





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       : Union[str, Any]			     =       False

class      lowerCAmelCase							(      unittest.TestCase    ):
 pass


@slow
@require_torch_gpu
class      lowerCAmelCase							(      unittest.TestCase    ):
 def   A_			(   self						:   Tuple			)    ->			Optional[int]:
     lowerCamelCase__					:   Union[str, Any]      				=	VersatileDiffusionImageVariationPipeline.from_pretrained('shi-labs/versatile-diffusion'			)
     pipe.to(UpperCAmelCase			)
     pipe.set_progress_bar_config(disable=UpperCAmelCase			)

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

     lowerCamelCase__					:   Tuple      				=	image[0, 253:256, 253:256, -1]

     assert image.shape == (1, 512, 512, 3)
     lowerCamelCase__					:   List[Any]      				=	np.array([0.0_4_4_1, 0.0_4_6_9, 0.0_5_0_7, 0.0_5_7_5, 0.0_6_3_2, 0.0_6_5_0, 0.0_8_6_5, 0.0_9_0_9, 0.0_9_4_5]			)

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












from __future__ import annotations

from collections.abc import Iterable, Iterator
from dataclasses import dataclass

_UpperCAmelCase       : Union[str, Any]			     =       (3, 9, -11, 0, 7, 5, 1, -1)
_UpperCAmelCase       : Union[str, Any]			     =       (4, 6, 2, 0, 8, 10, 3, -2)

@dataclass
class      lowerCAmelCase							:
 UpperCAmelCase__									=	42
 UpperCAmelCase__									=	42


class      lowerCAmelCase							:
 def __init__(   self						:   Any    ,  UpperCAmelCase						:   Iterable[int]			)    ->			None:
     lowerCamelCase__					:   Node | None      				=	None
     for i in sorted(UpperCAmelCase    ,  reverse=UpperCAmelCase			):
         lowerCamelCase__					:   Tuple      				=	Node(UpperCAmelCase    ,  self.head			)
 def __iter__(   self						:   Optional[int]			)    ->			Iterator[int]:
     lowerCamelCase__					:   str      				=	self.head
     while node:
         yield node.data
         lowerCamelCase__					:   List[str]      				=	node.next_node
 def __len__(   self						:   List[str]			)    ->			int:
     return sum(1 for _ in self			)







 def __str__(   self						:   Any			)    ->			str:
     return " -> ".join([str(UpperCAmelCase			) for node in self]			)


def  SCREAMING_SNAKE_CASE   ( _UpperCAmelCase		,			_UpperCAmelCase				)    ->  SortedLinkedList:
    return SortedLinkedList(list(_UpperCAmelCase				) + list(_UpperCAmelCase				)				)


if __name__ == "__main__":
    import doctest

    doctest.testmod()
    _UpperCAmelCase       : Optional[Any]			     =       SortedLinkedList
    print(merge_lists(SSL(test_data_odd), SSL(test_data_even)))





