
'''simple docstring'''
import warnings

from diffusers import StableDiffusionImgaImgPipeline  # noqa F401


warnings.warn(
    "The `image_to_image.py` script is outdated. Please use directly `from diffusers import"
    " StableDiffusionImg2ImgPipeline` instead."
)






'''simple docstring'''
import doctest
from collections import deque

import numpy as np






class    UpperCAmelCase_				:





 def __init__(    self):
     snake_case_ :    List[Any]     			=						[2, 1, 2, -1]
     snake_case_ :    int     			=						[1, 2, 3, 4]





 def        snake_case__		(    self):
     snake_case_ :    str     			=						len(self.first_signal)
     snake_case_ :    Any     			=						len(self.second_signal)

     snake_case_ :    List[Any]     			=						max(lowercase_ ,       lowercase_)

     # create a zero matrix of max_length x max_length
     snake_case_ :    Dict     			=						[[0] * max_length for i in range(lowercase_)]

     # 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(lowercase_):
         snake_case_ :    List[str]     			=						deque(self.second_signal)
         rotated_signal.rotate(lowercase_)
         for j, item in enumerate(lowercase_):
             matrix[i][j] += item

        # multiply the matrix with the first signal
     snake_case_ :    Any     			=						np.matmul(np.transpose(lowercase_) ,       np.transpose(self.first_signal))

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


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




