
'''simple docstring'''
from math import ceil

def 						UpperCamelCase_     (	__SCREAMING_SNAKE_CASE = 1_0_0_1       ):
    """simple docstring"""






    snake_case_ :    Optional[Any]     			=						1

    for i in range(1,		int(ceil(n / 2.0       )       )       ):
        snake_case_ :    Any     			=						2 * i + 1
        snake_case_ :    str     			=						2 * i
        snake_case_ :    Optional[Any]     			=						total + 4 * odd**2 - 6 * even

    return total


if __name__ == "__main__":
  import sys

  if len(sys.argv) == 1:
    print(solution())
  else:
    try:
      a_											=						int(sys.argv[1])
      print(solution(n))
    except ValueError:
      print("Invalid entry - please enter a number")






'''simple docstring'''
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding






class    UpperCAmelCase_				(	snake_case__					):
 UpperCAmelCase_		    =						"""ClapFeatureExtractor"""
 UpperCAmelCase_		    =						("""RobertaTokenizer""", """RobertaTokenizerFast""")





 def __init__(    self ,       lowercase_ ,       lowercase_):
     super().__init__(lowercase_ ,       lowercase_)





 def __call__(    self ,       lowercase_=None ,       lowercase_=None ,       lowercase_=None ,       **lowercase_):
     snake_case_ :    Any     			=						kwargs.pop("sampling_rate" ,       lowercase_)

     if text is None and audios is None:
         raise ValueError("You have to specify either text or audios. Both cannot be none.")

     if text is not None:
         snake_case_ :    Optional[int]     			=						self.tokenizer(lowercase_ ,       return_tensors=lowercase_ ,       **lowercase_)

     if audios is not None:
         snake_case_ :    Any     			=						self.feature_extractor(
             lowercase_ ,       sampling_rate=lowercase_ ,       return_tensors=lowercase_ ,       **lowercase_)

     if text is not None and audios is not None:
         snake_case_ :    Dict     			=						audio_features.input_features
         return encoding
     elif text is not None:
         return encoding
     else:
         return BatchEncoding(data=dict(**lowercase_) ,       tensor_type=lowercase_)





 def        snake_case__		(    self ,       *lowercase_ ,       **lowercase_):
     return self.tokenizer.batch_decode(*lowercase_ ,       **lowercase_)





 def        snake_case__		(    self ,       *lowercase_ ,       **lowercase_):
     return self.tokenizer.decode(*lowercase_ ,       **lowercase_)





 @property
 def        snake_case__		(    self):
     snake_case_ :    Union[str, Any]     			=						self.tokenizer.model_input_names
     snake_case_ :    int     			=						self.feature_extractor.model_input_names
     return list(dict.fromkeys(tokenizer_input_names + feature_extractor_input_names))




