





import unittest

import numpy as np
import torch

from diffusers import KarrasVePipeline, KarrasVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device


enable_full_determinism()

class   A							(						unittest.TestCase    ):



      @property
      def 						lowerCAmelCase__     (						self:    Tuple							)    ->     Optional[int]:
         '''simple docstring'''

         torch.manual_seed(0							)
         UpperCAmelCase_           =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






      def 						lowerCAmelCase__     (						self:    List[str]							)    ->     Optional[int]:
         '''simple docstring'''

         UpperCAmelCase_           =self.dummy_uncond_unet
         UpperCAmelCase_           =KarrasVeScheduler()

         UpperCAmelCase_           =KarrasVePipeline(unet=_lowerCAmelCase		,	scheduler=_lowerCAmelCase							)
         pipe.to(_lowerCAmelCase							)
         pipe.set_progress_bar_config(disable=_lowerCAmelCase							)

         UpperCAmelCase_           =torch.manual_seed(0							)
         UpperCAmelCase_           =pipe(num_inference_steps=2		,	generator=_lowerCAmelCase		,	output_type="numpy"							).images

         UpperCAmelCase_           =torch.manual_seed(0							)
         UpperCAmelCase_           =pipe(num_inference_steps=2		,	generator=_lowerCAmelCase		,	output_type="numpy"		,	return_dict=_lowerCAmelCase							)[0]

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

         assert image.shape == (1, 32, 32, 3)
         UpperCAmelCase_           =np.array([0.0, 1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0]							)

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

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



      def 						lowerCAmelCase__     (						self:    Any							)    ->     Optional[int]:
         '''simple docstring'''

         UpperCAmelCase_           ="google/ncsnpp-celebahq-256"
         UpperCAmelCase_           =UNetaDModel.from_pretrained(_lowerCAmelCase							)
         UpperCAmelCase_           =KarrasVeScheduler()

         UpperCAmelCase_           =KarrasVePipeline(unet=_lowerCAmelCase		,	scheduler=_lowerCAmelCase							)
         pipe.to(_lowerCAmelCase							)
         pipe.set_progress_bar_config(disable=_lowerCAmelCase							)

         UpperCAmelCase_           =torch.manual_seed(0							)
         UpperCAmelCase_           =pipe(num_inference_steps=20		,	generator=_lowerCAmelCase		,	output_type="numpy"							).images

         UpperCAmelCase_           =image[0, -3:, -3:, -1]
         assert image.shape == (1, 256, 256, 3)
         UpperCAmelCase_           =np.array([0.5_78, 0.58_11, 0.59_24, 0.58_09, 0.5_87, 0.58_86, 0.58_61, 0.58_02, 0.5_86]							)

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












import heapq as hq
import math
from collections.abc import Iterator
class  _UpperCAmelCase   :

				"""simple docstring"""




				def __init__(	self		:       str,    lowerCamelCase		:       List[Any]    ):

								'''simple docstring'''
								lowercase__  					=     str(id_    )
								lowercase__  					=     None
								lowercase__  					=     None
								lowercase__  					=     []
								lowercase__  					=     {}  # {vertex:distance}




				def __lt__(	self		:       Dict,    lowerCamelCase		:       Tuple    ):

								'''simple docstring'''
								return self.key < other.key




				def __repr__(	self		:       Dict    ):

								'''simple docstring'''
								return self.id




				def 							lowercase__  (	self		:       str,    lowerCamelCase		:       List[str]    ):

								'''simple docstring'''
								self.neighbors.append(lowerCamelCase    )




				def 							lowercase__  (	self		:       Any,    lowerCamelCase		:       Dict,    lowerCamelCase		:       Optional[Any]    ):

								'''simple docstring'''
								lowercase__  					=     weight






def     a     (		lowerCamelCase_						,  lowerCamelCase_						,  lowerCamelCase_						,  lowerCamelCase_							):






				'''simple docstring'''
				# add the neighbors:
				graph[a - 1].add_neighbor(graph[b - 1]							)
				graph[b - 1].add_neighbor(graph[a - 1]							)
				# add the edges:
				graph[a - 1].add_edge(graph[b - 1]						,  lowerCamelCase_							)
				graph[b - 1].add_edge(graph[a - 1]						,  lowerCamelCase_							)






def     a     (		lowerCamelCase_						,  lowerCamelCase_							):






				'''simple docstring'''
				lowercase__  					=     []
				for u in graph:
								lowercase__  					=     math.inf
								lowercase__  					=     None
				lowercase__  					=     0
				lowercase__  					=     graph[:]
				while q:
								lowercase__  					=     min(lowerCamelCase_							)
								q.remove(lowerCamelCase_							)
								for v in u.neighbors:
												if (v in q) and (u.edges[v.id] < v.key):
																lowercase__  					=     u
																lowercase__  					=     u.edges[v.id]
				for i in range(1						,  len(lowerCamelCase_							)							):
								a.append((int(graph[i].id							) + 1, int(graph[i].pi.id							) + 1)							)
				return a






def     a     (		lowerCamelCase_						,  lowerCamelCase_							):






				'''simple docstring'''
				for u in graph:
								lowercase__  					=     math.inf
								lowercase__  					=     None
				lowercase__  					=     0

				lowercase__  					=     list(lowerCamelCase_							)
				hq.heapify(lowerCamelCase_							)

				while h:
								lowercase__  					=     hq.heappop(lowerCamelCase_							)
								for v in u.neighbors:
												if (v in h) and (u.edges[v.id] < v.key):
																lowercase__  					=     u
																lowercase__  					=     u.edges[v.id]
																hq.heapify(lowerCamelCase_							)

				for i in range(1						,  len(lowerCamelCase_							)							):
								yield (int(graph[i].id							) + 1, int(graph[i].pi.id							) + 1)






def     a     (		):






				'''simple docstring'''


if __name__ == "__main__":
							import doctest

							doctest.testmod()




