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Fix all stable diffusion (#1415)

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This commit is contained in:
Patrick von Platen
2022-11-25 12:53:10 +01:00
committed by GitHub
parent f26cde3dff
commit 2902109061
10 changed files with 56 additions and 17 deletions
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6
examples/community/clip_guided_stable_diffusion.py
View File

@@ -78,7 +78,11 @@ class CLIPGuidedStableDiffusion(DiffusionPipeline):
)
self.normalize = transforms.Normalize(mean=feature_extractor.image_mean, std=feature_extractor.image_std)
cut_out_size = feature_extractor.size if isinstance(feature_extractor.size, int) else feature_extractor.size["shortest_edge"]
cut_out_size = (
feature_extractor.size
if isinstance(feature_extractor.size, int)
else feature_extractor.size["shortest_edge"]
)
self.make_cutouts = MakeCutouts(cut_out_size)
set_requires_grad(self.text_encoder, False)

7
src/diffusers/pipelines/alt_diffusion/pipeline_alt_diffusion.py
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@@ -229,10 +229,15 @@ class AltDiffusionPipeline(DiffusionPipeline):
device = torch.device(f"cuda:{gpu_id}")
for cpu_offloaded_model in [self.unet, self.text_encoder, self.vae, self.safety_checker]:
for cpu_offloaded_model in [self.unet, self.text_encoder, self.vae]:
if cpu_offloaded_model is not None:
cpu_offload(cpu_offloaded_model, device)
if self.safety_checker is not None:
# TODO(Patrick) - there is currently a bug with cpu offload of nn.Parameter in accelerate
# fix by only offloading self.safety_checker for now
cpu_offload(self.safety_checker.vision_model)
@property
def _execution_device(self):
r"""

7
src/diffusers/pipelines/alt_diffusion/pipeline_alt_diffusion_img2img.py
View File

@@ -224,10 +224,15 @@ class AltDiffusionImg2ImgPipeline(DiffusionPipeline):
device = torch.device(f"cuda:{gpu_id}")
for cpu_offloaded_model in [self.unet, self.text_encoder, self.vae, self.safety_checker]:
for cpu_offloaded_model in [self.unet, self.text_encoder, self.vae]:
if cpu_offloaded_model is not None:
cpu_offload(cpu_offloaded_model, device)
if self.safety_checker is not None:
# TODO(Patrick) - there is currently a bug with cpu offload of nn.Parameter in accelerate
# fix by only offloading self.safety_checker for now
cpu_offload(self.safety_checker.vision_model)
@property
def _execution_device(self):
r"""

7
src/diffusers/pipelines/stable_diffusion/pipeline_cycle_diffusion.py
View File

@@ -257,10 +257,15 @@ class CycleDiffusionPipeline(DiffusionPipeline):
device = torch.device(f"cuda:{gpu_id}")
for cpu_offloaded_model in [self.unet, self.text_encoder, self.vae, self.safety_checker]:
for cpu_offloaded_model in [self.unet, self.text_encoder, self.vae]:
if cpu_offloaded_model is not None:
cpu_offload(cpu_offloaded_model, device)
if self.safety_checker is not None:
# TODO(Patrick) - there is currently a bug with cpu offload of nn.Parameter in accelerate
# fix by only offloading self.safety_checker for now
cpu_offload(self.safety_checker.vision_model)
@property
# Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline._execution_device
def _execution_device(self):

7
src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion.py
View File

@@ -228,10 +228,15 @@ class StableDiffusionPipeline(DiffusionPipeline):
device = torch.device(f"cuda:{gpu_id}")
for cpu_offloaded_model in [self.unet, self.text_encoder, self.vae, self.safety_checker]:
for cpu_offloaded_model in [self.unet, self.text_encoder, self.vae]:
if cpu_offloaded_model is not None:
cpu_offload(cpu_offloaded_model, device)
if self.safety_checker is not None:
# TODO(Patrick) - there is currently a bug with cpu offload of nn.Parameter in accelerate
# fix by only offloading self.safety_checker for now
cpu_offload(self.safety_checker.vision_model)
@property
def _execution_device(self):
r"""

7
src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_img2img.py
View File

@@ -226,10 +226,15 @@ class StableDiffusionImg2ImgPipeline(DiffusionPipeline):
device = torch.device(f"cuda:{gpu_id}")
for cpu_offloaded_model in [self.unet, self.text_encoder, self.vae, self.safety_checker]:
for cpu_offloaded_model in [self.unet, self.text_encoder, self.vae]:
if cpu_offloaded_model is not None:
cpu_offload(cpu_offloaded_model, device)
if self.safety_checker is not None:
# TODO(Patrick) - there is currently a bug with cpu offload of nn.Parameter in accelerate
# fix by only offloading self.safety_checker for now
cpu_offload(self.safety_checker.vision_model)
@property
# Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline._execution_device
def _execution_device(self):

7
src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_inpaint.py
View File

@@ -291,10 +291,15 @@ class StableDiffusionInpaintPipeline(DiffusionPipeline):
device = torch.device(f"cuda:{gpu_id}")
for cpu_offloaded_model in [self.unet, self.text_encoder, self.vae, self.safety_checker]:
for cpu_offloaded_model in [self.unet, self.text_encoder, self.vae]:
if cpu_offloaded_model is not None:
cpu_offload(cpu_offloaded_model, device)
if self.safety_checker is not None:
# TODO(Patrick) - there is currently a bug with cpu offload of nn.Parameter in accelerate
# fix by only offloading self.safety_checker for now
cpu_offload(self.safety_checker.vision_model)
# Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline.enable_xformers_memory_efficient_attention
def enable_xformers_memory_efficient_attention(self):
r"""

7
src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_inpaint_legacy.py
View File

@@ -239,10 +239,15 @@ class StableDiffusionInpaintPipelineLegacy(DiffusionPipeline):
device = torch.device(f"cuda:{gpu_id}")
for cpu_offloaded_model in [self.unet, self.text_encoder, self.vae, self.safety_checker]:
for cpu_offloaded_model in [self.unet, self.text_encoder, self.vae]:
if cpu_offloaded_model is not None:
cpu_offload(cpu_offloaded_model, device)
if self.safety_checker is not None:
# TODO(Patrick) - there is currently a bug with cpu offload of nn.Parameter in accelerate
# fix by only offloading self.safety_checker for now
cpu_offload(self.safety_checker.vision_model)
# Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.StableDiffusionPipeline.enable_xformers_memory_efficient_attention
def enable_xformers_memory_efficient_attention(self):
r"""

2
tests/pipelines/stable_diffusion/test_stable_diffusion.py
View File

@@ -948,7 +948,7 @@ class StableDiffusionPipelineIntegrationTests(unittest.TestCase):
expected_slice = np.array(
[1.8285, 1.2857, -0.1024, 1.2406, -2.3068, 1.0747, -0.0818, -0.6520, -2.9506]
)
assert np.abs(latents_slice.flatten() - expected_slice).max() < 1e-3
assert np.abs(latents_slice.flatten() - expected_slice).max() < 5e-3
elif step == 50:
latents = latents.detach().cpu().numpy()
assert latents.shape == (1, 4, 64, 64)

16
tests/pipelines/stable_diffusion_2/test_stable_diffusion.py
View File

@@ -609,11 +609,12 @@ class StableDiffusion2PipelineIntegrationTests(unittest.TestCase):
assert mem_bytes > 3.75 * 10**9
assert np.abs(image_chunked.flatten() - image.flatten()).max() < 1e-3
def test_stable_diffusion_text2img_pipeline_fp16(self):
def test_stable_diffusion_same_quality(self):
torch.cuda.reset_peak_memory_stats()
model_id = "stabilityai/stable-diffusion-2-base"
pipe = StableDiffusionPipeline.from_pretrained(model_id, revision="fp16", torch_dtype=torch.float16)
pipe = pipe.to(torch_device)
pipe.enable_attention_slicing()
pipe.set_progress_bar_config(disable=None)
prompt = "a photograph of an astronaut riding a horse"
@@ -624,18 +625,17 @@ class StableDiffusion2PipelineIntegrationTests(unittest.TestCase):
)
image_chunked = output_chunked.images
pipe = StableDiffusionPipeline.from_pretrained(model_id)
pipe = pipe.to(torch_device)
generator = torch.Generator(device=torch_device).manual_seed(0)
with torch.autocast(torch_device):
output = pipe(
[prompt], generator=generator, guidance_scale=7.5, num_inference_steps=10, output_type="numpy"
)
image = output.images
output = pipe([prompt], generator=generator, guidance_scale=7.5, num_inference_steps=10, output_type="numpy")
image = output.images
# Make sure results are close enough
diff = np.abs(image_chunked.flatten() - image.flatten())
# They ARE different since ops are not run always at the same precision
# however, they should be extremely close.
assert diff.mean() < 2e-2
assert diff.mean() < 5e-2
def test_stable_diffusion_text2img_pipeline_default(self):
expected_image = load_numpy(
@@ -669,7 +669,7 @@ class StableDiffusion2PipelineIntegrationTests(unittest.TestCase):
assert latents.shape == (1, 4, 64, 64)
latents_slice = latents[0, -3:, -3:, -1]
expected_slice = np.array([1.8606, 1.3169, -0.0691, 1.2374, -2.309, 1.077, -0.1084, -0.6774, -2.9594])
assert np.abs(latents_slice.flatten() - expected_slice).max() < 1e-3
assert np.abs(latents_slice.flatten() - expected_slice).max() < 5e-3
elif step == 20:
latents = latents.detach().cpu().numpy()
assert latents.shape == (1, 4, 64, 64)