DarthAffe/stable-diffusion.cpp
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chore: format code

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leejet committed 2026-10-24 01:23:42 +08:00
1 parent 40b1788476
commit e0ed724e28
69 files changed
+711 -441
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src/conditioning/conditioner.hpp
+22 -22
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@@ -1833,11 +1833,11 @@ struct AnimaConditioner : public Conditioner {
std::shared_ptr<RunnerWeightManager> weight_manager = nullptr,
const TokenizerConfig& tokenizers = {}) {
llm = std::make_shared<LLM::LLMRunner>(LLM::LLMArch::QWEN3,
backend,
tensor_storage_map,
"text_encoders.llm",
false,
weight_manager);
backend,
tensor_storage_map,
"text_encoders.llm",
false,
weight_manager);
qwen_tokenizer = tokenizers.create(TokenizerConfig::MAIN, llm->config.vocab_size, 151643);
if (!qwen_tokenizer) {
qwen_tokenizer = std::make_shared<Qwen2Tokenizer>();
@@ -2026,11 +2026,11 @@ struct LLMEmbedder : public Conditioner {
arch = LLM::LLMArch::QWEN3_5;
}
llm = std::make_shared<LLM::LLMRunner>(arch,
backend,
tensor_storage_map,
"text_encoders.llm",
enable_vision,
weight_manager);
backend,
tensor_storage_map,
"text_encoders.llm",
enable_vision,
weight_manager);
int pad_id = 151643;
if (arch == LLM::LLMArch::MISTRAL_SMALL_3_2 || arch == LLM::LLMArch::MINISTRAL_3_3B) {
pad_id = 11;
@@ -3312,7 +3312,7 @@ struct LLMEmbedder : public Conditioner {
for (const auto& [index, image_embed] : image_embeds) {
int64_t begin = std::max<int64_t>(0, index - 1);
int64_t end = std::min<int64_t>(static_cast<int64_t>(tags.size()),
index + image_embed.shape()[1] + 1);
index + image_embed.shape()[1] + 1);
std::fill(tags.begin() + begin, tags.begin() + end, 0);
}
int64_t tag_count = static_cast<int64_t>(tags.size());
@@ -3492,9 +3492,9 @@ struct LLaDAImageEmbedder : public Conditioner {
// <|endoftext|> doubles as the pad token in LLaDA2's tokenizer.json.
tokenizer = tokenizers.create(TokenizerConfig::MAIN, llm->config.vocab_size, 156892);
query_former = std::make_shared<LLaDAImageTE::QueryFormerRunner>(backend,
tensor_storage_map,
query_former_prefix,
weight_manager);
tensor_storage_map,
query_former_prefix,
weight_manager);
text_projection = std::make_shared<LLaDAImageTE::TextProjectionRunner>(backend,
tensor_storage_map,
text_projection_prefix,
@@ -3696,20 +3696,20 @@ struct LTXAVEmbedder : public Conditioner {
LLM::LLMArch arch = detect_gemma_arch(tensor_storage_map, llm_prefix);
LOG_INFO("ltxav text encoder: %s", arch == LLM::LLMArch::GEMMA4_12B ? "gemma 4" : "gemma 3");
llm = std::make_shared<LLM::LLMRunner>(arch,
backend,
tensor_storage_map,
llm_prefix,
false,
weight_manager);
backend,
tensor_storage_map,
llm_prefix,
false,
weight_manager);
tokenizer = tokenizers.create(TokenizerConfig::MAIN, llm->config.vocab_size, 0, true);
if (!tokenizer) {
tokenizer = std::make_shared<GemmaTokenizer>();
}
dual_projection = tensor_storage_map.find(projector_prefix + ".video_aggregate_embed.weight") != tensor_storage_map.end();
projector = std::make_shared<LTXAVTextProjectionRunner>(backend,
tensor_storage_map,
projector_prefix,
weight_manager);
tensor_storage_map,
projector_prefix,
weight_manager);
}
void get_param_tensors(std::map<std::string, ggml_tensor*>& tensors) override {