





'''simple docstring'''


import random
import unittest

import torch

from diffusers import IFInpaintingPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device

from ..pipeline_params import (
    TEXT_GUIDED_IMAGE_INPAINTING_BATCH_PARAMS,
    TEXT_GUIDED_IMAGE_INPAINTING_PARAMS,
)
from ..test_pipelines_common import PipelineTesterMixin
from . import IFPipelineTesterMixin
@skip_mps
class       a_   (				_lowerCAmelCase	,						_lowerCAmelCase	,						unittest.TestCase							):
     __A      =			IFInpaintingPipeline
     __A      =			TEXT_GUIDED_IMAGE_INPAINTING_PARAMS - {"width", "height"}
     __A      =			TEXT_GUIDED_IMAGE_INPAINTING_BATCH_PARAMS
     __A      =			PipelineTesterMixin.required_optional_params - {"latents"}





     def 							lowercase__      ( self		:					Union[str, Any]						):





        """simple docstring"""




        return self._get_dummy_components()





     def 							lowercase__      ( self		:					Tuple	,      lowercase		:					Optional[Any]	,      lowercase		:					Tuple=0						):





        """simple docstring"""




        if str(lowercase						).startswith("mps"						):
           lowercase_			:Union[str, Any]    			= torch.manual_seed(lowercase						)
        else:
           lowercase_			:Tuple    			= torch.Generator(device=lowercase						).manual_seed(lowercase						)

        lowercase_			:Dict    			= floats_tensor((1, 3, 32, 32)	,      rng=random.Random(lowercase						)						).to(lowercase						)
        lowercase_			:List[str]    			= floats_tensor((1, 3, 32, 32)	,      rng=random.Random(lowercase						)						).to(lowercase						)

        lowercase_			:List[str]    			= {
            "prompt": "A painting of a squirrel eating a burger",
            "image": image,
            "mask_image": mask_image,
            "generator": generator,
            "num_inference_steps": 2,
            "output_type": "numpy",
        }

        return inputs





     @unittest.skipIf(
         torch_device != "cuda" or not is_xformers_available()	,      reason="XFormers attention is only available with CUDA and `xformers` installed"	,      )
     def 							lowercase__      ( self		:					Optional[Any]						):





        """simple docstring"""




        self._test_xformers_attention_forwardGenerator_pass(expected_max_diff=1e-3						)





     def 							lowercase__      ( self		:					List[str]						):





        """simple docstring"""




        self._test_save_load_optional_components()





     @unittest.skipIf(torch_device != "cuda"	,      reason="float16 requires CUDA"						)
     def 							lowercase__      ( self		:					Optional[int]						):





        """simple docstring"""




        super().test_save_load_floataa(expected_max_diff=1e-1						)





     def 							lowercase__      ( self		:					Any						):





        """simple docstring"""




        self._test_attention_slicing_forward_pass(expected_max_diff=1e-2						)





     def 							lowercase__      ( self		:					Any						):





        """simple docstring"""




        self._test_save_load_local()







     def 							lowercase__      ( self		:					List[Any]						):





        """simple docstring"""




        self._test_inference_batch_single_identical(
            expected_max_diff=1e-2	,      )









'''simple docstring'''


import math
def 							UpperCAmelCase_  (						__lowerCamelCase					:					int ):
   lowercase_			:Dict    			= []
   lowercase_			:List[Any]    			= 2
   lowercase_			:Optional[Any]    			= int(math.sqrt(__lowerCamelCase ) )  # Size of every segment
   lowercase_			:Optional[Any]    			= [True] * (end + 1)
   lowercase_			:Dict    			= []

   while start <= end:
      if temp[start] is True:
         in_prime.append(__lowerCamelCase )
         for i in range(start * start	,end + 1	,__lowerCamelCase ):
            lowercase_			:List[str]    			= False
      start += 1
   prime += in_prime

   lowercase_			:Dict    			= end + 1
   lowercase_			:Dict    			= min(2 * end	,__lowerCamelCase )

   while low <= n:
      lowercase_			:Any    			= [True] * (high - low + 1)
      for each in in_prime:
         lowercase_			:List[Any]    			= math.floor(low / each ) * each
         if t < low:
            t += each

         for j in range(__lowerCamelCase	,high + 1	,__lowerCamelCase ):
            lowercase_			:str    			= False

      for j in range(len(__lowerCamelCase ) ):
         if temp[j] is True:
            prime.append(j + low )

      lowercase_			:Dict    			= high + 1
      lowercase_			:Dict    			= min(high + end	,__lowerCamelCase )

   return prime


print(sieve(10**6))


