merge branch 'master' into ltx2.3

This commit is contained in:
leejet committed 2026-05-16 16:58:17 +08:00
commit 22d9a8374b
28 files changed
+2352 -564

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+21 -4
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@@ -405,7 +405,7 @@ ArgOptions SDContextParams::get_options() {
options.float_options = {
{"",
"--max-vram",
"maximum VRAM budget in GiB for graph-cut segmented execution. 0 disables graph splitting",
"maximum VRAM budget in GiB for graph-cut segmented execution. 0 disables graph splitting; -1 auto-detects free VRAM minus 1 GiB",
&max_vram},
};
@@ -819,6 +819,10 @@ ArgOptions SDGenerationParams::get_options() {
"Latent (antialiased), Latent (bicubic), Latent (bicubic antialiased), or a model name "
"under --hires-upscalers-dir (default: Latent)",
&hires_upscaler},
{"",
"--extra-sample-args",
"extra sampler args, key=value list. Currently lcm supports noise_clip_std, noise_scale_start, noise_scale_end",
&extra_sample_args},
};
options.int_options = {
@@ -1261,12 +1265,12 @@ ArgOptions SDGenerationParams::get_options() {
on_seed_arg},
{"",
"--sampling-method",
"sampling method, one of [euler, euler_a, heun, dpm2, dpm++2s_a, dpm++2m, dpm++2mv2, ipndm, ipndm_v, lcm, ddim_trailing, tcd, res_multistep, res_2s, er_sde] "
"sampling method, one of [euler, euler_a, heun, dpm2, dpm++2s_a, dpm++2m, dpm++2mv2, ipndm, ipndm_v, lcm, ddim_trailing, tcd, res_multistep, res_2s, er_sde, euler_cfg_pp, euler_a_cfg_pp]"
"(default: euler for Flux/SD3/Wan, euler_a otherwise)",
on_sample_method_arg},
{"",
"--high-noise-sampling-method",
"(high noise) sampling method, one of [euler, euler_a, heun, dpm2, dpm++2s_a, dpm++2m, dpm++2mv2, ipndm, ipndm_v, lcm, ddim_trailing, tcd, res_multistep, res_2s, er_sde]"
"(high noise) sampling method, one of [euler, euler_a, heun, dpm2, dpm++2s_a, dpm++2m, dpm++2mv2, ipndm, ipndm_v, lcm, ddim_trailing, tcd, res_multistep, res_2s, er_sde, euler_cfg_pp, euler_a_cfg_pp]"
" default: euler for Flux/SD3/Wan, euler_a otherwise",
on_high_noise_sample_method_arg},
{"",
@@ -1624,6 +1628,7 @@ bool SDGenerationParams::from_json_str(
auto parse_sample_params_json = [&](const json& sample_json,
sd_sample_params_t& target_params,
std::string& target_extra_sample_args,
std::vector<int>& target_skip_layers,
std::vector<float>* target_custom_sigmas) {
if (sample_json.contains("sample_steps") && sample_json["sample_steps"].is_number_integer()) {
@@ -1638,6 +1643,9 @@ bool SDGenerationParams::from_json_str(
if (sample_json.contains("flow_shift") && sample_json["flow_shift"].is_number()) {
target_params.flow_shift = sample_json["flow_shift"];
}
if (sample_json.contains("extra_sample_args") && sample_json["extra_sample_args"].is_string()) {
target_extra_sample_args = sample_json["extra_sample_args"].get<std::string>();
}
if (target_custom_sigmas != nullptr &&
sample_json.contains("custom_sigmas") &&
sample_json["custom_sigmas"].is_array()) {
@@ -1685,11 +1693,12 @@ bool SDGenerationParams::from_json_str(
};
if (j.contains("sample_params") && j["sample_params"].is_object()) {
parse_sample_params_json(j["sample_params"], sample_params, skip_layers, &custom_sigmas);
parse_sample_params_json(j["sample_params"], sample_params, extra_sample_args, skip_layers, &custom_sigmas);
}
if (j.contains("high_noise_sample_params") && j["high_noise_sample_params"].is_object()) {
parse_sample_params_json(j["high_noise_sample_params"],
high_noise_sample_params,
high_noise_extra_sample_args,
high_noise_skip_layers,
nullptr);
}
@@ -2119,6 +2128,8 @@ sd_img_gen_params_t SDGenerationParams::to_sd_img_gen_params_t() {
high_noise_sample_params.guidance.slg.layer_count = high_noise_skip_layers.size();
sample_params.custom_sigmas = custom_sigmas.empty() ? nullptr : custom_sigmas.data();
sample_params.custom_sigmas_count = static_cast<int>(custom_sigmas.size());
sample_params.extra_sample_args = extra_sample_args.empty() ? nullptr : extra_sample_args.c_str();
high_noise_sample_params.extra_sample_args = high_noise_extra_sample_args.empty() ? nullptr : high_noise_extra_sample_args.c_str();
cache_params.scm_mask = scm_mask.empty() ? nullptr : scm_mask.c_str();
sd_pm_params_t pm_params = {
@@ -2188,6 +2199,8 @@ sd_vid_gen_params_t SDGenerationParams::to_sd_vid_gen_params_t() {
high_noise_sample_params.guidance.slg.layer_count = high_noise_skip_layers.size();
sample_params.custom_sigmas = custom_sigmas.empty() ? nullptr : custom_sigmas.data();
sample_params.custom_sigmas_count = static_cast<int>(custom_sigmas.size());
sample_params.extra_sample_args = extra_sample_args.empty() ? nullptr : extra_sample_args.c_str();
high_noise_sample_params.extra_sample_args = high_noise_extra_sample_args.empty() ? nullptr : high_noise_extra_sample_args.c_str();
cache_params.scm_mask = scm_mask.empty() ? nullptr : scm_mask.c_str();
params.loras = lora_vec.empty() ? nullptr : lora_vec.data();
@@ -2328,6 +2341,7 @@ static json build_sampling_metadata_json(const sd_sample_params_t& sample_params
{"eta", sample_params.eta},
{"shifted_timestep", sample_params.shifted_timestep},
{"flow_shift", sample_params.flow_shift},
{"extra_sample_args", safe_json_string(sample_params.extra_sample_args)},
{"guidance",
{
{"txt_cfg", sample_params.guidance.txt_cfg},
@@ -2519,6 +2533,9 @@ std::string get_image_params(const SDContextParams& ctx_params,
}
parameter_string += "Guidance: " + std::to_string(gen_params.sample_params.guidance.distilled_guidance) + ", ";
parameter_string += "Eta: " + std::to_string(gen_params.sample_params.eta) + ", ";
if (!gen_params.extra_sample_args.empty()) {
parameter_string += "Extra sample args: " + gen_params.extra_sample_args + ", ";
}
parameter_string += "Seed: " + std::to_string(seed) + ", ";
parameter_string += "Size: " + std::to_string(gen_params.get_resolved_width()) + "x" + std::to_string(gen_params.get_resolved_height()) + ", ";
parameter_string += "Model: " + sd_basename(ctx_params.model_path) + ", ";
+2
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@@ -170,6 +170,8 @@ struct SDGenerationParams {
sd_sample_params_t sample_params;
sd_sample_params_t high_noise_sample_params;
std::string extra_sample_args;
std::string high_noise_extra_sample_args;
std::vector<int> skip_layers = {7, 8, 9};
std::vector<int> high_noise_skip_layers = {7, 8, 9};