



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 ):






   '''simple docstring'''






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

       UpperCAmelCase_     :       Optional[int]  		=					"""A bear is playing a guitar on Times Square"""
       UpperCAmelCase_     :       List[str]  		=					pipe(prompt=lowerCamelCase_  ,generator=lowerCamelCase_							).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(lowerCamelCase_  ,lowerCamelCase_							)

'''simple docstring'''




def _UpperCamelCase (							SCREAMING_SNAKE_CASE_				):
     return " ".join([word[::-1] for word in input_str.split()]				)


if __name__ == "__main__":
 import doctest

 doctest.testmod()




