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cmake : add sanitizer flags for llama.cpp (#11279)

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* cmake : add sanitizer flags for llama.cpp

ggml-ci

* tests : fix compile warnings

ggml-ci

* cmake : move sanitizer flags to llama_add_compile_flags

ggml-ci

* cmake : move llama.cpp compile flags to top level lists

ggml-ci

* cmake : apply only sanitizer flags at top level

ggml-ci

* tests : fix gguf context use in same_tensor_data

* gguf-test: tensor data comparison

* dummy : trigger ggml-ci

* unicode : silence gcc warnings

ggml-ci

* ci : use sanitizer builds only in Debug mode

ggml-ci

* cmake : add status messages [no ci]

---------

Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
This commit is contained in:
Georgi Gerganov 2025-01-18 16:18:15 +02:00 committed by GitHub
parent f30f099228
commit 4dd34ff831
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
7 changed files with 74 additions and 41 deletions
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2
.github/workflows/build.yml vendored
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@ -234,7 +234,7 @@ jobs:
strategy:
matrix:
sanitizer: [ADDRESS, THREAD, UNDEFINED]
build_type: [Debug, Release]
build_type: [Debug]
steps:
- name: Clone

73
CMakeLists.txt
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@ -83,11 +83,8 @@ include(${CMAKE_CURRENT_SOURCE_DIR}/cmake/build-info.cmake)
include(${CMAKE_CURRENT_SOURCE_DIR}/cmake/common.cmake)
# override ggml options
set(GGML_SANITIZE_THREAD ${LLAMA_SANITIZE_THREAD})
set(GGML_SANITIZE_ADDRESS ${LLAMA_SANITIZE_ADDRESS})
set(GGML_SANITIZE_UNDEFINED ${LLAMA_SANITIZE_UNDEFINED})
set(GGML_ALL_WARNINGS ${LLAMA_ALL_WARNINGS})
set(GGML_FATAL_WARNINGS ${LLAMA_FATAL_WARNINGS})
set(GGML_ALL_WARNINGS ${LLAMA_ALL_WARNINGS})
set(GGML_FATAL_WARNINGS ${LLAMA_FATAL_WARNINGS})
# change the default for these ggml options
if (NOT DEFINED GGML_LLAMAFILE)
@ -117,16 +114,62 @@ llama_option_depr(WARNING LLAMA_SYCL GGML_SYCL)
llama_option_depr(WARNING LLAMA_SYCL_F16 GGML_SYCL_F16)
llama_option_depr(WARNING LLAMA_CANN GGML_CANN)
if (NOT MSVC)
if (LLAMA_SANITIZE_THREAD)
message(STATUS "Using -fsanitize=thread")
add_compile_options(-fsanitize=thread)
link_libraries (-fsanitize=thread)
endif()
if (LLAMA_SANITIZE_ADDRESS)
message(STATUS "Using -fsanitize=address")
add_compile_options(-fsanitize=address -fno-omit-frame-pointer)
link_libraries (-fsanitize=address)
endif()
if (LLAMA_SANITIZE_UNDEFINED)
message(STATUS "Using -fsanitize=undefined")
add_compile_options(-fsanitize=undefined)
link_libraries (-fsanitize=undefined)
endif()
endif()
#
# build the library
# 3rd-party
#
if (NOT TARGET ggml)
add_subdirectory(ggml)
# ... otherwise assume ggml is added by a parent CMakeLists.txt
endif()
#
# build the library
#
add_subdirectory(src)
#
# utils, programs, examples and tests
#
if (LLAMA_BUILD_COMMON)
add_subdirectory(common)
endif()
if (LLAMA_BUILD_COMMON AND LLAMA_BUILD_TESTS AND NOT CMAKE_JS_VERSION)
include(CTest)
add_subdirectory(tests)
endif()
if (LLAMA_BUILD_COMMON AND LLAMA_BUILD_EXAMPLES)
add_subdirectory(examples)
add_subdirectory(pocs)
endif()
#
# install
#
@ -200,21 +243,3 @@ configure_file(cmake/llama.pc.in
install(FILES "${CMAKE_CURRENT_BINARY_DIR}/llama.pc"
DESTINATION lib/pkgconfig)
#
# utils, programs, examples and tests
#
if (LLAMA_BUILD_COMMON)
add_subdirectory(common)
endif()
if (LLAMA_BUILD_COMMON AND LLAMA_BUILD_TESTS AND NOT CMAKE_JS_VERSION)
include(CTest)
add_subdirectory(tests)
endif()
if (LLAMA_BUILD_COMMON AND LLAMA_BUILD_EXAMPLES)
add_subdirectory(examples)
add_subdirectory(pocs)
endif()

4
ggml/src/gguf.cpp
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@ -648,6 +648,10 @@ struct gguf_context * gguf_init_from_file_impl(FILE * file, struct gguf_init_par
ok = ok && data != nullptr;
if (ok) {
ggml_set_name(data, "GGUF tensor data binary blob");
}
// read the binary blob with the tensor data
ok = ok && gr.read(data->data, ctx->size);

5
src/unicode.cpp
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@ -7,18 +7,17 @@
#include <algorithm>
#include <cassert>
#include <codecvt>
#include <cstddef>
#include <cstdint>
#include <locale>
#include <map>
#include <regex>
#include <stdexcept>
#include <string>
#include <unordered_map>
#include <unordered_set>
#include <utility>
#include <vector>
#include <locale>
#include <codecvt>
size_t unicode_len_utf8(char src) {
const size_t lookup[] = { 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 3, 4 };

2
tests/CMakeLists.txt
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@ -1,3 +1,5 @@
llama_add_compile_flags()
function(llama_test target)
include(CMakeParseArguments)
set(options)

28
tests/test-gguf.cpp
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@ -48,7 +48,7 @@ enum handcrafted_file_type {
HANDCRAFTED_DATA_CUSTOM_ALIGN = 810 + offset_has_data,
};
std::string handcrafted_file_type_name(const enum handcrafted_file_type hft) {
static std::string handcrafted_file_type_name(const enum handcrafted_file_type hft) {
switch (hft) {
case HANDCRAFTED_HEADER_BAD_MAGIC: return "HEADER_BAD_MAGIC";
case HANDCRAFTED_HEADER_BAD_VERSION_1: return "HEADER_BAD_VERSION_1";
@ -99,7 +99,7 @@ static bool expect_context_not_null(const enum handcrafted_file_type hft) {
typedef std::pair<enum ggml_type, std::array<int64_t, GGML_MAX_DIMS>> tensor_config_t;
std::vector<tensor_config_t> get_tensor_configs(std::mt19937 & rng) {
static std::vector<tensor_config_t> get_tensor_configs(std::mt19937 & rng) {
std::vector<tensor_config_t> tensor_configs;
tensor_configs.reserve(100);
@ -122,7 +122,7 @@ std::vector<tensor_config_t> get_tensor_configs(std::mt19937 & rng) {
return tensor_configs;
}
std::vector<std::pair<enum gguf_type, enum gguf_type>> get_kv_types(std::mt19937 rng) {
static std::vector<std::pair<enum gguf_type, enum gguf_type>> get_kv_types(std::mt19937 rng) {
std::vector<std::pair<enum gguf_type, enum gguf_type>> kv_types;
kv_types.reserve(100);
@ -626,8 +626,6 @@ static bool handcrafted_check_tensor_data(const gguf_context * gguf_ctx, const u
bool ok = true;
const uint32_t alignment = GGUF_DEFAULT_ALIGNMENT;
for (int i = 0; i < int(tensor_configs.size()); ++i) {
const ggml_type type = tensor_configs[i].first;
const std::array<int64_t, GGML_MAX_DIMS> shape = tensor_configs[i].second;
@ -866,13 +864,13 @@ static struct random_gguf_context_result get_random_gguf_context(ggml_backend_t
case GGUF_TYPE_COUNT:
default: {
GGML_ABORT("fatal error");
} break;
}
}
} break;
case GGUF_TYPE_COUNT:
default: {
GGML_ABORT("fatal error");
} break;
}
}
}
@ -938,7 +936,7 @@ static bool all_kv_in_other(const gguf_context * ctx, const gguf_context * other
}
if (type == GGUF_TYPE_ARRAY) {
const int arr_n = gguf_get_arr_n(ctx, id);
const size_t arr_n = gguf_get_arr_n(ctx, id);
if (arr_n != gguf_get_arr_n(other, idx_other)) {
ok = false;
continue;
@ -953,7 +951,7 @@ static bool all_kv_in_other(const gguf_context * ctx, const gguf_context * other
if (type_arr == GGUF_TYPE_BOOL) {
const int8_t * data = reinterpret_cast<const int8_t *>(gguf_get_arr_data(ctx, id));
const int8_t * data_other = reinterpret_cast<const int8_t *>(gguf_get_arr_data(other, idx_other));
for (int arr_i = 0; arr_i < arr_n; ++arr_i) {
for (size_t arr_i = 0; arr_i < arr_n; ++arr_i) {
if (bool(data[arr_i]) != bool(data_other[arr_i])) {
ok = false;
}
@ -962,7 +960,7 @@ static bool all_kv_in_other(const gguf_context * ctx, const gguf_context * other
}
if (type_arr == GGUF_TYPE_STRING) {
for (int arr_i = 0; arr_i < arr_n; ++arr_i) {
for (size_t arr_i = 0; arr_i < arr_n; ++arr_i) {
const std::string str = gguf_get_arr_str(ctx, id, arr_i);
const std::string str_other = gguf_get_arr_str(other, idx_other, arr_i);
if (str != str_other) {
@ -1033,6 +1031,12 @@ static bool same_tensor_data(const struct ggml_context * orig, const struct ggml
struct ggml_tensor * t_orig = ggml_get_first_tensor(orig);
struct ggml_tensor * t_read = ggml_get_first_tensor(read);
if (std::string(t_read->name) != "GGUF tensor data binary blob") {
return false;
}
t_read = ggml_get_next_tensor(read, t_read);
while (t_orig) {
if (!t_read) {
ok = false;
@ -1051,13 +1055,13 @@ static bool same_tensor_data(const struct ggml_context * orig, const struct ggml
}
t_orig = ggml_get_next_tensor(orig, t_orig);
t_read = ggml_get_next_tensor(orig, t_read);
t_read = ggml_get_next_tensor(read, t_read);
}
if (t_read) {
ok = false;
}
return true;
return ok;
}
static std::pair<int, int> test_roundtrip(ggml_backend_dev_t dev, const unsigned int seed, const bool only_meta) {

1
tests/test-sampling.cpp
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@ -144,7 +144,6 @@ static void test_penalties(
sampler_tester tester(probs, probs_expected);
const size_t n_vocab = probs.size();
auto * sampler = llama_sampler_init_penalties(last_tokens.size(), repeat_penalty, alpha_frequency, alpha_presence);
for (size_t i = 0; i < last_tokens.size(); i++) {