DarthAffe/stable-diffusion.cpp
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refactor: route all runner params through model manager (#1649)

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leejet authored and GitHub committed 2026-06-14 02:05:23 +08:00
1 parent 9b0fceb41b
commit 8d4c7af95b
36 files changed
+596 -677
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src/model/vae/ltx_vae.hpp
+19 -21
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@@ -957,8 +957,8 @@ namespace LTXVAE {
ggml_tensor* scaled_timestep = timestep;
if (timestep_conditioning) {
auto multiplier = ggml_ext_backend_tensor_get_f32(params["timestep_scale_multiplier"]);
scaled_timestep = ggml_ext_scale(ctx->ggml_ctx, timestep, multiplier);
auto multiplier = ggml_ext_cast_f32(ctx->ggml_ctx, ctx->backend, params["timestep_scale_multiplier"]);
scaled_timestep = ggml_mul(ctx->ggml_ctx, timestep, multiplier);
}
x = conv_in->forward(ctx, x, causal_decoder);
@@ -1008,8 +1008,8 @@ namespace LTXVAE {
ggml_tensor* scaled_timestep = timestep;
if (timestep_conditioning && timestep != nullptr) {
auto multiplier = ggml_ext_backend_tensor_get_f32(params["timestep_scale_multiplier"]);
scaled_timestep = ggml_ext_scale(ctx->ggml_ctx, timestep, multiplier);
auto multiplier = ggml_ext_cast_f32(ctx->ggml_ctx, ctx->backend, params["timestep_scale_multiplier"]);
scaled_timestep = ggml_mul(ctx->ggml_ctx, timestep, multiplier);
}
// conv_in with feat_map for left temporal context
@@ -1223,11 +1223,11 @@ struct LTXVideoVAE : public VAE {
LTXVAE::VideoVAE vae;
LTXVideoVAE(ggml_backend_t backend,
ggml_backend_t params_backend,
const String2TensorStorage& tensor_storage_map,
const std::string& prefix,
bool decode_only = true,
SDVersion version = VERSION_LTXAV)
bool decode_only = true,
SDVersion version = VERSION_LTXAV,
std::shared_ptr<RunnerWeightManager> weight_manager = nullptr)
: decode_only(decode_only),
ltx_vae_version(LTXVAE::detect_ltx_vae_version(tensor_storage_map, prefix)),
timestep_conditioning(LTXVAE::detect_ltx_vae_timestep_conditioning(tensor_storage_map, prefix)),
@@ -1239,7 +1239,7 @@ struct LTXVideoVAE : public VAE {
patch_size,
tensor_storage_map,
prefix),
VAE(version, backend, params_backend, prefix) {
VAE(version, backend, prefix, weight_manager) {
vae.init(params_ctx, tensor_storage_map, prefix);
decode_timestep_tensor.values()[0] = vae.decode_timestep;
}
@@ -1521,7 +1521,8 @@ struct LTXVideoVAE : public VAE {
ggml_backend_t backend = sd_backend_cpu_init();
LOG_INFO("loading ltx vae from '%s'", model_path.c_str());
ModelLoader model_loader;
auto model_manager = std::make_shared<ModelManager>();
ModelLoader& model_loader = model_manager->loader();
if (!model_loader.init_from_file_and_convert_name(model_path, "vae.")) {
LOG_ERROR("init model loader from file failed: '%s'", model_path.c_str());
return;
@@ -1529,22 +1530,19 @@ struct LTXVideoVAE : public VAE {
auto& tensor_storage_map = model_loader.get_tensor_storage_map();
std::shared_ptr<LTXVideoVAE> vae = std::make_shared<LTXVideoVAE>(backend,
backend,
tensor_storage_map,
"first_stage_model",
true,
VERSION_LTXAV);
VERSION_LTXAV,
model_manager);
if (!vae->alloc_params_buffer()) {
LOG_ERROR("vae buffer allocation failed");
return;
}
std::map<std::string, ggml_tensor*> tensors;
vae->get_param_tensors(tensors);
if (!model_loader.load_tensors(tensors)) {
LOG_ERROR("load tensors from model loader failed");
if (!model_manager->register_runner_params("LTX VAE test",
*vae,
ModelManager::ResidencyMode::Resident,
backend,
backend) ||
!model_manager->validate_registered_tensors()) {
LOG_ERROR("register ltx vae tensors with model manager failed");
return;
}