fix: prevent crash in case of a mem alloc error and graceful exit (#1566)

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akleine 2026-05-30 12:34:07 +02:00 committed by GitHub
parent b54bd83a3f
commit b4ba55d8d7
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GPG Key ID: B5690EEEBB952194
18 changed files with 156 additions and 48 deletions

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@ -113,7 +113,7 @@ struct Conditioner {
public:
virtual SDCondition get_learned_condition(int n_threads,
const ConditionerParams& conditioner_params) = 0;
virtual void alloc_params_buffer() = 0;
virtual bool alloc_params_buffer() = 0;
virtual void free_params_buffer() = 0;
virtual void get_param_tensors(std::map<std::string, ggml_tensor*>& tensors) = 0;
virtual size_t get_params_buffer_size() = 0;
@ -176,11 +176,16 @@ struct FrozenCLIPEmbedderWithCustomWords : public Conditioner {
}
}
void alloc_params_buffer() override {
text_model->alloc_params_buffer();
if (sd_version_is_sdxl(version)) {
text_model2->alloc_params_buffer();
bool alloc_params_buffer() override {
if (!text_model->alloc_params_buffer()) {
return false;
}
if (sd_version_is_sdxl(version)) {
if (!text_model2->alloc_params_buffer()) {
return false;
}
}
return true;
}
void free_params_buffer() override {
@ -781,16 +786,23 @@ struct SD3CLIPEmbedder : public Conditioner {
}
}
void alloc_params_buffer() override {
bool alloc_params_buffer() override {
if (clip_l) {
clip_l->alloc_params_buffer();
if (!clip_l->alloc_params_buffer()) {
return false;
}
}
if (clip_g) {
clip_g->alloc_params_buffer();
if (!clip_g->alloc_params_buffer()) {
return false;
}
}
if (t5) {
t5->alloc_params_buffer();
if (!t5->alloc_params_buffer()) {
return false;
}
}
return true;
}
void free_params_buffer() override {
@ -1145,15 +1157,21 @@ struct FluxCLIPEmbedder : public Conditioner {
}
}
void alloc_params_buffer() override {
bool alloc_params_buffer() override {
if (clip_l) {
clip_l->alloc_params_buffer();
if (!clip_l->alloc_params_buffer()) {
return false;
}
}
if (t5) {
t5->alloc_params_buffer();
if (!t5->alloc_params_buffer()) {
return false;
}
}
return true;
}
void free_params_buffer() override {
if (clip_l) {
clip_l->free_params_buffer();
@ -1388,10 +1406,13 @@ struct T5CLIPEmbedder : public Conditioner {
}
}
void alloc_params_buffer() override {
bool alloc_params_buffer() override {
if (t5) {
t5->alloc_params_buffer();
if (!t5->alloc_params_buffer()) {
return false;
}
}
return true;
}
void free_params_buffer() override {
@ -1578,8 +1599,11 @@ struct AnimaConditioner : public Conditioner {
llm->get_param_tensors(tensors, "text_encoders.llm");
}
void alloc_params_buffer() override {
llm->alloc_params_buffer();
bool alloc_params_buffer() override {
if (!llm->alloc_params_buffer()) {
return false;
}
return true;
}
void free_params_buffer() override {
@ -1717,8 +1741,11 @@ struct LLMEmbedder : public Conditioner {
llm->get_param_tensors(tensors, "text_encoders.llm");
}
void alloc_params_buffer() override {
llm->alloc_params_buffer();
bool alloc_params_buffer() override {
if (!llm->alloc_params_buffer()) {
return false;
}
return true;
}
void free_params_buffer() override {
@ -2239,9 +2266,14 @@ struct LTXAVEmbedder : public Conditioner {
projector->get_param_tensors(tensors, "text_embedding_projection");
}
void alloc_params_buffer() override {
llm->alloc_params_buffer();
projector->alloc_params_buffer();
bool alloc_params_buffer() override {
if (!llm->alloc_params_buffer()) {
return false;
}
if (!projector->alloc_params_buffer()) {
return false;
}
return true;
}
void free_params_buffer() override {

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@ -457,7 +457,11 @@ struct ControlNet : public GGMLRunner {
bool load_from_file(const std::string& file_path, int n_threads) {
LOG_INFO("loading control net from '%s'", file_path.c_str());
alloc_params_buffer();
if (!alloc_params_buffer()) {
LOG_ERROR("control net model buffer allocation failed");
return false;
}
std::map<std::string, ggml_tensor*> tensors;
control_net.get_param_tensors(tensors);
std::set<std::string> ignore_tensors;

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@ -270,7 +270,11 @@ struct ESRGAN : public GGMLRunner {
rrdb_net = std::make_unique<RRDBNet>(detected_scale, detected_num_block, detected_num_in_ch, detected_num_out_ch, detected_num_feat, detected_num_grow_ch);
rrdb_net->init(params_ctx, {}, "");
alloc_params_buffer();
if (!alloc_params_buffer()) {
LOG_ERROR("esrgan model buffer allocation failed");
return false;
}
std::map<std::string, ggml_tensor*> esrgan_tensors;
rrdb_net->get_param_tensors(esrgan_tensors);

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@ -1592,7 +1592,11 @@ namespace Flux {
VERSION_FLUX2,
false);
flux->alloc_params_buffer();
if (!flux->alloc_params_buffer()) {
LOG_ERROR("flux model allocation failed");
return;
}
std::map<std::string, ggml_tensor*> tensors;
flux->get_param_tensors(tensors, "model.diffusion_model");

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@ -492,8 +492,11 @@ namespace HiDreamO1 {
vision_runner->get_param_tensors(tensors);
}
void alloc_params_buffer() override {
vision_runner->alloc_params_buffer();
bool alloc_params_buffer() override {
if (!vision_runner->alloc_params_buffer()) {
return false;
}
return true;
}
void free_params_buffer() override {

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@ -1769,8 +1769,11 @@ namespace LLM {
model.get_param_tensors(tensors, prefix);
}
void alloc_params_buffer() {
model.alloc_params_buffer();
bool alloc_params_buffer() {
if (!model.alloc_params_buffer()) {
return false;
}
return true;
}
std::tuple<std::vector<int>, std::vector<float>> tokenize(std::string text,
@ -2012,7 +2015,11 @@ namespace LLM {
"text_encoders.llm",
true);
llm->alloc_params_buffer();
if (!llm->alloc_params_buffer()) {
LOG_ERROR("llm model allocation failed");
return;
}
std::map<std::string, ggml_tensor*> tensors;
llm->get_param_tensors(tensors, "text_encoders.llm");

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@ -86,7 +86,11 @@ struct LoraModel : public GGMLRunner {
lora_tensors[name] = real;
}
alloc_params_buffer();
if (!alloc_params_buffer()) {
LOG_ERROR("lora model buffer allocation failed");
return false;
}
dry_run = false;
model_loader.load_tensors(on_new_tensor_cb, n_threads);

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@ -1068,7 +1068,11 @@ namespace LTXV {
tensor_storage_map,
prefix);
ltx_audio_vae->alloc_params_buffer();
if (!ltx_audio_vae->alloc_params_buffer()) {
LOG_ERROR("ltx audio vae buffer allocation failed");
return;
}
std::map<std::string, ggml_tensor*> tensors;
ltx_audio_vae->get_param_tensors(tensors, "");

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@ -1534,7 +1534,11 @@ struct LTXVideoVAE : public VAE {
true,
VERSION_LTXAV);
vae->alloc_params_buffer();
if (!vae->alloc_params_buffer()) {
LOG_ERROR("vae buffer allocation failed");
return;
}
std::map<std::string, ggml_tensor*> tensors;
vae->get_param_tensors(tensors, "first_stage_model");

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@ -2017,7 +2017,10 @@ namespace LTXV {
tensor_storage_map,
"model.diffusion_model");
ltxav->alloc_params_buffer();
if (!ltxav->alloc_params_buffer()) {
LOG_ERROR("ltxav buffer allocation failed");
return;
}
std::map<std::string, ggml_tensor*> tensors;
ltxav->get_param_tensors(tensors, "model.diffusion_model");

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@ -953,7 +953,11 @@ struct MMDiTRunner : public DiffusionModelRunner {
{
LOG_INFO("loading from '%s'", file_path.c_str());
mmdit->alloc_params_buffer();
if (!mmdit->alloc_params_buffer()) {
LOG_ERROR("mmdit embeds buffer allocation failed");
return;
}
std::map<std::string, ggml_tensor*> tensors;
mmdit->get_param_tensors(tensors, "model.diffusion_model");

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@ -1004,6 +1004,12 @@ bool ModelLoader::load_tensors(on_new_tensor_cb_t on_new_tensor_cb, int n_thread
continue;
}
if (dst_tensor->data == nullptr) {
LOG_ERROR("process tensor data failed: '%s'", tensor_storage.name.c_str());
failed = true;
break;
}
// skip mmapped tensors
if (dst_tensor->buffer != nullptr && dst_tensor->buffer == fdata.mmbuffer.get()) {
continue;

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@ -615,7 +615,10 @@ struct PhotoMakerIDEmbed : public GGMLRunner {
};
model_loader->load_tensors(on_new_tensor_cb, n_threads);
alloc_params_buffer();
if (!alloc_params_buffer()) {
LOG_ERROR("PhotoMaker ID embeds buffer allocation failed");
return false;
}
dry_run = false;
model_loader->load_tensors(on_new_tensor_cb, n_threads);

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@ -705,7 +705,11 @@ namespace Qwen {
"model.diffusion_model",
VERSION_QWEN_IMAGE);
qwen_image->alloc_params_buffer();
if (!qwen_image->alloc_params_buffer()) {
LOG_ERROR("qwen_image buffer allocation failed");
return;
}
std::map<std::string, ggml_tensor*> tensors;
qwen_image->get_param_tensors(tensors, "model.diffusion_model");

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@ -984,14 +984,20 @@ public:
ggml_free(ctx);
return false;
}
if (cond_stage_model) {
cond_stage_model->alloc_params_buffer();
if (cond_stage_model && !cond_stage_model->alloc_params_buffer()) {
LOG_ERROR("Conditioner model params buffer allocation failed");
ggml_free(ctx);
return false;
}
if (diffusion_model) {
diffusion_model->alloc_params_buffer();
if (diffusion_model && !diffusion_model->alloc_params_buffer()) {
LOG_ERROR("Diffusion model params buffer allocation failed");
ggml_free(ctx);
return false;
}
if (high_noise_diffusion_model) {
high_noise_diffusion_model->alloc_params_buffer();
if (high_noise_diffusion_model && !high_noise_diffusion_model->alloc_params_buffer()) {
LOG_ERROR("High noise diffusion model params buffer allocation failed");
ggml_free(ctx);
return false;
}
if (first_stage_model && !first_stage_model->alloc_params_buffer()) {
LOG_ERROR("VAE params buffer allocation failed");

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@ -475,8 +475,11 @@ struct T5Embedder {
model.get_param_tensors(tensors, prefix);
}
void alloc_params_buffer() {
model.alloc_params_buffer();
bool alloc_params_buffer() {
if (!model.alloc_params_buffer()) {
return false;
}
return true;
}
std::tuple<std::vector<int>, std::vector<float>, std::vector<float>> tokenize(std::string text,
@ -578,7 +581,10 @@ struct T5Embedder {
std::shared_ptr<T5Embedder> t5 = std::make_shared<T5Embedder>(backend, backend, tensor_storage_map, "", true);
t5->alloc_params_buffer();
if (!t5->alloc_params_buffer()) {
LOG_ERROR("t5 params buffer allocation failed");
return;
}
std::map<std::string, ggml_tensor*> tensors;
t5->get_param_tensors(tensors, "");

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@ -1334,7 +1334,10 @@ namespace WAN {
{
LOG_INFO("loading from '%s'", file_path.c_str());
vae->alloc_params_buffer();
if (!vae->alloc_params_buffer()) {
LOG_ERROR("vae buffer allocation failed");
return;
}
std::map<std::string, ggml_tensor*> tensors;
vae->get_param_tensors(tensors, "first_stage_model");
@ -2368,7 +2371,11 @@ namespace WAN {
"model.diffusion_model",
VERSION_WAN2_2_TI2V);
wan->alloc_params_buffer();
if (!wan->alloc_params_buffer()) {
LOG_ERROR("wan buffer allocation failed");
return;
}
std::map<std::string, ggml_tensor*> tensors;
wan->get_param_tensors(tensors, "model.diffusion_model");

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@ -639,7 +639,10 @@ namespace ZImage {
"model.diffusion_model",
VERSION_QWEN_IMAGE);
z_image->alloc_params_buffer();
if (!z_image->alloc_params_buffer()) {
LOG_ERROR("z_image buffer allocation failed");
return;
}
std::map<std::string, ggml_tensor*> tensors;
z_image->get_param_tensors(tensors, "model.diffusion_model");