





"""simple docstring"""




import unittest

import torch

from diffusers import DDIMScheduler, TextToVideoZeroPipeline
from diffusers.utils import load_pt, require_torch_gpu, slow

from ..test_pipelines_common import assert_mean_pixel_difference




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






				def        snake_case			(				self	:					int							)			->   Any:




										'''simple docstring'''



										_UpperCamelCase    :      Tuple						     =					'''runwayml/stable-diffusion-v1-5'''
										_UpperCamelCase    :      str						     =					TextToVideoZeroPipeline.from_pretrained(lowerCAmelCase__,				torch_dtype=torch.floataa							).to('''cuda'''							)
										_UpperCamelCase    :      Any						     =					DDIMScheduler.from_config(pipe.scheduler.config							)
										_UpperCamelCase    :      Optional[int]						     =					torch.Generator(device='''cuda'''							).manual_seed(0							)

										_UpperCamelCase    :      List[Any]						     =					'''A bear is playing a guitar on Times Square'''
										_UpperCamelCase    :      int						     =					pipe(prompt=lowerCAmelCase__,				generator=lowerCAmelCase__							).images

										_UpperCamelCase    :      Dict						     =					load_pt(
										    '''https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/text-to-video/A bear is playing a guitar on Times Square.pt'''							)

										assert_mean_pixel_difference(lowerCAmelCase__,				lowerCAmelCase__							)










"""simple docstring"""




def  a_       (							_lowercase ,		_lowercase     ):
						sequence.append(_lowercase     )

						_UpperCamelCase    :      int						     =					0
						while sequence[index] != target:
												index += 1

						sequence.pop()

						if index == len(_lowercase     ):
												return None

						return index


if __name__ == "__main__":
						UpperCamelCase_     =input("""Enter numbers separated by comma:\n""").strip()
						UpperCamelCase_     =[int(item) for item in user_input.split(""",""")]

						UpperCamelCase_     =input("""Enter a single number to be found in the list:\n""")
						UpperCamelCase_     =int(target_input)
						UpperCamelCase_     =sentinel_linear_search(sequence, target)
						if result is not None:
												print(F"{target} found at positions: {result}")
						else:
												print("""Not found""")



