			,		):
           A__	:							List[Any]						    = vocab_size
           A__	:							Union[str, Any]						    = max_position_embeddings
           A__	:							Optional[int]						    = d_model
           A__	:							Optional[Any]						    = d_ff
           A__	:							Any						    = d_ext
           A__	:							Optional[int]						    = d_spout
           A__	:							List[Any]						    = num_switch_layers
           A__	:							Dict						    = num_ext_layers
           A__	:							List[str]						    = num_switch_layers + num_ext_layers
           A__	:							List[Any]						    = num_heads
           A__	:							List[str]						    = num_experts
           A__	:							Union[str, Any]						    = expert_capacity
           A__	:							Dict						    = dropout_rate
           A__	:							Any						    = layer_norm_epsilon
           A__	:							List[Any]						    = router_bias
           A__	:							Dict						    = router_jitter_noise
           A__	:							List[Any]						    = router_dtype
           A__	:							Any						    = router_ignore_padding_tokens
           A__	:							Optional[Any]						    = output_hidden_states
           A__	:							Dict						    = output_attentions
           A__	:							Optional[Any]						    = initializer_factor
           A__	:							Union[str, Any]						    = output_router_logits
           A__	:							str						    = use_cache

           super().__init__(
               separator_token_id=_A			,		pad_token_id=_A			,		eos_token_id=_A			,		**_A			,		)




def 	snake_case__       (					)		->		Union[str, Any]:







						"""simple docstring"""

						A__	:							Tuple						    = []
						A__	:							Optional[int]						    = 1

						while len(__lowercase       ) < 1E6:
												constant.append(str(__lowercase       )       )
												i += 1

						A__	:							Any						    = "".join(__lowercase       )

						return (
						    int(constant[0]       )
						    * int(constant[9]       )
						    * int(constant[9_9]       )
						    * int(constant[9_9_9]       )
						    * int(constant[9_9_9_9]       )
						    * int(constant[9_9_9_9_9]       )
						    * int(constant[9_9_9_9_9_9]       )
						)


if __name__ == "__main__":
		print(solution())