From 3256b75ad827825a975b93df3198410e734801ad Mon Sep 17 00:00:00 2001 From: DarkSpark <50876682+DarkSparkAg@users.noreply.github.com> Date: Sat, 16 Mar 2024 08:54:41 -0500 Subject: [PATCH 1/2] Update to KSampler SDXL (Eff.) Changed the total number of steps when using the base model from steps to refine at step. There are two reasons I believe this is beneficial. 1) It allows EfficiencyNode users to duplicate exact image results they would get by using SDXL base and SDXL refiner separately using base comfyui. 2) It allows for iteration on an exact base image with a refiner rather than the base image changing when you increase the number of steps to add refiner steps on the end. @jags111 I couldn't find a working invite to a discord channel, but I'd be happy to join and discuss this change further with you. --- efficiency_nodes.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/efficiency_nodes.py b/efficiency_nodes.py index e5eb5ec..581e008 100644 --- a/efficiency_nodes.py +++ b/efficiency_nodes.py @@ -545,7 +545,7 @@ def process_latent_image(model, seed, steps, cfg, sampler_name, scheduler, posit # Perform base model sampling add_noise = return_with_leftover_noise = True - samples = KSamplerAdvanced().sample(model, add_noise, seed, steps, cfg, sampler_name, scheduler, + samples = KSamplerAdvanced().sample(model, add_noise, seed, end_at_step, cfg, sampler_name, scheduler, positive, negative, latent_image, start_at_step, end_at_step, return_with_leftover_noise, denoise=1.0)[0] From 4fe3b1c9174072c98faf17ee21f408c1eea7c221 Mon Sep 17 00:00:00 2001 From: DarkSpark <50876682+DarkSparkAg@users.noreply.github.com> Date: Sat, 16 Mar 2024 09:28:16 -0500 Subject: [PATCH 2/2] Bugfix Fixed an issue where setting refine_at_step above steps would unintentionally change the output of the model. --- efficiency_nodes.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/efficiency_nodes.py b/efficiency_nodes.py index 581e008..42b8f34 100644 --- a/efficiency_nodes.py +++ b/efficiency_nodes.py @@ -545,7 +545,8 @@ def process_latent_image(model, seed, steps, cfg, sampler_name, scheduler, posit # Perform base model sampling add_noise = return_with_leftover_noise = True - samples = KSamplerAdvanced().sample(model, add_noise, seed, end_at_step, cfg, sampler_name, scheduler, + base_steps = min(end_at_step, steps) + samples = KSamplerAdvanced().sample(model, add_noise, seed, base_steps, cfg, sampler_name, scheduler, positive, negative, latent_image, start_at_step, end_at_step, return_with_leftover_noise, denoise=1.0)[0]