


class    UpperCAmelCase_	:
       '''simple docstring'''






       def __init__(     self						):




              """simple docstring"""




              UpperCamelCase    :	Optional[Any]   	=		{}






       def  _lowercase   (     self						):




              """simple docstring"""




              print(self.vertex						)
              for i in self.vertex:
                     print(lowercase_ ,					''' -> ''' ,					''' -> '''.join([str(lowercase_						) for j in self.vertex[i]]						)						)






       def  _lowercase   (     self ,					__SCREAMING_SNAKE_CASE ,					__SCREAMING_SNAKE_CASE						):




              """simple docstring"""




              if from_vertex in self.vertex:
                     self.vertex[from_vertex].append(lowercase_						)
              else:
                     # else make a new vertex
                     UpperCamelCase    :	Union[str, Any]   	=		[to_vertex]






       def  _lowercase   (     self						):




              """simple docstring"""




              UpperCamelCase    :	List[Any]   	=		[False] * len(self.vertex						)

              # call the recursive helper function
              for i in range(len(self.vertex						)						):
                     if not visited[i]:
                            self.dfs_recursive(lowercase_ ,					lowercase_						)






       def  _lowercase   (     self ,					__SCREAMING_SNAKE_CASE ,					__SCREAMING_SNAKE_CASE						):




              """simple docstring"""




              UpperCamelCase    :	List[Any]   	=		True

              print(lowercase_ ,					end=''' '''						)

              # Recur for all the vertices that are adjacent to this node
              for i in self.vertex:
                     if not visited[i]:
                            self.dfs_recursive(lowercase_ ,					lowercase_						)


if __name__ == "__main__":
       __UpperCAmelCase : Optional[int] 			=				Graph()
       g.add_edge(0, 1)
       g.add_edge(0, 2)
       g.add_edge(1, 2)
       g.add_edge(2, 0)
       g.add_edge(2, 3)
       g.add_edge(3, 3)

       g.print_graph()
       print("DFS:")
       g.dfs()

       # OUTPUT:
       # 0  ->  1 -> 2
       # 1  ->  2
       # 2  ->  0 -> 3
       # 3  ->  3
       # DFS:
       #  0 1 2 3





import unittest

import numpy as np
import torch

from diffusers import VersatileDiffusionImageVariationPipeline
from diffusers.utils.testing_utils import load_image, require_torch_gpu, slow, torch_device


__UpperCAmelCase : Dict 			=				False



class    UpperCAmelCase_	(							unittest.TestCase):
       '''simple docstring'''
       pass




@slow
@require_torch_gpu
class    UpperCAmelCase_	(							unittest.TestCase):
       '''simple docstring'''






       def  _lowercase   (     self						):




              """simple docstring"""




              UpperCamelCase    :	Dict   	=		VersatileDiffusionImageVariationPipeline.from_pretrained('''shi-labs/versatile-diffusion'''						)
              pipe.to(__SCREAMING_SNAKE_CASE						)
              pipe.set_progress_bar_config(disable=__SCREAMING_SNAKE_CASE						)

              UpperCamelCase    :	Union[str, Any]   	=		load_image(
                  '''https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/versatile_diffusion/benz.jpg'''						)
              UpperCamelCase    :	str   	=		torch.manual_seed(0						)
              UpperCamelCase    :	Union[str, Any]   	=		pipe(
                  image=__SCREAMING_SNAKE_CASE ,					generator=__SCREAMING_SNAKE_CASE ,					guidance_scale=7.5 ,					num_inference_steps=50 ,					output_type='''numpy''' ,					).images

              UpperCamelCase    :	List[Any]   	=		image[0, 253:256, 253:256, -1]

              assert image.shape == (1, 512, 512, 3)
              UpperCamelCase    :	Dict   	=		np.array([0.0_441, 0.0_469, 0.0_507, 0.0_575, 0.0_632, 0.0_650, 0.0_865, 0.0_909, 0.0_945]						)

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

