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refactor: extract model loader initialization #1844

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Merged
leejet merged 1 commit into from
Aug 2, 2026
Merged

refactor: extract model loader initialization #1844

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123 changes: 66 additions & 57 deletions src/stable-diffusion.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -696,45 +696,11 @@ class StableDiffusionGGML {
LOG_DEBUG("loaded alphas_cumprod from model file");
}

bool init(const sd_ctx_params_t* sd_ctx_params) {
n_threads = sd_ctx_params->n_threads;
enable_mmap = sd_ctx_params->enable_mmap;
stream_layers = sd_ctx_params->stream_layers;
eager_load = sd_ctx_params->eager_load;
backend_spec = SAFE_STR(sd_ctx_params->backend);
params_backend_spec = SAFE_STR(sd_ctx_params->params_backend);
split_mode_spec = SAFE_STR(sd_ctx_params->split_mode);
auto_fit_enabled = sd_ctx_params->auto_fit;
max_vram_assignment.reset(0.f);
{
std::string error;
if (!max_vram_assignment.parse(SAFE_STR(sd_ctx_params->max_vram), &error)) {
LOG_ERROR("%s", error.c_str());
return false;
}
}

std::string rpc_servers_spec = SAFE_STR(sd_ctx_params->rpc_servers);
add_rpc_devices(rpc_servers_spec);

bool use_tae = false;
bool use_audio_vae = false;
bool use_control_net = false;

rng = get_rng(sd_ctx_params->rng_type);
if (sd_ctx_params->sampler_rng_type != RNG_TYPE_COUNT && sd_ctx_params->sampler_rng_type != sd_ctx_params->rng_type) {
sampler_rng = get_rng(sd_ctx_params->sampler_rng_type);
} else {
sampler_rng = rng;
}

ggml_log_set(ggml_log_callback_default, nullptr);

model_manager = std::make_shared<ModelManager>();
model_manager->set_n_threads(n_threads);
model_manager->set_enable_mmap(enable_mmap);
ModelLoader& model_loader = model_manager->loader();

bool init_model_loader(ModelLoader& model_loader,
const sd_ctx_params_t* sd_ctx_params,
bool& use_tae,
bool& use_audio_vae,
bool& use_control_net) {
if (strlen(SAFE_STR(sd_ctx_params->model_path)) > 0) {
LOG_INFO("loading model from '%s'", sd_ctx_params->model_path);
if (!model_loader.init_from_file(sd_ctx_params->model_path)) {
Expand Down Expand Up @@ -874,24 +840,69 @@ class StableDiffusionGGML {

model_loader.convert_tensors_name();

version = model_loader.get_sd_version();
if (version == VERSION_COUNT) {
LOG_ERROR("get sd version from file failed: '%s'", SAFE_STR(sd_ctx_params->model_path));
return false;
}

auto& tensor_storage_map = model_loader.get_tensor_storage_map();

LOG_INFO("Version: %s ", model_version_to_str[version]);
ggml_type wtype = sd_type_to_ggml_type(sd_ctx_params->wtype);
std::string tensor_type_rules = SAFE_STR(sd_ctx_params->tensor_type_rules);
if (wtype != GGML_TYPE_COUNT || tensor_type_rules.size() > 0) {
model_loader.set_wtype_override(wtype, tensor_type_rules);
}

return true;
}

bool init(const sd_ctx_params_t* sd_ctx_params) {
n_threads = sd_ctx_params->n_threads;
enable_mmap = sd_ctx_params->enable_mmap;
stream_layers = sd_ctx_params->stream_layers;
eager_load = sd_ctx_params->eager_load;
backend_spec = SAFE_STR(sd_ctx_params->backend);
params_backend_spec = SAFE_STR(sd_ctx_params->params_backend);
split_mode_spec = SAFE_STR(sd_ctx_params->split_mode);
auto_fit_enabled = sd_ctx_params->auto_fit;
max_vram_assignment.reset(0.f);
{
std::string error;
if (!max_vram_assignment.parse(SAFE_STR(sd_ctx_params->max_vram), &error)) {
LOG_ERROR("%s", error.c_str());
return false;
}
}

std::string rpc_servers_spec = SAFE_STR(sd_ctx_params->rpc_servers);
add_rpc_devices(rpc_servers_spec);

bool use_tae = false;
bool use_audio_vae = false;
bool use_control_net = false;

rng = get_rng(sd_ctx_params->rng_type);
if (sd_ctx_params->sampler_rng_type != RNG_TYPE_COUNT && sd_ctx_params->sampler_rng_type != sd_ctx_params->rng_type) {
sampler_rng = get_rng(sd_ctx_params->sampler_rng_type);
} else {
sampler_rng = rng;
}

ggml_log_set(ggml_log_callback_default, nullptr);

model_manager = std::make_shared<ModelManager>();
model_manager->set_n_threads(n_threads);
model_manager->set_enable_mmap(enable_mmap);
ModelLoader& model_loader = model_manager->loader();

if (!init_model_loader(model_loader, sd_ctx_params, use_tae, use_audio_vae, use_control_net)) {
return false;
}

version = model_loader.get_sd_version();
if (version == VERSION_COUNT) {
LOG_ERROR("get sd version from file failed: '%s'", SAFE_STR(sd_ctx_params->model_path));
return false;
} else {
LOG_INFO("Version: %s ", model_version_to_str[version]);
}

if (auto_fit_enabled) {
if (!sd::backend_fit::derive_backend_specs(model_loader,
wtype,
sd_type_to_ggml_type(sd_ctx_params->wtype),
max_vram_assignment,
backend_spec,
params_backend_spec)) {
Expand Down Expand Up @@ -946,14 +957,10 @@ class StableDiffusionGGML {

if (sd_ctx_params->lora_apply_mode == LORA_APPLY_AUTO) {
bool have_quantized_weight = false;
if (wtype != GGML_TYPE_COUNT && ggml_is_quantized(wtype)) {
have_quantized_weight = true;
} else {
for (const auto& [type, _] : wtype_stat) {
if (ggml_is_quantized(type)) {
have_quantized_weight = true;
break;
}
for (const auto& [type, _] : wtype_stat) {
if (ggml_is_quantized(type)) {
have_quantized_weight = true;
break;
}
}
// Avoid full-model LoRA merge buffers on constrained setups.
Expand Down Expand Up @@ -997,6 +1004,8 @@ class StableDiffusionGGML {
use_tae = true;
}

auto& tensor_storage_map = model_loader.get_tensor_storage_map();

{
if (!ensure_backend_pair(SDBackendModule::TE) ||
!ensure_backend_pair(SDBackendModule::DIFFUSION)) {
Expand Down
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