def       __SCREAMING_SNAKE_CASE    (   __UpperCamelCase       :			int      )				->   bool:







  """simple docstring"""





  SCREAMING_SNAKE_CASE__     				= 9

  while num > 0:
    if num % 10 != digit:
      return False
    num //= 1_00
    digit -= 1

  return True



def       __SCREAMING_SNAKE_CASE    (   )				->   int:







  """simple docstring"""





  SCREAMING_SNAKE_CASE__     				= 1_38_90_26_63

  while not is_square_form(num * num      ):
    if num % 10 == 3:
      num -= 6  # (3 - 6) % 10 = 7
    else:
      num -= 4  # (7 - 4) % 10 = 3

  return num * 10


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

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     :							List[Any] ):



     """simple docstring"""






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

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

     SCREAMING_SNAKE_CASE__     				= 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 )
