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fix

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This commit is contained in:
Patrick von Platen
2023-11-01 21:39:30 +01:00
parent 5712c3d2ef
commit 839c2a5ece
2 changed files with 23 additions and 43 deletions
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3
src/diffusers/pipelines/t2i_adapter/pipeline_stable_diffusion_xl_adapter.py
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@@ -1068,7 +1068,6 @@ class StableDiffusionXLAdapterPipeline(
return StableDiffusionXLPipelineOutput(images=image)
# Overrride to properly handle the loading and unloading of the additional text encoder.
# Copied from diffusers.pipelines.stable_diffusion_xl.pipeline_stable_diffusion_xl.StableDiffusionXLPipeline.load_lora_weights
def load_lora_weights(self, pretrained_model_name_or_path_or_dict: Union[str, Dict[str, torch.Tensor]], **kwargs):
@@ -1140,4 +1139,4 @@ class StableDiffusionXLAdapterPipeline(
# Copied from diffusers.pipelines.stable_diffusion_xl.pipeline_stable_diffusion_xl.StableDiffusionXLPipeline._remove_text_encoder_monkey_patch
def _remove_text_encoder_monkey_patch(self):
self._remove_text_encoder_monkey_patch_classmethod(self.text_encoder)
self._remove_text_encoder_monkey_patch_classmethod(self.text_encoder_2)
self._remove_text_encoder_monkey_patch_classmethod(self.text_encoder_2)

63
tests/pipelines/stable_diffusion_xl/test_stable_diffusion_xl_adapter.py
View File

@@ -13,8 +13,8 @@
# See the License for the specific language governing permissions and
# limitations under the License.
import random
import gc
import random
import unittest
import numpy as np
@@ -30,14 +30,17 @@ from diffusers import (
StableDiffusionXLAdapterPipeline,
T2IAdapter,
UNet2DConditionModel,
EulerAncestralDiscreteScheduler,
)
from diffusers.utils import logging
from diffusers.utils.testing_utils import enable_full_determinism, floats_tensor, torch_device
from diffusers.utils import load_image
from diffusers.utils.torch_utils import randn_tensor
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, slow, torch_device
from diffusers.utils import load_image, logging
from diffusers.utils.testing_utils import (
enable_full_determinism,
floats_tensor,
numpy_cosine_similarity_distance,
require_torch_gpu,
slow,
torch_device,
)
from ..pipeline_params import TEXT_GUIDED_IMAGE_VARIATION_BATCH_PARAMS, TEXT_GUIDED_IMAGE_VARIATION_PARAMS
from ..test_pipelines_common import (
PipelineTesterMixin,
@@ -575,38 +578,15 @@ class AdapterSDXLPipelineSlowTests(unittest.TestCase):
gc.collect()
torch.cuda.empty_cache()
def test_canny(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_sequential_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)
original_image = images[0, -3:, -3:, -1].flatten()
assert numpy_cosine_similarity_distance(original_image, expected_image) < 1e-4
assert np.allclose(original_image, expected_image, atol=1e-04)
def test_canny_lora(self):
adapter = T2IAdapter.from_pretrained(
"TencentARC/t2i-adapter-lineart-sdxl-1.0", torch_dtype=torch.float16
).to("cpu")
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",
"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_sequential_cpu_offload()
@@ -615,7 +595,7 @@ class AdapterSDXLPipelineSlowTests(unittest.TestCase):
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"
"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
@@ -623,6 +603,7 @@ class AdapterSDXLPipelineSlowTests(unittest.TestCase):
assert images[0].shape == (768, 512, 3)
original_image = images[0, -3:, -3:, -1].flatten()
expected_image = np.array([0.50346327, 0.50708383, 0.50719553, 0.5135172, 0.5155377, 0.5066059, 0.49680984, 0.5005894, 0.48509413])
expected_image = np.array(
[0.50346327, 0.50708383, 0.50719553, 0.5135172, 0.5155377, 0.5066059, 0.49680984, 0.5005894, 0.48509413]
)
assert numpy_cosine_similarity_distance(original_image, expected_image) < 1e-4