





from ..utils import DummyObject, requires_backends







class       __A							(   metaclass=lowerCamelCase__	):




      """simple docstring"""







      UpperCAmelCase__							=   ["""torch""", """transformers""", """onnx"""]


      def __init__(		self   ,				*a__   ,				**a__):



             """simple docstring"""





             requires_backends(self   ,				['''torch''', '''transformers''', '''onnx'''])


      @classmethod
      def 					__snake_case      (		cls   ,				*a__   ,				**a__):



             """simple docstring"""





             requires_backends(cls   ,				['''torch''', '''transformers''', '''onnx'''])



      @classmethod
      def 					__snake_case      (		cls   ,				*a__   ,				**a__):



             """simple docstring"""





             requires_backends(cls   ,				['''torch''', '''transformers''', '''onnx'''])







class       __A							(   metaclass=lowerCamelCase__	):




      """simple docstring"""







      UpperCAmelCase__							=   ["""torch""", """transformers""", """onnx"""]


      def __init__(		self   ,				*a__   ,				**a__):



             """simple docstring"""





             requires_backends(self   ,				['''torch''', '''transformers''', '''onnx'''])


      @classmethod
      def 					__snake_case      (		cls   ,				*a__   ,				**a__):



             """simple docstring"""





             requires_backends(cls   ,				['''torch''', '''transformers''', '''onnx'''])



      @classmethod
      def 					__snake_case      (		cls   ,				*a__   ,				**a__):



             """simple docstring"""





             requires_backends(cls   ,				['''torch''', '''transformers''', '''onnx'''])







class       __A							(   metaclass=lowerCamelCase__	):




      """simple docstring"""







      UpperCAmelCase__							=   ["""torch""", """transformers""", """onnx"""]


      def __init__(		self   ,				*a__   ,				**a__):



             """simple docstring"""





             requires_backends(self   ,				['''torch''', '''transformers''', '''onnx'''])


      @classmethod
      def 					__snake_case      (		cls   ,				*a__   ,				**a__):



             """simple docstring"""





             requires_backends(cls   ,				['''torch''', '''transformers''', '''onnx'''])



      @classmethod
      def 					__snake_case      (		cls   ,				*a__   ,				**a__):



             """simple docstring"""





             requires_backends(cls   ,				['''torch''', '''transformers''', '''onnx'''])







class       __A							(   metaclass=lowerCamelCase__	):




      """simple docstring"""







      UpperCAmelCase__							=   ["""torch""", """transformers""", """onnx"""]


      def __init__(		self   ,				*a__   ,				**a__):



             """simple docstring"""





             requires_backends(self   ,				['''torch''', '''transformers''', '''onnx'''])


      @classmethod
      def 					__snake_case      (		cls   ,				*a__   ,				**a__):



             """simple docstring"""





             requires_backends(cls   ,				['''torch''', '''transformers''', '''onnx'''])



      @classmethod
      def 					__snake_case      (		cls   ,				*a__   ,				**a__):



             """simple docstring"""





             requires_backends(cls   ,				['''torch''', '''transformers''', '''onnx'''])







class       __A							(   metaclass=lowerCamelCase__	):




      """simple docstring"""







      UpperCAmelCase__							=   ["""torch""", """transformers""", """onnx"""]


      def __init__(		self   ,				*a__   ,				**a__):



             """simple docstring"""





             requires_backends(self   ,				['''torch''', '''transformers''', '''onnx'''])


      @classmethod
      def 					__snake_case      (		cls   ,				*a__   ,				**a__):



             """simple docstring"""





             requires_backends(cls   ,				['''torch''', '''transformers''', '''onnx'''])



      @classmethod
      def 					__snake_case      (		cls   ,				*a__   ,				**a__):



             """simple docstring"""





             requires_backends(cls   ,				['''torch''', '''transformers''', '''onnx'''])







class       __A							(   metaclass=lowerCamelCase__	):




      """simple docstring"""







      UpperCAmelCase__							=   ["""torch""", """transformers""", """onnx"""]


      def __init__(		self   ,				*a__   ,				**a__):



             """simple docstring"""





             requires_backends(self   ,				['''torch''', '''transformers''', '''onnx'''])


      @classmethod
      def 					__snake_case      (		cls   ,				*a__   ,				**a__):



             """simple docstring"""





             requires_backends(cls   ,				['''torch''', '''transformers''', '''onnx'''])



      @classmethod
      def 					__snake_case      (		cls   ,				*a__   ,				**a__):



             """simple docstring"""





             requires_backends(cls   ,				['''torch''', '''transformers''', '''onnx'''])








import doctest
from collections import deque

import numpy as np







class       __A							:




      """simple docstring"""







      def __init__(		self):



             """simple docstring"""





             _lowerCamelCase				:  Any						=		[2, 1, 2, -1]
             _lowerCamelCase				:  Optional[int]						=		[1, 2, 3, 4]



      def 					__snake_case      (		self):



             """simple docstring"""





             _lowerCamelCase				:  Optional[int]						=		len(self.first_signal)
             _lowerCamelCase				:  str						=		len(self.second_signal)

             _lowerCamelCase				:  str						=		max(a__   ,				a__)

             # create a zero matrix of max_length x max_length
             _lowerCamelCase				:  Optional[Any]						=		[[0] * max_length for i in range(a__)]

             # fills the smaller signal with zeros to make both signals of same length
             if length_first_signal < length_second_signal:
                    self.first_signal += [0] * (max_length - length_first_signal)
             elif length_first_signal > length_second_signal:
                    self.second_signal += [0] * (max_length - length_second_signal)
             for i in range(a__):
                    _lowerCamelCase				:  Optional[Any]						=		deque(self.second_signal)
                    rotated_signal.rotate(a__)
                    for j, item in enumerate(a__):
                           matrix[i][j] += item

        # multiply the matrix with the first signal
             _lowerCamelCase				:  List[Any]						=		np.matmul(np.transpose(a__)   ,				np.transpose(self.first_signal))

             # rounding-off to two decimal places
             return [round(a__   ,				2) for i in final_signal]


if __name__ == "__main__":
       doctest.testmod()

