From 0df83c79e4247e6b58c4c0aacfcb40b74db8d96e Mon Sep 17 00:00:00 2001 From: neverix Date: Tue, 3 Jan 2023 19:24:36 +0400 Subject: [PATCH] Fixes in comments in SD2 D2I (#1903) --- .../stable_diffusion/pipeline_stable_diffusion_depth2img.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_depth2img.py b/src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_depth2img.py index b5ec8fe391..1ba74d8b64 100644 --- a/src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_depth2img.py +++ b/src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_depth2img.py @@ -551,7 +551,7 @@ class StableDiffusionDepth2ImgPipeline(DiffusionPipeline): prompt, device, num_images_per_prompt, do_classifier_free_guidance, negative_prompt ) - # 4. Preprocess image + # 4. Prepare depth mask depth_mask = self.prepare_depth_map( image, depth_map, @@ -561,10 +561,10 @@ class StableDiffusionDepth2ImgPipeline(DiffusionPipeline): device, ) - # 5. Prepare depth mask + # 5. Preprocess image image = preprocess(image) - # 6. set timesteps + # 6. Set timesteps self.scheduler.set_timesteps(num_inference_steps, device=device) timesteps, num_inference_steps = self.get_timesteps(num_inference_steps, strength, device) latent_timestep = timesteps[:1].repeat(batch_size * num_images_per_prompt)