






"""simple docstring"""




from transformers import HfArgumentParser, PyTorchBenchmark, PyTorchBenchmarkArguments


def __A   (				)->  Any:





						"""simple docstring"""



						_UpperCAmelCase     =      HfArgumentParser(_lowerCAmelCase     )
						try:
												_UpperCAmelCase     =      parser.parse_args_into_dataclasses()[0]
						except ValueError as e:
												_UpperCAmelCase     =      'Arg --no_{0} is no longer used, please use --no-{0} instead.'
												_UpperCAmelCase     =      ' '.join(str(_lowerCAmelCase     ).split(' '     )[:-1]     )
												_UpperCAmelCase     =      ''
												_UpperCAmelCase     =      eval(str(_lowerCAmelCase     ).split(' '     )[-1]     )
												_UpperCAmelCase     =      []
												for arg in depreciated_args:
																		# arg[2:] removes '--'
																		if arg[2:] in PyTorchBenchmarkArguments.deprecated_args:
																								# arg[5:] removes '--no_'
																								full_error_msg += arg_error_msg.format(arg[5:]     )
																		else:
																								wrong_args.append(_lowerCAmelCase     )
												if len(_lowerCAmelCase     ) > 0:
																		_UpperCAmelCase     =      full_error_msg + begin_error_msg + str(_lowerCAmelCase     )
												raise ValueError(_lowerCAmelCase     )

						_UpperCAmelCase     =      PyTorchBenchmark(args=_lowerCAmelCase     )
						benchmark.run()


if __name__ == "__main__":
		main()








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 __lowerCamelCase			(				unittest.TestCase):





	"""simple docstring"""






	def 	UpperCamelCase   (							self   ):
							"""simple docstring"""







							_UpperCAmelCase     =      'runwayml/stable-diffusion-v1-5'
							_UpperCAmelCase     =      TextToVideoZeroPipeline.from_pretrained(UpperCAmelCase	,   torch_dtype=torch.floataa   ).to('cuda'   )
							_UpperCAmelCase     =      DDIMScheduler.from_config(pipe.scheduler.config   )
							_UpperCAmelCase     =      torch.Generator(device='cuda'   ).manual_seed(0   )

							_UpperCAmelCase     =      'A bear is playing a guitar on Times Square'
							_UpperCAmelCase     =      pipe(prompt=UpperCAmelCase	,   generator=UpperCAmelCase   ).images

							_UpperCAmelCase     =      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(UpperCAmelCase	,   UpperCAmelCase   )
