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/image.cpp
+8 -1
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@@ -531,6 +531,7 @@ namespace sd::pipeline {
condition_params.ref_image_params = ref_image_params;
sd->generation_progress.report("conditioning", "extensions");
sd->prepare_generation_extensions(request->pm_params,
request->pulid_params,
condition_params,
@@ -538,7 +539,8 @@ namespace sd::pipeline {
sd->compute_ip_adapter_tokens(sd_img_gen_params->ip_adapter_image, sd_img_gen_params->ip_adapter_strength);
int64_t prepare_start_ms = ggml_time_ms();
condition_params.zero_out_masked = false;
auto cond = sd->get_learned_condition(condition_params);
sd->generation_progress.report("conditioning", "positive_prompt");
auto cond = sd->get_learned_condition(condition_params);
if (cond.empty()) {
LOG_ERROR("failed to encode prompt");
return std::nullopt;
@@ -584,6 +586,7 @@ namespace sd::pipeline {
// Keep source latents in CFG, but omit source images from the text encoder.
condition_params.ref_images = nullptr;
}
sd->generation_progress.report("conditioning", "negative_prompt");
uncond = sd->get_learned_condition(condition_params);
if (uncond.empty()) {
LOG_ERROR("failed to encode negative prompt");
@@ -615,6 +618,7 @@ namespace sd::pipeline {
if (use_ref_latent_img_cfg) {
condition_params.ref_images = &empty_ref_images;
}
sd->generation_progress.report("conditioning", "image_condition");
img_uncond = sd->get_learned_condition(condition_params);
if (img_uncond.empty()) {
LOG_ERROR("failed to encode image guidance prompt");
@@ -830,6 +834,7 @@ namespace sd::pipeline {
return {};
}
sd->generation_progress.report("upscaling", "hires");
sd::Tensor<float> upscaled_tensor;
if (request.hires.upscaler == SD_HIRES_UPSCALER_MODEL) {
upscaled_tensor = upscaler->upscale_tensor(decoded);
@@ -930,6 +935,7 @@ namespace sd::pipeline {
ImageVaeAxesGuard axes_guard(sd, sd_img_gen_params, request);
SamplePlan plan(sd, sd_img_gen_params, request);
sd->generation_progress.report("preparing", "inputs");
auto latents_opt = prepare_image_generation_latents(sd,
sd_img_gen_params,
&request,
@@ -1027,6 +1033,7 @@ namespace sd::pipeline {
}
LOG_INFO("hires fix: upscaling to %dx%d", request.hires.target_width, request.hires.target_height);
sd->generation_progress.report("upscaling", "hires");
std::unique_ptr<UpscalerGGML> hires_upscaler;
if (request.hires.upscaler == SD_HIRES_UPSCALER_MODEL) {
if (sd->get_cancel_flag() == SD_CANCEL_ALL) {