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https://github.com/leejet/stable-diffusion.cpp.git
synced 2026-11-11 11:26:34 +00:00
feat: support safetensors export in convert mode (#1444)
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@@ -95,7 +95,7 @@ bool read_gguf_file(const std::string& file_path,
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}
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bool write_gguf_file(const std::string& file_path,
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const std::vector<ggml_tensor*>& tensors,
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const std::vector<TensorWriteInfo>& tensors,
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std::string* error) {
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gguf_context* gguf_ctx = gguf_init_empty();
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if (gguf_ctx == nullptr) {
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@@ -103,7 +103,8 @@ bool write_gguf_file(const std::string& file_path,
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return false;
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}
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for (ggml_tensor* tensor : tensors) {
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for (const TensorWriteInfo& write_tensor : tensors) {
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ggml_tensor* tensor = write_tensor.tensor;
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if (tensor == nullptr) {
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set_error(error, "null tensor cannot be written to GGUF");
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gguf_free(gguf_ctx);
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@@ -11,7 +11,7 @@ bool read_gguf_file(const std::string& file_path,
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std::vector<TensorStorage>& tensor_storages,
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std::string* error = nullptr);
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bool write_gguf_file(const std::string& file_path,
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const std::vector<ggml_tensor*>& tensors,
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const std::vector<TensorWriteInfo>& tensors,
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std::string* error = nullptr);
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#endif // __SD_MODEL_IO_GGUF_IO_H__
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@@ -8,6 +8,7 @@
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#include "binary_io.h"
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#include "json.hpp"
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#include "util.h"
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static constexpr size_t ST_HEADER_SIZE_LEN = 8;
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@@ -60,7 +61,7 @@ bool is_safetensors_file(const std::string& file_path) {
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return true;
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}
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static ggml_type str_to_ggml_type(const std::string& dtype) {
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static ggml_type safetensors_dtype_to_ggml_type(const std::string& dtype) {
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ggml_type ttype = GGML_TYPE_COUNT;
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if (dtype == "F16") {
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ttype = GGML_TYPE_F16;
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@@ -154,7 +155,7 @@ bool read_safetensors_file(const std::string& file_path,
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size_t begin = tensor_info["data_offsets"][0].get<size_t>();
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size_t end = tensor_info["data_offsets"][1].get<size_t>();
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ggml_type type = str_to_ggml_type(dtype);
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ggml_type type = safetensors_dtype_to_ggml_type(dtype);
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if (type == GGML_TYPE_COUNT) {
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set_error(error, "unsupported dtype '" + dtype + "' (tensor '" + name + "')");
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return false;
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@@ -221,3 +222,95 @@ bool read_safetensors_file(const std::string& file_path,
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return true;
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}
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static bool ggml_type_to_safetensors_dtype(ggml_type type, std::string* dtype) {
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switch (type) {
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case GGML_TYPE_F16:
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*dtype = "F16";
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return true;
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case GGML_TYPE_BF16:
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*dtype = "BF16";
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return true;
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case GGML_TYPE_F32:
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*dtype = "F32";
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return true;
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case GGML_TYPE_I32:
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*dtype = "I32";
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return true;
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default:
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return false;
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}
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}
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bool write_safetensors_file(const std::string& file_path,
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const std::vector<TensorWriteInfo>& tensors,
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std::string* error) {
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nlohmann::ordered_json header = nlohmann::ordered_json::object();
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uint64_t data_offset = 0;
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for (const TensorWriteInfo& write_tensor : tensors) {
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ggml_tensor* tensor = write_tensor.tensor;
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if (tensor == nullptr) {
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set_error(error, "null tensor cannot be written to safetensors");
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return false;
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}
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const std::string name = ggml_get_name(tensor);
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std::string dtype;
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if (!ggml_type_to_safetensors_dtype(tensor->type, &dtype)) {
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set_error(error,
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"unsupported safetensors dtype '" + std::string(ggml_type_name(tensor->type)) +
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"' for tensor '" + name + "'");
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return false;
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}
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const uint64_t tensor_nbytes = ggml_nbytes(tensor);
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nlohmann::ordered_json json_tensor_info = nlohmann::ordered_json::object();
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json_tensor_info["dtype"] = dtype;
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nlohmann::ordered_json shape = nlohmann::ordered_json::array();
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for (int i = 0; i < write_tensor.n_dims; ++i) {
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shape.push_back(write_tensor.ne[write_tensor.n_dims - 1 - i]);
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}
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json_tensor_info["shape"] = shape;
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nlohmann::ordered_json data_offsets = nlohmann::ordered_json::array();
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data_offsets.push_back(data_offset);
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data_offsets.push_back(data_offset + tensor_nbytes);
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json_tensor_info["data_offsets"] = data_offsets;
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header[name] = json_tensor_info;
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data_offset += tensor_nbytes;
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}
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const std::string header_str = header.dump();
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std::ofstream file(file_path, std::ios::binary);
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if (!file.is_open()) {
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set_error(error, "failed to open '" + file_path + "' for writing");
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return false;
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}
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LOG_INFO("trying to save tensors to %s", file_path.c_str());
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model_io::write_u64(file, header_str.size());
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file.write(header_str.data(), header_str.size());
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if (!file) {
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set_error(error, "failed to write safetensors header to '" + file_path + "'");
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return false;
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}
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for (const TensorWriteInfo& write_tensor : tensors) {
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ggml_tensor* tensor = write_tensor.tensor;
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const std::string name = ggml_get_name(tensor);
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const size_t tensor_nbytes = ggml_nbytes(tensor);
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file.write((const char*)tensor->data, tensor_nbytes);
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if (!file) {
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set_error(error,
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"failed to write tensor '" + name + "' to '" + file_path + "'");
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return false;
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}
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}
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return true;
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}
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@@ -10,5 +10,8 @@ bool is_safetensors_file(const std::string& file_path);
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bool read_safetensors_file(const std::string& file_path,
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std::vector<TensorStorage>& tensor_storages,
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std::string* error = nullptr);
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bool write_safetensors_file(const std::string& file_path,
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const std::vector<TensorWriteInfo>& tensors,
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std::string* error = nullptr);
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#endif // __SD_MODEL_IO_SAFETENSORS_IO_H__
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@@ -121,6 +121,12 @@ struct TensorStorage {
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}
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};
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struct TensorWriteInfo {
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int64_t ne[SD_MAX_DIMS] = {1, 1, 1, 1, 1};
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int n_dims = 0;
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ggml_tensor* tensor = nullptr;
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};
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typedef std::function<bool(const TensorStorage&, ggml_tensor**)> on_new_tensor_cb_t;
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#endif // __SD_TENSOR_STORAGE_H__
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