"docs/source/en/vscode:/vscode.git/clone" did not exist on "7404f1e9dcdac286caf6ca3cfa43b294f61583bf"
Unverified Commit 27150793 authored by cmdr2's avatar cmdr2 Committed by GitHub
Browse files

Fix broken cpu-offloading in legacy inpainting SD pipeline (#3773)

parent 1ae15fa6
...@@ -548,7 +548,7 @@ class StableDiffusionInpaintPipelineLegacy( ...@@ -548,7 +548,7 @@ class StableDiffusionInpaintPipelineLegacy(
return timesteps, num_inference_steps - t_start return timesteps, num_inference_steps - t_start
def prepare_latents(self, image, timestep, num_images_per_prompt, dtype, device, generator): def prepare_latents(self, image, timestep, num_images_per_prompt, dtype, device, generator):
image = image.to(device=self.device, dtype=dtype) image = image.to(device=device, dtype=dtype)
init_latent_dist = self.vae.encode(image).latent_dist init_latent_dist = self.vae.encode(image).latent_dist
init_latents = init_latent_dist.sample(generator=generator) init_latents = init_latent_dist.sample(generator=generator)
init_latents = self.vae.config.scaling_factor * init_latents init_latents = self.vae.config.scaling_factor * init_latents
...@@ -558,7 +558,7 @@ class StableDiffusionInpaintPipelineLegacy( ...@@ -558,7 +558,7 @@ class StableDiffusionInpaintPipelineLegacy(
init_latents_orig = init_latents init_latents_orig = init_latents
# add noise to latents using the timesteps # add noise to latents using the timesteps
noise = randn_tensor(init_latents.shape, generator=generator, device=self.device, dtype=dtype) noise = randn_tensor(init_latents.shape, generator=generator, device=device, dtype=dtype)
init_latents = self.scheduler.add_noise(init_latents, noise, timestep) init_latents = self.scheduler.add_noise(init_latents, noise, timestep)
latents = init_latents latents = init_latents
return latents, init_latents_orig, noise return latents, init_latents_orig, noise
...@@ -710,7 +710,7 @@ class StableDiffusionInpaintPipelineLegacy( ...@@ -710,7 +710,7 @@ class StableDiffusionInpaintPipelineLegacy(
) )
# 7. Prepare mask latent # 7. Prepare mask latent
mask = mask_image.to(device=self.device, dtype=latents.dtype) mask = mask_image.to(device=device, dtype=latents.dtype)
mask = torch.cat([mask] * num_images_per_prompt) mask = torch.cat([mask] * num_images_per_prompt)
# 8. Prepare extra step kwargs. TODO: Logic should ideally just be moved out of the pipeline # 8. Prepare extra step kwargs. TODO: Logic should ideally just be moved out of the pipeline
......
Markdown is supported
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment