upstream-archive/stable-diffusion.cpp
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refactor: optimize the handling of embedding (#1068)

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* optimize the handling of embedding

* support case-insensitive embedding names
This commit is contained in:
leejet
2025-12-08 23:59:04 +08:00
committed by GitHub
parent 0392273e10
commit 96c3e64057
5 changed files with 165 additions and 82 deletions
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61
examples/cli/main.cpp
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@@ -501,6 +501,9 @@ struct SDContextParams {
std::string tensor_type_rules;
std::string lora_model_dir;
std::map<std::string, std::string> embedding_map;
std::vector<sd_embedding_t> embedding_array;
rng_type_t rng_type = CUDA_RNG;
rng_type_t sampler_rng_type = RNG_TYPE_COUNT;
bool offload_params_to_cpu = false;
@@ -828,6 +831,37 @@ struct SDContextParams {
return options;
}
void build_embedding_map() {
static const std::vector<std::string> valid_ext = {".pt", ".safetensors", ".gguf"};
if (!fs::exists(embedding_dir) || !fs::is_directory(embedding_dir)) {
return;
}
for (auto& p : fs::directory_iterator(embedding_dir)) {
if (!p.is_regular_file())
continue;
auto path = p.path();
std::string ext = path.extension().string();
bool valid = false;
for (auto& e : valid_ext) {
if (ext == e) {
valid = true;
break;
}
}
if (!valid)
continue;
std::string key = path.stem().string();
std::string value = path.string();
embedding_map[key] = value;
}
}
bool process_and_check(SDMode mode) {
if (mode != UPSCALE && model_path.length() == 0 && diffusion_model_path.length() == 0) {
fprintf(stderr, "error: the following arguments are required: model_path/diffusion_model\n");
@@ -845,10 +879,24 @@ struct SDContextParams {
n_threads = sd_get_num_physical_cores();
}
build_embedding_map();
return true;
}
std::string to_string() const {
std::ostringstream emb_ss;
emb_ss << "{\n";
for (auto it = embedding_map.begin(); it != embedding_map.end(); ++it) {
emb_ss << " \"" << it->first << "\": \"" << it->second << "\"";
if (std::next(it) != embedding_map.end()) {
emb_ss << ",";
}
emb_ss << "\n";
}
emb_ss << " }";
std::string embeddings_str = emb_ss.str();
std::ostringstream oss;
oss << "SDContextParams {\n"
<< " n_threads: " << n_threads << ",\n"
@@ -866,6 +914,7 @@ struct SDContextParams {
<< " esrgan_path: \"" << esrgan_path << "\",\n"
<< " control_net_path: \"" << control_net_path << "\",\n"
<< " embedding_dir: \"" << embedding_dir << "\",\n"
<< " embeddings: " << embeddings_str << "\n"
<< " wtype: " << sd_type_name(wtype) << ",\n"
<< " tensor_type_rules: \"" << tensor_type_rules << "\",\n"
<< " lora_model_dir: \"" << lora_model_dir << "\",\n"
@@ -898,6 +947,15 @@ struct SDContextParams {
}
sd_ctx_params_t to_sd_ctx_params_t(bool vae_decode_only, bool free_params_immediately, bool taesd_preview) {
embedding_array.clear();
embedding_array.reserve(embedding_map.size());
for (const auto& kv : embedding_map) {
sd_embedding_t item;
item.name = kv.first.c_str();
item.path = kv.second.c_str();
embedding_array.emplace_back(item);
}
sd_ctx_params_t sd_ctx_params = {
model_path.c_str(),
clip_l_path.c_str(),
@@ -912,7 +970,8 @@ struct SDContextParams {
taesd_path.c_str(),
control_net_path.c_str(),
lora_model_dir.c_str(),
embedding_dir.c_str(),
embedding_array.data(),
static_cast<uint32_t>(embedding_array.size()),
photo_maker_path.c_str(),
tensor_type_rules.c_str(),
vae_decode_only,