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WIP on sdcpp integration

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Concedo 2024-02-29 00:40:07 +08:00
parent 1e3ac7d803
commit f75e479db0
12 changed files with 154 additions and 664 deletions
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3
Makefile
View file

@ -479,7 +479,7 @@ expose.o: expose.cpp expose.h
$(CXX) $(CXXFLAGS) -c $< -o $@
# sd.cpp objects
sdcpp_default.o: otherarch/sdcpp/util.cpp otherarch/sdcpp/sd_adapter.cpp otherarch/sdcpp/stable-diffusion.cpp otherarch/sdcpp/upscaler.cpp otherarch/sdcpp/model.cpp otherarch/sdcpp/thirdparty/zip.c
sdcpp_default.o: otherarch/sdcpp/sd_adapter.cpp otherarch/sdcpp/stable-diffusion.h otherarch/sdcpp/stable-diffusion.cpp otherarch/sdcpp/util.cpp otherarch/sdcpp/upscaler.cpp otherarch/sdcpp/model.cpp otherarch/sdcpp/thirdparty/zip.c
$(CXX) $(CXXFLAGS) -c $< -o $@
# idiotic "for easier compilation"
@ -608,6 +608,5 @@ quantize_mpt: ggml.o llama.o ggml-quants.o ggml-alloc.o ggml-backend.o otherarch
simpleclinfo: simpleclinfo.cpp
$(CXX) $(CXXFLAGS) $^ lib/OpenCL.lib lib/clblast.lib -o $@ $(LDFLAGS)
build-info.h:
$(DONOTHING)

11
expose.cpp
View file

@ -211,6 +211,15 @@ extern "C"
return gpttype_generate(inputs, output);
}
bool load_model_sd(const load_sd_model_inputs inputs)
{
return sdtype_load_model(inputs);
}
sd_generation_outputs generate_sd(const sd_generation_inputs inputs, sd_generation_outputs &output)
{
return sdtype_generate(inputs, output);
}
const char * new_token(int idx) {
if (generated_tokens.size() <= idx || idx < 0) return nullptr;
@ -263,4 +272,6 @@ extern "C"
output.ids = toks.data(); //this may be slightly unsafe
return output;
}
}

22
expose.h
View file

@ -20,7 +20,7 @@ enum stop_reason
{
INVALID=-1,
OUT_OF_TOKENS=0,
EOS_TOKEN=1,
EOS_TOKEN_HIT=1,
CUSTOM_STOPPER=2,
};
struct logit_bias {
@ -92,13 +92,31 @@ struct generation_inputs
struct generation_outputs
{
int status = -1;
char text[32768]; //32kb should be enough for any response
char text[24576]; //24kb should be enough for any response
};
struct token_count_outputs
{
int count = 0;
int * ids; //we'll just use shared memory for this one, bit of a hack
};
struct load_sd_model_inputs
{
const char * model_filename;
};
struct sd_generation_inputs
{
const char * prompt;
const char * negative_prompt;
const float cfg_scale;
const int sample_steps;
const int seed;
const char * sample_method;
};
struct sd_generation_outputs
{
int status = -1;
char data[24576];
};
extern std::string executable_path;
extern std::string lora_filename;

4
gpttype_adapter.cpp
View file

@ -949,7 +949,7 @@ ModelLoadResult gpttype_load_model(const load_model_inputs inputs, FileFormat in
#if defined(GGML_USE_CLBLAST)
if(file_format==FileFormat::GGUF_GENERIC && model_params.n_gpu_layers>0)
{
if(file_format_meta.model_architecture == GGUFArch::FALCON)
if(file_format_meta.model_architecture == GGUFArch::ARCH_FALCON)
{
printf("\nOpenCL does not support GPU Layer offloading for this model architecture! GPU Offload has been disabled.\n");
model_params.n_gpu_layers = 0;
@ -2032,7 +2032,7 @@ generation_outputs gpttype_generate(const generation_inputs inputs, generation_o
printf("\n(EOS token triggered!)");
}
remaining_tokens = 0;
last_stop_reason = stop_reason::EOS_TOKEN;
last_stop_reason = stop_reason::EOS_TOKEN_HIT;
}
for (const auto &matched : stop_sequence)

2
kcpp_docs.embd
View file

@ -316,7 +316,7 @@
},
"stop_reason": {
"type": "integer",
"description": "Reason the generation stopped. INVALID=-1, OUT_OF_TOKENS=0, EOS_TOKEN=1, CUSTOM_STOPPER=2"
"description": "Reason the generation stopped. INVALID=-1, OUT_OF_TOKENS=0, EOS_TOKEN_HIT=1, CUSTOM_STOPPER=2"
},
"queue": {
"type": "integer",

2
koboldcpp.py
View file

@ -87,7 +87,7 @@ class generation_inputs(ctypes.Structure):
class generation_outputs(ctypes.Structure):
_fields_ = [("status", ctypes.c_int),
("text", ctypes.c_char * 32768)]
("text", ctypes.c_char * 24576)]
class token_count_outputs(ctypes.Structure):
_fields_ = [("count", ctypes.c_int),

6
model_adapter.cpp
View file

@ -284,14 +284,14 @@ void print_tok_vec(std::vector<float> &embd)
int filever = gguf_get_version(ctx);
fileformatmeta->fileversion = filever;
fileformatmeta->model_architecture = GGUFArch::DEFAULT;
fileformatmeta->model_architecture = GGUFArch::ARCH_DEFAULT;
if(modelarch=="phi2")
{
fileformatmeta->model_architecture = GGUFArch::PHI;
fileformatmeta->model_architecture = GGUFArch::ARCH_PHI;
}
else if(modelarch=="falcon")
{
fileformatmeta->model_architecture = GGUFArch::FALCON;
fileformatmeta->model_architecture = GGUFArch::ARCH_FALCON;
}
}
gguf_free(ctx);

11
model_adapter.h
View file

@ -52,16 +52,16 @@ enum FileFormat
enum GGUFArch
{
DEFAULT = 0, //used for llama and other generic gguf
FALCON = 1,
PHI = 2,
ARCH_DEFAULT = 0, //used for llama and other generic gguf
ARCH_FALCON = 1,
ARCH_PHI = 2,
};
struct FileFormatExtraMeta
{
int n_ctx_train = 2048;
int fileversion = 0;
GGUFArch model_architecture = GGUFArch::DEFAULT;
GGUFArch model_architecture = GGUFArch::ARCH_DEFAULT;
int n_expert_count = 0;
};
@ -78,6 +78,9 @@ bool gpttype_generate_abort();
const std::string & gpttype_get_pending_output();
std::vector<int> gpttype_get_token_arr(const std::string & input);
bool sdtype_load_model(const load_sd_model_inputs inputs);
sd_generation_outputs sdtype_generate(const sd_generation_inputs inputs, sd_generation_outputs &output);
void timer_start();
double timer_check();
void print_tok_vec(std::vector<int> &embd);

2
otherarch/sdcpp/main.cpp
View file

@ -440,7 +440,7 @@ void parse_args(int argc, const char** argv, SDParams& params) {
exit(1);
}
if (params.n_threads <= 0) {
params.n_threads = get_num_physical_cores();
params.n_threads = sd_get_num_physical_cores();
}
if (params.mode != CONVERT && params.mode != IMG2VID && params.prompt.length() == 0) {

749
otherarch/sdcpp/sd_adapter.cpp
View file

@ -6,6 +6,14 @@
#include <string>
#include <vector>
#include "model_adapter.h"
#include "stable-diffusion.cpp"
#include "util.cpp"
#include "upscaler.cpp"
#include "model.cpp"
#include "zip.c"
// #include "preprocessing.hpp"
#include "stable-diffusion.h"
@ -99,679 +107,130 @@ struct SDParams {
int upscale_repeats = 1;
};
void print_params(SDParams params) {
printf("Option: \n");
printf(" n_threads: %d\n", params.n_threads);
printf(" mode: %s\n", modes_str[params.mode]);
printf(" model_path: %s\n", params.model_path.c_str());
printf(" wtype: %s\n", params.wtype < SD_TYPE_COUNT ? sd_type_name(params.wtype) : "unspecified");
printf(" vae_path: %s\n", params.vae_path.c_str());
printf(" taesd_path: %s\n", params.taesd_path.c_str());
printf(" esrgan_path: %s\n", params.esrgan_path.c_str());
printf(" controlnet_path: %s\n", params.controlnet_path.c_str());
printf(" embeddings_path: %s\n", params.embeddings_path.c_str());
printf(" output_path: %s\n", params.output_path.c_str());
printf(" init_img: %s\n", params.input_path.c_str());
printf(" control_image: %s\n", params.control_image_path.c_str());
printf(" controlnet cpu: %s\n", params.control_net_cpu ? "true" : "false");
printf(" strength(control): %.2f\n", params.control_strength);
printf(" prompt: %s\n", params.prompt.c_str());
printf(" negative_prompt: %s\n", params.negative_prompt.c_str());
printf(" min_cfg: %.2f\n", params.min_cfg);
printf(" cfg_scale: %.2f\n", params.cfg_scale);
printf(" clip_skip: %d\n", params.clip_skip);
printf(" width: %d\n", params.width);
printf(" height: %d\n", params.height);
printf(" sample_method: %s\n", sample_method_str[params.sample_method]);
printf(" schedule: %s\n", schedule_str[params.schedule]);
printf(" sample_steps: %d\n", params.sample_steps);
printf(" strength(img2img): %.2f\n", params.strength);
printf(" rng: %s\n", rng_type_to_str[params.rng_type]);
printf(" seed: %ld\n", params.seed);
printf(" batch_count: %d\n", params.batch_count);
printf(" vae_tiling: %s\n", params.vae_tiling ? "true" : "false");
printf(" upscale_repeats: %d\n", params.upscale_repeats);
}
//global static vars for SD
static SDParams * sd_params = nullptr;
static sd_ctx_t * sd_ctx = nullptr;
void print_usage(int argc, const char* argv[]) {
printf("usage: %s [arguments]\n", argv[0]);
printf("\n");
printf("arguments:\n");
printf(" -h, --help show this help message and exit\n");
printf(" -M, --mode [MODEL] run mode (txt2img or img2img or convert, default: txt2img)\n");
printf(" -t, --threads N number of threads to use during computation (default: -1).\n");
printf(" If threads <= 0, then threads will be set to the number of CPU physical cores\n");
printf(" -m, --model [MODEL] path to model\n");
printf(" --vae [VAE] path to vae\n");
printf(" --taesd [TAESD_PATH] path to taesd. Using Tiny AutoEncoder for fast decoding (low quality)\n");
printf(" --control-net [CONTROL_PATH] path to control net model\n");
printf(" --embd-dir [EMBEDDING_PATH] path to embeddings.\n");
printf(" --upscale-model [ESRGAN_PATH] path to esrgan model. Upscale images after generate, just RealESRGAN_x4plus_anime_6B supported by now.\n");
printf(" --upscale-repeats Run the ESRGAN upscaler this many times (default 1)\n");
printf(" --type [TYPE] weight type (f32, f16, q4_0, q4_1, q5_0, q5_1, q8_0)\n");
printf(" If not specified, the default is the type of the weight file.\n");
printf(" --lora-model-dir [DIR] lora model directory\n");
printf(" -i, --init-img [IMAGE] path to the input image, required by img2img\n");
printf(" --control-image [IMAGE] path to image condition, control net\n");
printf(" -o, --output OUTPUT path to write result image to (default: ./output.png)\n");
printf(" -p, --prompt [PROMPT] the prompt to render\n");
printf(" -n, --negative-prompt PROMPT the negative prompt (default: \"\")\n");
printf(" --cfg-scale SCALE unconditional guidance scale: (default: 7.0)\n");
printf(" --strength STRENGTH strength for noising/unnoising (default: 0.75)\n");
printf(" --control-strength STRENGTH strength to apply Control Net (default: 0.9)\n");
printf(" 1.0 corresponds to full destruction of information in init image\n");
printf(" -H, --height H image height, in pixel space (default: 512)\n");
printf(" -W, --width W image width, in pixel space (default: 512)\n");
printf(" --sampling-method {euler, euler_a, heun, dpm2, dpm++2s_a, dpm++2m, dpm++2mv2, lcm}\n");
printf(" sampling method (default: \"euler_a\")\n");
printf(" --steps STEPS number of sample steps (default: 20)\n");
printf(" --rng {std_default, cuda} RNG (default: cuda)\n");
printf(" -s SEED, --seed SEED RNG seed (default: 42, use random seed for < 0)\n");
printf(" -b, --batch-count COUNT number of images to generate.\n");
printf(" --schedule {discrete, karras} Denoiser sigma schedule (default: discrete)\n");
printf(" --clip-skip N ignore last layers of CLIP network; 1 ignores none, 2 ignores one layer (default: -1)\n");
printf(" <= 0 represents unspecified, will be 1 for SD1.x, 2 for SD2.x\n");
printf(" --vae-tiling process vae in tiles to reduce memory usage\n");
printf(" --control-net-cpu keep controlnet in cpu (for low vram)\n");
printf(" --canny apply canny preprocessor (edge detection)\n");
printf(" -v, --verbose print extra info\n");
}
bool sdtype_load_model(const load_sd_model_inputs inputs) {
sd_params = new SDParams();
sd_params->model_path = inputs.model_filename;
sd_params->wtype = SD_TYPE_F16;
sd_params->n_threads = -1; //use physical cores
sd_params->input_path = ""; //unused
void parse_args(int argc, const char** argv, SDParams& params) {
bool invalid_arg = false;
std::string arg;
for (int i = 1; i < argc; i++) {
arg = argv[i];
bool vae_decode_only = false;
if (arg == "-t" || arg == "--threads") {
if (++i >= argc) {
invalid_arg = true;
break;
}
params.n_threads = std::stoi(argv[i]);
} else if (arg == "-M" || arg == "--mode") {
if (++i >= argc) {
invalid_arg = true;
break;
}
const char* mode_selected = argv[i];
int mode_found = -1;
for (int d = 0; d < MODE_COUNT; d++) {
if (!strcmp(mode_selected, modes_str[d])) {
mode_found = d;
}
}
if (mode_found == -1) {
fprintf(stderr,
"error: invalid mode %s, must be one of [txt2img, img2img, img2vid, convert]\n",
mode_selected);
exit(1);
}
params.mode = (SDMode)mode_found;
} else if (arg == "-m" || arg == "--model") {
if (++i >= argc) {
invalid_arg = true;
break;
}
params.model_path = argv[i];
} else if (arg == "--vae") {
if (++i >= argc) {
invalid_arg = true;
break;
}
params.vae_path = argv[i];
} else if (arg == "--taesd") {
if (++i >= argc) {
invalid_arg = true;
break;
}
params.taesd_path = argv[i];
} else if (arg == "--control-net") {
if (++i >= argc) {
invalid_arg = true;
break;
}
params.controlnet_path = argv[i];
} else if (arg == "--upscale-model") {
if (++i >= argc) {
invalid_arg = true;
break;
}
params.esrgan_path = argv[i];
} else if (arg == "--embd-dir") {
if (++i >= argc) {
invalid_arg = true;
break;
}
params.embeddings_path = argv[i];
} else if (arg == "--type") {
if (++i >= argc) {
invalid_arg = true;
break;
}
std::string type = argv[i];
if (type == "f32") {
params.wtype = SD_TYPE_F32;
} else if (type == "f16") {
params.wtype = SD_TYPE_F16;
} else if (type == "q4_0") {
params.wtype = SD_TYPE_Q4_0;
} else if (type == "q4_1") {
params.wtype = SD_TYPE_Q4_1;
} else if (type == "q5_0") {
params.wtype = SD_TYPE_Q5_0;
} else if (type == "q5_1") {
params.wtype = SD_TYPE_Q5_1;
} else if (type == "q8_0") {
params.wtype = SD_TYPE_Q8_0;
} else {
fprintf(stderr, "error: invalid weight format %s, must be one of [f32, f16, q4_0, q4_1, q5_0, q5_1, q8_0]\n",
type.c_str());
exit(1);
}
} else if (arg == "--lora-model-dir") {
if (++i >= argc) {
invalid_arg = true;
break;
}
params.lora_model_dir = argv[i];
} else if (arg == "-i" || arg == "--init-img") {
if (++i >= argc) {
invalid_arg = true;
break;
}
params.input_path = argv[i];
} else if (arg == "--control-image") {
if (++i >= argc) {
invalid_arg = true;
break;
}
params.control_image_path = argv[i];
} else if (arg == "-o" || arg == "--output") {
if (++i >= argc) {
invalid_arg = true;
break;
}
params.output_path = argv[i];
} else if (arg == "-p" || arg == "--prompt") {
if (++i >= argc) {
invalid_arg = true;
break;
}
params.prompt = argv[i];
} else if (arg == "--upscale-repeats") {
if (++i >= argc) {
invalid_arg = true;
break;
}
params.upscale_repeats = std::stoi(argv[i]);
if (params.upscale_repeats < 1) {
fprintf(stderr, "error: upscale multiplier must be at least 1\n");
exit(1);
}
} else if (arg == "-n" || arg == "--negative-prompt") {
if (++i >= argc) {
invalid_arg = true;
break;
}
params.negative_prompt = argv[i];
} else if (arg == "--cfg-scale") {
if (++i >= argc) {
invalid_arg = true;
break;
}
params.cfg_scale = std::stof(argv[i]);
} else if (arg == "--strength") {
if (++i >= argc) {
invalid_arg = true;
break;
}
params.strength = std::stof(argv[i]);
} else if (arg == "--control-strength") {
if (++i >= argc) {
invalid_arg = true;
break;
}
params.control_strength = std::stof(argv[i]);
} else if (arg == "-H" || arg == "--height") {
if (++i >= argc) {
invalid_arg = true;
break;
}
params.height = std::stoi(argv[i]);
} else if (arg == "-W" || arg == "--width") {
if (++i >= argc) {
invalid_arg = true;
break;
}
params.width = std::stoi(argv[i]);
} else if (arg == "--steps") {
if (++i >= argc) {
invalid_arg = true;
break;
}
params.sample_steps = std::stoi(argv[i]);
} else if (arg == "--clip-skip") {
if (++i >= argc) {
invalid_arg = true;
break;
}
params.clip_skip = std::stoi(argv[i]);
} else if (arg == "--vae-tiling") {
params.vae_tiling = true;
} else if (arg == "--control-net-cpu") {
params.control_net_cpu = true;
} else if (arg == "--canny") {
params.canny_preprocess = true;
} else if (arg == "-b" || arg == "--batch-count") {
if (++i >= argc) {
invalid_arg = true;
break;
}
params.batch_count = std::stoi(argv[i]);
} else if (arg == "--rng") {
if (++i >= argc) {
invalid_arg = true;
break;
}
std::string rng_type_str = argv[i];
if (rng_type_str == "std_default") {
params.rng_type = STD_DEFAULT_RNG;
} else if (rng_type_str == "cuda") {
params.rng_type = CUDA_RNG;
} else {
invalid_arg = true;
break;
}
} else if (arg == "--schedule") {
if (++i >= argc) {
invalid_arg = true;
break;
}
const char* schedule_selected = argv[i];
int schedule_found = -1;
for (int d = 0; d < N_SCHEDULES; d++) {
if (!strcmp(schedule_selected, schedule_str[d])) {
schedule_found = d;
}
}
if (schedule_found == -1) {
invalid_arg = true;
break;
}
params.schedule = (schedule_t)schedule_found;
} else if (arg == "-s" || arg == "--seed") {
if (++i >= argc) {
invalid_arg = true;
break;
}
params.seed = std::stoll(argv[i]);
} else if (arg == "--sampling-method") {
if (++i >= argc) {
invalid_arg = true;
break;
}
const char* sample_method_selected = argv[i];
int sample_method_found = -1;
for (int m = 0; m < N_SAMPLE_METHODS; m++) {
if (!strcmp(sample_method_selected, sample_method_str[m])) {
sample_method_found = m;
}
}
if (sample_method_found == -1) {
invalid_arg = true;
break;
}
params.sample_method = (sample_method_t)sample_method_found;
} else if (arg == "-h" || arg == "--help") {
print_usage(argc, argv);
exit(0);
} else if (arg == "-v" || arg == "--verbose") {
params.verbose = true;
} else {
fprintf(stderr, "error: unknown argument: %s\n", arg.c_str());
print_usage(argc, argv);
exit(1);
}
}
if (invalid_arg) {
fprintf(stderr, "error: invalid parameter for argument: %s\n", arg.c_str());
print_usage(argc, argv);
exit(1);
}
if (params.n_threads <= 0) {
params.n_threads = get_num_physical_cores();
}
if (params.mode != CONVERT && params.mode != IMG2VID && params.prompt.length() == 0) {
fprintf(stderr, "error: the following arguments are required: prompt\n");
print_usage(argc, argv);
exit(1);
}
if (params.model_path.length() == 0) {
fprintf(stderr, "error: the following arguments are required: model_path\n");
print_usage(argc, argv);
exit(1);
}
if ((params.mode == IMG2IMG || params.mode == IMG2VID) && params.input_path.length() == 0) {
fprintf(stderr, "error: when using the img2img mode, the following arguments are required: init-img\n");
print_usage(argc, argv);
exit(1);
}
if (params.output_path.length() == 0) {
fprintf(stderr, "error: the following arguments are required: output_path\n");
print_usage(argc, argv);
exit(1);
}
if (params.width <= 0 || params.width % 64 != 0) {
fprintf(stderr, "error: the width must be a multiple of 64\n");
exit(1);
}
if (params.height <= 0 || params.height % 64 != 0) {
fprintf(stderr, "error: the height must be a multiple of 64\n");
exit(1);
}
if (params.sample_steps <= 0) {
fprintf(stderr, "error: the sample_steps must be greater than 0\n");
exit(1);
}
if (params.strength < 0.f || params.strength > 1.f) {
fprintf(stderr, "error: can only work with strength in [0.0, 1.0]\n");
exit(1);
}
if (params.seed < 0) {
srand((int)time(NULL));
params.seed = rand();
}
if (params.mode == CONVERT) {
if (params.output_path == "output.png") {
params.output_path = "output.gguf";
}
}
}
static std::string sd_basename(const std::string& path) {
size_t pos = path.find_last_of('/');
if (pos != std::string::npos) {
return path.substr(pos + 1);
}
pos = path.find_last_of('\\');
if (pos != std::string::npos) {
return path.substr(pos + 1);
}
return path;
}
std::string get_image_params(SDParams params, int64_t seed) {
std::string parameter_string = params.prompt + "\n";
if (params.negative_prompt.size() != 0) {
parameter_string += "Negative prompt: " + params.negative_prompt + "\n";
}
parameter_string += "Steps: " + std::to_string(params.sample_steps) + ", ";
parameter_string += "CFG scale: " + std::to_string(params.cfg_scale) + ", ";
parameter_string += "Seed: " + std::to_string(seed) + ", ";
parameter_string += "Size: " + std::to_string(params.width) + "x" + std::to_string(params.height) + ", ";
parameter_string += "Model: " + sd_basename(params.model_path) + ", ";
parameter_string += "RNG: " + std::string(rng_type_to_str[params.rng_type]) + ", ";
parameter_string += "Sampler: " + std::string(sample_method_str[params.sample_method]);
if (params.schedule == KARRAS) {
parameter_string += " karras";
}
parameter_string += ", ";
parameter_string += "Version: stable-diffusion.cpp";
return parameter_string;
}
void sd_log_cb(enum sd_log_level_t level, const char* log, void* data) {
SDParams* params = (SDParams*)data;
if (!params->verbose && level <= SD_LOG_DEBUG) {
return;
}
if (level <= SD_LOG_INFO) {
fputs(log, stdout);
fflush(stdout);
} else {
fputs(log, stderr);
fflush(stderr);
}
}
int load_sd_model() {
SDParams params;
sd_set_log_callback(sd_log_cb, (void*)&params);
if (params.verbose) {
print_params(params);
printf("%s", sd_get_system_info());
}
if (params.mode == CONVERT) {
bool success = convert(params.model_path.c_str(), params.vae_path.c_str(), params.output_path.c_str(), params.wtype);
if (!success) {
fprintf(stderr,
"convert '%s'/'%s' to '%s' failed\n",
params.model_path.c_str(),
params.vae_path.c_str(),
params.output_path.c_str());
return 1;
} else {
printf("convert '%s'/'%s' to '%s' success\n",
params.model_path.c_str(),
params.vae_path.c_str(),
params.output_path.c_str());
return 0;
}
}
if (params.mode == IMG2VID) {
fprintf(stderr, "SVD support is broken, do not use it!!!\n");
return 1;
}
bool vae_decode_only = true;
uint8_t* input_image_buffer = NULL;
if (params.mode == IMG2IMG || params.mode == IMG2VID) {
vae_decode_only = false;
int c = 0;
input_image_buffer = stbi_load(params.input_path.c_str(), &params.width, &params.height, &c, 3);
if (input_image_buffer == NULL) {
fprintf(stderr, "load image from '%s' failed\n", params.input_path.c_str());
return 1;
}
if (c != 3) {
fprintf(stderr, "input image must be a 3 channels RGB image, but got %d channels\n", c);
free(input_image_buffer);
return 1;
}
if (params.width <= 0 || params.width % 64 != 0) {
fprintf(stderr, "error: the width of image must be a multiple of 64\n");
free(input_image_buffer);
return 1;
}
if (params.height <= 0 || params.height % 64 != 0) {
fprintf(stderr, "error: the height of image must be a multiple of 64\n");
free(input_image_buffer);
return 1;
}
}
sd_ctx_t* sd_ctx = new_sd_ctx(params.model_path.c_str(),
params.vae_path.c_str(),
params.taesd_path.c_str(),
params.controlnet_path.c_str(),
params.lora_model_dir.c_str(),
params.embeddings_path.c_str(),
sd_ctx = new_sd_ctx(sd_params->model_path.c_str(),
sd_params->vae_path.c_str(),
sd_params->taesd_path.c_str(),
sd_params->controlnet_path.c_str(),
sd_params->lora_model_dir.c_str(),
sd_params->embeddings_path.c_str(),
vae_decode_only,
params.vae_tiling,
sd_params->vae_tiling,
true,
params.n_threads,
params.wtype,
params.rng_type,
params.schedule,
params.control_net_cpu);
sd_params->n_threads,
sd_params->wtype,
sd_params->rng_type,
sd_params->schedule,
sd_params->control_net_cpu);
if (sd_ctx == NULL) {
printf("new_sd_ctx_t failed\n");
return 1;
printf("\nError: KCPP SD Failed to create context!\n");
return false;
}
sd_image_t* results;
if (params.mode == TXT2IMG) {
sd_image_t* control_image = NULL;
if (params.controlnet_path.size() > 0 && params.control_image_path.size() > 0) {
int c = 0;
input_image_buffer = stbi_load(params.control_image_path.c_str(), &params.width, &params.height, &c, 3);
if (input_image_buffer == NULL) {
fprintf(stderr, "load image from '%s' failed\n", params.control_image_path.c_str());
return 1;
}
control_image = new sd_image_t{(uint32_t)params.width,
(uint32_t)params.height,
3,
input_image_buffer};
if (params.canny_preprocess) { // apply preprocessor
control_image->data = preprocess_canny(control_image->data,
control_image->width,
control_image->height,
0.08f,
0.08f,
0.8f,
1.0f,
false);
}
}
return true;
}
sd_generation_outputs sdtype_generate(const sd_generation_inputs inputs, sd_generation_outputs &output)
{
if(sd_ctx == nullptr || sd_params == nullptr)
{
printf("\nError: KCPP SD is not initialized!\n");
snprintf(output.data, sizeof(output.data), "%s", "");
output.status = 0;
return output;
}
uint8_t * input_image_buffer = NULL;
sd_image_t * results;
sd_image_t* control_image = NULL;
sd_params->prompt = inputs.prompt;
sd_params->negative_prompt = inputs.negative_prompt;
sd_params->cfg_scale = inputs.cfg_scale;
sd_params->sample_steps = inputs.sample_steps;
sd_params->seed = inputs.seed;
if(inputs.sample_method=="euler a") //all lowercase
{
sd_params->sample_method = sample_method_t::EULER_A;
}
else
{
sd_params->sample_method = sample_method_t::EULER_A;
}
if (sd_params->mode == TXT2IMG) {
results = txt2img(sd_ctx,
params.prompt.c_str(),
params.negative_prompt.c_str(),
params.clip_skip,
params.cfg_scale,
params.width,
params.height,
params.sample_method,
params.sample_steps,
params.seed,
params.batch_count,
sd_params->prompt.c_str(),
sd_params->negative_prompt.c_str(),
sd_params->clip_skip,
sd_params->cfg_scale,
sd_params->width,
sd_params->height,
sd_params->sample_method,
sd_params->sample_steps,
sd_params->seed,
sd_params->batch_count,
control_image,
params.control_strength);
sd_params->control_strength);
} else {
sd_image_t input_image = {(uint32_t)params.width,
(uint32_t)params.height,
sd_image_t input_image = {(uint32_t)sd_params->width,
(uint32_t)sd_params->height,
3,
input_image_buffer};
if (params.mode == IMG2VID) {
results = img2vid(sd_ctx,
input_image,
params.width,
params.height,
params.video_frames,
params.motion_bucket_id,
params.fps,
params.augmentation_level,
params.min_cfg,
params.cfg_scale,
params.sample_method,
params.sample_steps,
params.strength,
params.seed);
if (results == NULL) {
printf("generate failed\n");
free_sd_ctx(sd_ctx);
return 1;
}
size_t last = params.output_path.find_last_of(".");
std::string dummy_name = last != std::string::npos ? params.output_path.substr(0, last) : params.output_path;
for (int i = 0; i < params.video_frames; i++) {
if (results[i].data == NULL) {
continue;
}
std::string final_image_path = i > 0 ? dummy_name + "_" + std::to_string(i + 1) + ".png" : dummy_name + ".png";
stbi_write_png(final_image_path.c_str(), results[i].width, results[i].height, results[i].channel,
results[i].data, 0, get_image_params(params, params.seed + i).c_str());
printf("save result image to '%s'\n", final_image_path.c_str());
free(results[i].data);
results[i].data = NULL;
}
free(results);
free_sd_ctx(sd_ctx);
return 0;
} else {
results = img2img(sd_ctx,
input_image,
params.prompt.c_str(),
params.negative_prompt.c_str(),
params.clip_skip,
params.cfg_scale,
params.width,
params.height,
params.sample_method,
params.sample_steps,
params.strength,
params.seed,
params.batch_count);
}
results = img2img(sd_ctx,
input_image,
sd_params->prompt.c_str(),
sd_params->negative_prompt.c_str(),
sd_params->clip_skip,
sd_params->cfg_scale,
sd_params->width,
sd_params->height,
sd_params->sample_method,
sd_params->sample_steps,
sd_params->strength,
sd_params->seed,
sd_params->batch_count);
}
if (results == NULL) {
printf("generate failed\n");
free_sd_ctx(sd_ctx);
return 1;
printf("\nKCPP SD generate failed!\n");
snprintf(output.data, sizeof(output.data), "%s", "");
output.status = 0;
return output;
}
int upscale_factor = 4; // unused for RealESRGAN_x4plus_anime_6B.pth
if (params.esrgan_path.size() > 0 && params.upscale_repeats > 0) {
upscaler_ctx_t* upscaler_ctx = new_upscaler_ctx(params.esrgan_path.c_str(),
params.n_threads,
params.wtype);
if (upscaler_ctx == NULL) {
printf("new_upscaler_ctx failed\n");
} else {
for (int i = 0; i < params.batch_count; i++) {
if (results[i].data == NULL) {
continue;
}
sd_image_t current_image = results[i];
for (int u = 0; u < params.upscale_repeats; ++u) {
sd_image_t upscaled_image = upscale(upscaler_ctx, current_image, upscale_factor);
if (upscaled_image.data == NULL) {
printf("upscale failed\n");
break;
}
free(current_image.data);
current_image = upscaled_image;
}
results[i] = current_image; // Set the final upscaled image as the result
}
}
}
size_t last = params.output_path.find_last_of(".");
std::string dummy_name = last != std::string::npos ? params.output_path.substr(0, last) : params.output_path;
for (int i = 0; i < params.batch_count; i++) {
size_t last = sd_params->output_path.find_last_of(".");
std::string dummy_name = last != std::string::npos ? sd_params->output_path.substr(0, last) : sd_params->output_path;
for (int i = 0; i < sd_params->batch_count; i++) {
if (results[i].data == NULL) {
continue;
}
std::string final_image_path = i > 0 ? dummy_name + "_" + std::to_string(i + 1) + ".png" : dummy_name + ".png";
stbi_write_png(final_image_path.c_str(), results[i].width, results[i].height, results[i].channel,
results[i].data, 0, get_image_params(params, params.seed + i).c_str());
results[i].data, 0, "Made By KoboldCpp");
printf("save result image to '%s'\n", final_image_path.c_str());
free(results[i].data);
results[i].data = NULL;
}
free(results);
free_sd_ctx(sd_ctx);
return 0;
free(results);
snprintf(output.data, sizeof(output.data), "%s", "");
output.status = 1;
return output;
}

2
otherarch/sdcpp/stable-diffusion.h
View file

@ -94,7 +94,7 @@ enum sd_log_level_t {
typedef void (*sd_log_cb_t)(enum sd_log_level_t level, const char* text, void* data);
SD_API void sd_set_log_callback(sd_log_cb_t sd_log_cb, void* data);
SD_API int32_t get_num_physical_cores();
SD_API int32_t sd_get_num_physical_cores();
SD_API const char* sd_get_system_info();
typedef struct {

2
otherarch/sdcpp/util.cpp
View file

@ -126,7 +126,7 @@ std::string get_full_path(const std::string& dir, const std::string& filename) {
// get_num_physical_cores is copy from
// https://github.com/ggerganov/llama.cpp/blob/master/examples/common.cpp
// LICENSE: https://github.com/ggerganov/llama.cpp/blob/master/LICENSE
int32_t get_num_physical_cores() {
int32_t sd_get_num_physical_cores() {
#ifdef __linux__
// enumerate the set of thread siblings, num entries is num cores
std::unordered_set<std::string> siblings;