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feat: turn flow_shift into a generation parameter (#1289)

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* feat: turn flow_shift into a generation parameter

* format code

* simplify set_shift/set_parameters

* fix sd_sample_params_to_str

* remove unused variable

* update docs

---------

Co-authored-by: leejet <leejet714@gmail.com>
This commit is contained in:
Wagner Bruna 2026-02-25 13:26:04 -03:00 committed by GitHub
parent c9cd49701a
commit b314d80ad0
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6 changed files with 48 additions and 78 deletions
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2
examples/cli/README.md
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@ -44,7 +44,6 @@ Context Options:
CPU physical cores
--chroma-t5-mask-pad <int> t5 mask pad size of chroma
--vae-tile-overlap <float> tile overlap for vae tiling, in fraction of tile size (default: 0.5)
--flow-shift <float> shift value for Flow models like SD3.x or WAN (default: auto)
--vae-tiling process vae in tiles to reduce memory usage
--force-sdxl-vae-conv-scale force use of conv scale on sdxl vae
--offload-to-cpu place the weights in RAM to save VRAM, and automatically load them into VRAM when needed
@ -109,6 +108,7 @@ Generation Options:
--skip-layer-start <float> SLG enabling point (default: 0.01)
--skip-layer-end <float> SLG disabling point (default: 0.2)
--eta <float> eta in DDIM, only for DDIM/TCD/res_multistep/res_2s (default: 0)
--flow-shift <float> shift value for Flow models like SD3.x or WAN (default: auto)
--high-noise-cfg-scale <float> (high noise) unconditional guidance scale: (default: 7.0)
--high-noise-img-cfg-scale <float> (high noise) image guidance scale for inpaint or instruct-pix2pix models (default: same as --cfg-scale)
--high-noise-guidance <float> (high noise) distilled guidance scale for models with guidance input (default: 3.5)

11
examples/common/common.hpp
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@ -581,10 +581,6 @@ struct SDContextParams {
"--vae-tile-overlap",
"tile overlap for vae tiling, in fraction of tile size (default: 0.5)",
&vae_tiling_params.target_overlap},
{"",
"--flow-shift",
"shift value for Flow models like SD3.x or WAN (default: auto)",
&flow_shift},
};
options.bool_options = {
@ -903,7 +899,6 @@ struct SDContextParams {
<< " photo_maker_path: \"" << photo_maker_path << "\",\n"
<< " rng_type: " << sd_rng_type_name(rng_type) << ",\n"
<< " sampler_rng_type: " << sd_rng_type_name(sampler_rng_type) << ",\n"
<< " flow_shift: " << (std::isinf(flow_shift) ? "INF" : std::to_string(flow_shift)) << "\n"
<< " offload_params_to_cpu: " << (offload_params_to_cpu ? "true" : "false") << ",\n"
<< " enable_mmap: " << (enable_mmap ? "true" : "false") << ",\n"
<< " control_net_cpu: " << (control_net_cpu ? "true" : "false") << ",\n"
@ -986,7 +981,6 @@ struct SDContextParams {
chroma_use_t5_mask,
chroma_t5_mask_pad,
qwen_image_zero_cond_t,
flow_shift,
};
return sd_ctx_params;
}
@ -1206,6 +1200,10 @@ struct SDGenerationParams {
"--eta",
"eta in DDIM, only for DDIM and TCD (default: 0)",
&sample_params.eta},
{"",
"--flow-shift",
"shift value for Flow models like SD3.x or WAN (default: auto)",
&sample_params.flow_shift},
{"",
"--high-noise-cfg-scale",
"(high noise) unconditional guidance scale: (default: 7.0)",
@ -1606,6 +1604,7 @@ struct SDGenerationParams {
load_if_exists("cfg_scale", sample_params.guidance.txt_cfg);
load_if_exists("img_cfg_scale", sample_params.guidance.img_cfg);
load_if_exists("guidance", sample_params.guidance.distilled_guidance);
load_if_exists("flow_shift", sample_params.flow_shift);
auto load_sampler_if_exists = [&](const char* key, enum sample_method_t& out) {
if (j.contains(key) && j[key].is_string()) {

2
examples/server/README.md
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@ -36,7 +36,6 @@ Context Options:
CPU physical cores
--chroma-t5-mask-pad <int> t5 mask pad size of chroma
--vae-tile-overlap <float> tile overlap for vae tiling, in fraction of tile size (default: 0.5)
--flow-shift <float> shift value for Flow models like SD3.x or WAN (default: auto)
--vae-tiling process vae in tiles to reduce memory usage
--force-sdxl-vae-conv-scale force use of conv scale on sdxl vae
--offload-to-cpu place the weights in RAM to save VRAM, and automatically load them into VRAM when needed
@ -101,6 +100,7 @@ Default Generation Options:
--skip-layer-start <float> SLG enabling point (default: 0.01)
--skip-layer-end <float> SLG disabling point (default: 0.2)
--eta <float> eta in DDIM, only for DDIM/TCD/res_multistep/res_2s (default: 0)
--flow-shift <float> shift value for Flow models like SD3.x or WAN (default: auto)
--high-noise-cfg-scale <float> (high noise) unconditional guidance scale: (default: 7.0)
--high-noise-img-cfg-scale <float> (high noise) image guidance scale for inpaint or instruct-pix2pix models (default: same as --cfg-scale)
--high-noise-guidance <float> (high noise) distilled guidance scale for models with guidance input (default: 3.5)

2
include/stable-diffusion.h
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@ -201,7 +201,6 @@ typedef struct {
bool chroma_use_t5_mask;
int chroma_t5_mask_pad;
bool qwen_image_zero_cond_t;
float flow_shift;
} sd_ctx_params_t;
typedef struct {
@ -235,6 +234,7 @@ typedef struct {
int shifted_timestep;
float* custom_sigmas;
int custom_sigmas_count;
float flow_shift;
} sd_sample_params_t;
typedef struct {

60
src/denoiser.hpp
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@ -657,9 +657,8 @@ struct DiscreteFlowDenoiser : public Denoiser {
float sigma_data = 1.0f;
DiscreteFlowDenoiser(float shift = 3.0f)
: shift(shift) {
set_parameters();
DiscreteFlowDenoiser(float shift = 3.0f) {
set_shift(shift);
}
void set_parameters() {
@ -668,6 +667,11 @@ struct DiscreteFlowDenoiser : public Denoiser {
}
}
void set_shift(float shift) {
this->shift = shift;
set_parameters();
}
float sigma_min() override {
return sigmas[0];
}
@ -710,34 +714,8 @@ float flux_time_shift(float mu, float sigma, float t) {
return ::expf(mu) / (::expf(mu) + ::powf((1.0f / t - 1.0f), sigma));
}
struct FluxFlowDenoiser : public Denoiser {
float sigmas[TIMESTEPS];
float shift = 1.15f;
float sigma_data = 1.0f;
FluxFlowDenoiser(float shift = 1.15f) {
set_parameters(shift);
}
void set_shift(float shift) {
this->shift = shift;
}
void set_parameters(float shift) {
set_shift(shift);
for (int i = 0; i < TIMESTEPS; i++) {
sigmas[i] = t_to_sigma(static_cast<float>(i));
}
}
float sigma_min() override {
return sigmas[0];
}
float sigma_max() override {
return sigmas[TIMESTEPS - 1];
}
struct FluxFlowDenoiser : public DiscreteFlowDenoiser {
FluxFlowDenoiser() = default;
float sigma_to_t(float sigma) override {
return sigma;
@ -747,26 +725,6 @@ struct FluxFlowDenoiser : public Denoiser {
t = t + 1;
return flux_time_shift(shift, 1.0f, t / TIMESTEPS);
}
std::vector<float> get_scalings(float sigma) override {
float c_skip = 1.0f;
float c_out = -sigma;
float c_in = 1.0f;
return {c_skip, c_out, c_in};
}
// this function will modify noise/latent
ggml_tensor* noise_scaling(float sigma, ggml_tensor* noise, ggml_tensor* latent) override {
ggml_ext_tensor_scale_inplace(noise, sigma);
ggml_ext_tensor_scale_inplace(latent, 1.0f - sigma);
ggml_ext_tensor_add_inplace(latent, noise);
return latent;
}
ggml_tensor* inverse_noise_scaling(float sigma, ggml_tensor* latent) override {
ggml_ext_tensor_scale_inplace(latent, 1.0f / (1.0f - sigma));
return latent;
}
};
struct Flux2FlowDenoiser : public FluxFlowDenoiser {

49
src/stable-diffusion.cpp
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@ -115,6 +115,7 @@ public:
int n_threads = -1;
float scale_factor = 0.18215f;
float shift_factor = 0.f;
float default_flow_shift = INFINITY;
std::shared_ptr<Conditioner> cond_stage_model;
std::shared_ptr<FrozenCLIPVisionEmbedder> clip_vision; // for svd or wan2.1 i2v
@ -881,7 +882,6 @@ public:
// init denoiser
{
prediction_t pred_type = sd_ctx_params->prediction;
float flow_shift = sd_ctx_params->flow_shift;
if (pred_type == PREDICTION_COUNT) {
if (sd_version_is_sd2(version)) {
@ -906,22 +906,19 @@ public:
sd_version_is_qwen_image(version) ||
sd_version_is_z_image(version)) {
pred_type = FLOW_PRED;
if (flow_shift == INFINITY) {
if (sd_version_is_wan(version)) {
flow_shift = 5.f;
} else {
flow_shift = 3.f;
}
if (sd_version_is_wan(version)) {
default_flow_shift = 5.f;
} else {
default_flow_shift = 3.f;
}
} else if (sd_version_is_flux(version)) {
pred_type = FLUX_FLOW_PRED;
if (flow_shift == INFINITY) {
flow_shift = 1.0f; // TODO: validate
for (const auto& [name, tensor_storage] : tensor_storage_map) {
if (starts_with(name, "model.diffusion_model.guidance_in.in_layer.weight")) {
flow_shift = 1.15f;
}
default_flow_shift = 1.0f; // TODO: validate
for (const auto& [name, tensor_storage] : tensor_storage_map) {
if (starts_with(name, "model.diffusion_model.guidance_in.in_layer.weight")) {
default_flow_shift = 1.15f;
break;
}
}
} else if (sd_version_is_flux2(version)) {
@ -945,12 +942,12 @@ public:
break;
case FLOW_PRED: {
LOG_INFO("running in FLOW mode");
denoiser = std::make_shared<DiscreteFlowDenoiser>(flow_shift);
denoiser = std::make_shared<DiscreteFlowDenoiser>();
break;
}
case FLUX_FLOW_PRED: {
LOG_INFO("running in Flux FLOW mode");
denoiser = std::make_shared<FluxFlowDenoiser>(flow_shift);
denoiser = std::make_shared<FluxFlowDenoiser>();
break;
}
case FLUX2_FLOW_PRED: {
@ -2711,6 +2708,16 @@ public:
ggml_ext_tensor_clamp_inplace(result, 0.0f, 1.0f);
return result;
}
void set_flow_shift(float flow_shift = INFINITY) {
auto flow_denoiser = std::dynamic_pointer_cast<DiscreteFlowDenoiser>(denoiser);
if (flow_denoiser) {
if (flow_shift == INFINITY) {
flow_shift = default_flow_shift;
}
flow_denoiser->set_shift(flow_shift);
}
}
};
/*================================================= SD API ==================================================*/
@ -2931,7 +2938,6 @@ void sd_ctx_params_init(sd_ctx_params_t* sd_ctx_params) {
sd_ctx_params->chroma_use_dit_mask = true;
sd_ctx_params->chroma_use_t5_mask = false;
sd_ctx_params->chroma_t5_mask_pad = 1;
sd_ctx_params->flow_shift = INFINITY;
}
char* sd_ctx_params_to_str(const sd_ctx_params_t* sd_ctx_params) {
@ -3023,6 +3029,7 @@ void sd_sample_params_init(sd_sample_params_t* sample_params) {
sample_params->sample_steps = 20;
sample_params->custom_sigmas = nullptr;
sample_params->custom_sigmas_count = 0;
sample_params->flow_shift = INFINITY;
}
char* sd_sample_params_to_str(const sd_sample_params_t* sample_params) {
@ -3043,7 +3050,8 @@ char* sd_sample_params_to_str(const sd_sample_params_t* sample_params) {
"sample_method: %s, "
"sample_steps: %d, "
"eta: %.2f, "
"shifted_timestep: %d)",
"shifted_timestep: %d, "
"flow_shift: %.2f)",
sample_params->guidance.txt_cfg,
std::isfinite(sample_params->guidance.img_cfg)
? sample_params->guidance.img_cfg
@ -3057,7 +3065,8 @@ char* sd_sample_params_to_str(const sd_sample_params_t* sample_params) {
sd_sample_method_name(sample_params->sample_method),
sample_params->sample_steps,
sample_params->eta,
sample_params->shifted_timestep);
sample_params->shifted_timestep,
sample_params->flow_shift);
return buf;
}
@ -3528,6 +3537,8 @@ sd_image_t* generate_image(sd_ctx_t* sd_ctx, const sd_img_gen_params_t* sd_img_g
size_t t0 = ggml_time_ms();
sd_ctx->sd->set_flow_shift(sd_img_gen_params->sample_params.flow_shift);
// Apply lora
sd_ctx->sd->apply_loras(sd_img_gen_params->loras, sd_img_gen_params->lora_count);
@ -3803,6 +3814,8 @@ SD_API sd_image_t* generate_video(sd_ctx_t* sd_ctx, const sd_vid_gen_params_t* s
}
LOG_INFO("generate_video %dx%dx%d", width, height, frames);
sd_ctx->sd->set_flow_shift(sd_vid_gen_params->sample_params.flow_shift);
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);