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Make it working
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
This commit is contained in:
Ettore Di Giacinto
parent
606f21520b
commit
bef0d4ffc9
2 changed files with 24 additions and 138 deletions
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@ -23,13 +23,6 @@
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#define STB_IMAGE_RESIZE_STATIC
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#include "stb_image_resize.h"
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const char* rng_type_to_str[] = {
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"std_default",
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"cuda",
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};
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// Names of the sampler method, same order as enum sample_method in stable-diffusion.h
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const char* sample_method_str[] = {
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"euler_a",
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@ -54,131 +47,7 @@ const char* schedule_str[] = {
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"gits",
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};
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const char* modes_str[] = {
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"txt2img",
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"img2img",
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"img2vid",
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"convert",
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};
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enum SDMode {
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TXT2IMG,
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IMG2IMG,
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IMG2VID,
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CONVERT,
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MODE_COUNT
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};
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struct SDParams {
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int n_threads = -1;
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SDMode mode = TXT2IMG;
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std::string model_path;
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std::string clip_l_path;
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std::string clip_g_path;
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std::string t5xxl_path;
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std::string diffusion_model_path;
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std::string vae_path;
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std::string taesd_path;
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std::string esrgan_path;
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std::string controlnet_path;
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std::string embeddings_path;
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std::string stacked_id_embeddings_path;
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std::string input_id_images_path;
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sd_type_t wtype = SD_TYPE_COUNT;
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std::string lora_model_dir;
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std::string output_path = "output.png";
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std::string input_path;
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std::string control_image_path;
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std::string prompt;
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std::string negative_prompt;
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float min_cfg = 1.0f;
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float cfg_scale = 7.0f;
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float guidance = 3.5f;
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float style_ratio = 20.f;
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int clip_skip = -1; // <= 0 represents unspecified
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int width = 512;
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int height = 512;
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int batch_count = 1;
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int video_frames = 6;
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int motion_bucket_id = 127;
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int fps = 6;
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float augmentation_level = 0.f;
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sample_method_t sample_method = EULER_A;
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schedule_t schedule = DEFAULT;
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int sample_steps = 20;
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float strength = 0.75f;
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float control_strength = 0.9f;
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rng_type_t rng_type = CUDA_RNG;
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int64_t seed = 42;
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bool verbose = false;
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bool vae_tiling = false;
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bool control_net_cpu = false;
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bool normalize_input = false;
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bool clip_on_cpu = false;
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bool vae_on_cpu = false;
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bool diffusion_flash_attn = false;
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bool canny_preprocess = false;
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bool color = false;
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int upscale_repeats = 1;
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std::vector<int> skip_layers = {7, 8, 9};
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float slg_scale = 0.;
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float skip_layer_start = 0.01;
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float skip_layer_end = 0.2;
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};
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void print_params(SDParams params) {
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printf("Option: \n");
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printf(" n_threads: %d\n", params.n_threads);
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printf(" mode: %s\n", modes_str[params.mode]);
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printf(" model_path: %s\n", params.model_path.c_str());
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printf(" wtype: %s\n", params.wtype < SD_TYPE_COUNT ? sd_type_name(params.wtype) : "unspecified");
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printf(" clip_l_path: %s\n", params.clip_l_path.c_str());
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printf(" clip_g_path: %s\n", params.clip_g_path.c_str());
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printf(" t5xxl_path: %s\n", params.t5xxl_path.c_str());
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printf(" diffusion_model_path: %s\n", params.diffusion_model_path.c_str());
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printf(" vae_path: %s\n", params.vae_path.c_str());
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printf(" taesd_path: %s\n", params.taesd_path.c_str());
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printf(" esrgan_path: %s\n", params.esrgan_path.c_str());
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printf(" controlnet_path: %s\n", params.controlnet_path.c_str());
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printf(" embeddings_path: %s\n", params.embeddings_path.c_str());
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printf(" stacked_id_embeddings_path: %s\n", params.stacked_id_embeddings_path.c_str());
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printf(" input_id_images_path: %s\n", params.input_id_images_path.c_str());
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printf(" style ratio: %.2f\n", params.style_ratio);
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printf(" normalize input image : %s\n", params.normalize_input ? "true" : "false");
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printf(" output_path: %s\n", params.output_path.c_str());
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printf(" init_img: %s\n", params.input_path.c_str());
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printf(" control_image: %s\n", params.control_image_path.c_str());
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printf(" clip on cpu: %s\n", params.clip_on_cpu ? "true" : "false");
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printf(" controlnet cpu: %s\n", params.control_net_cpu ? "true" : "false");
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printf(" vae decoder on cpu:%s\n", params.vae_on_cpu ? "true" : "false");
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printf(" diffusion flash attention:%s\n", params.diffusion_flash_attn ? "true" : "false");
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printf(" strength(control): %.2f\n", params.control_strength);
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printf(" prompt: %s\n", params.prompt.c_str());
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printf(" negative_prompt: %s\n", params.negative_prompt.c_str());
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printf(" min_cfg: %.2f\n", params.min_cfg);
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printf(" cfg_scale: %.2f\n", params.cfg_scale);
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printf(" slg_scale: %.2f\n", params.slg_scale);
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printf(" guidance: %.2f\n", params.guidance);
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printf(" clip_skip: %d\n", params.clip_skip);
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printf(" width: %d\n", params.width);
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printf(" height: %d\n", params.height);
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printf(" sample_method: %s\n", sample_method_str[params.sample_method]);
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printf(" schedule: %s\n", schedule_str[params.schedule]);
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printf(" sample_steps: %d\n", params.sample_steps);
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printf(" strength(img2img): %.2f\n", params.strength);
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printf(" rng: %s\n", rng_type_to_str[params.rng_type]);
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printf(" seed: %ld\n", params.seed);
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printf(" batch_count: %d\n", params.batch_count);
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printf(" vae_tiling: %s\n", params.vae_tiling ? "true" : "false");
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printf(" upscale_repeats: %d\n", params.upscale_repeats);
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}
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sd_ctx_t* sd_c;
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sd_ctx_t* sd_c;
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sample_method_t sample_method;
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@ -295,6 +164,9 @@ int gen_image(char *text, char *negativeText, int width, int height, int steps,
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sd_image_t* results;
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std::vector<int> skip_layers = {7, 8, 9};
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fprintf (stderr, "Generating image\n");
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results = txt2img(sd_c,
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text,
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negativeText,
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@ -319,22 +191,35 @@ int gen_image(char *text, char *negativeText, int width, int height, int steps,
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0.2);
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if (results == NULL) {
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printf("generate failed\n");
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fprintf (stderr, "NO results\n");
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return 1;
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}
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if (results[0].data == NULL) {
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printf("generate failed\n");
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fprintf (stderr, "Results with no data\n");
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return 1;
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}
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stbi_write_png(dst, results[0].width, results[0].height, results[0].channel,
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results[0].data, 0, "");
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printf("save result image to '%s'\n", dst);
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fprintf (stderr, "Writing PNG\n");
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fprintf (stderr, "DST: %s\n", dst);
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fprintf (stderr, "Width: %d\n", results[0].width);
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fprintf (stderr, "Height: %d\n", results[0].height);
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fprintf (stderr, "Channel: %d\n", results[0].channel);
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fprintf (stderr, "Data: %p\n", results[0].data);
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stbi_write_png(dst, results[0].width, results[0].height, results[0].channel,
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results[0].data, 0, NULL);
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fprintf (stderr, "Saved resulting image to '%s'\n", dst);
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// TODO: free results. Why does it crash?
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free(results[0].data);
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results[0].data = NULL;
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free(results);
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fprintf (stderr, "gen_image is done", dst);
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return 0;
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}
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int unload() {
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@ -33,6 +33,7 @@ func (sd *SDGGML) Load(opts *pb.ModelOptions) error {
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defer C.free(unsafe.Pointer(modelFile))
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var options **C.char
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// prepare the options array to pass to C
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size := C.size_t(unsafe.Sizeof((*C.char)(nil)))
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length := C.size_t(len(opts.Options))
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