


from typing import List, Optional

import numpy as np

from ...processing_utils import ProcessorMixin
from ...utils import to_numpy







class 		_snake_case  (				_snake_case							):
 SCREAMING_SNAKE_CASE__				=	'EncodecFeatureExtractor'
 SCREAMING_SNAKE_CASE__				=	('T5Tokenizer', 'T5TokenizerFast')




 def __init__(		self ,  _lowerCamelCase ,  _lowerCamelCase   ):
       super().__init__(_lowerCamelCase ,  _lowerCamelCase   )
       a						:List[Any]										=	self.feature_extractor
       a						:List[str]										=	False




 def 	SCREAMING_SNAKE_CASE__    (		self ,  _lowerCamelCase=None ,  _lowerCamelCase=None ,  _lowerCamelCase=True   ):
       return self.tokenizer.get_decoder_prompt_ids(task=_lowerCamelCase ,  language=_lowerCamelCase ,  no_timestamps=_lowerCamelCase   )




 def __call__(		self ,  *_lowerCamelCase ,  **_lowerCamelCase   ):
       # For backward compatibility
       if self._in_target_context_manager:
             return self.current_processor(*_lowerCamelCase ,  **_lowerCamelCase   )

       a						:Any										=	kwargs.pop('''audio''' ,  _lowerCamelCase   )
       a						:Tuple										=	kwargs.pop('''sampling_rate''' ,  _lowerCamelCase   )
       a						:List[str]										=	kwargs.pop('''text''' ,  _lowerCamelCase   )
       if len(_lowerCamelCase   ) > 0:
             a						:Tuple										=	args[0]
             a						:Tuple										=	args[1:]

       if audio is None and text is None:
             raise ValueError('''You need to specify either an `audio` or `text` input to process.'''   )

       if text is not None:
             a						:Dict										=	self.tokenizer(_lowerCamelCase ,  **_lowerCamelCase   )

       if audio is not None:
             a						:Tuple										=	self.feature_extractor(_lowerCamelCase ,  *_lowerCamelCase ,  sampling_rate=_lowerCamelCase ,  **_lowerCamelCase   )

       if audio is None:
             return inputs

       elif text is None:
             return audio_inputs

       else:
             a						:List[Any]										=	audio_inputs['''input_values''']
             if "padding_mask" in audio_inputs:
                   a						:Tuple										=	audio_inputs['''padding_mask''']
             return inputs




 def 	SCREAMING_SNAKE_CASE__    (		self ,  *_lowerCamelCase ,  **_lowerCamelCase   ):
       a						:List[Any]										=	kwargs.pop('''audio''' ,  _lowerCamelCase   )
       a						:Tuple										=	kwargs.pop('''padding_mask''' ,  _lowerCamelCase   )

       if len(_lowerCamelCase   ) > 0:
             a						:Union[str, Any]										=	args[0]
             a						:Dict										=	args[1:]

       if audio_values is not None:
             return self._decode_audio(_lowerCamelCase ,  padding_mask=_lowerCamelCase   )
       else:
             return self.tokenizer.batch_decode(*_lowerCamelCase ,  **_lowerCamelCase   )




 def 	SCREAMING_SNAKE_CASE__    (		self ,  *_lowerCamelCase ,  **_lowerCamelCase   ):
       return self.tokenizer.decode(*_lowerCamelCase ,  **_lowerCamelCase   )




 def 	SCREAMING_SNAKE_CASE__    (		self ,  _lowerCamelCase ,  _lowerCamelCase = None   ):
       a						:str										=	to_numpy(_lowerCamelCase   )
       a						:Union[str, Any]										=	audio_values.shape

       if padding_mask is None:
             return list(_lowerCamelCase   )

       a						:Dict										=	to_numpy(_lowerCamelCase   )

       # match the sequence length of the padding mask to the generated audio arrays by padding with the **non-padding**
       # token (so that the generated audio values are **not** treated as padded tokens)
       a						:str										=	seq_len - padding_mask.shape[-1]
       a						:Optional[Any]										=	1 - self.feature_extractor.padding_value
       a						:Tuple										=	np.pad(_lowerCamelCase ,  ((0, 0), (0, difference)) ,  '''constant''' ,  constant_values=_lowerCamelCase   )

       a						:Any										=	audio_values.tolist()
       for i in range(_lowerCamelCase   ):
             a						:Optional[int]										=	np.asarray(audio_values[i]   )[
                 padding_mask[i][None, :] != self.feature_extractor.padding_value
             ]
             a						:Any										=	sliced_audio.reshape(_lowerCamelCase ,  -1   )

       return audio_values









def     __lowerCamelCase						(			UpperCAmelCase_						:		str						):




      """simple docstring"""





      if n_term == "":
            return []
      a						:list										=	[]
      for temp in range(int(UpperCAmelCase_						)						):
            series.append(F'''1/{temp + 1}''' if series else '''1'''						)
      return series


if __name__ == "__main__":
     snake_case    :   Tuple	    =					input('''Enter the last number (nth term) of the Harmonic Series''')
     print('''Formula of Harmonic Series => 1+1/2+1/3 ..... 1/n''')
     print(harmonic_series(nth_term))





