DarthAffe/stable-diffusion.cpp
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feat(server): report generation stages independently of previews (#2303)

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Co-authored-by: Maxime Dréan <maximedrean@proton.me>
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leejetandMaxime Dréan authored and GitHub committed 2026-11-09 02:32:27 +08:00
1 parent b43ce4badd
commit fc350be2ce
12 files changed
+259 -11
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src/pipeline/diffusion_engine.cpp
+8
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@@ -1807,6 +1807,7 @@ void StableDiffusionGGML::lora_stat() {
}
bool StableDiffusionGGML::apply_loras(const sd_lora_t* loras, uint32_t lora_count) {
generation_progress.report("preparing", "loras");
std::vector<ModelManager::LoraSpec> all_loras;
all_loras.reserve(lora_count);
for (uint32_t i = 0; i < lora_count; i++) {
@@ -2243,6 +2244,7 @@ void StableDiffusionGGML::report_sample_progress(int step,
? (now - *last_progress_us) / 1000000.f
: 0.f;
pretty_progress(showstep, (int)total_steps, step_seconds);
generation_progress.report_sample(showstep, static_cast<int64_t>(total_steps));
if (last_progress_us != nullptr) {
*last_progress_us = now;
}
@@ -2424,6 +2426,9 @@ sd::Tensor<float> StableDiffusionGGML::sample(const std::shared_ptr<DiffusionMod
int64_t last_progress_us = ggml_time_us();
sd_begin_preview_pass(static_cast<int>(steps));
generation_progress.begin_sample(static_cast<int64_t>(steps),
work_diffusion_model == high_noise_diffusion_model ? "high_noise" : high_noise_diffusion_model != nullptr ? "low_noise"
: "");
SamplePreviewContext preview = prepare_sample_preview_context();
sd::Tensor<float> processed_init_latent = denoiser->process_latent_in(init_latent);
@@ -2995,6 +3000,7 @@ int StableDiffusionGGML::align_video_frames(int frames) {
}
sd::Tensor<float> StableDiffusionGGML::encode_to_vae_latents(const sd::Tensor<float>& x) {
generation_progress.report("vae_encode");
auto latents = first_stage_model->encode(n_threads, x, vae_tiling_params, circular_x, circular_y);
if (latents.empty()) {
return {};
@@ -3015,6 +3021,7 @@ sd::Tensor<float> StableDiffusionGGML::encode_first_stage(const sd::Tensor<float
}
sd::Tensor<float> StableDiffusionGGML::decode_first_stage(const sd::Tensor<float>& x, bool decode_video) {
generation_progress.report("vae_decode");
if (sd_version_is_pid(version) || sd_version_is_minit2i(version) || version == VERSION_IRIS) {
return sd::ops::clamp((x + 1.f) * 0.5f, 0.0f, 1.0f);
}
@@ -3069,6 +3076,7 @@ sd::Tensor<float> StableDiffusionGGML::decode_ltx_audio_latent(const sd::Tensor<
if (audio_vae_model == nullptr || audio_latent.empty()) {
return {};
}
generation_progress.report("audio_decode");
auto waveform = audio_vae_model->decode(n_threads, audio_latent);
return waveform;
}