






'''simple docstring'''



from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


__UpperCamelCase   :							Optional[Any]         =   logging.get_logger(__name__)

__UpperCamelCase   :							Optional[Any]         =   {
    """facebook/xlm-roberta-xl""": """https://huggingface.co/facebook/xlm-roberta-xl/resolve/main/config.json""",
    """facebook/xlm-roberta-xxl""": """https://huggingface.co/facebook/xlm-roberta-xxl/resolve/main/config.json""",
    # See all XLM-RoBERTa-XL models at https://huggingface.co/models?filter=xlm-roberta-xl
}
class 				__SCREAMING_SNAKE_CASE							(				_lowerCAmelCase  ):
      __a	       ="xlm-roberta-xl"




      def __init__(	self			, lowerCamelCase=25_0880			, lowerCamelCase=2560			, lowerCamelCase=36			, lowerCamelCase=32			, lowerCamelCase=1_0240			, lowerCamelCase="gelu"			, lowerCamelCase=0.1			, lowerCamelCase=0.1			, lowerCamelCase=514			, lowerCamelCase=1			, lowerCamelCase=0.02			, lowerCamelCase=1e-05			, lowerCamelCase=1			, lowerCamelCase=0			, lowerCamelCase=2			, lowerCamelCase="absolute"			, lowerCamelCase=True			, lowerCamelCase=None			, **lowerCamelCase			, )				->int:



         '''simple docstring'''
         super().__init__(pad_token_id=lowerCamelCase			, bos_token_id=lowerCamelCase			, eos_token_id=lowerCamelCase			, **lowerCamelCase   )
         __a					  =     vocab_size
         __a					  =     hidden_size
         __a					  =     num_hidden_layers
         __a					  =     num_attention_heads
         __a					  =     hidden_act
         __a					  =     intermediate_size
         __a					  =     hidden_dropout_prob
         __a					  =     attention_probs_dropout_prob
         __a					  =     max_position_embeddings
         __a					  =     type_vocab_size
         __a					  =     initializer_range
         __a					  =     layer_norm_eps
         __a					  =     position_embedding_type
         __a					  =     use_cache
         __a					  =     classifier_dropout







class 				__SCREAMING_SNAKE_CASE							(				_lowerCAmelCase  ):




      @property
      def 			__UpperCamelCase				(	self   )				->Mapping[str, Mapping[int, str]]:



         '''simple docstring'''
         if self.task == "multiple-choice":
            __a					  =     {0: 'batch', 1: 'choice', 2: 'sequence'}
         else:
            __a					  =     {0: 'batch', 1: 'sequence'}
         return OrderedDict(
             [
                 ('input_ids', dynamic_axis),
                 ('attention_mask', dynamic_axis),
             ]   )







'''simple docstring'''



def  __UpperCAmelCase						(					SCREAMING_SNAKE_CASE__:						str     )	->      bool:

   """simple docstring"""
   if not all(x.isalpha() for x in string     ):
      raise ValueError('String must only contain alphabetic characters.'     )

   __a					  =     sorted(string.lower()     )
   return len(SCREAMING_SNAKE_CASE__     ) == len(set(SCREAMING_SNAKE_CASE__     )     )


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

 __UpperCamelCase   :							Tuple         =   is_isogram(input_str)
 print(f"""{input_str} is {"an" if isogram else "not an"} isogram.""")