diffusers/tests/single_file/test_stable_diffusion_upscale_single_file.py at main · huggingface/diffusers · GitHub

Name: diffusers/tests/single_file/test_stable_diffusion_upscale_single_file.py at main · huggingface/diffusers · GitHub
Rating: 4.6 (9952 reviews)
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importgc
importunittest

importpytest
importtorch

fromdiffusersimport (
StableDiffusionUpscalePipeline,
)
fromdiffusers.utilsimportload_image
fromdiffusers.utils.testing_utilsimport (
backend_empty_cache,
enable_full_determinism,
numpy_cosine_similarity_distance,
require_torch_accelerator,
slow,
torch_device,
)

from .single_file_testing_utilsimportSDSingleFileTesterMixin


enable_full_determinism()


@slow
@require_torch_accelerator
classStableDiffusionUpscalePipelineSingleFileSlowTests(unittest.TestCase, SDSingleFileTesterMixin):
pipeline_class=StableDiffusionUpscalePipeline
ckpt_path="https://huggingface.co/stabilityai/stable-diffusion-x4-upscaler/blob/main/x4-upscaler-ema.safetensors"
original_config="https://raw.githubusercontent.com/Stability-AI/stablediffusion/main/configs/stable-diffusion/x4-upscaling.yaml"
repo_id="stabilityai/stable-diffusion-x4-upscaler"

defsetUp(self):
super().setUp()
gc.collect()
backend_empty_cache(torch_device)

deftearDown(self):
super().tearDown()
gc.collect()
backend_empty_cache(torch_device)

deftest_single_file_format_inference_is_same_as_pretrained(self):
image=load_image(
"https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main"
"/sd2-upscale/low_res_cat.png"
 )

prompt="a cat sitting on a park bench"
pipe=StableDiffusionUpscalePipeline.from_pretrained(self.repo_id)
pipe.enable_model_cpu_offload(device=torch_device)

generator=torch.Generator("cpu").manual_seed(0)
output=pipe(prompt=prompt, image=image, generator=generator, output_type="np", num_inference_steps=3)
image_from_pretrained=output.images[0]

pipe_from_single_file=StableDiffusionUpscalePipeline.from_single_file(self.ckpt_path)
pipe_from_single_file.enable_model_cpu_offload(device=torch_device)

generator=torch.Generator("cpu").manual_seed(0)
output_from_single_file=pipe_from_single_file(
prompt=prompt, image=image, generator=generator, output_type="np", num_inference_steps=3
 )
image_from_single_file=output_from_single_file.images[0]

assertimage_from_pretrained.shape== (512, 512, 3)
assertimage_from_single_file.shape== (512, 512, 3)
assert (
numpy_cosine_similarity_distance(image_from_pretrained.flatten(), image_from_single_file.flatten()) <1e-3
 )

@pytest.mark.xfail(
condition=True,
reason="Test fails because of mismatches in the configs but it is very hard to properly fix this considering downstream usecase.",
strict=True,
 )
deftest_single_file_components_with_original_config(self):
super().test_single_file_components_with_original_config()

@pytest.mark.xfail(
condition=True,
reason="Test fails because of mismatches in the configs but it is very hard to properly fix this considering downstream usecase.",
strict=True,
 )
deftest_single_file_components_with_original_config_local_files_only(self):
super().test_single_file_components_with_original_config_local_files_only()