






import random
import unittest

import torch

from diffusers import IFImgaImgSuperResolutionPipeline
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_VARIATION_BATCH_PARAMS, TEXT_GUIDED_IMAGE_VARIATION_PARAMS
from ..test_pipelines_common import PipelineTesterMixin
from . import IFPipelineTesterMixin
@skip_mps
class 							A_    (						__snake_case ,   __snake_case ,   unittest.TestCase			):






 '''simple docstring'''




 _SCREAMING_SNAKE_CASE							:			List[Any] =					IFImgaImgSuperResolutionPipeline
 _SCREAMING_SNAKE_CASE							:			Optional[int] =					TEXT_GUIDED_IMAGE_VARIATION_PARAMS - {'width', 'height'}
 _SCREAMING_SNAKE_CASE							:			Union[str, Any] =					TEXT_GUIDED_IMAGE_VARIATION_BATCH_PARAMS.union({"original_image"}			)
 _SCREAMING_SNAKE_CASE							:			Optional[Any] =					PipelineTesterMixin.required_optional_params - {'latents'}


 def  snake_case__				(	self) ->		Optional[int]:

     """simple docstring"""



     return self._get_superresolution_dummy_components()


 def  snake_case__				(	self							,  _A							,  _A=0) ->		Optional[Any]:

     """simple docstring"""



     if str(A_).startswith('''mps'''):
         _UpperCAmelCase				:      List[str]			  =				torch.manual_seed(A_)
     else:
         _UpperCAmelCase				:      Optional[int]			  =				torch.Generator(device=A_).manual_seed(A_)

     _UpperCAmelCase				:      Union[str, Any]			  =				floats_tensor((1, 3, 32, 32)							,  rng=random.Random(A_)).to(A_)
     _UpperCAmelCase				:      Tuple			  =				floats_tensor((1, 3, 16, 16)							,  rng=random.Random(A_)).to(A_)

     _UpperCAmelCase				:      Any			  =				{
         "prompt": "A painting of a squirrel eating a burger",
         "image": image,
         "original_image": original_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  snake_case__				(	self) ->		List[str]:

     """simple docstring"""



     self._test_xformers_attention_forwardGenerator_pass(expected_max_diff=1e-3)


 def  snake_case__				(	self) ->		List[str]:

     """simple docstring"""



     self._test_save_load_optional_components()


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

     """simple docstring"""



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


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

     """simple docstring"""



     self._test_attention_slicing_forward_pass(expected_max_diff=1e-2)


 def  snake_case__				(	self) ->		Optional[Any]:

     """simple docstring"""



     self._test_save_load_local()


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

     """simple docstring"""



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












import os
from collections.abc import Iterator

def      _lowerCamelCase	(						__A    :							str = "." )      ->					Iterator[str]:
    for dir_path, dir_names, filenames in os.walk(__A ):
        _UpperCAmelCase				:      List[Any]			  =				[d for d in dir_names if d != '''scripts''' and d[0] not in '''._''']
        for filename in filenames:
            if filename == "__init__.py":
                continue
            if os.path.splitext(__A )[1] in (".py", ".ipynb"):
                yield os.path.join(__A		,		__A ).lstrip('''./''' )

def      _lowerCamelCase	(						__A    :							Dict )      ->					List[Any]:
    return f'''{i * '  '}*''' if i else "\n##"

def      _lowerCamelCase	(						__A    :							str		,		__A    :							str )      ->					str:
    _UpperCAmelCase				:      int			  =				old_path.split(os.sep )
    for i, new_part in enumerate(new_path.split(os.sep ) ):
        if (i + 1 > len(__A ) or old_parts[i] != new_part) and new_part:
            print(f'''{md_prefix(__A )} {new_part.replace('_'		,		' ' ).title()}''' )
    return new_path

def      _lowerCamelCase	(						__A    :							str = "." )      ->					None:
    _UpperCAmelCase				:      List[str]			  =				''''''
    for filepath in sorted(good_file_paths(__A ) ):
        _UpperCAmelCase  , _UpperCAmelCase				:      Optional[Any]			  =				os.path.split(__A )
        if filepath != old_path:
            _UpperCAmelCase				:      Optional[int]			  =				print_path(__A		,		__A )
        _UpperCAmelCase				:      Dict			  =				(filepath.count(os.sep ) + 1) if filepath else 0
        _UpperCAmelCase				:      Union[str, Any]			  =				f'''{filepath}/{filename}'''.replace(''' '''		,		'''%20''' )
        _UpperCAmelCase				:      List[Any]			  =				os.path.splitext(filename.replace('''_'''		,		''' ''' ).title() )[0]
        print(f'''{md_prefix(__A )} [{filename}]({url})''' )


if __name__ == "__main__":
  print_directory_md('.')




