DarthAffe/stable-diffusion.cpp
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refactor: split model loader from model definitions (#1619)

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leejet authored and GitHub committed 2026-06-07 23:20:12 +08:00
1 parent 2a07540c2a
commit b3d56d0ba1
25 files changed
+106 -84
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src/model.h
+1 -73
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@@ -1,11 +1,8 @@
#ifndef __MODEL_H__
#define __MODEL_H__
#include <functional>
#include <map>
#include <memory>
#include <set>
#include <string>
#include <utility>
#include <vector>
#include "core/ordered_map.hpp"
@@ -238,73 +235,4 @@ enum PMVersion {
typedef OrderedMap<std::string, TensorStorage> String2TensorStorage;
using TensorTypeRules = std::vector<std::pair<std::string, ggml_type>>;
TensorTypeRules parse_tensor_type_rules(const std::string& tensor_type_rules);
class MmapWrapper;
struct ModelFileData {
std::string path;
std::vector<TensorStorage> tensors;
std::shared_ptr<MmapWrapper> mmapped;
std::shared_ptr<struct ggml_backend_buffer> mmbuffer;
bool is_zip;
};
struct MmapTensorStore {
std::shared_ptr<MmapWrapper> mmapped;
std::shared_ptr<struct ggml_backend_buffer> mmbuffer;
};
class ModelLoader {
protected:
SDVersion version_ = VERSION_COUNT;
std::vector<std::string> file_paths_;
std::vector<ModelFileData> file_data;
bool model_files_processed = false;
String2TensorStorage tensor_storage_map;
void add_tensor_storage(const TensorStorage& tensor_storage);
bool init_from_gguf_file(const std::string& file_path, const std::string& prefix = "");
bool init_from_safetensors_file(const std::string& file_path, const std::string& prefix = "");
bool init_from_torch_zip_file(const std::string& file_path, const std::string& prefix = "");
bool init_from_torch_legacy_file(const std::string& file_path, const std::string& prefix = "");
bool init_from_diffusers_file(const std::string& file_path, const std::string& prefix = "");
public:
bool init_from_file(const std::string& file_path, const std::string& prefix = "");
void convert_tensors_name();
bool init_from_file_and_convert_name(const std::string& file_path,
const std::string& prefix = "",
SDVersion version = VERSION_COUNT);
SDVersion get_sd_version();
std::map<ggml_type, uint32_t> get_wtype_stat();
std::map<ggml_type, uint32_t> get_conditioner_wtype_stat();
std::map<ggml_type, uint32_t> get_diffusion_model_wtype_stat();
std::map<ggml_type, uint32_t> get_vae_wtype_stat();
String2TensorStorage& get_tensor_storage_map() { return tensor_storage_map; }
void set_wtype_override(ggml_type wtype, std::string tensor_type_rules = "");
void process_model_files(bool enable_mmap = false, bool writable_mmap = true);
std::vector<MmapTensorStore> mmap_tensors(std::map<std::string, ggml_tensor*>& tensors,
std::set<std::string> ignore_tensors = {},
bool writable = true);
bool load_tensors(on_new_tensor_cb_t on_new_tensor_cb, int n_threads = 0, bool use_mmap = false);
bool load_tensors(std::map<std::string, ggml_tensor*>& tensors,
std::set<std::string> ignore_tensors = {},
int n_threads = 0,
bool use_mmap = false);
std::vector<std::string> get_tensor_names() const {
std::vector<std::string> names;
for (const auto& [name, tensor_storage] : tensor_storage_map) {
names.push_back(name);
}
return names;
}
bool tensor_should_be_converted(const TensorStorage& tensor_storage, ggml_type type);
int64_t get_params_mem_size(ggml_backend_t backend, ggml_type type = GGML_TYPE_COUNT);
~ModelLoader() = default;
};
#endif // __MODEL_H__