upstream-archive/stable-diffusion.cpp
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chore: add .clang-tidy configuration and apply modernize checks (#902)

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leejet
2025-10-18 23:23:40 +08:00
committed by GitHub
parent 64a7698347
commit d05e46ca5e
32 changed files with 766 additions and 747 deletions
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39
model.cpp
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@@ -1,7 +1,7 @@
#include <stdarg.h>
#include <algorithm>
#include <atomic>
#include <chrono>
#include <cstdarg>
#include <fstream>
#include <functional>
#include <mutex>
@@ -869,7 +869,6 @@ uint16_t f8_e5m2_to_f16(uint8_t fp8) {
}
if (exponent == 0) { // subnormal numbers
fp16_exponent = 0;
fp16_mantissa = (mantissa << 8);
return fp16_sign | fp16_mantissa;
}
@@ -948,7 +947,7 @@ void convert_tensor(void* src,
ggml_fp16_to_fp32_row((ggml_fp16_t*)src, (float*)dst, n);
} else {
auto qtype = ggml_get_type_traits(src_type);
if (qtype->to_float == NULL) {
if (qtype->to_float == nullptr) {
throw std::runtime_error(format("type %s unsupported for integer quantization: no dequantization available",
ggml_type_name(src_type)));
}
@@ -958,7 +957,7 @@ void convert_tensor(void* src,
// src_type == GGML_TYPE_F16 => dst_type is quantized
// src_type is quantized => dst_type == GGML_TYPE_F16 or dst_type is quantized
auto qtype = ggml_get_type_traits(src_type);
if (qtype->to_float == NULL) {
if (qtype->to_float == nullptr) {
throw std::runtime_error(format("type %s unsupported for integer quantization: no dequantization available",
ggml_type_name(src_type)));
}
@@ -1020,7 +1019,7 @@ std::map<char, int> unicode_to_byte() {
bool is_zip_file(const std::string& file_path) {
struct zip_t* zip = zip_open(file_path.c_str(), 0, 'r');
if (zip == NULL) {
if (zip == nullptr) {
return false;
}
zip_close(zip);
@@ -1116,8 +1115,8 @@ bool ModelLoader::init_from_gguf_file(const std::string& file_path, const std::s
file_paths_.push_back(file_path);
size_t file_index = file_paths_.size() - 1;
gguf_context* ctx_gguf_ = NULL;
ggml_context* ctx_meta_ = NULL;
gguf_context* ctx_gguf_ = nullptr;
ggml_context* ctx_meta_ = nullptr;
ctx_gguf_ = gguf_init_from_file(file_path.c_str(), {true, &ctx_meta_});
if (!ctx_gguf_) {
@@ -1726,7 +1725,7 @@ bool ModelLoader::init_from_ckpt_file(const std::string& file_path, const std::s
size_t file_index = file_paths_.size() - 1;
struct zip_t* zip = zip_open(file_path.c_str(), 0, 'r');
if (zip == NULL) {
if (zip == nullptr) {
LOG_ERROR("failed to open '%s'", file_path.c_str());
return false;
}
@@ -1739,7 +1738,7 @@ bool ModelLoader::init_from_ckpt_file(const std::string& file_path, const std::s
if (pos != std::string::npos) {
std::string dir = name.substr(0, pos);
printf("ZIP %d, name = %s, dir = %s \n", i, name.c_str(), dir.c_str());
void* pkl_data = NULL;
void* pkl_data = nullptr;
size_t pkl_size;
zip_entry_read(zip, &pkl_data, &pkl_size);
@@ -2144,10 +2143,10 @@ bool ModelLoader::load_tensors(on_new_tensor_cb_t on_new_tensor_cb, int n_thread
for (int i = 0; i < n_threads; ++i) {
workers.emplace_back([&, file_path, is_zip]() {
std::ifstream file;
struct zip_t* zip = NULL;
struct zip_t* zip = nullptr;
if (is_zip) {
zip = zip_open(file_path.c_str(), 0, 'r');
if (zip == NULL) {
if (zip == nullptr) {
LOG_ERROR("failed to open zip '%s'", file_path.c_str());
failed = true;
return;
@@ -2172,7 +2171,7 @@ bool ModelLoader::load_tensors(on_new_tensor_cb_t on_new_tensor_cb, int n_thread
}
const TensorStorage& tensor_storage = *file_tensors[idx];
ggml_tensor* dst_tensor = NULL;
ggml_tensor* dst_tensor = nullptr;
t0 = ggml_time_ms();
@@ -2182,7 +2181,7 @@ bool ModelLoader::load_tensors(on_new_tensor_cb_t on_new_tensor_cb, int n_thread
break;
}
if (dst_tensor == NULL) {
if (dst_tensor == nullptr) {
t1 = ggml_time_ms();
read_time_ms.fetch_add(t1 - t0);
continue;
@@ -2191,7 +2190,7 @@ bool ModelLoader::load_tensors(on_new_tensor_cb_t on_new_tensor_cb, int n_thread
size_t nbytes_to_read = tensor_storage.nbytes_to_read();
auto read_data = [&](char* buf, size_t n) {
if (zip != NULL) {
if (zip != nullptr) {
zip_entry_openbyindex(zip, tensor_storage.index_in_zip);
size_t entry_size = zip_entry_size(zip);
if (entry_size != n) {
@@ -2215,7 +2214,7 @@ bool ModelLoader::load_tensors(on_new_tensor_cb_t on_new_tensor_cb, int n_thread
}
};
if (dst_tensor->buffer == NULL || ggml_backend_buffer_is_host(dst_tensor->buffer)) {
if (dst_tensor->buffer == nullptr || ggml_backend_buffer_is_host(dst_tensor->buffer)) {
if (tensor_storage.type == dst_tensor->type) {
GGML_ASSERT(ggml_nbytes(dst_tensor) == tensor_storage.nbytes());
if (tensor_storage.is_f64 || tensor_storage.is_i64) {
@@ -2317,7 +2316,7 @@ bool ModelLoader::load_tensors(on_new_tensor_cb_t on_new_tensor_cb, int n_thread
}
}
}
if (zip != NULL) {
if (zip != nullptr) {
zip_close(zip);
}
});
@@ -2507,7 +2506,7 @@ bool ModelLoader::save_to_gguf_file(const std::string& file_path, ggml_type type
mem_size += tensor_storages.size() * ggml_tensor_overhead();
mem_size += get_params_mem_size(backend, type);
LOG_INFO("model tensors mem size: %.2fMB", mem_size / 1024.f / 1024.f);
ggml_context* ggml_ctx = ggml_init({mem_size, NULL, false});
ggml_context* ggml_ctx = ggml_init({mem_size, nullptr, false});
gguf_context* gguf_ctx = gguf_init_empty();
@@ -2533,7 +2532,7 @@ bool ModelLoader::save_to_gguf_file(const std::string& file_path, ggml_type type
std::lock_guard<std::mutex> lock(tensor_mutex);
ggml_tensor* tensor = ggml_new_tensor(ggml_ctx, tensor_type, tensor_storage.n_dims, tensor_storage.ne);
if (tensor == NULL) {
if (tensor == nullptr) {
LOG_ERROR("ggml_new_tensor failed");
return false;
}
@@ -2566,7 +2565,7 @@ bool ModelLoader::save_to_gguf_file(const std::string& file_path, ggml_type type
int64_t ModelLoader::get_params_mem_size(ggml_backend_t backend, ggml_type type) {
size_t alignment = 128;
if (backend != NULL) {
if (backend != nullptr) {
alignment = ggml_backend_get_alignment(backend);
}
int64_t mem_size = 0;
@@ -2596,7 +2595,7 @@ bool convert(const char* input_path, const char* vae_path, const char* output_pa
return false;
}
if (vae_path != NULL && strlen(vae_path) > 0) {
if (vae_path != nullptr && strlen(vae_path) > 0) {
if (!model_loader.init_from_file(vae_path, "vae.")) {
LOG_ERROR("init model loader from file failed: '%s'", vae_path);
return false;