mirror of
https://github.com/leejet/stable-diffusion.cpp.git
synced 2025-12-12 13:28:37 +00:00
Compare commits
6 Commits
master-402
...
master
| Author | SHA1 | Date | |
|---|---|---|---|
|
|
8823dc48bc | ||
|
|
1ac5a616de | ||
|
|
d939f6e86a | ||
|
|
e72aea796e | ||
|
|
a908436729 | ||
|
|
583a02e29e |
@ -87,6 +87,38 @@ file(GLOB SD_LIB_SOURCES
|
||||
"*.hpp"
|
||||
)
|
||||
|
||||
find_program(GIT_EXE NAMES git git.exe NO_CMAKE_FIND_ROOT_PATH)
|
||||
if(GIT_EXE)
|
||||
execute_process(COMMAND ${GIT_EXE} describe --tags --abbrev=7 --dirty=+
|
||||
WORKING_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR}
|
||||
OUTPUT_VARIABLE SDCPP_BUILD_VERSION
|
||||
OUTPUT_STRIP_TRAILING_WHITESPACE
|
||||
ERROR_QUIET
|
||||
)
|
||||
execute_process(COMMAND ${GIT_EXE} rev-parse --short HEAD
|
||||
WORKING_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR}
|
||||
OUTPUT_VARIABLE SDCPP_BUILD_COMMIT
|
||||
OUTPUT_STRIP_TRAILING_WHITESPACE
|
||||
ERROR_QUIET
|
||||
)
|
||||
endif()
|
||||
|
||||
if(NOT SDCPP_BUILD_VERSION)
|
||||
set(SDCPP_BUILD_VERSION unknown)
|
||||
endif()
|
||||
message(STATUS "stable-diffusion.cpp version ${SDCPP_BUILD_VERSION}")
|
||||
|
||||
if(NOT SDCPP_BUILD_COMMIT)
|
||||
set(SDCPP_BUILD_COMMIT unknown)
|
||||
endif()
|
||||
message(STATUS "stable-diffusion.cpp commit ${SDCPP_BUILD_COMMIT}")
|
||||
|
||||
set_property(
|
||||
SOURCE ${CMAKE_CURRENT_SOURCE_DIR}/version.cpp
|
||||
APPEND PROPERTY COMPILE_DEFINITIONS
|
||||
SDCPP_BUILD_COMMIT=${SDCPP_BUILD_COMMIT} SDCPP_BUILD_VERSION=${SDCPP_BUILD_VERSION}
|
||||
)
|
||||
|
||||
if(SD_BUILD_SHARED_LIBS)
|
||||
message("-- Build shared library")
|
||||
message(${SD_LIB_SOURCES})
|
||||
|
||||
@ -105,7 +105,7 @@ API and command-line option may change frequently.***
|
||||
### Download model weights
|
||||
|
||||
- download weights(.ckpt or .safetensors or .gguf). For example
|
||||
- Stable Diffusion v1.5 from https://huggingface.co/runwayml/stable-diffusion-v1-5
|
||||
- Stable Diffusion v1.5 from https://huggingface.co/stable-diffusion-v1-5/stable-diffusion-v1-5
|
||||
|
||||
```sh
|
||||
curl -L -O https://huggingface.co/runwayml/stable-diffusion-v1-5/resolve/main/v1-5-pruned-emaonly.safetensors
|
||||
|
||||
25
clip.hpp
25
clip.hpp
@ -7,31 +7,6 @@
|
||||
|
||||
/*================================================== CLIPTokenizer ===================================================*/
|
||||
|
||||
__STATIC_INLINE__ std::pair<std::unordered_map<std::string, float>, std::string> extract_and_remove_lora(std::string text) {
|
||||
std::regex re("<lora:([^:]+):([^>]+)>");
|
||||
std::smatch matches;
|
||||
std::unordered_map<std::string, float> filename2multiplier;
|
||||
|
||||
while (std::regex_search(text, matches, re)) {
|
||||
std::string filename = matches[1].str();
|
||||
float multiplier = std::stof(matches[2].str());
|
||||
|
||||
text = std::regex_replace(text, re, "", std::regex_constants::format_first_only);
|
||||
|
||||
if (multiplier == 0.f) {
|
||||
continue;
|
||||
}
|
||||
|
||||
if (filename2multiplier.find(filename) == filename2multiplier.end()) {
|
||||
filename2multiplier[filename] = multiplier;
|
||||
} else {
|
||||
filename2multiplier[filename] += multiplier;
|
||||
}
|
||||
}
|
||||
|
||||
return std::make_pair(filename2multiplier, text);
|
||||
}
|
||||
|
||||
__STATIC_INLINE__ std::vector<std::pair<int, std::u32string>> bytes_to_unicode() {
|
||||
std::vector<std::pair<int, std::u32string>> byte_unicode_pairs;
|
||||
std::set<int> byte_set;
|
||||
|
||||
@ -156,9 +156,10 @@ struct ESRGAN : public GGMLRunner {
|
||||
|
||||
ESRGAN(ggml_backend_t backend,
|
||||
bool offload_params_to_cpu,
|
||||
int tile_size = 128,
|
||||
const String2TensorStorage& tensor_storage_map = {})
|
||||
: GGMLRunner(backend, offload_params_to_cpu) {
|
||||
// rrdb_net will be created in load_from_file
|
||||
this->tile_size = tile_size;
|
||||
}
|
||||
|
||||
std::string get_desc() override {
|
||||
|
||||
@ -324,6 +324,7 @@ struct SDCliParams {
|
||||
std::string output_path = "output.png";
|
||||
|
||||
bool verbose = false;
|
||||
bool version = false;
|
||||
bool canny_preprocess = false;
|
||||
|
||||
preview_t preview_method = PREVIEW_NONE;
|
||||
@ -366,6 +367,10 @@ struct SDCliParams {
|
||||
"--verbose",
|
||||
"print extra info",
|
||||
true, &verbose},
|
||||
{"",
|
||||
"--version",
|
||||
"print stable-diffusion.cpp version",
|
||||
true, &version},
|
||||
{"",
|
||||
"--color",
|
||||
"colors the logging tags according to level",
|
||||
@ -502,7 +507,7 @@ struct SDContextParams {
|
||||
std::string lora_model_dir;
|
||||
|
||||
std::map<std::string, std::string> embedding_map;
|
||||
std::vector<sd_embedding_t> embedding_array;
|
||||
std::vector<sd_embedding_t> embedding_vec;
|
||||
|
||||
rng_type_t rng_type = CUDA_RNG;
|
||||
rng_type_t sampler_rng_type = RNG_TYPE_COUNT;
|
||||
@ -947,13 +952,13 @@ 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());
|
||||
embedding_vec.clear();
|
||||
embedding_vec.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);
|
||||
embedding_vec.emplace_back(item);
|
||||
}
|
||||
|
||||
sd_ctx_params_t sd_ctx_params = {
|
||||
@ -970,8 +975,8 @@ struct SDContextParams {
|
||||
taesd_path.c_str(),
|
||||
control_net_path.c_str(),
|
||||
lora_model_dir.c_str(),
|
||||
embedding_array.data(),
|
||||
static_cast<uint32_t>(embedding_array.size()),
|
||||
embedding_vec.data(),
|
||||
static_cast<uint32_t>(embedding_vec.size()),
|
||||
photo_maker_path.c_str(),
|
||||
tensor_type_rules.c_str(),
|
||||
vae_decode_only,
|
||||
@ -1025,6 +1030,15 @@ static std::string vec_str_to_string(const std::vector<std::string>& v) {
|
||||
return oss.str();
|
||||
}
|
||||
|
||||
static bool is_absolute_path(const std::string& p) {
|
||||
#ifdef _WIN32
|
||||
// Windows: C:/path or C:\path
|
||||
return p.size() > 1 && std::isalpha(static_cast<unsigned char>(p[0])) && p[1] == ':';
|
||||
#else
|
||||
return !p.empty() && p[0] == '/';
|
||||
#endif
|
||||
}
|
||||
|
||||
struct SDGenerationParams {
|
||||
std::string prompt;
|
||||
std::string negative_prompt;
|
||||
@ -1065,7 +1079,12 @@ struct SDGenerationParams {
|
||||
std::string pm_id_embed_path;
|
||||
float pm_style_strength = 20.f;
|
||||
|
||||
int upscale_repeats = 1;
|
||||
int upscale_repeats = 1;
|
||||
int upscale_tile_size = 128;
|
||||
|
||||
std::map<std::string, float> lora_map;
|
||||
std::map<std::string, float> high_noise_lora_map;
|
||||
std::vector<sd_lora_t> lora_vec;
|
||||
|
||||
SDGenerationParams() {
|
||||
sd_sample_params_init(&sample_params);
|
||||
@ -1158,6 +1177,10 @@ struct SDGenerationParams {
|
||||
"--upscale-repeats",
|
||||
"Run the ESRGAN upscaler this many times (default: 1)",
|
||||
&upscale_repeats},
|
||||
{"",
|
||||
"--upscale-tile-size",
|
||||
"tile size for ESRGAN upscaling (default: 128)",
|
||||
&upscale_tile_size},
|
||||
};
|
||||
|
||||
options.float_options = {
|
||||
@ -1437,7 +1460,88 @@ struct SDGenerationParams {
|
||||
return options;
|
||||
}
|
||||
|
||||
bool process_and_check(SDMode mode) {
|
||||
void extract_and_remove_lora(const std::string& lora_model_dir) {
|
||||
static const std::regex re(R"(<lora:([^:>]+):([^>]+)>)");
|
||||
static const std::vector<std::string> valid_ext = {".pt", ".safetensors", ".gguf"};
|
||||
std::smatch m;
|
||||
|
||||
std::string tmp = prompt;
|
||||
|
||||
while (std::regex_search(tmp, m, re)) {
|
||||
std::string raw_path = m[1].str();
|
||||
const std::string raw_mul = m[2].str();
|
||||
|
||||
float mul = 0.f;
|
||||
try {
|
||||
mul = std::stof(raw_mul);
|
||||
} catch (...) {
|
||||
tmp = m.suffix().str();
|
||||
prompt = std::regex_replace(prompt, re, "", std::regex_constants::format_first_only);
|
||||
continue;
|
||||
}
|
||||
|
||||
bool is_high_noise = false;
|
||||
static const std::string prefix = "|high_noise|";
|
||||
if (raw_path.rfind(prefix, 0) == 0) {
|
||||
raw_path.erase(0, prefix.size());
|
||||
is_high_noise = true;
|
||||
}
|
||||
|
||||
fs::path final_path;
|
||||
if (is_absolute_path(raw_path)) {
|
||||
final_path = raw_path;
|
||||
} else {
|
||||
final_path = fs::path(lora_model_dir) / raw_path;
|
||||
}
|
||||
if (!fs::exists(final_path)) {
|
||||
bool found = false;
|
||||
for (const auto& ext : valid_ext) {
|
||||
fs::path try_path = final_path;
|
||||
try_path += ext;
|
||||
if (fs::exists(try_path)) {
|
||||
final_path = try_path;
|
||||
found = true;
|
||||
break;
|
||||
}
|
||||
}
|
||||
if (!found) {
|
||||
printf("can not found lora %s\n", final_path.lexically_normal().string().c_str());
|
||||
tmp = m.suffix().str();
|
||||
prompt = std::regex_replace(prompt, re, "", std::regex_constants::format_first_only);
|
||||
continue;
|
||||
}
|
||||
}
|
||||
|
||||
const std::string key = final_path.lexically_normal().string();
|
||||
|
||||
if (is_high_noise)
|
||||
high_noise_lora_map[key] += mul;
|
||||
else
|
||||
lora_map[key] += mul;
|
||||
|
||||
prompt = std::regex_replace(prompt, re, "", std::regex_constants::format_first_only);
|
||||
|
||||
tmp = m.suffix().str();
|
||||
}
|
||||
|
||||
for (const auto& kv : lora_map) {
|
||||
sd_lora_t item;
|
||||
item.is_high_noise = false;
|
||||
item.path = kv.first.c_str();
|
||||
item.multiplier = kv.second;
|
||||
lora_vec.emplace_back(item);
|
||||
}
|
||||
|
||||
for (const auto& kv : high_noise_lora_map) {
|
||||
sd_lora_t item;
|
||||
item.is_high_noise = true;
|
||||
item.path = kv.first.c_str();
|
||||
item.multiplier = kv.second;
|
||||
lora_vec.emplace_back(item);
|
||||
}
|
||||
}
|
||||
|
||||
bool process_and_check(SDMode mode, const std::string& lora_model_dir) {
|
||||
if (width <= 0) {
|
||||
fprintf(stderr, "error: the width must be greater than 0\n");
|
||||
return false;
|
||||
@ -1536,6 +1640,10 @@ struct SDGenerationParams {
|
||||
return false;
|
||||
}
|
||||
|
||||
if (upscale_tile_size < 1) {
|
||||
return false;
|
||||
}
|
||||
|
||||
if (mode == UPSCALE) {
|
||||
if (init_image_path.length() == 0) {
|
||||
fprintf(stderr, "error: upscale mode needs an init image (--init-img)\n");
|
||||
@ -1548,14 +1656,44 @@ struct SDGenerationParams {
|
||||
seed = rand();
|
||||
}
|
||||
|
||||
extract_and_remove_lora(lora_model_dir);
|
||||
|
||||
return true;
|
||||
}
|
||||
|
||||
std::string to_string() const {
|
||||
char* sample_params_str = sd_sample_params_to_str(&sample_params);
|
||||
char* high_noise_sample_params_str = sd_sample_params_to_str(&high_noise_sample_params);
|
||||
|
||||
std::ostringstream lora_ss;
|
||||
lora_ss << "{\n";
|
||||
for (auto it = lora_map.begin(); it != lora_map.end(); ++it) {
|
||||
lora_ss << " \"" << it->first << "\": \"" << it->second << "\"";
|
||||
if (std::next(it) != lora_map.end()) {
|
||||
lora_ss << ",";
|
||||
}
|
||||
lora_ss << "\n";
|
||||
}
|
||||
lora_ss << " }";
|
||||
std::string loras_str = lora_ss.str();
|
||||
|
||||
lora_ss = std::ostringstream();
|
||||
;
|
||||
lora_ss << "{\n";
|
||||
for (auto it = high_noise_lora_map.begin(); it != high_noise_lora_map.end(); ++it) {
|
||||
lora_ss << " \"" << it->first << "\": \"" << it->second << "\"";
|
||||
if (std::next(it) != high_noise_lora_map.end()) {
|
||||
lora_ss << ",";
|
||||
}
|
||||
lora_ss << "\n";
|
||||
}
|
||||
lora_ss << " }";
|
||||
std::string high_noise_loras_str = lora_ss.str();
|
||||
|
||||
std::ostringstream oss;
|
||||
oss << "SDGenerationParams {\n"
|
||||
<< " loras: \"" << loras_str << "\",\n"
|
||||
<< " high_noise_loras: \"" << high_noise_loras_str << "\",\n"
|
||||
<< " prompt: \"" << prompt << "\",\n"
|
||||
<< " negative_prompt: \"" << negative_prompt << "\",\n"
|
||||
<< " clip_skip: " << clip_skip << ",\n"
|
||||
@ -1591,6 +1729,7 @@ struct SDGenerationParams {
|
||||
<< " control_strength: " << control_strength << ",\n"
|
||||
<< " seed: " << seed << ",\n"
|
||||
<< " upscale_repeats: " << upscale_repeats << ",\n"
|
||||
<< " upscale_tile_size: " << upscale_tile_size << ",\n"
|
||||
<< "}";
|
||||
free(sample_params_str);
|
||||
free(high_noise_sample_params_str);
|
||||
@ -1598,7 +1737,12 @@ struct SDGenerationParams {
|
||||
}
|
||||
};
|
||||
|
||||
static std::string version_string() {
|
||||
return std::string("stable-diffusion.cpp version ") + sd_version() + ", commit " + sd_commit();
|
||||
}
|
||||
|
||||
void print_usage(int argc, const char* argv[], const std::vector<ArgOptions>& options_list) {
|
||||
std::cout << version_string() << "\n";
|
||||
std::cout << "Usage: " << argv[0] << " [options]\n\n";
|
||||
std::cout << "CLI Options:\n";
|
||||
options_list[0].print();
|
||||
@ -1616,7 +1760,9 @@ void parse_args(int argc, const char** argv, SDCliParams& cli_params, SDContextP
|
||||
exit(cli_params.normal_exit ? 0 : 1);
|
||||
}
|
||||
|
||||
if (!cli_params.process_and_check() || !ctx_params.process_and_check(cli_params.mode) || !gen_params.process_and_check(cli_params.mode)) {
|
||||
if (!cli_params.process_and_check() ||
|
||||
!ctx_params.process_and_check(cli_params.mode) ||
|
||||
!gen_params.process_and_check(cli_params.mode, ctx_params.lora_model_dir)) {
|
||||
print_usage(argc, argv, options_vec);
|
||||
exit(1);
|
||||
}
|
||||
@ -1881,11 +2027,19 @@ void step_callback(int step, int frame_count, sd_image_t* image, bool is_noisy,
|
||||
}
|
||||
|
||||
int main(int argc, const char* argv[]) {
|
||||
if (argc > 1 && std::string(argv[1]) == "--version") {
|
||||
std::cout << version_string() << "\n";
|
||||
return EXIT_SUCCESS;
|
||||
}
|
||||
|
||||
SDCliParams cli_params;
|
||||
SDContextParams ctx_params;
|
||||
SDGenerationParams gen_params;
|
||||
|
||||
parse_args(argc, argv, cli_params, ctx_params, gen_params);
|
||||
if (cli_params.verbose || cli_params.version) {
|
||||
std::cout << version_string() << "\n";
|
||||
}
|
||||
if (gen_params.video_frames > 4) {
|
||||
size_t last_dot_pos = cli_params.preview_path.find_last_of(".");
|
||||
std::string base_path = cli_params.preview_path;
|
||||
@ -2121,6 +2275,8 @@ int main(int argc, const char* argv[]) {
|
||||
|
||||
if (cli_params.mode == IMG_GEN) {
|
||||
sd_img_gen_params_t img_gen_params = {
|
||||
gen_params.lora_vec.data(),
|
||||
static_cast<uint32_t>(gen_params.lora_vec.size()),
|
||||
gen_params.prompt.c_str(),
|
||||
gen_params.negative_prompt.c_str(),
|
||||
gen_params.clip_skip,
|
||||
@ -2152,6 +2308,8 @@ int main(int argc, const char* argv[]) {
|
||||
num_results = gen_params.batch_count;
|
||||
} else if (cli_params.mode == VID_GEN) {
|
||||
sd_vid_gen_params_t vid_gen_params = {
|
||||
gen_params.lora_vec.data(),
|
||||
static_cast<uint32_t>(gen_params.lora_vec.size()),
|
||||
gen_params.prompt.c_str(),
|
||||
gen_params.negative_prompt.c_str(),
|
||||
gen_params.clip_skip,
|
||||
@ -2188,7 +2346,8 @@ int main(int argc, const char* argv[]) {
|
||||
upscaler_ctx_t* upscaler_ctx = new_upscaler_ctx(ctx_params.esrgan_path.c_str(),
|
||||
ctx_params.offload_params_to_cpu,
|
||||
ctx_params.diffusion_conv_direct,
|
||||
ctx_params.n_threads);
|
||||
ctx_params.n_threads,
|
||||
gen_params.upscale_tile_size);
|
||||
|
||||
if (upscaler_ctx == nullptr) {
|
||||
printf("new_upscaler_ctx failed\n");
|
||||
|
||||
@ -60,6 +60,14 @@
|
||||
#define SD_UNUSED(x) (void)(x)
|
||||
#endif
|
||||
|
||||
__STATIC_INLINE__ int align_up_offset(int n, int multiple) {
|
||||
return (multiple - n % multiple) % multiple;
|
||||
}
|
||||
|
||||
__STATIC_INLINE__ int align_up(int n, int multiple) {
|
||||
return n + align_up_offset(n, multiple);
|
||||
}
|
||||
|
||||
__STATIC_INLINE__ void ggml_log_callback_default(ggml_log_level level, const char* text, void*) {
|
||||
switch (level) {
|
||||
case GGML_LOG_LEVEL_DEBUG:
|
||||
|
||||
@ -91,6 +91,41 @@ const float flux_latent_rgb_proj[16][3] = {
|
||||
{-0.111849f, -0.055589f, -0.032361f}};
|
||||
float flux_latent_rgb_bias[3] = {0.024600f, -0.006937f, -0.008089f};
|
||||
|
||||
const float flux2_latent_rgb_proj[32][3] = {
|
||||
{0.000736f, -0.008385f, -0.019710f},
|
||||
{-0.001352f, -0.016392f, 0.020693f},
|
||||
{-0.006376f, 0.002428f, 0.036736f},
|
||||
{0.039384f, 0.074167f, 0.119789f},
|
||||
{0.007464f, -0.005705f, -0.004734f},
|
||||
{-0.004086f, 0.005287f, -0.000409f},
|
||||
{-0.032835f, 0.050802f, -0.028120f},
|
||||
{-0.003158f, -0.000835f, 0.000406f},
|
||||
{-0.112840f, -0.084337f, -0.023083f},
|
||||
{0.001462f, -0.006656f, 0.000549f},
|
||||
{-0.009980f, -0.007480f, 0.009702f},
|
||||
{0.032540f, 0.000214f, -0.061388f},
|
||||
{0.011023f, 0.000694f, 0.007143f},
|
||||
{-0.001468f, -0.006723f, -0.001678f},
|
||||
{-0.005921f, -0.010320f, -0.003907f},
|
||||
{-0.028434f, 0.027584f, 0.018457f},
|
||||
{0.014349f, 0.011523f, 0.000441f},
|
||||
{0.009874f, 0.003081f, 0.001507f},
|
||||
{0.002218f, 0.005712f, 0.001563f},
|
||||
{0.053010f, -0.019844f, 0.008683f},
|
||||
{-0.002507f, 0.005384f, 0.000938f},
|
||||
{-0.002177f, -0.011366f, 0.003559f},
|
||||
{-0.000261f, 0.015121f, -0.003240f},
|
||||
{-0.003944f, -0.002083f, 0.005043f},
|
||||
{-0.009138f, 0.011336f, 0.003781f},
|
||||
{0.011429f, 0.003985f, -0.003855f},
|
||||
{0.010518f, -0.005586f, 0.010131f},
|
||||
{0.007883f, 0.002912f, -0.001473f},
|
||||
{-0.003318f, -0.003160f, 0.003684f},
|
||||
{-0.034560f, -0.008740f, 0.012996f},
|
||||
{0.000166f, 0.001079f, -0.012153f},
|
||||
{0.017772f, 0.000937f, -0.011953f}};
|
||||
float flux2_latent_rgb_bias[3] = {-0.028738f, -0.098463f, -0.107619f};
|
||||
|
||||
// This one was taken straight from
|
||||
// https://github.com/Stability-AI/sd3.5/blob/8565799a3b41eb0c7ba976d18375f0f753f56402/sd3_impls.py#L288-L303
|
||||
// (MiT Licence)
|
||||
@ -128,16 +163,42 @@ const float sd_latent_rgb_proj[4][3] = {
|
||||
{-0.178022f, -0.200862f, -0.678514f}};
|
||||
float sd_latent_rgb_bias[3] = {-0.017478f, -0.055834f, -0.105825f};
|
||||
|
||||
void preview_latent_video(uint8_t* buffer, struct ggml_tensor* latents, const float (*latent_rgb_proj)[3], const float latent_rgb_bias[3], int width, int height, int frames, int dim) {
|
||||
void preview_latent_video(uint8_t* buffer, struct ggml_tensor* latents, const float (*latent_rgb_proj)[3], const float latent_rgb_bias[3], int patch_size) {
|
||||
size_t buffer_head = 0;
|
||||
|
||||
uint32_t latent_width = latents->ne[0];
|
||||
uint32_t latent_height = latents->ne[1];
|
||||
uint32_t dim = latents->ne[ggml_n_dims(latents) - 1];
|
||||
uint32_t frames = 1;
|
||||
if (ggml_n_dims(latents) == 4) {
|
||||
frames = latents->ne[2];
|
||||
}
|
||||
|
||||
uint32_t rgb_width = latent_width * patch_size;
|
||||
uint32_t rgb_height = latent_height * patch_size;
|
||||
|
||||
uint32_t unpatched_dim = dim / (patch_size * patch_size);
|
||||
|
||||
for (int k = 0; k < frames; k++) {
|
||||
for (int j = 0; j < height; j++) {
|
||||
for (int i = 0; i < width; i++) {
|
||||
size_t latent_id = (i * latents->nb[0] + j * latents->nb[1] + k * latents->nb[2]);
|
||||
for (int rgb_x = 0; rgb_x < rgb_width; rgb_x++) {
|
||||
for (int rgb_y = 0; rgb_y < rgb_height; rgb_y++) {
|
||||
int latent_x = rgb_x / patch_size;
|
||||
int latent_y = rgb_y / patch_size;
|
||||
|
||||
int channel_offset = 0;
|
||||
if (patch_size > 1) {
|
||||
channel_offset = ((rgb_y % patch_size) * patch_size + (rgb_x % patch_size));
|
||||
}
|
||||
|
||||
size_t latent_id = (latent_x * latents->nb[0] + latent_y * latents->nb[1] + k * latents->nb[2]);
|
||||
|
||||
// should be incremented by 1 for each pixel
|
||||
size_t pixel_id = k * rgb_width * rgb_height + rgb_y * rgb_width + rgb_x;
|
||||
|
||||
float r = 0, g = 0, b = 0;
|
||||
if (latent_rgb_proj != nullptr) {
|
||||
for (int d = 0; d < dim; d++) {
|
||||
float value = *(float*)((char*)latents->data + latent_id + d * latents->nb[ggml_n_dims(latents) - 1]);
|
||||
for (int d = 0; d < unpatched_dim; d++) {
|
||||
float value = *(float*)((char*)latents->data + latent_id + (d * patch_size * patch_size + channel_offset) * latents->nb[ggml_n_dims(latents) - 1]);
|
||||
r += value * latent_rgb_proj[d][0];
|
||||
g += value * latent_rgb_proj[d][1];
|
||||
b += value * latent_rgb_proj[d][2];
|
||||
@ -164,9 +225,9 @@ void preview_latent_video(uint8_t* buffer, struct ggml_tensor* latents, const fl
|
||||
g = g >= 0 ? g <= 1 ? g : 1 : 0;
|
||||
b = b >= 0 ? b <= 1 ? b : 1 : 0;
|
||||
|
||||
buffer[buffer_head++] = (uint8_t)(r * 255);
|
||||
buffer[buffer_head++] = (uint8_t)(g * 255);
|
||||
buffer[buffer_head++] = (uint8_t)(b * 255);
|
||||
buffer[pixel_id * 3 + 0] = (uint8_t)(r * 255);
|
||||
buffer[pixel_id * 3 + 1] = (uint8_t)(g * 255);
|
||||
buffer[pixel_id * 3 + 2] = (uint8_t)(b * 255);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@ -937,28 +937,17 @@ public:
|
||||
float multiplier,
|
||||
ggml_backend_t backend,
|
||||
LoraModel::filter_t lora_tensor_filter = nullptr) {
|
||||
std::string lora_name = lora_id;
|
||||
std::string high_noise_tag = "|high_noise|";
|
||||
bool is_high_noise = false;
|
||||
if (starts_with(lora_name, high_noise_tag)) {
|
||||
lora_name = lora_name.substr(high_noise_tag.size());
|
||||
std::string lora_path = lora_id;
|
||||
static std::string high_noise_tag = "|high_noise|";
|
||||
bool is_high_noise = false;
|
||||
if (starts_with(lora_path, high_noise_tag)) {
|
||||
lora_path = lora_path.substr(high_noise_tag.size());
|
||||
is_high_noise = true;
|
||||
LOG_DEBUG("high noise lora: %s", lora_name.c_str());
|
||||
LOG_DEBUG("high noise lora: %s", lora_path.c_str());
|
||||
}
|
||||
std::string st_file_path = path_join(lora_model_dir, lora_name + ".safetensors");
|
||||
std::string ckpt_file_path = path_join(lora_model_dir, lora_name + ".ckpt");
|
||||
std::string file_path;
|
||||
if (file_exists(st_file_path)) {
|
||||
file_path = st_file_path;
|
||||
} else if (file_exists(ckpt_file_path)) {
|
||||
file_path = ckpt_file_path;
|
||||
} else {
|
||||
LOG_WARN("can not find %s or %s for lora %s", st_file_path.c_str(), ckpt_file_path.c_str(), lora_name.c_str());
|
||||
return nullptr;
|
||||
}
|
||||
auto lora = std::make_shared<LoraModel>(lora_id, backend, file_path, is_high_noise ? "model.high_noise_" : "", version);
|
||||
auto lora = std::make_shared<LoraModel>(lora_id, backend, lora_path, is_high_noise ? "model.high_noise_" : "", version);
|
||||
if (!lora->load_from_file(n_threads, lora_tensor_filter)) {
|
||||
LOG_WARN("load lora tensors from %s failed", file_path.c_str());
|
||||
LOG_WARN("load lora tensors from %s failed", lora_path.c_str());
|
||||
return nullptr;
|
||||
}
|
||||
|
||||
@ -1143,12 +1132,15 @@ public:
|
||||
}
|
||||
}
|
||||
|
||||
std::string apply_loras_from_prompt(const std::string& prompt) {
|
||||
auto result_pair = extract_and_remove_lora(prompt);
|
||||
std::unordered_map<std::string, float> lora_f2m = result_pair.first; // lora_name -> multiplier
|
||||
|
||||
for (auto& kv : lora_f2m) {
|
||||
LOG_DEBUG("lora %s:%.2f", kv.first.c_str(), kv.second);
|
||||
void apply_loras(const sd_lora_t* loras, uint32_t lora_count) {
|
||||
std::unordered_map<std::string, float> lora_f2m;
|
||||
for (int i = 0; i < lora_count; i++) {
|
||||
std::string lora_id = SAFE_STR(loras[i].path);
|
||||
if (loras[i].is_high_noise) {
|
||||
lora_id = "|high_noise|" + lora_id;
|
||||
}
|
||||
lora_f2m[lora_id] = loras[i].multiplier;
|
||||
LOG_DEBUG("lora %s:%.2f", lora_id.c_str(), loras[i].multiplier);
|
||||
}
|
||||
int64_t t0 = ggml_time_ms();
|
||||
if (apply_lora_immediately) {
|
||||
@ -1159,9 +1151,7 @@ public:
|
||||
int64_t t1 = ggml_time_ms();
|
||||
if (!lora_f2m.empty()) {
|
||||
LOG_INFO("apply_loras completed, taking %.2fs", (t1 - t0) * 1.0f / 1000);
|
||||
LOG_DEBUG("prompt after extract and remove lora: \"%s\"", result_pair.second.c_str());
|
||||
}
|
||||
return result_pair.second;
|
||||
}
|
||||
|
||||
ggml_tensor* id_encoder(ggml_context* work_ctx,
|
||||
@ -1326,10 +1316,17 @@ public:
|
||||
uint32_t dim = latents->ne[ggml_n_dims(latents) - 1];
|
||||
|
||||
if (preview_mode == PREVIEW_PROJ) {
|
||||
int64_t patch_sz = 1;
|
||||
const float(*latent_rgb_proj)[channel] = nullptr;
|
||||
float* latent_rgb_bias = nullptr;
|
||||
|
||||
if (dim == 48) {
|
||||
if (dim == 128) {
|
||||
if (sd_version_is_flux2(version)) {
|
||||
latent_rgb_proj = flux2_latent_rgb_proj;
|
||||
latent_rgb_bias = flux2_latent_rgb_bias;
|
||||
patch_sz = 2;
|
||||
}
|
||||
} else if (dim == 48) {
|
||||
if (sd_version_is_wan(version)) {
|
||||
latent_rgb_proj = wan_22_latent_rgb_proj;
|
||||
latent_rgb_bias = wan_22_latent_rgb_bias;
|
||||
@ -1382,12 +1379,15 @@ public:
|
||||
frames = latents->ne[2];
|
||||
}
|
||||
|
||||
uint8_t* data = (uint8_t*)malloc(frames * width * height * channel * sizeof(uint8_t));
|
||||
uint32_t img_width = width * patch_sz;
|
||||
uint32_t img_height = height * patch_sz;
|
||||
|
||||
preview_latent_video(data, latents, latent_rgb_proj, latent_rgb_bias, width, height, frames, dim);
|
||||
uint8_t* data = (uint8_t*)malloc(frames * img_width * img_height * channel * sizeof(uint8_t));
|
||||
|
||||
preview_latent_video(data, latents, latent_rgb_proj, latent_rgb_bias, patch_sz);
|
||||
sd_image_t* images = (sd_image_t*)malloc(frames * sizeof(sd_image_t));
|
||||
for (int i = 0; i < frames; i++) {
|
||||
images[i] = {width, height, channel, data + i * width * height * channel};
|
||||
images[i] = {img_width, img_height, channel, data + i * img_width * img_height * channel};
|
||||
}
|
||||
step_callback(step, frames, images, is_noisy, step_callback_data);
|
||||
free(data);
|
||||
@ -1898,6 +1898,18 @@ public:
|
||||
return vae_scale_factor;
|
||||
}
|
||||
|
||||
int get_diffusion_model_down_factor() {
|
||||
int down_factor = 8; // unet
|
||||
if (sd_version_is_dit(version)) {
|
||||
if (sd_version_is_wan(version)) {
|
||||
down_factor = 2;
|
||||
} else {
|
||||
down_factor = 1;
|
||||
}
|
||||
}
|
||||
return down_factor;
|
||||
}
|
||||
|
||||
int get_latent_channel() {
|
||||
int latent_channel = 4;
|
||||
if (sd_version_is_dit(version)) {
|
||||
@ -2805,8 +2817,6 @@ sd_image_t* generate_image_internal(sd_ctx_t* sd_ctx,
|
||||
int sample_steps = sigmas.size() - 1;
|
||||
|
||||
int64_t t0 = ggml_time_ms();
|
||||
// Apply lora
|
||||
prompt = sd_ctx->sd->apply_loras_from_prompt(prompt);
|
||||
|
||||
// Photo Maker
|
||||
std::string prompt_text_only;
|
||||
@ -3135,22 +3145,19 @@ sd_image_t* generate_image(sd_ctx_t* sd_ctx, const sd_img_gen_params_t* sd_img_g
|
||||
sd_ctx->sd->vae_tiling_params = sd_img_gen_params->vae_tiling_params;
|
||||
int width = sd_img_gen_params->width;
|
||||
int height = sd_img_gen_params->height;
|
||||
int vae_scale_factor = sd_ctx->sd->get_vae_scale_factor();
|
||||
if (sd_version_is_dit(sd_ctx->sd->version)) {
|
||||
if (width % 16 || height % 16) {
|
||||
LOG_ERROR("Image dimensions must be must be a multiple of 16 on each axis for %s models. (Got %dx%d)",
|
||||
model_version_to_str[sd_ctx->sd->version],
|
||||
width,
|
||||
height);
|
||||
return nullptr;
|
||||
}
|
||||
} else if (width % 64 || height % 64) {
|
||||
LOG_ERROR("Image dimensions must be must be a multiple of 64 on each axis for %s models. (Got %dx%d)",
|
||||
model_version_to_str[sd_ctx->sd->version],
|
||||
width,
|
||||
height);
|
||||
return nullptr;
|
||||
|
||||
int vae_scale_factor = sd_ctx->sd->get_vae_scale_factor();
|
||||
int diffusion_model_down_factor = sd_ctx->sd->get_diffusion_model_down_factor();
|
||||
int spatial_multiple = vae_scale_factor * diffusion_model_down_factor;
|
||||
|
||||
int width_offset = align_up_offset(width, spatial_multiple);
|
||||
int height_offset = align_up_offset(height, spatial_multiple);
|
||||
if (width_offset > 0 || height_offset > 0) {
|
||||
width += width_offset;
|
||||
height += height_offset;
|
||||
LOG_WARN("align up %dx%d to %dx%d (multiple=%d)", sd_img_gen_params->width, sd_img_gen_params->height, width, height, spatial_multiple);
|
||||
}
|
||||
|
||||
LOG_DEBUG("generate_image %dx%d", width, height);
|
||||
if (sd_ctx == nullptr || sd_img_gen_params == nullptr) {
|
||||
return nullptr;
|
||||
@ -3178,6 +3185,9 @@ sd_image_t* generate_image(sd_ctx_t* sd_ctx, const sd_img_gen_params_t* sd_img_g
|
||||
|
||||
size_t t0 = ggml_time_ms();
|
||||
|
||||
// Apply lora
|
||||
sd_ctx->sd->apply_loras(sd_img_gen_params->loras, sd_img_gen_params->lora_count);
|
||||
|
||||
enum sample_method_t sample_method = sd_img_gen_params->sample_params.sample_method;
|
||||
if (sample_method == SAMPLE_METHOD_COUNT) {
|
||||
sample_method = sd_get_default_sample_method(sd_ctx);
|
||||
@ -3421,9 +3431,19 @@ SD_API sd_image_t* generate_video(sd_ctx_t* sd_ctx, const sd_vid_gen_params_t* s
|
||||
int frames = sd_vid_gen_params->video_frames;
|
||||
frames = (frames - 1) / 4 * 4 + 1;
|
||||
int sample_steps = sd_vid_gen_params->sample_params.sample_steps;
|
||||
LOG_INFO("generate_video %dx%dx%d", width, height, frames);
|
||||
|
||||
int vae_scale_factor = sd_ctx->sd->get_vae_scale_factor();
|
||||
int vae_scale_factor = sd_ctx->sd->get_vae_scale_factor();
|
||||
int diffusion_model_down_factor = sd_ctx->sd->get_diffusion_model_down_factor();
|
||||
int spatial_multiple = vae_scale_factor * diffusion_model_down_factor;
|
||||
|
||||
int width_offset = align_up_offset(width, spatial_multiple);
|
||||
int height_offset = align_up_offset(height, spatial_multiple);
|
||||
if (width_offset > 0 || height_offset > 0) {
|
||||
width += width_offset;
|
||||
height += height_offset;
|
||||
LOG_WARN("align up %dx%d to %dx%d (multiple=%d)", sd_vid_gen_params->width, sd_vid_gen_params->height, width, height, spatial_multiple);
|
||||
}
|
||||
LOG_INFO("generate_video %dx%dx%d", width, height, frames);
|
||||
|
||||
enum sample_method_t sample_method = sd_vid_gen_params->sample_params.sample_method;
|
||||
if (sample_method == SAMPLE_METHOD_COUNT) {
|
||||
@ -3477,7 +3497,7 @@ SD_API sd_image_t* generate_video(sd_ctx_t* sd_ctx, const sd_vid_gen_params_t* s
|
||||
int64_t t0 = ggml_time_ms();
|
||||
|
||||
// Apply lora
|
||||
prompt = sd_ctx->sd->apply_loras_from_prompt(prompt);
|
||||
sd_ctx->sd->apply_loras(sd_vid_gen_params->loras, sd_vid_gen_params->lora_count);
|
||||
|
||||
ggml_tensor* init_latent = nullptr;
|
||||
ggml_tensor* clip_vision_output = nullptr;
|
||||
|
||||
@ -242,6 +242,14 @@ typedef struct {
|
||||
} sd_easycache_params_t;
|
||||
|
||||
typedef struct {
|
||||
bool is_high_noise;
|
||||
float multiplier;
|
||||
const char* path;
|
||||
} sd_lora_t;
|
||||
|
||||
typedef struct {
|
||||
const sd_lora_t* loras;
|
||||
uint32_t lora_count;
|
||||
const char* prompt;
|
||||
const char* negative_prompt;
|
||||
int clip_skip;
|
||||
@ -265,6 +273,8 @@ typedef struct {
|
||||
} sd_img_gen_params_t;
|
||||
|
||||
typedef struct {
|
||||
const sd_lora_t* loras;
|
||||
uint32_t lora_count;
|
||||
const char* prompt;
|
||||
const char* negative_prompt;
|
||||
int clip_skip;
|
||||
@ -337,7 +347,8 @@ typedef struct upscaler_ctx_t upscaler_ctx_t;
|
||||
SD_API upscaler_ctx_t* new_upscaler_ctx(const char* esrgan_path,
|
||||
bool offload_params_to_cpu,
|
||||
bool direct,
|
||||
int n_threads);
|
||||
int n_threads,
|
||||
int tile_size);
|
||||
SD_API void free_upscaler_ctx(upscaler_ctx_t* upscaler_ctx);
|
||||
|
||||
SD_API sd_image_t upscale(upscaler_ctx_t* upscaler_ctx,
|
||||
@ -359,6 +370,9 @@ SD_API bool preprocess_canny(sd_image_t image,
|
||||
float strong,
|
||||
bool inverse);
|
||||
|
||||
SD_API const char* sd_commit(void);
|
||||
SD_API const char* sd_version(void);
|
||||
|
||||
#ifdef __cplusplus
|
||||
}
|
||||
#endif
|
||||
|
||||
16
upscaler.cpp
16
upscaler.cpp
@ -9,12 +9,15 @@ struct UpscalerGGML {
|
||||
std::shared_ptr<ESRGAN> esrgan_upscaler;
|
||||
std::string esrgan_path;
|
||||
int n_threads;
|
||||
bool direct = false;
|
||||
bool direct = false;
|
||||
int tile_size = 128;
|
||||
|
||||
UpscalerGGML(int n_threads,
|
||||
bool direct = false)
|
||||
bool direct = false,
|
||||
int tile_size = 128)
|
||||
: n_threads(n_threads),
|
||||
direct(direct) {
|
||||
direct(direct),
|
||||
tile_size(tile_size) {
|
||||
}
|
||||
|
||||
bool load_from_file(const std::string& esrgan_path,
|
||||
@ -51,7 +54,7 @@ struct UpscalerGGML {
|
||||
backend = ggml_backend_cpu_init();
|
||||
}
|
||||
LOG_INFO("Upscaler weight type: %s", ggml_type_name(model_data_type));
|
||||
esrgan_upscaler = std::make_shared<ESRGAN>(backend, offload_params_to_cpu, model_loader.get_tensor_storage_map());
|
||||
esrgan_upscaler = std::make_shared<ESRGAN>(backend, offload_params_to_cpu, tile_size, model_loader.get_tensor_storage_map());
|
||||
if (direct) {
|
||||
esrgan_upscaler->set_conv2d_direct_enabled(true);
|
||||
}
|
||||
@ -113,14 +116,15 @@ struct upscaler_ctx_t {
|
||||
upscaler_ctx_t* new_upscaler_ctx(const char* esrgan_path_c_str,
|
||||
bool offload_params_to_cpu,
|
||||
bool direct,
|
||||
int n_threads) {
|
||||
int n_threads,
|
||||
int tile_size) {
|
||||
upscaler_ctx_t* upscaler_ctx = (upscaler_ctx_t*)malloc(sizeof(upscaler_ctx_t));
|
||||
if (upscaler_ctx == nullptr) {
|
||||
return nullptr;
|
||||
}
|
||||
std::string esrgan_path(esrgan_path_c_str);
|
||||
|
||||
upscaler_ctx->upscaler = new UpscalerGGML(n_threads, direct);
|
||||
upscaler_ctx->upscaler = new UpscalerGGML(n_threads, direct, tile_size);
|
||||
if (upscaler_ctx->upscaler == nullptr) {
|
||||
return nullptr;
|
||||
}
|
||||
|
||||
34
util.cpp
34
util.cpp
@ -95,20 +95,6 @@ bool is_directory(const std::string& path) {
|
||||
return (attributes != INVALID_FILE_ATTRIBUTES && (attributes & FILE_ATTRIBUTE_DIRECTORY));
|
||||
}
|
||||
|
||||
std::string get_full_path(const std::string& dir, const std::string& filename) {
|
||||
std::string full_path = dir + "\\" + filename;
|
||||
|
||||
WIN32_FIND_DATA find_file_data;
|
||||
HANDLE hFind = FindFirstFile(full_path.c_str(), &find_file_data);
|
||||
|
||||
if (hFind != INVALID_HANDLE_VALUE) {
|
||||
FindClose(hFind);
|
||||
return full_path;
|
||||
} else {
|
||||
return "";
|
||||
}
|
||||
}
|
||||
|
||||
#else // Unix
|
||||
#include <dirent.h>
|
||||
#include <sys/stat.h>
|
||||
@ -123,26 +109,6 @@ bool is_directory(const std::string& path) {
|
||||
return (stat(path.c_str(), &buffer) == 0 && S_ISDIR(buffer.st_mode));
|
||||
}
|
||||
|
||||
// TODO: add windows version
|
||||
std::string get_full_path(const std::string& dir, const std::string& filename) {
|
||||
DIR* dp = opendir(dir.c_str());
|
||||
|
||||
if (dp != nullptr) {
|
||||
struct dirent* entry;
|
||||
|
||||
while ((entry = readdir(dp)) != nullptr) {
|
||||
if (strcasecmp(entry->d_name, filename.c_str()) == 0) {
|
||||
closedir(dp);
|
||||
return dir + "/" + entry->d_name;
|
||||
}
|
||||
}
|
||||
|
||||
closedir(dp);
|
||||
}
|
||||
|
||||
return "";
|
||||
}
|
||||
|
||||
#endif
|
||||
|
||||
// get_num_physical_cores is copy from
|
||||
|
||||
1
util.h
1
util.h
@ -22,7 +22,6 @@ int round_up_to(int value, int base);
|
||||
|
||||
bool file_exists(const std::string& filename);
|
||||
bool is_directory(const std::string& path);
|
||||
std::string get_full_path(const std::string& dir, const std::string& filename);
|
||||
|
||||
std::u32string utf8_to_utf32(const std::string& utf8_str);
|
||||
std::string utf32_to_utf8(const std::u32string& utf32_str);
|
||||
|
||||
20
version.cpp
Normal file
20
version.cpp
Normal file
@ -0,0 +1,20 @@
|
||||
#include "stable-diffusion.h"
|
||||
|
||||
#ifndef SDCPP_BUILD_COMMIT
|
||||
#define SDCPP_BUILD_COMMIT unknown
|
||||
#endif
|
||||
|
||||
#ifndef SDCPP_BUILD_VERSION
|
||||
#define SDCPP_BUILD_VERSION unknown
|
||||
#endif
|
||||
|
||||
#define STRINGIZE2(x) #x
|
||||
#define STRINGIZE(x) STRINGIZE2(x)
|
||||
|
||||
const char* sd_commit(void) {
|
||||
return STRINGIZE(SDCPP_BUILD_COMMIT);
|
||||
}
|
||||
|
||||
const char* sd_version(void) {
|
||||
return STRINGIZE(SDCPP_BUILD_VERSION);
|
||||
}
|
||||
Loading…
x
Reference in New Issue
Block a user