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feat: optimize cfg special cases with guidance schdeule #2033

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feat: optimize cfg special cases with guidance schdeule
stduhpf Sep 23, 2026
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stduhpf Sep 23, 2026
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106 changes: 79 additions & 27 deletions src/pipeline/diffusion_engine.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -2569,41 +2569,93 @@ sd::Tensor<float> StableDiffusionGGML::sample(const std::shared_ptr<DiffusionMod
}
}

float effective_guidance_scale = guidance_schedule.empty()
? cfg_scale
: guidance_schedule[guidance_schedule.size() - 1 - step];

float image_guidance_scale = img_cfg_scale;

constexpr float kEpsilon = 1e-5f;

bool skip_uncond = false;
if (!uncond.empty() && !needs_uncond_denoised && !use_apg_guidance) {
if (!img_uncond.empty()) {
skip_uncond = std::abs(image_guidance_scale - effective_guidance_scale) < kEpsilon;
} else {
skip_uncond = std::abs(effective_guidance_scale - 1.0f) < kEpsilon;
}
}

bool skip_img_uncond = false;
if (!img_uncond.empty() && !needs_uncond_denoised && !use_apg_guidance) {
if (!uncond.empty()) {
skip_img_uncond = std::abs(image_guidance_scale - 1.0f) < kEpsilon;
} else {
skip_img_uncond = std::abs(effective_guidance_scale - 1.0f) < kEpsilon;
}
}

cond_out = run_condition(*positive_condition, c_concat_override);
if (cond_out.empty()) {
return {};
}

if (!uncond.empty()) {
if (!step_cache.is_step_skipped()) {
compute_sample_controls(control_image,
noised_input,
timesteps_tensor,
uncond,
&controls);
}
const std::vector<int>* uncond_skip_layers = nullptr;
if (is_skiplayer_step && slg_uncond) {
LOG_VERBOSE("Skipping layers at uncond step %d\n", step);
uncond_skip_layers = &skip_layer_guidance.layers();
}
uncond_out = run_condition(uncond,
uncond.c_concat.empty() ? nullptr : &uncond.c_concat,
uncond_skip_layers,
nullptr,
true);
if (uncond_out.empty()) {
return {};
if (!skip_uncond) {
if (!step_cache.is_step_skipped()) {
compute_sample_controls(control_image,
noised_input,
timesteps_tensor,
uncond,
&controls);
}
const std::vector<int>* uncond_skip_layers = nullptr;
if (is_skiplayer_step && slg_uncond) {
LOG_VERBOSE("Skipping layers at uncond step %d\n", step);
uncond_skip_layers = &skip_layer_guidance.layers();
}
uncond_out = run_condition(uncond,
uncond.c_concat.empty() ? nullptr : &uncond.c_concat,
uncond_skip_layers,
nullptr,
true);
if (uncond_out.empty()) {
return {};
}
} else {
if (step_cache.runtime.easycache_enabled())
step_cache.runtime.easycache.reset_runtime();
if (step_cache.runtime.ucache_enabled())
step_cache.runtime.ucache.reset_runtime();
if (step_cache.runtime.cachedit_enabled())
step_cache.runtime.cachedit.reset_runtime();
if (!img_uncond.empty() && !skip_img_uncond && !step_cache.is_step_skipped()) {
compute_sample_controls(control_image,
noised_input,
timesteps_tensor,
uncond,
&controls);
}
}
}

if (!img_uncond.empty()) {
img_uncond_out = run_condition(img_uncond,
img_uncond.c_concat.empty() ? nullptr : &img_uncond.c_concat,
nullptr,
uncond_without_ref_latents ? &empty_ref_latents : nullptr,
true);
if (img_uncond_out.empty()) {
return {};
if (!skip_img_uncond) {
img_uncond_out = run_condition(img_uncond,
img_uncond.c_concat.empty() ? nullptr : &img_uncond.c_concat,
nullptr,
uncond_without_ref_latents ? &empty_ref_latents : nullptr,
true);
if (img_uncond_out.empty()) {
return {};
}
} else {
if (step_cache.runtime.easycache_enabled())
step_cache.runtime.easycache.reset_runtime();
if (step_cache.runtime.ucache_enabled())
step_cache.runtime.ucache.reset_runtime();
if (step_cache.runtime.cachedit_enabled())
step_cache.runtime.cachedit.reset_runtime();
}
}
sd::guidance::GuidanceInput guidance_input;
Expand All @@ -2613,7 +2665,7 @@ sd::Tensor<float> StableDiffusionGGML::sample(const std::shared_ptr<DiffusionMod
guidance_input.pred_uncond = uncond_out.empty() ? nullptr : &uncond_out;
guidance_input.pred_img_uncond = img_uncond_out.empty() ? nullptr : &img_uncond_out;

sd::guidance::GuiderOutput guided = guidance_schedule.empty() ? primary_guidance.forward(guidance_input, {}) : primary_guidance.forward(guidance_input, {}, guidance_schedule[guidance_schedule.size() - 1 - step]);
sd::guidance::GuiderOutput guided = primary_guidance.forward(guidance_input, {}, effective_guidance_scale);
if (guided.pred.empty()) {
return {};
}
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