DarthAffe/stable-diffusion.cpp
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chore: format code

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leejet committed 2026-10-24 01:23:42 +08:00
1 parent 40b1788476
commit e0ed724e28
69 files changed
+711 -441
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src/pipeline/diffusion_engine.cpp
+13 -13
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@@ -407,7 +407,7 @@ bool StableDiffusionGGML::register_row_split_runner_params(ModelComponent compon
size_t free_bytes = 0, total_bytes = 0;
ggml_backend_dev_memory(dev, &free_bytes, &total_bytes);
int64_t usable_bytes = std::max<int64_t>((int64_t)free_bytes - compute_headroom_bytes,
(int64_t)free_bytes / 8);
(int64_t)free_bytes / 8);
tensor_split[reg_index] = usable_bytes > 0 ? (float)((double)usable_bytes / (1024.0 * 1024.0)) : 1.0f;
}
@@ -511,8 +511,8 @@ bool StableDiffusionGGML::register_layer_split_runner_params(ModelComponent comp
model->set_runtime_backends(module_backends);
model->set_graph_cut_layer_split_backend_vram_limits(layer_split_vram_limits_for_backends(module_backends));
model->set_graph_cut_layer_split_enabled(true);
const bool params_follow_runtime = backend_manager.params_backend_follows_runtime(module) ||
backend_manager.params_backend_is_disk(module);
const bool params_follow_runtime = backend_manager.params_backend_follows_runtime(module) ||
backend_manager.params_backend_is_disk(module);
ggml_backend_t initial_params_backend = params_follow_runtime ? module_backends[0] : params_backend_for(module);
if (initial_params_backend == nullptr) {
return false;
@@ -1593,8 +1593,8 @@ std::shared_ptr<LoraModel> StableDiffusionGGML::load_lora_model(const ModelManag
? ModelManager::ResidencyMode::Disk
: ModelManager::ResidencyMode::ParamBackend;
auto lora = std::make_shared<LoraModel>(lora_log_id(lora_spec), backend_for(module), params_backend_for(module),
model_manager, lora_spec.file_id, version, mode,
backend_manager.params_backend_follows_runtime(module));
model_manager, lora_spec.file_id, version, mode,
backend_manager.params_backend_follows_runtime(module));
LoraModel::filter_t lora_tensor_filter = module_filter;
if (!lora_spec.tensor_name_prefix_filter.empty()) {
lora_tensor_filter = [module_filter, prefix = lora_spec.tensor_name_prefix_filter](const std::string& tensor_name) {
@@ -2008,11 +2008,11 @@ void StableDiffusionGGML::preview_image(int step,
: sd::ops::slice(latents, 2, 0, channels)
: latents;
if (preview_mode == PREVIEW_PROJ) {
int patch_sz = 1;
const float(*latent_rgb_proj)[3] = nullptr;
float* latent_rgb_bias = nullptr;
const float* latent_alpha_proj = nullptr;
float latent_alpha_bias = 1.f;
int patch_sz = 1;
const float (*latent_rgb_proj)[3] = nullptr;
float* latent_rgb_bias = nullptr;
const float* latent_alpha_proj = nullptr;
float latent_alpha_bias = 1.f;
if (channels == 128) {
if (sd_version_uses_flux2_vae(version)) {
@@ -2294,8 +2294,8 @@ sd::Tensor<float> StableDiffusionGGML::sample(const std::shared_ptr<DiffusionMod
const bool cache_qwen_prefix = version == VERSION_QWEN_IMAGE_2_1 &&
std::none_of(generation_extensions.begin(), generation_extensions.end(),
[](const auto& extension) { return extension->is_enabled(); });
using QwenPrefixInputs = std::tuple<const sd::Tensor<float>*, const sd::Tensor<int32_t>*,
const std::vector<sd::Tensor<float>>*>;
using QwenPrefixInputs = std::tuple<const sd::Tensor<float>*, const sd::Tensor<int32_t>*,
const std::vector<sd::Tensor<float>>*>;
std::vector<QwenPrefixInputs> qwen_prefix_inputs;
RunnerEndOnExit sample_control_runner_end{!control_image.empty() && control_net != nullptr ? control_net.get() : nullptr};
@@ -2596,7 +2596,7 @@ sd::Tensor<float> StableDiffusionGGML::sample(const std::shared_ptr<DiffusionMod
auto* extra = std::get_if<QwenImage21DiffusionExtra>(&diffusion_params.extra);
if (extra != nullptr) {
auto key = std::make_tuple(diffusion_params.context, extra->image_slots,
diffusion_params.ref_image_params.pass_to_dit ? diffusion_params.ref_latents : nullptr);
diffusion_params.ref_image_params.pass_to_dit ? diffusion_params.ref_latents : nullptr);
auto entry = std::find(qwen_prefix_inputs.begin(), qwen_prefix_inputs.end(), key);
extra->prefix_id = static_cast<uint64_t>(entry - qwen_prefix_inputs.begin()) + 1;
if (entry == qwen_prefix_inputs.end()) {