

class        lowerCAmelCase__  :



       '''simple docstring'''







       def __init__(							self ,   lowercase__ ,   lowercase__     ):







             '''simple docstring'''



             __A    =name
             __A    =val

       def __str__(							self     ):







             '''simple docstring'''



             return f'''{self.__class__.__name__}({self.name}, {self.val})'''


       def __lt__(							self ,   lowercase__     ):







             '''simple docstring'''



             return self.val < other.val





class        lowerCAmelCase__  :



       '''simple docstring'''







       def __init__(							self ,   lowercase__     ):







             '''simple docstring'''



             __A    ={}
             __A    ={}
             __A    =self.build_heap(lowercase__     )

       def __getitem__(							self ,   lowercase__     ):







             '''simple docstring'''



             return self.get_value(lowercase__     )

       def     __UpperCamelCase     (							self ,   lowercase__     ):







             '''simple docstring'''



             return (idx - 1) // 2

       def     __UpperCamelCase     (							self ,   lowercase__     ):







             '''simple docstring'''



             return idx * 2 + 1

       def     __UpperCamelCase     (							self ,   lowercase__     ):







             '''simple docstring'''



             return idx * 2 + 2

       def     __UpperCamelCase     (							self ,   lowercase__     ):







             '''simple docstring'''



             return self.heap_dict[key]

       def     __UpperCamelCase     (							self ,   lowercase__     ):







             '''simple docstring'''



             __A    =len(lowercase__     ) - 1
             __A    =self.get_parent_idx(lowercase__     )

             for idx, i in enumerate(lowercase__     ):
                   __A    =idx
                   __A    =i.val

             for i in range(lowercase__ ,   -1 ,   -1     ):
                   self.sift_down(lowercase__ ,   lowercase__     )
             return array

       def     __UpperCamelCase     (							self ,   lowercase__ ,   lowercase__     ):







             '''simple docstring'''



             while True:
                   __A    =self.get_left_child_idx(lowercase__     )  # noqa: E741
                   __A    =self.get_right_child_idx(lowercase__     )

                   __A    =idx
                   if l < len(lowercase__     ) and array[l] < array[idx]:
                         __A    =l
                   if r < len(lowercase__     ) and array[r] < array[smallest]:
                         __A    =r

                   if smallest != idx:
                         __A    ,		__A    =array[smallest], array[idx]
                         (
                             (
                             __A
                         )    ,		(
                             __A
                         )    ,		
                         )    =(
                             self.idx_of_element[array[smallest]],
                             self.idx_of_element[array[idx]],
                         )
                         __A    =smallest
                   else:
                         break

       def     __UpperCamelCase     (							self ,   lowercase__     ):







             '''simple docstring'''



             __A    =self.get_parent_idx(lowercase__     )
             while p >= 0 and self.heap[p] > self.heap[idx]:
                   __A    ,		__A    =self.heap[idx], self.heap[p]
                   __A    ,		__A    =(
                       self.idx_of_element[self.heap[idx]],
                       self.idx_of_element[self.heap[p]],
                   )
                   __A    =p
                   __A    =self.get_parent_idx(lowercase__     )

       def     __UpperCamelCase     (							self     ):







             '''simple docstring'''



             return self.heap[0]

       def     __UpperCamelCase     (							self     ):







             '''simple docstring'''



             __A    ,		__A    =self.heap[-1], self.heap[0]
             __A    ,		__A    =(
                 self.idx_of_element[self.heap[-1]],
                 self.idx_of_element[self.heap[0]],
             )

             __A    =self.heap.pop()
             del self.idx_of_element[x]
             self.sift_down(0 ,   self.heap     )
             return x

       def     __UpperCamelCase     (							self ,   lowercase__     ):







             '''simple docstring'''



             self.heap.append(lowercase__     )
             __A    =len(self.heap     ) - 1
             __A    =node.val
             self.sift_up(len(self.heap     ) - 1     )

       def     __UpperCamelCase     (							self     ):







             '''simple docstring'''



             return len(self.heap     ) == 0


       def     __UpperCamelCase     (							self ,   lowercase__ ,   lowercase__     ):







             '''simple docstring'''



             assert (
                 self.heap[self.idx_of_element[node]].val > new_value
             ), "newValue must be less that current value"
             __A    =new_value
             __A    =new_value
             self.sift_up(self.idx_of_element[node]     )

_lowerCamelCase      :					Dict					    =      Node('''R''', -1)
_lowerCamelCase      :					int					    =      Node('''B''', 6)
_lowerCamelCase      :					Any					    =      Node('''A''', 3)
_lowerCamelCase      :					Dict					    =      Node('''X''', 1)
_lowerCamelCase      :					Tuple					    =      Node('''E''', 4)

# Use one of these two ways to generate Min-Heap

# Generating Min-Heap from array
_lowerCamelCase      :					Any					    =      MinHeap([r, b, a, x, e])

# Generating Min-Heap by Insert method
# myMinHeap.insert(a)
# myMinHeap.insert(b)
# myMinHeap.insert(x)
# myMinHeap.insert(r)
# myMinHeap.insert(e)

# Before
print('''Min Heap - before decrease key''')
for i in my_min_heap.heap:
   print(i)

print('''Min Heap - After decrease key of node [B -> -17]''')
my_min_heap.decrease_key(b, -17)

# After
for i in my_min_heap.heap:
   print(i)

if __name__ == "__main__":
   import doctest

   doctest.testmod()





import gc
import unittest

import numpy as np
import torch

from diffusers import StableDiffusionKDiffusionPipeline
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu


enable_full_determinism()





@slow
@require_torch_gpu
class        lowerCAmelCase__  (					unittest.TestCase			):



       '''simple docstring'''







       def     __UpperCamelCase     (							self     ):







             '''simple docstring'''



             super().tearDown()
             gc.collect()
             torch.cuda.empty_cache()

       def     __UpperCamelCase     (							self     ):







             '''simple docstring'''



             __A    =StableDiffusionKDiffusionPipeline.from_pretrained('''CompVis/stable-diffusion-v1-4'''     )
             __A    =sd_pipe.to(lowercase__     )
             sd_pipe.set_progress_bar_config(disable=lowercase__     )

             sd_pipe.set_scheduler('''sample_euler'''     )

             __A    ='''A painting of a squirrel eating a burger'''
             __A    =torch.manual_seed(0     )
             __A    =sd_pipe([prompt] ,   generator=lowercase__ ,   guidance_scale=9.0 ,   num_inference_steps=2_0 ,   output_type='''np'''     )

             __A    =output.images

             __A    =image[0, -3:, -3:, -1]

             assert image.shape == (1, 5_1_2, 5_1_2, 3)
             __A    =np.array([0.0447, 0.0492, 0.0468, 0.0408, 0.0383, 0.0408, 0.0354, 0.0380, 0.0339]     )

             assert np.abs(image_slice.flatten() - expected_slice     ).max() < 1E-2

       def     __UpperCamelCase     (							self     ):







             '''simple docstring'''



             __A    =StableDiffusionKDiffusionPipeline.from_pretrained('''stabilityai/stable-diffusion-2-1-base'''     )
             __A    =sd_pipe.to(lowercase__     )
             sd_pipe.set_progress_bar_config(disable=lowercase__     )

             sd_pipe.set_scheduler('''sample_euler'''     )

             __A    ='''A painting of a squirrel eating a burger'''
             __A    =torch.manual_seed(0     )
             __A    =sd_pipe([prompt] ,   generator=lowercase__ ,   guidance_scale=9.0 ,   num_inference_steps=2_0 ,   output_type='''np'''     )

             __A    =output.images

             __A    =image[0, -3:, -3:, -1]

             assert image.shape == (1, 5_1_2, 5_1_2, 3)
             __A    =np.array([0.1237, 0.1320, 0.1438, 0.1359, 0.1390, 0.1132, 0.1277, 0.1175, 0.1112]     )

             assert np.abs(image_slice.flatten() - expected_slice     ).max() < 5E-1


       def     __UpperCamelCase     (							self     ):







             '''simple docstring'''



             __A    =StableDiffusionKDiffusionPipeline.from_pretrained('''stabilityai/stable-diffusion-2-1-base'''     )
             __A    =sd_pipe.to(lowercase__     )
             sd_pipe.set_progress_bar_config(disable=lowercase__     )

             sd_pipe.set_scheduler('''sample_dpmpp_2m'''     )

             __A    ='''A painting of a squirrel eating a burger'''
             __A    =torch.manual_seed(0     )
             __A    =sd_pipe(
                 [prompt] ,   generator=lowercase__ ,   guidance_scale=7.5 ,   num_inference_steps=1_5 ,   output_type='''np''' ,   use_karras_sigmas=lowercase__ ,   )

             __A    =output.images

             __A    =image[0, -3:, -3:, -1]

             assert image.shape == (1, 5_1_2, 5_1_2, 3)
             __A    =np.array(
                 [0.1138_1689, 0.1211_2921, 0.138_9457, 0.1254_9606, 0.124_4964, 0.1083_1517, 0.1156_2866, 0.1086_7816, 0.1049_9048]     )

             assert np.abs(image_slice.flatten() - expected_slice     ).max() < 1E-2


