

'''simple docstring'''





class SCREAMING_SNAKE_CASE  :






			"""simple docstring"""




			def __init__(    self ,				__UpperCamelCase ,				__UpperCamelCase							):

				"""simple docstring"""


				snake_case_      		= name
				snake_case_      		= val


			def __str__(    self							):

				"""simple docstring"""


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







			def __lt__(    self ,				__UpperCamelCase							):

				"""simple docstring"""


				return self.val < other.val







class SCREAMING_SNAKE_CASE  :






			"""simple docstring"""




			def __init__(    self ,				__UpperCamelCase							):

				"""simple docstring"""


				snake_case_      		= {}
				snake_case_      		= {}
				snake_case_      		= self.build_heap(UpperCamelCase_							)


			def __getitem__(    self ,				__UpperCamelCase							):

				"""simple docstring"""


				return self.get_value(UpperCamelCase_							)


			def 			__lowerCAmelCase (    self ,				__UpperCamelCase							):

				"""simple docstring"""


				return (idx - 1) // 2


			def 			__lowerCAmelCase (    self ,				__UpperCamelCase							):

				"""simple docstring"""


				return idx * 2 + 1


			def 			__lowerCAmelCase (    self ,				__UpperCamelCase							):

				"""simple docstring"""


				return idx * 2 + 2


			def 			__lowerCAmelCase (    self ,				__UpperCamelCase							):

				"""simple docstring"""


				return self.heap_dict[key]


			def 			__lowerCAmelCase (    self ,				__UpperCamelCase							):

				"""simple docstring"""


				snake_case_      		= len(UpperCamelCase_							) - 1
				snake_case_      		= self.get_parent_idx(UpperCamelCase_							)

				for idx, i in enumerate(UpperCamelCase_							):
					snake_case_      		= idx
					snake_case_      		= i.val

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


			def 			__lowerCAmelCase (    self ,				__UpperCamelCase ,				__UpperCamelCase							):

				"""simple docstring"""


				while True:
					snake_case_      		= self.get_left_child_idx(UpperCamelCase_							)  # noqa: E741
					snake_case_      		= self.get_right_child_idx(UpperCamelCase_							)

					snake_case_      		= idx
					if l < len(UpperCamelCase_							) and array[l] < array[idx]:
						snake_case_      		= l
					if r < len(UpperCamelCase_							) and array[r] < array[smallest]:
						snake_case_      		= r

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


			def 			__lowerCAmelCase (    self ,				__UpperCamelCase							):

				"""simple docstring"""


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


			def 			__lowerCAmelCase (    self							):

				"""simple docstring"""


				return self.heap[0]


			def 			__lowerCAmelCase (    self							):

				"""simple docstring"""


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

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


			def 			__lowerCAmelCase (    self ,				__UpperCamelCase							):

				"""simple docstring"""


				self.heap.append(UpperCamelCase_							)
				snake_case_      		= len(self.heap							) - 1
				snake_case_      		= node.val
				self.sift_up(len(self.heap							) - 1							)


			def 			__lowerCAmelCase (    self							):

				"""simple docstring"""


				return len(self.heap							) == 0







			def 			__lowerCAmelCase (    self ,				__UpperCamelCase ,				__UpperCamelCase							):

				"""simple docstring"""


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







A											=     Node('R', -1)
A											=     Node('B', 6)
A											=     Node('A', 3)
A											=     Node('X', 1)
A											=     Node('E', 4)

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

# Generating Min-Heap from array
A											=     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 unittest

import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel

from diffusers import DDIMScheduler, LDMPipeline, UNetaDModel, VQModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device


enable_full_determinism()


class SCREAMING_SNAKE_CASE  (		unittest.TestCase							):






			"""simple docstring"""




			@property
			def 			__lowerCAmelCase (    self							):

				"""simple docstring"""


				torch.manual_seed(0							)
				snake_case_      		= UNetaDModel(
				    block_out_channels=(32, 64) ,				layers_per_block=2 ,				sample_size=32 ,				in_channels=3 ,				out_channels=3 ,				down_block_types=('DownBlock2D', 'AttnDownBlock2D') ,				up_block_types=('AttnUpBlock2D', 'UpBlock2D') ,				)
				return model


			@property
			def 			__lowerCAmelCase (    self							):

				"""simple docstring"""


				torch.manual_seed(0							)
				snake_case_      		= VQModel(
				    block_out_channels=[32, 64] ,				in_channels=3 ,				out_channels=3 ,				down_block_types=['DownEncoderBlock2D', 'DownEncoderBlock2D'] ,				up_block_types=['UpDecoderBlock2D', 'UpDecoderBlock2D'] ,				latent_channels=3 ,				)
				return model


			@property
			def 			__lowerCAmelCase (    self							):

				"""simple docstring"""


				torch.manual_seed(0							)
				snake_case_      		= CLIPTextConfig(
				    bos_token_id=0 ,				eos_token_id=2 ,				hidden_size=32 ,				intermediate_size=37 ,				layer_norm_eps=1E-05 ,				num_attention_heads=4 ,				num_hidden_layers=5 ,				pad_token_id=1 ,				vocab_size=10_00 ,				)
				return CLIPTextModel(__UpperCamelCase							)







			def 			__lowerCAmelCase (    self							):

				"""simple docstring"""


				snake_case_      		= self.dummy_uncond_unet
				snake_case_      		= DDIMScheduler()
				snake_case_      		= self.dummy_vq_model

				snake_case_      		= LDMPipeline(unet=__UpperCamelCase ,				vqvae=__UpperCamelCase ,				scheduler=__UpperCamelCase							)
				ldm.to(__UpperCamelCase							)
				ldm.set_progress_bar_config(disable=__UpperCamelCase							)

				snake_case_      		= torch.manual_seed(0							)
				snake_case_      		= ldm(generator=__UpperCamelCase ,				num_inference_steps=2 ,				output_type='numpy'							).images

				snake_case_      		= torch.manual_seed(0							)
				snake_case_      		= ldm(generator=__UpperCamelCase ,				num_inference_steps=2 ,				output_type='numpy' ,				return_dict=__UpperCamelCase							)[0]

				snake_case_      		= image[0, -3:, -3:, -1]
				snake_case_      		= image_from_tuple[0, -3:, -3:, -1]

				assert image.shape == (1, 64, 64, 3)
				snake_case_      		= np.array([0.8512, 0.818, 0.6411, 0.6808, 0.4465, 0.5618, 0.46, 0.6231, 0.5172]							)
				snake_case_      		= 1E-2 if torch_device != 'mps' else 3E-2

				assert np.abs(image_slice.flatten() - expected_slice							).max() < tolerance
				assert np.abs(image_from_tuple_slice.flatten() - expected_slice							).max() < tolerance







@slow
@require_torch
class SCREAMING_SNAKE_CASE  (		unittest.TestCase							):






			"""simple docstring"""




			def 			__lowerCAmelCase (    self							):

				"""simple docstring"""


				snake_case_      		= LDMPipeline.from_pretrained('CompVis/ldm-celebahq-256'							)
				ldm.to(__UpperCamelCase							)
				ldm.set_progress_bar_config(disable=__UpperCamelCase							)

				snake_case_      		= torch.manual_seed(0							)
				snake_case_      		= ldm(generator=__UpperCamelCase ,				num_inference_steps=5 ,				output_type='numpy'							).images

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

				assert image.shape == (1, 2_56, 2_56, 3)
				snake_case_      		= np.array([0.4399, 0.4_4975, 0.4_6825, 0.474, 0.4359, 0.4581, 0.4_5095, 0.4341, 0.4447]							)
				snake_case_      		= 1E-2 if torch_device != 'mps' else 3E-2

				assert np.abs(image_slice.flatten() - expected_slice							).max() < tolerance
