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


a_							=      logging.get_logger(__name__)

a_							=      {
    """speechbrain/m-ctc-t-large""": """https://huggingface.co/speechbrain/m-ctc-t-large/resolve/main/config.json""",
    # See all M-CTC-T models at https://huggingface.co/models?filter=mctct
}


class 			UpperCAmelCase__    (		snake_case					):



  """simple docstring"""






  lowerCAmelCase__		:	Union[str, Any]    		= 'mctct'






  def __init__(				self:			Any				,				__lowerCAmelCase:			Dict=8_065				,				__lowerCAmelCase:			int=1_536				,				__lowerCAmelCase:			List[str]=36				,				__lowerCAmelCase:			List[str]=6_144				,				__lowerCAmelCase:			str=4				,				__lowerCAmelCase:			str=384				,				__lowerCAmelCase:			Optional[int]=920				,				__lowerCAmelCase:			List[str]=1E-5				,				__lowerCAmelCase:			Dict=0.3				,				__lowerCAmelCase:			Union[str, Any]="relu"				,				__lowerCAmelCase:			List[Any]=0.02				,				__lowerCAmelCase:			Union[str, Any]=0.3				,				__lowerCAmelCase:			Union[str, Any]=0.3				,				__lowerCAmelCase:			Union[str, Any]=1				,				__lowerCAmelCase:			Any=0				,				__lowerCAmelCase:			Tuple=2				,				__lowerCAmelCase:			str=1				,				__lowerCAmelCase:			Tuple=0.3				,				__lowerCAmelCase:			int=1				,				__lowerCAmelCase:			Union[str, Any]=(7,)				,				__lowerCAmelCase:			Optional[Any]=(3,)				,				__lowerCAmelCase:			Optional[int]=80				,				__lowerCAmelCase:			Optional[int]=1				,				__lowerCAmelCase:			Any=None				,				__lowerCAmelCase:			Any="sum"				,				__lowerCAmelCase:			List[Any]=False				,				**__lowerCAmelCase:			List[Any]				,				) -> int:




    '''simple docstring'''




    super().__init__(**__lowerCAmelCase				,				pad_token_id=__lowerCAmelCase				,				bos_token_id=__lowerCAmelCase				,				eos_token_id=__lowerCAmelCase   )
    __UpperCAmelCase						    =       vocab_size
    __UpperCAmelCase						    =       hidden_size
    __UpperCAmelCase						    =       num_hidden_layers
    __UpperCAmelCase						    =       intermediate_size
    __UpperCAmelCase						    =       num_attention_heads
    __UpperCAmelCase						    =       attention_head_dim
    __UpperCAmelCase						    =       max_position_embeddings
    __UpperCAmelCase						    =       layer_norm_eps
    __UpperCAmelCase						    =       layerdrop
    __UpperCAmelCase						    =       hidden_act
    __UpperCAmelCase						    =       initializer_range
    __UpperCAmelCase						    =       hidden_dropout_prob
    __UpperCAmelCase						    =       attention_probs_dropout_prob
    __UpperCAmelCase						    =       pad_token_id
    __UpperCAmelCase						    =       bos_token_id
    __UpperCAmelCase						    =       eos_token_id
    __UpperCAmelCase						    =       conv_glu_dim
    __UpperCAmelCase						    =       conv_dropout
    __UpperCAmelCase						    =       num_conv_layers
    __UpperCAmelCase						    =       input_feat_per_channel
    __UpperCAmelCase						    =       input_channels
    __UpperCAmelCase						    =       conv_channels
    __UpperCAmelCase						    =       ctc_loss_reduction
    __UpperCAmelCase						    =       ctc_zero_infinity

    # prevents config testing fail with exporting to json
    __UpperCAmelCase						    =       list(__lowerCAmelCase   )
    __UpperCAmelCase						    =       list(__lowerCAmelCase   )

    if len(self.conv_kernel   ) != self.num_conv_layers:
      raise ValueError(
          "Configuration for convolutional module is incorrect. "
          "It is required that `len(config.conv_kernel)` == `config.num_conv_layers` "
          F'''but is `len(config.conv_kernel) = {len(self.conv_kernel   )}`, '''
          F'''`config.num_conv_layers = {self.num_conv_layers}`.'''   )




def       __lowerCAmelCase      (						A_   : str					)    ->  bool:
  if not all(x.isalpha() for x in string					):
    raise ValueError("String must only contain alphabetic characters."					)

  __UpperCAmelCase						    =       sorted(string.lower()					)
  return len(A_					) == len(set(A_					)					)


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

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



