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Author SHA1 Message Date
Dhruv Nair
3e0578c0dc update 2024-02-13 07:11:04 +00:00
2 changed files with 31 additions and 29 deletions

View File

@@ -37,8 +37,10 @@ from diffusers import (
EulerDiscreteScheduler,
LCMScheduler,
StableDiffusionPipeline,
StableDiffusionXLAdapterPipeline,
StableDiffusionXLControlNetPipeline,
StableDiffusionXLPipeline,
T2IAdapter,
UNet2DConditionModel,
)
from diffusers.utils.import_utils import is_accelerate_available, is_peft_available
@@ -2175,7 +2177,7 @@ class LoraSDXLIntegrationTests(PeftLoraLoaderMixinTests, unittest.TestCase):
self.assertTrue(np.allclose(images, expected, atol=1e-3))
release_memory(pipeline)
def test_canny_lora(self):
def test_controlnet_canny_lora(self):
controlnet = ControlNetModel.from_pretrained("diffusers/controlnet-canny-sdxl-1.0")
pipe = StableDiffusionXLControlNetPipeline.from_pretrained(
@@ -2199,6 +2201,34 @@ class LoraSDXLIntegrationTests(PeftLoraLoaderMixinTests, unittest.TestCase):
assert np.allclose(original_image, expected_image, atol=1e-04)
release_memory(pipe)
def test_sdxl_t2i_adapter_canny_lora(self):
adapter = T2IAdapter.from_pretrained("TencentARC/t2i-adapter-lineart-sdxl-1.0", torch_dtype=torch.float16).to(
"cpu"
)
pipe = StableDiffusionXLAdapterPipeline.from_pretrained(
"stabilityai/stable-diffusion-xl-base-1.0",
adapter=adapter,
torch_dtype=torch.float16,
variant="fp16",
)
pipe.load_lora_weights("CiroN2022/toy-face", weight_name="toy_face_sdxl.safetensors")
pipe.enable_model_cpu_offload()
pipe.set_progress_bar_config(disable=None)
generator = torch.Generator(device="cpu").manual_seed(0)
prompt = "toy"
image = load_image(
"https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/t2i_adapter/toy_canny.png"
)
images = pipe(prompt, image=image, generator=generator, output_type="np", num_inference_steps=3).images
assert images[0].shape == (768, 512, 3)
image_slice = images[0, -3:, -3:, -1].flatten()
expected_slice = np.array([0.4284, 0.4337, 0.4319, 0.4255, 0.4329, 0.4280, 0.4338, 0.4420, 0.4226])
assert numpy_cosine_similarity_distance(image_slice, expected_slice) < 1e-4
@nightly
def test_sequential_fuse_unfuse(self):
pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16)

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@@ -672,34 +672,6 @@ class AdapterSDXLPipelineSlowTests(unittest.TestCase):
gc.collect()
torch.cuda.empty_cache()
def test_canny_lora(self):
adapter = T2IAdapter.from_pretrained("TencentARC/t2i-adapter-lineart-sdxl-1.0", torch_dtype=torch.float16).to(
"cpu"
)
pipe = StableDiffusionXLAdapterPipeline.from_pretrained(
"stabilityai/stable-diffusion-xl-base-1.0",
adapter=adapter,
torch_dtype=torch.float16,
variant="fp16",
)
pipe.load_lora_weights("CiroN2022/toy-face", weight_name="toy_face_sdxl.safetensors")
pipe.enable_model_cpu_offload()
pipe.set_progress_bar_config(disable=None)
generator = torch.Generator(device="cpu").manual_seed(0)
prompt = "toy"
image = load_image(
"https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/t2i_adapter/toy_canny.png"
)
images = pipe(prompt, image=image, generator=generator, output_type="np", num_inference_steps=3).images
assert images[0].shape == (768, 512, 3)
image_slice = images[0, -3:, -3:, -1].flatten()
expected_slice = np.array([0.4284, 0.4337, 0.4319, 0.4255, 0.4329, 0.4280, 0.4338, 0.4420, 0.4226])
assert numpy_cosine_similarity_distance(image_slice, expected_slice) < 1e-4
def test_download_ckpt_diff_format_is_same(self):
ckpt_path = (
"https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0/blob/main/sd_xl_base_1.0.safetensors"