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sd: sync to master-358-347710f

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Also adapt Koboldcpp LoRA loading function, and add
backend support for lora_apply_mode.
This commit is contained in:
Wagner Bruna
2025-11-13 22:15:56 -03:00
committed by Wagner Bruna
parent 3318b73c94
commit 3a7dd1a97f
24 changed files with 1035 additions and 216 deletions
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otherarch/sdcpp/main.cpp
+26 -1
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@@ -137,7 +137,8 @@ struct SDParams {
int chroma_t5_mask_pad = 1;
float flow_shift = INFINITY;
prediction_t prediction = DEFAULT_PRED;
prediction_t prediction = DEFAULT_PRED;
lora_apply_mode_t lora_apply_mode = LORA_APPLY_AUTO;
sd_tiling_params_t vae_tiling_params = {false, 0, 0, 0.5f, 0.0f, 0.0f};
bool force_sdxl_vae_conv_scale = false;
@@ -209,6 +210,7 @@ void print_params(SDParams params) {
printf(" high_noise_sample_params: %s\n", SAFE_STR(high_noise_sample_params_str));
printf(" moe_boundary: %.3f\n", params.moe_boundary);
printf(" prediction: %s\n", sd_prediction_name(params.prediction));
printf(" lora_apply_mode: %s\n", sd_lora_apply_mode_name(params.lora_apply_mode));
printf(" flow_shift: %.2f\n", params.flow_shift);
printf(" strength(img2img): %.2f\n", params.strength);
printf(" rng: %s\n", sd_rng_type_name(params.rng_type));
@@ -926,6 +928,20 @@ void parse_args(int argc, const char** argv, SDParams& params) {
return 1;
};
auto on_lora_apply_mode_arg = [&](int argc, const char** argv, int index) {
if (++index >= argc) {
return -1;
}
const char* arg = argv[index];
params.lora_apply_mode = str_to_lora_apply_mode(arg);
if (params.lora_apply_mode == LORA_APPLY_MODE_COUNT) {
fprintf(stderr, "error: invalid lora apply model %s\n",
arg);
return -1;
}
return 1;
};
auto on_sample_method_arg = [&](int argc, const char** argv, int index) {
if (++index >= argc) {
return -1;
@@ -1123,6 +1139,14 @@ void parse_args(int argc, const char** argv, SDParams& params) {
"--prediction",
"prediction type override, one of [eps, v, edm_v, sd3_flow, flux_flow]",
on_prediction_arg},
{"",
"--lora-apply-mode",
"the way to apply LoRA, one of [auto, immediately, at_runtime], default is auto. "
"In auto mode, if the model weights contain any quantized parameters, the at_runtime mode will be used; otherwise, immediately will be used."
"The immediately mode may have precision and compatibility issues with quantized parameters, "
"but it usually offers faster inference speed and, in some cases, lower memory usage"
"The at_runtime mode, on the other hand, is exactly the opposite.",
on_lora_apply_mode_arg},
{"",
"--scheduler",
"denoiser sigma scheduler, one of [discrete, karras, exponential, ays, gits, smoothstep, sgm_uniform, simple], default: discrete",
@@ -1738,6 +1762,7 @@ int main(int argc, const char* argv[]) {
params.wtype,
params.rng_type,
params.prediction,
params.lora_apply_mode,
params.offload_params_to_cpu,
params.clip_on_cpu,
params.control_net_cpu,