





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 SCREAMING_SNAKE_CASE_  (   snake_case_    ,			snake_case_    ,			unittest.TestCase   ):
						__magic_name__:     str	 =    IFImgaImgSuperResolutionPipeline
						__magic_name__:     List[str]	 =    TEXT_GUIDED_IMAGE_VARIATION_PARAMS - {"width", "height"}
						__magic_name__:     Dict	 =    TEXT_GUIDED_IMAGE_VARIATION_BATCH_PARAMS.union({"original_image"}   )
						__magic_name__:     Tuple	 =    PipelineTesterMixin.required_optional_params - {"latents"}






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







							"""simple docstring"""


							return self._get_superresolution_dummy_components()






						def UpperCAmelCase_			( self : List[str]						,				_A : Dict						,				_A : Optional[int]=0		)							->      Any:







							"""simple docstring"""


							if str(_A		).startswith('mps'		):
								snake_case_						:     List[Any]     =		torch.manual_seed(_A		)
							else:
								snake_case_						:     Optional[Any]     =		torch.Generator(device=_A		).manual_seed(_A		)

							snake_case_						:     Dict     =		floats_tensor((1, 3, 32, 32)						,				rng=random.Random(_A		)		).to(_A		)
							snake_case_						:     Any     =		floats_tensor((1, 3, 16, 16)						,				rng=random.Random(_A		)		).to(_A		)

							snake_case_						:     Tuple     =		{
							    '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 UpperCAmelCase_			( self : Optional[int]		)							->      Tuple:







							"""simple docstring"""


							self._test_xformers_attention_forwardGenerator_pass(expected_max_diff=1E-3		)






						def UpperCAmelCase_			( self : List[str]		)							->      List[Any]:







							"""simple docstring"""


							self._test_save_load_optional_components()






						@unittest.skipIf(torch_device != 'cuda'						,				reason='float16 requires CUDA'		)
						def UpperCAmelCase_			( self : Optional[int]		)							->      Tuple:







							"""simple docstring"""


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






						def UpperCAmelCase_			( self : Union[str, Any]		)							->      str:







							"""simple docstring"""


							self._test_attention_slicing_forward_pass(expected_max_diff=1E-2		)






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







							"""simple docstring"""


							self._test_save_load_local()






						def UpperCAmelCase_			( self : List[Any]		)							->      Dict:







							"""simple docstring"""


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








_SCREAMING_SNAKE_CASE 		=						{
    """Pillow""": """Pillow""",
    """accelerate""": """accelerate>=0.11.0""",
    """compel""": """compel==0.1.8""",
    """black""": """black~=23.1""",
    """datasets""": """datasets""",
    """filelock""": """filelock""",
    """flax""": """flax>=0.4.1""",
    """hf-doc-builder""": """hf-doc-builder>=0.3.0""",
    """huggingface-hub""": """huggingface-hub>=0.13.2""",
    """requests-mock""": """requests-mock==1.10.0""",
    """importlib_metadata""": """importlib_metadata""",
    """invisible-watermark""": """invisible-watermark""",
    """isort""": """isort>=5.5.4""",
    """jax""": """jax>=0.2.8,!=0.3.2""",
    """jaxlib""": """jaxlib>=0.1.65""",
    """Jinja2""": """Jinja2""",
    """k-diffusion""": """k-diffusion>=0.0.12""",
    """torchsde""": """torchsde""",
    """note_seq""": """note_seq""",
    """librosa""": """librosa""",
    """numpy""": """numpy""",
    """omegaconf""": """omegaconf""",
    """parameterized""": """parameterized""",
    """protobuf""": """protobuf>=3.20.3,<4""",
    """pytest""": """pytest""",
    """pytest-timeout""": """pytest-timeout""",
    """pytest-xdist""": """pytest-xdist""",
    """ruff""": """ruff>=0.0.241""",
    """safetensors""": """safetensors""",
    """sentencepiece""": """sentencepiece>=0.1.91,!=0.1.92""",
    """scipy""": """scipy""",
    """onnx""": """onnx""",
    """regex""": """regex!=2019.12.17""",
    """requests""": """requests""",
    """tensorboard""": """tensorboard""",
    """torch""": """torch>=1.4""",
    """torchvision""": """torchvision""",
    """transformers""": """transformers>=4.25.1""",
    """urllib3""": """urllib3<=2.0.0""",
}

