"""simple docstring"""





from __future__ import annotations





def 				a_     (      _lowerCAmelCase  : int | float | str   , _lowerCAmelCase  : int | float | str     ):





       '''simple docstring'''

       if nth_term == "":
              return [""]
       lowercase__			:		List[Any]       =	int(_lowerCAmelCase     )
       lowercase__			:		List[Any]       =	int(_lowerCAmelCase     )
       lowercase__			:		list[str]       =	[]
       for temp in range(int(_lowerCAmelCase     )     ):
              series.append(f"""1 / {pow(temp + 1   , int(_lowerCAmelCase     )     )}""" if series else '1'     )
       return series


if __name__ == "__main__":
       import doctest

       doctest.testmod()

       _UpperCamelCase   :						Tuple      =    int(input("Enter the last number (nth term) of the P-Series"))
       _UpperCamelCase   :						str      =    int(input("Enter the power for  P-Series"))
       print("Formula of P-Series => 1+1/2^p+1/3^p ..... 1/n^p")
       print(p_series(nth_term, power))



'''simple docstring'''







from ...utils import is_torch_available, is_transformers_available


if is_transformers_available() and is_torch_available():
					from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline

