






'''simple docstring'''





from .stack import Stack
def __UpperCAmelCase (			A			:	str						)  -> bool:
			UpperCAmelCase_     :   Stack[str]       =   Stack()
			UpperCAmelCase_     :   List[Any]       =   {'''(''': ''')''', '''[''': ''']''', '''{''': '''}'''}
			for bracket in parentheses:
						if bracket in bracket_pairs:
									stack.push(A						)
						elif bracket in (")", "]", "}"):
									if stack.is_empty() or bracket_pairs[stack.pop()] != bracket:
												return False
			return stack.is_empty()


if __name__ == "__main__":
						from doctest import testmod

						testmod()

						_UpperCamelCase		:		str								=			['((()))', '((())', '(()))']
						print('Balanced parentheses demonstration:\n')
						for example in examples:
												_UpperCamelCase		:		List[Any]								=			'' if balanced_parentheses(example) else 'not '
												print(f'''{example} is {not_str}balanced''')










'''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 				snake_case__     (			unittest.TestCase):




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

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

								UpperCAmelCase_     :   Any       =   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(_A							,				_A     )


