DarthAffe/stable-diffusion.cpp
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refactor: optimize the handling of sample method (#999)

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leejet 2025-11-22 14:00:25 +08:00 committed by GitHub
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4 changed files with 64 additions and 52 deletions
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28
denoiser.hpp
View File

@ -640,7 +640,7 @@ static void sample_k_diffusion(sample_method_t method,
size_t steps = sigmas.size() - 1;
// sample_euler_ancestral
switch (method) {
case EULER_A: {
case EULER_A_SAMPLE_METHOD: {
struct ggml_tensor* noise = ggml_dup_tensor(work_ctx, x);
struct ggml_tensor* d = ggml_dup_tensor(work_ctx, x);
@ -693,7 +693,7 @@ static void sample_k_diffusion(sample_method_t method,
}
}
} break;
case EULER: // Implemented without any sigma churn
case EULER_SAMPLE_METHOD: // Implemented without any sigma churn
{
struct ggml_tensor* d = ggml_dup_tensor(work_ctx, x);
@ -726,7 +726,7 @@ static void sample_k_diffusion(sample_method_t method,
}
}
} break;
case HEUN: {
case HEUN_SAMPLE_METHOD: {
struct ggml_tensor* d = ggml_dup_tensor(work_ctx, x);
struct ggml_tensor* x2 = ggml_dup_tensor(work_ctx, x);
@ -776,7 +776,7 @@ static void sample_k_diffusion(sample_method_t method,
}
}
} break;
case DPM2: {
case DPM2_SAMPLE_METHOD: {
struct ggml_tensor* d = ggml_dup_tensor(work_ctx, x);
struct ggml_tensor* x2 = ggml_dup_tensor(work_ctx, x);
@ -828,7 +828,7 @@ static void sample_k_diffusion(sample_method_t method,
}
} break;
case DPMPP2S_A: {
case DPMPP2S_A_SAMPLE_METHOD: {
struct ggml_tensor* noise = ggml_dup_tensor(work_ctx, x);
struct ggml_tensor* x2 = ggml_dup_tensor(work_ctx, x);
@ -892,7 +892,7 @@ static void sample_k_diffusion(sample_method_t method,
}
}
} break;
case DPMPP2M: // DPM++ (2M) from Karras et al (2022)
case DPMPP2M_SAMPLE_METHOD: // DPM++ (2M) from Karras et al (2022)
{
struct ggml_tensor* old_denoised = ggml_dup_tensor(work_ctx, x);
@ -931,7 +931,7 @@ static void sample_k_diffusion(sample_method_t method,
}
}
} break;
case DPMPP2Mv2: // Modified DPM++ (2M) from https://github.com/AUTOMATIC1111/stable-diffusion-webui/discussions/8457
case DPMPP2Mv2_SAMPLE_METHOD: // Modified DPM++ (2M) from https://github.com/AUTOMATIC1111/stable-diffusion-webui/discussions/8457
{
struct ggml_tensor* old_denoised = ggml_dup_tensor(work_ctx, x);
@ -974,7 +974,7 @@ static void sample_k_diffusion(sample_method_t method,
}
}
} break;
case IPNDM: // iPNDM sampler from https://github.com/zju-pi/diff-sampler/tree/main/diff-solvers-main
case IPNDM_SAMPLE_METHOD: // iPNDM sampler from https://github.com/zju-pi/diff-sampler/tree/main/diff-solvers-main
{
int max_order = 4;
ggml_tensor* x_next = x;
@ -1049,7 +1049,7 @@ static void sample_k_diffusion(sample_method_t method,
}
}
} break;
case IPNDM_V: // iPNDM_v sampler from https://github.com/zju-pi/diff-sampler/tree/main/diff-solvers-main
case IPNDM_V_SAMPLE_METHOD: // iPNDM_v sampler from https://github.com/zju-pi/diff-sampler/tree/main/diff-solvers-main
{
int max_order = 4;
std::vector<ggml_tensor*> buffer_model;
@ -1123,7 +1123,7 @@ static void sample_k_diffusion(sample_method_t method,
d_cur = ggml_dup_tensor(work_ctx, x_next);
}
} break;
case LCM: // Latent Consistency Models
case LCM_SAMPLE_METHOD: // Latent Consistency Models
{
struct ggml_tensor* noise = ggml_dup_tensor(work_ctx, x);
struct ggml_tensor* d = ggml_dup_tensor(work_ctx, x);
@ -1158,8 +1158,8 @@ static void sample_k_diffusion(sample_method_t method,
}
}
} break;
case DDIM_TRAILING: // Denoising Diffusion Implicit Models
// with the "trailing" timestep spacing
case DDIM_TRAILING_SAMPLE_METHOD: // Denoising Diffusion Implicit Models
// with the "trailing" timestep spacing
{
// See J. Song et al., "Denoising Diffusion Implicit
// Models", arXiv:2010.02502 [cs.LG]
@ -1352,8 +1352,8 @@ static void sample_k_diffusion(sample_method_t method,
// factor c_in.
}
} break;
case TCD: // Strategic Stochastic Sampling (Algorithm 4) in
// Trajectory Consistency Distillation
case TCD_SAMPLE_METHOD: // Strategic Stochastic Sampling (Algorithm 4) in
// Trajectory Consistency Distillation
{
// See J. Zheng et al., "Trajectory Consistency
// Distillation: Improved Latent Consistency Distillation

6
examples/cli/main.cpp
View File

@ -1902,10 +1902,14 @@ int main(int argc, const char* argv[]) {
return 1;
}
if (params.sample_params.sample_method == SAMPLE_METHOD_DEFAULT) {
if (params.sample_params.sample_method == SAMPLE_METHOD_COUNT) {
params.sample_params.sample_method = sd_get_default_sample_method(sd_ctx);
}
if (params.high_noise_sample_params.sample_method == SAMPLE_METHOD_COUNT) {
params.high_noise_sample_params.sample_method = sd_get_default_sample_method(sd_ctx);
}
if (params.sample_params.scheduler == SCHEDULER_COUNT) {
params.sample_params.scheduler = sd_get_default_scheduler(sd_ctx);
}

57
stable-diffusion.cpp
View File

@ -47,8 +47,8 @@ const char* model_version_to_str[] = {
};
const char* sampling_methods_str[] = {
"default",
"Euler",
"Euler A",
"Heun",
"DPM2",
"DPM++ (2s)",
@ -59,7 +59,6 @@ const char* sampling_methods_str[] = {
"LCM",
"DDIM \"trailing\"",
"TCD",
"Euler A",
};
/*================================================== Helper Functions ================================================*/
@ -2228,8 +2227,8 @@ enum rng_type_t str_to_rng_type(const char* str) {
}
const char* sample_method_to_str[] = {
"default",
"euler",
"euler_a",
"heun",
"dpm2",
"dpm++2s_a",
@ -2240,7 +2239,6 @@ const char* sample_method_to_str[] = {
"lcm",
"ddim_trailing",
"tcd",
"euler_a",
};
const char* sd_sample_method_name(enum sample_method_t sample_method) {
@ -2469,7 +2467,7 @@ void sd_sample_params_init(sd_sample_params_t* sample_params) {
sample_params->guidance.slg.layer_end = 0.2f;
sample_params->guidance.slg.scale = 0.f;
sample_params->scheduler = SCHEDULER_COUNT;
sample_params->sample_method = SAMPLE_METHOD_DEFAULT;
sample_params->sample_method = SAMPLE_METHOD_COUNT;
sample_params->sample_steps = 20;
}
@ -2627,19 +2625,19 @@ void free_sd_ctx(sd_ctx_t* sd_ctx) {
enum sample_method_t sd_get_default_sample_method(const sd_ctx_t* sd_ctx) {
if (sd_ctx != nullptr && sd_ctx->sd != nullptr) {
SDVersion version = sd_ctx->sd->version;
if (sd_version_is_dit(version))
return EULER;
else
return EULER_A;
if (sd_version_is_dit(sd_ctx->sd->version)) {
return EULER_SAMPLE_METHOD;
}
}
return SAMPLE_METHOD_COUNT;
return EULER_A_SAMPLE_METHOD;
}
enum scheduler_t sd_get_default_scheduler(const sd_ctx_t* sd_ctx) {
auto edm_v_denoiser = std::dynamic_pointer_cast<EDMVDenoiser>(sd_ctx->sd->denoiser);
if (edm_v_denoiser) {
return EXPONENTIAL_SCHEDULER;
if (sd_ctx != nullptr && sd_ctx->sd != nullptr) {
auto edm_v_denoiser = std::dynamic_pointer_cast<EDMVDenoiser>(sd_ctx->sd->denoiser);
if (edm_v_denoiser) {
return EXPONENTIAL_SCHEDULER;
}
}
return DISCRETE_SCHEDULER;
}
@ -2827,7 +2825,6 @@ sd_image_t* generate_image_internal(sd_ctx_t* sd_ctx,
int C = sd_ctx->sd->get_latent_channel();
int W = width / sd_ctx->sd->get_vae_scale_factor();
int H = height / sd_ctx->sd->get_vae_scale_factor();
LOG_INFO("sampling using %s method", sampling_methods_str[sample_method]);
struct ggml_tensor* control_latent = nullptr;
if (sd_version_is_control(sd_ctx->sd->version) && image_hint != nullptr) {
@ -3056,10 +3053,15 @@ sd_image_t* generate_image(sd_ctx_t* sd_ctx, const sd_img_gen_params_t* sd_img_g
sd_ctx->sd->rng->manual_seed(seed);
sd_ctx->sd->sampler_rng->manual_seed(seed);
int sample_steps = sd_img_gen_params->sample_params.sample_steps;
size_t t0 = ggml_time_ms();
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);
}
LOG_INFO("sampling using %s method", sampling_methods_str[sample_method]);
int sample_steps = sd_img_gen_params->sample_params.sample_steps;
std::vector<float> sigmas = sd_ctx->sd->denoiser->get_sigmas(sample_steps, sd_img_gen_params->sample_params.scheduler, sd_ctx->sd->version);
ggml_tensor* init_latent = nullptr;
@ -3248,11 +3250,6 @@ sd_image_t* generate_image(sd_ctx_t* sd_ctx, const sd_img_gen_params_t* sd_img_g
LOG_INFO("encode_first_stage completed, taking %.2fs", (t1 - t0) * 1.0f / 1000);
}
enum sample_method_t sample_method = sd_img_gen_params->sample_params.sample_method;
if (sample_method == SAMPLE_METHOD_DEFAULT) {
sample_method = sd_get_default_sample_method(sd_ctx);
}
sd_image_t* result_images = generate_image_internal(sd_ctx,
work_ctx,
init_latent,
@ -3302,6 +3299,12 @@ SD_API sd_image_t* generate_video(sd_ctx_t* sd_ctx, const sd_vid_gen_params_t* s
int vae_scale_factor = sd_ctx->sd->get_vae_scale_factor();
enum sample_method_t sample_method = sd_vid_gen_params->sample_params.sample_method;
if (sample_method == SAMPLE_METHOD_COUNT) {
sample_method = sd_get_default_sample_method(sd_ctx);
}
LOG_INFO("sampling using %s method", sampling_methods_str[sample_method]);
int high_noise_sample_steps = 0;
if (sd_ctx->sd->high_noise_diffusion_model) {
high_noise_sample_steps = sd_vid_gen_params->high_noise_sample_params.sample_steps;
@ -3570,6 +3573,12 @@ SD_API sd_image_t* generate_video(sd_ctx_t* sd_ctx, const sd_vid_gen_params_t* s
// High Noise Sample
if (high_noise_sample_steps > 0) {
LOG_DEBUG("sample(high noise) %dx%dx%d", W, H, T);
enum sample_method_t high_noise_sample_method = sd_vid_gen_params->high_noise_sample_params.sample_method;
if (high_noise_sample_method == SAMPLE_METHOD_COUNT) {
high_noise_sample_method = sd_get_default_sample_method(sd_ctx);
}
LOG_INFO("sampling(high noise) using %s method", sampling_methods_str[high_noise_sample_method]);
int64_t sampling_start = ggml_time_ms();
std::vector<float> high_noise_sigmas = std::vector<float>(sigmas.begin(), sigmas.begin() + high_noise_sample_steps + 1);
@ -3588,7 +3597,7 @@ SD_API sd_image_t* generate_video(sd_ctx_t* sd_ctx, const sd_vid_gen_params_t* s
sd_vid_gen_params->high_noise_sample_params.guidance,
sd_vid_gen_params->high_noise_sample_params.eta,
sd_vid_gen_params->high_noise_sample_params.shifted_timestep,
sd_vid_gen_params->high_noise_sample_params.sample_method,
high_noise_sample_method,
high_noise_sigmas,
-1,
{},
@ -3625,7 +3634,7 @@ SD_API sd_image_t* generate_video(sd_ctx_t* sd_ctx, const sd_vid_gen_params_t* s
sd_vid_gen_params->sample_params.guidance,
sd_vid_gen_params->sample_params.eta,
sd_vid_gen_params->sample_params.shifted_timestep,
sd_vid_gen_params->sample_params.sample_method,
sample_method,
sigmas,
-1,
{},

25
stable-diffusion.h
View File

@ -36,19 +36,18 @@ enum rng_type_t {
};
enum sample_method_t {
SAMPLE_METHOD_DEFAULT,
EULER,
HEUN,
DPM2,
DPMPP2S_A,
DPMPP2M,
DPMPP2Mv2,
IPNDM,
IPNDM_V,
LCM,
DDIM_TRAILING,
TCD,
EULER_A,
EULER_SAMPLE_METHOD,
EULER_A_SAMPLE_METHOD,
HEUN_SAMPLE_METHOD,
DPM2_SAMPLE_METHOD,
DPMPP2S_A_SAMPLE_METHOD,
DPMPP2M_SAMPLE_METHOD,
DPMPP2Mv2_SAMPLE_METHOD,
IPNDM_SAMPLE_METHOD,
IPNDM_V_SAMPLE_METHOD,
LCM_SAMPLE_METHOD,
DDIM_TRAILING_SAMPLE_METHOD,
TCD_SAMPLE_METHOD,
SAMPLE_METHOD_COUNT
};