





'''simple docstring'''







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


lowerCAmelCase_					:    Tuple      	=			logging.get_logger(__name__)

lowerCAmelCase_					:    Any      	=			{
    's-JoL/Open-Llama-V1': 'https://huggingface.co/s-JoL/Open-Llama-V1/blob/main/config.json',
}
class 				__SCREAMING_SNAKE_CASE  (_UpperCAmelCase      ):






				"""simple docstring"""







				__a            ='open-llama'




				def __init__(  self     :					Tuple					,				__a     :					str=10_00_00					,				__a     :					str=40_96					,				__a     :					List[str]=1_10_08					,				__a     :					Optional[Any]=32					,				__a     :					str=32					,				__a     :					int="silu"					,				__a     :					int=20_48					,				__a     :					Union[str, Any]=0.02					,				__a     :					Dict=1e-6					,				__a     :					Dict=True					,				__a     :					Optional[Any]=0					,				__a     :					List[Any]=1					,				__a     :					Dict=2					,				__a     :					List[str]=False					,				__a     :					int=True					,				__a     :					List[Any]=0.1					,				__a     :					Union[str, Any]=0.1					,				__a     :					str=True					,				__a     :					Tuple=True					,				__a     :					List[str]=None					,				**__a     :					Tuple					,				):
								_a								= vocab_size
								_a								= max_position_embeddings
								_a								= hidden_size
								_a								= intermediate_size
								_a								= num_hidden_layers
								_a								= num_attention_heads
								_a								= hidden_act
								_a								= initializer_range
								_a								= rms_norm_eps
								_a								= use_cache
								_a								= kwargs.pop(
								    "use_memorry_efficient_attention"					,				A_					)
								_a								= hidden_dropout_prob
								_a								= attention_dropout_prob
								_a								= use_stable_embedding
								_a								= shared_input_output_embedding
								_a								= rope_scaling
								self._rope_scaling_validation()

								super().__init__(
								    pad_token_id=A_					,				bos_token_id=A_					,				eos_token_id=A_					,				tie_word_embeddings=A_					,				**A_					,				)




				def   UpperCamelCase__   (  self     :					Union[str, Any]					):





								if self.rope_scaling is None:
												return

								if not isinstance(self.rope_scaling					,				A_					) or len(self.rope_scaling					) != 2:
												raise ValueError(
												    "`rope_scaling` must be a dictionary with with two fields, `name` and `factor`, "
												    f'got {self.rope_scaling}'					)
								_a								= self.rope_scaling.get("type"					,				A_					)
								_a								= self.rope_scaling.get("factor"					,				A_					)
								if rope_scaling_type is None or rope_scaling_type not in ["linear", "dynamic"]:
												raise ValueError(
												    f'`rope_scaling`\'s name field must be one of [\'linear\', \'dynamic\'], got {rope_scaling_type}'					)
								if rope_scaling_factor is None or not isinstance(A_					,				A_					) or rope_scaling_factor <= 1.0:
												raise ValueError(f'`rope_scaling`\'s factor field must be an float > 1, got {rope_scaling_factor}'					)



def 		_lowercase (     lowercase__						):
      if not all(x.isalpha() for x in string						):
            raise ValueError('''String must only contain alphabetic characters.'''						)

      __lowerCAmelCase					:						int					=					sorted(string.lower()						)
      return len(lowercase__						) == len(set(lowercase__						)						)


if __name__ == "__main__":
 _UpperCamelCase 			=		input("Enter a string ").strip()

 _UpperCamelCase 			=		is_isogram(input_str)
 print(F"{input_str} is {'an' if isogram else 'not an'} isogram.")


