




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   ):



 '''simple docstring'''


 UpperCamelCase						   =						IFInpaintingPipeline
 UpperCamelCase						   =						TEXT_GUIDED_IMAGE_INPAINTING_PARAMS - {"""width""", """height"""}
 UpperCamelCase						   =						TEXT_GUIDED_IMAGE_INPAINTING_BATCH_PARAMS
 UpperCamelCase						   =						PipelineTesterMixin.required_optional_params - {"""latents"""}

 def 				a__ (				self					:  Optional[int]  )   ->	str:

       """simple docstring"""






       return self._get_dummy_components()

 def 				a__ (				self					:  Optional[Any]						,							A_					:  Any						,							A_					:  str=0  )   ->	Union[str, Any]:

       """simple docstring"""






       if str(lowerCAmelCase__  ).startswith('mps'  ):
             lowerCamelCase_		     =    torch.manual_seed(lowerCAmelCase__  )
       else:
             lowerCamelCase_		     =    torch.Generator(device=lowerCAmelCase__  ).manual_seed(lowerCAmelCase__  )

       lowerCamelCase_		     =    floats_tensor((1, 3, 32, 32)						,							rng=random.Random(lowerCAmelCase__  )  ).to(lowerCAmelCase__  )
       lowerCamelCase_		     =    floats_tensor((1, 3, 32, 32)						,							rng=random.Random(lowerCAmelCase__  )  ).to(lowerCAmelCase__  )

       lowerCamelCase_		     =    {
           '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 				a__ (				self					:  Optional[Any]  )   ->	List[str]:

       """simple docstring"""






       self._test_xformers_attention_forwardGenerator_pass(expected_max_diff=1E-3  )

 def 				a__ (				self					:  List[str]  )   ->	Tuple:

       """simple docstring"""






       self._test_save_load_optional_components()

 @unittest.skipIf(torch_device != 'cuda'						,							reason='float16 requires CUDA'  )
 def 				a__ (				self					:  Tuple  )   ->	Any:

       """simple docstring"""






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

 def 				a__ (				self					:  List[Any]  )   ->	Any:

       """simple docstring"""






       self._test_attention_slicing_forward_pass(expected_max_diff=1E-2  )

 def 				a__ (				self					:  List[Any]  )   ->	Tuple:

       """simple docstring"""






       self._test_save_load_local()





 def 				a__ (				self					:  Optional[Any]  )   ->	int:

       """simple docstring"""






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







"""simple docstring"""




def     lowercase			(SCREAMING_SNAKE_CASE_		:				int  )   ->						str:
						SCREAMING_SNAKE_CASE													=					int(SCREAMING_SNAKE_CASE_  )
						if decimal in (0, 1):  # Exit cases for the recursion
												return str(SCREAMING_SNAKE_CASE_  )
						SCREAMING_SNAKE_CASE							,				SCREAMING_SNAKE_CASE													=					divmod(SCREAMING_SNAKE_CASE_ ,			2  )
						return binary_recursive(SCREAMING_SNAKE_CASE_  ) + str(SCREAMING_SNAKE_CASE_  )


def     lowercase			(SCREAMING_SNAKE_CASE_		:				str  )   ->						str:
						SCREAMING_SNAKE_CASE													=					str(SCREAMING_SNAKE_CASE_  ).strip()
						if not number:
												raise ValueError('No input value was provided'  )
						SCREAMING_SNAKE_CASE													=					'-' if number.startswith('-'  ) else ''
						SCREAMING_SNAKE_CASE													=					number.lstrip('-'  )
						if not number.isnumeric():
												raise ValueError('Input value is not an integer'  )
						return F'{negative}0b{binary_recursive(int(SCREAMING_SNAKE_CASE_  )  )}'


if __name__ == "__main__":
	from doctest import testmod

	testmod()


