






'''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    ):
     '''simple docstring'''







     def      _UpperCamelCase (self     :						Optional[int]       )	->							Optional[int]:
           __A		 =   "runwayml/stable-diffusion-v1-5"
           __A		 =   TextToVideoZeroPipeline.from_pretrained(lowercase__					,					torch_dtype=torch.floataa       ).to("cuda"       )
           __A		 =   DDIMScheduler.from_config(pipe.scheduler.config       )
           __A		 =   torch.Generator(device="cuda"       ).manual_seed(0       )

           __A		 =   "A bear is playing a guitar on Times Square"
           __A		 =   pipe(prompt=lowercase__					,					generator=lowercase__       ).images

           __A		 =   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(lowercase__					,					lowercase__       )










'''simple docstring'''







def     _UpperCamelCase				(  snake_case__ = 1_000				):
      __A		 =   []
      __A		 =   []
      __A		 =   3
      __A		 =   5
      __A		 =   1
      while True:
            __A		 =   z * temp
            if result < n:
                  zmulti.append(snake_case__				)
                  temp += 1
            else:
                  __A		 =   1
                  break
      while True:
            __A		 =   x * temp
            if result < n:
                  xmulti.append(snake_case__				)
                  temp += 1
            else:
                  break
      __A		 =   list(set(xmulti + zmulti				)				)
      return sum(snake_case__				)


if __name__ == "__main__":
       print(F"""{solution() = }""")


