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5 Commits

Author SHA1 Message Date
Jesse Gross
accf266be6
Merge a2d4b6fc81 into 30caac3a68 2024-12-24 13:18:46 +05:30
Georgi Gerganov
30caac3a68
llama : the WPM vocabs use the CLS token as BOS (#10930)
* llama : the WPM vocabs use the CLS token as BOS

ggml-ci

* llama : add comment
2024-12-24 09:44:20 +02:00
Diego Devesa
60cfa728e2
ggml : use wstring for backend search paths (#10960)
ggml-ci
2024-12-24 04:05:27 +01:00
Diego Devesa
3327bb0f8d
ggml : fix arm enabled features check (#10961) 2024-12-24 04:05:17 +01:00
Jesse Gross
a2d4b6fc81 llama: Ensure KV cache is fully defragmented.
Sometimes the KV cache requires defragmentation even without
triggering the threshold heuristic. In this case, decoding
will not being able to find a KV cache slot. This is particularly
difficult for the caller to handle if it happens in between
ubatches. To avoid this, we should immediately trigger a defrag.

In addition, a heavily fragmented cache can require more than
max_moves to defragment. Currently, we stop when we hit the limit
but this can leave a cache that still does not have adequate space
even after defragmentation is triggered. Instead, we should do
multiple batches of processing until everything is complete.
2024-12-17 12:43:17 -08:00
6 changed files with 131 additions and 105 deletions

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@ -234,6 +234,7 @@ function(ggml_add_backend_library backend)
# write the shared library to the output directory
set_target_properties(${backend} PROPERTIES LIBRARY_OUTPUT_DIRECTORY ${CMAKE_RUNTIME_OUTPUT_DIRECTORY})
target_compile_definitions(${backend} PRIVATE GGML_BACKEND_DL)
add_dependencies(ggml ${backend})
else()
add_library(${backend} ${ARGN})
target_link_libraries(ggml PUBLIC ${backend})

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@ -66,6 +66,26 @@
#include "ggml-kompute.h"
#endif
// disable C++17 deprecation warning for std::codecvt_utf8
#if defined(__clang__)
# pragma clang diagnostic push
# pragma clang diagnostic ignored "-Wdeprecated-declarations"
#endif
static std::wstring utf8_to_utf16(const std::string & str) {
std::wstring_convert<std::codecvt_utf8_utf16<wchar_t>> converter;
return converter.from_bytes(str);
}
static std::string utf16_to_utf8(const std::wstring & str) {
std::wstring_convert<std::codecvt_utf8_utf16<wchar_t>> converter;
return converter.to_bytes(str);
}
#if defined(__clang__)
# pragma clang diagnostic pop
#endif
#ifdef _WIN32
using dl_handle = std::remove_pointer_t<HMODULE>;
@ -88,11 +108,6 @@ static dl_handle * dl_load_library(const std::wstring & path) {
return handle;
}
static dl_handle * dl_load_library(const std::string & path) {
std::wstring_convert<std::codecvt_utf8_utf16<wchar_t>> converter;
return dl_load_library(converter.from_bytes(path));
}
static void * dl_get_sym(dl_handle * handle, const char * name) {
DWORD old_mode = SetErrorMode(SEM_FAILCRITICALERRORS);
SetErrorMode(old_mode | SEM_FAILCRITICALERRORS);
@ -114,8 +129,8 @@ struct dl_handle_deleter {
}
};
static void * dl_load_library(const std::string & path) {
dl_handle * handle = dlopen(path.c_str(), RTLD_NOW | RTLD_LOCAL);
static void * dl_load_library(const std::wstring & path) {
dl_handle * handle = dlopen(utf16_to_utf8(path).c_str(), RTLD_NOW | RTLD_LOCAL);
return handle;
}
@ -202,11 +217,11 @@ struct ggml_backend_registry {
devices.push_back(device);
}
ggml_backend_reg_t load_backend(const char * path, bool silent) {
ggml_backend_reg_t load_backend(const std::wstring & path, bool silent) {
dl_handle_ptr handle { dl_load_library(path) };
if (!handle) {
if (!silent) {
GGML_LOG_ERROR("%s: failed to load %s\n", __func__, path);
GGML_LOG_ERROR("%s: failed to load %s\n", __func__, utf16_to_utf8(path).c_str());
}
return nullptr;
}
@ -214,7 +229,7 @@ struct ggml_backend_registry {
auto score_fn = (ggml_backend_score_t) dl_get_sym(handle.get(), "ggml_backend_score");
if (score_fn && score_fn() == 0) {
if (!silent) {
GGML_LOG_INFO("%s: backend %s is not supported on this system\n", __func__, path);
GGML_LOG_INFO("%s: backend %s is not supported on this system\n", __func__, utf16_to_utf8(path).c_str());
}
return nullptr;
}
@ -222,7 +237,7 @@ struct ggml_backend_registry {
auto backend_init_fn = (ggml_backend_init_t) dl_get_sym(handle.get(), "ggml_backend_init");
if (!backend_init_fn) {
if (!silent) {
GGML_LOG_ERROR("%s: failed to find ggml_backend_init in %s\n", __func__, path);
GGML_LOG_ERROR("%s: failed to find ggml_backend_init in %s\n", __func__, utf16_to_utf8(path).c_str());
}
return nullptr;
}
@ -231,16 +246,16 @@ struct ggml_backend_registry {
if (!reg || reg->api_version != GGML_BACKEND_API_VERSION) {
if (!silent) {
if (!reg) {
GGML_LOG_ERROR("%s: failed to initialize backend from %s: ggml_backend_init returned NULL\n", __func__, path);
GGML_LOG_ERROR("%s: failed to initialize backend from %s: ggml_backend_init returned NULL\n", __func__, utf16_to_utf8(path).c_str());
} else {
GGML_LOG_ERROR("%s: failed to initialize backend from %s: incompatible API version (backend: %d, current: %d)\n",
__func__, path, reg->api_version, GGML_BACKEND_API_VERSION);
__func__, utf16_to_utf8(path).c_str(), reg->api_version, GGML_BACKEND_API_VERSION);
}
}
return nullptr;
}
GGML_LOG_INFO("%s: loaded %s backend from %s\n", __func__, ggml_backend_reg_name(reg), path);
GGML_LOG_INFO("%s: loaded %s backend from %s\n", __func__, ggml_backend_reg_name(reg), utf16_to_utf8(path).c_str());
register_backend(reg, std::move(handle));
@ -376,14 +391,14 @@ ggml_backend_t ggml_backend_init_best(void) {
// Dynamic loading
ggml_backend_reg_t ggml_backend_load(const char * path) {
return get_reg().load_backend(path, false);
return get_reg().load_backend(utf8_to_utf16(path), false);
}
void ggml_backend_unload(ggml_backend_reg_t reg) {
get_reg().unload_backend(reg, true);
}
static std::string get_executable_path() {
static std::wstring get_executable_path() {
#if defined(__APPLE__)
// get executable path
std::vector<char> path;
@ -401,7 +416,7 @@ static std::string get_executable_path() {
if (last_slash != std::string::npos) {
base_path = base_path.substr(0, last_slash);
}
return base_path + "/";
return utf8_to_utf16(base_path + "/");
#elif defined(__linux__) || defined(__FreeBSD__)
std::string base_path = ".";
std::vector<char> path(1024);
@ -427,57 +442,63 @@ static std::string get_executable_path() {
path.resize(path.size() * 2);
}
return base_path + "/";
return utf8_to_utf16(base_path + "/");
#elif defined(_WIN32)
std::vector<char> path(MAX_PATH);
DWORD len = GetModuleFileNameA(NULL, path.data(), path.size());
std::vector<wchar_t> path(MAX_PATH);
DWORD len = GetModuleFileNameW(NULL, path.data(), path.size());
if (len == 0) {
return "";
return {};
}
std::string base_path(path.data(), len);
std::wstring base_path(path.data(), len);
// remove executable name
auto last_slash = base_path.find_last_of('\\');
if (last_slash != std::string::npos) {
base_path = base_path.substr(0, last_slash);
}
return base_path + "\\";
return base_path + L"\\";
#else
return {};
#endif
}
static std::string backend_filename_prefix() {
static std::wstring backend_filename_prefix() {
#ifdef _WIN32
return "ggml-";
return L"ggml-";
#else
return "libggml-";
return L"libggml-";
#endif
}
static std::string backend_filename_suffix() {
static std::wstring backend_filename_suffix() {
#ifdef _WIN32
return ".dll";
return L".dll";
#else
return ".so";
return L".so";
#endif
}
static std::wstring path_separator() {
#ifdef _WIN32
return L"\\";
#else
return L"/";
#endif
}
static ggml_backend_reg_t ggml_backend_load_best(const char * name, bool silent, const char * user_search_path) {
// enumerate all the files that match [lib]ggml-name-*.[so|dll] in the search paths
// TODO: search system paths
std::string file_prefix = backend_filename_prefix() + name + "-";
std::vector<std::string> search_paths;
std::wstring file_prefix = backend_filename_prefix() + utf8_to_utf16(name) + L"-";
std::vector<std::wstring> search_paths;
if (user_search_path == nullptr) {
search_paths.push_back("./");
search_paths.push_back(L"." + path_separator());
search_paths.push_back(get_executable_path());
} else {
#if defined(_WIN32)
search_paths.push_back(std::string(user_search_path) + "\\");
#else
search_paths.push_back(std::string(user_search_path) + "/");
#endif
search_paths.push_back(utf8_to_utf16(user_search_path) + path_separator());
}
int best_score = 0;
std::string best_path;
std::wstring best_path;
namespace fs = std::filesystem;
for (const auto & search_path : search_paths) {
@ -487,27 +508,27 @@ static ggml_backend_reg_t ggml_backend_load_best(const char * name, bool silent,
fs::directory_iterator dir_it(search_path, fs::directory_options::skip_permission_denied);
for (const auto & entry : dir_it) {
if (entry.is_regular_file()) {
std::string filename = entry.path().filename().string();
std::string ext = entry.path().extension().string();
std::wstring filename = entry.path().filename().wstring();
std::wstring ext = entry.path().extension().wstring();
if (filename.find(file_prefix) == 0 && ext == backend_filename_suffix()) {
dl_handle_ptr handle { dl_load_library(entry.path().c_str()) };
dl_handle_ptr handle { dl_load_library(entry.path().wstring()) };
if (!handle && !silent) {
GGML_LOG_ERROR("%s: failed to load %s\n", __func__, entry.path().string().c_str());
GGML_LOG_ERROR("%s: failed to load %s\n", __func__, utf16_to_utf8(entry.path().wstring()).c_str());
}
if (handle) {
auto score_fn = (ggml_backend_score_t) dl_get_sym(handle.get(), "ggml_backend_score");
if (score_fn) {
int s = score_fn();
#ifndef NDEBUG
GGML_LOG_DEBUG("%s: %s score: %d\n", __func__, entry.path().string().c_str(), s);
GGML_LOG_DEBUG("%s: %s score: %d\n", __func__, utf16_to_utf8(entry.path().wstring()).c_str(), s);
#endif
if (s > best_score) {
best_score = s;
best_path = entry.path().string();
best_path = entry.path().wstring();
}
} else {
if (!silent) {
GGML_LOG_INFO("%s: failed to find ggml_backend_score in %s\n", __func__, entry.path().string().c_str());
GGML_LOG_INFO("%s: failed to find ggml_backend_score in %s\n", __func__, utf16_to_utf8(entry.path().wstring()).c_str());
}
}
}
@ -519,15 +540,15 @@ static ggml_backend_reg_t ggml_backend_load_best(const char * name, bool silent,
if (best_score == 0) {
// try to load the base backend
for (const auto & search_path : search_paths) {
std::string path = search_path + backend_filename_prefix() + name + backend_filename_suffix();
std::wstring path = search_path + backend_filename_prefix() + utf8_to_utf16(name) + backend_filename_suffix();
if (fs::exists(path)) {
return get_reg().load_backend(path.c_str(), silent);
return get_reg().load_backend(path, silent);
}
}
return nullptr;
}
return get_reg().load_backend(best_path.c_str(), silent);
return get_reg().load_backend(best_path, silent);
}
void ggml_backend_load_all() {

View File

@ -135,14 +135,20 @@ function(ggml_add_cpu_backend_variant_impl tag_name)
endif()
# show enabled features
if (CMAKE_HOST_SYSTEM_NAME STREQUAL "Windows")
set(FEAT_INPUT_FILE "NUL")
else()
set(FEAT_INPUT_FILE "/dev/null")
endif()
execute_process(
COMMAND ${CMAKE_C_COMPILER} ${ARCH_FLAGS} -dM -E -
INPUT_FILE "/dev/null"
INPUT_FILE ${FEAT_INPUT_FILE}
OUTPUT_VARIABLE ARM_FEATURE
RESULT_VARIABLE ARM_FEATURE_RESULT
)
if (ARM_FEATURE_RESULT)
message(FATAL_ERROR "Failed to get ARM features")
message(WARNING "Failed to get ARM features")
else()
foreach(feature DOTPROD SVE MATMUL_INT8 FMA FP16_VECTOR_ARITHMETIC)
string(FIND "${ARM_FEATURE}" "__ARM_FEATURE_${feature} 1" feature_pos)
@ -317,6 +323,11 @@ function(ggml_add_cpu_backend_variant_impl tag_name)
target_compile_definitions(${GGML_CPU_NAME} PRIVATE ${ARCH_DEFINITIONS})
if (GGML_BACKEND_DL)
if (GGML_NATIVE)
# the feature check relies on ARCH_DEFINITIONS, but it is not set with GGML_NATIVE
message(FATAL_ERROR "GGML_NATIVE is not compatible with GGML_BACKEND_DL, consider using GGML_CPU_ALL_VARIANTS")
endif()
# The feature detection code is compiled as a separate target so that
# it can be built without the architecture flags
# Since multiple variants of the CPU backend may be included in the same

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@ -1657,7 +1657,7 @@ bool llama_token_is_control_impl(const struct llama_vocab & vocab, llama_token t
}
llama_token llama_token_bos_impl(const struct llama_vocab & vocab) {
return vocab.special_bos_id;
return vocab.type != LLAMA_VOCAB_TYPE_WPM ? vocab.special_bos_id : vocab.special_cls_id;
}
llama_token llama_token_eos_impl(const struct llama_vocab & vocab) {

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@ -45,7 +45,7 @@ struct llama_vocab {
id special_unk_id = 0;
id special_sep_id = LLAMA_TOKEN_NULL;
id special_pad_id = LLAMA_TOKEN_NULL;
id special_cls_id = LLAMA_TOKEN_NULL;
id special_cls_id = LLAMA_TOKEN_NULL; // TODO: revisit if this is really needed https://github.com/ggerganov/llama.cpp/pull/10930
id special_mask_id = LLAMA_TOKEN_NULL;
id linefeed_id = 13;

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@ -3053,6 +3053,13 @@ struct llama_kv_cache {
}
};
// block of KV slots to move when defragging
struct llama_kv_defrag_move {
uint32_t src;
uint32_t dst;
uint32_t len;
};
struct llama_control_vector {
std::vector<struct ggml_tensor *> tensors; // per layer
std::vector<ggml_context_ptr> ctxs;
@ -10990,35 +10997,23 @@ struct llm_build_context {
return gf;
}
struct ggml_cgraph * build_defrag(const std::vector<uint32_t> & ids) {
struct ggml_cgraph * build_defrag(const std::vector<struct llama_kv_defrag_move> & moves) {
struct ggml_cgraph * gf = ggml_new_graph_custom(ctx0, llama_model_max_nodes(model), false);
for (uint32_t i = 0; i < ids.size(); ++i) {
const uint32_t id = ids[i];
if (i == id || id == ids.size()) {
continue;
}
uint32_t nm = 1;
while (i + nm < ids.size() && ids[i + nm] == id + nm) {
nm++;
}
for (const auto & move : moves) {
for (int il = 0; il < n_layer; ++il) {
const int64_t n_embd_k_gqa = hparams.n_embd_k_gqa(il);
const int64_t n_embd_v_gqa = hparams.n_embd_v_gqa(il);
ggml_tensor * view_k_src = ggml_view_2d(ctx0, kv_self.k_l[il],
n_embd_k_gqa, nm,
n_embd_k_gqa, move.len,
ggml_row_size(kv_self.k_l[il]->type, n_embd_k_gqa),
ggml_row_size(kv_self.k_l[il]->type, n_embd_k_gqa*i));
ggml_row_size(kv_self.k_l[il]->type, n_embd_k_gqa*move.src));
ggml_tensor * view_k_dst = ggml_view_2d(ctx0, kv_self.k_l[il],
n_embd_k_gqa, nm,
n_embd_k_gqa, move.len,
ggml_row_size(kv_self.k_l[il]->type, n_embd_k_gqa),
ggml_row_size(kv_self.k_l[il]->type, n_embd_k_gqa*id));
ggml_row_size(kv_self.k_l[il]->type, n_embd_k_gqa*move.dst));
ggml_tensor * view_v_src;
ggml_tensor * view_v_dst;
@ -11026,31 +11021,29 @@ struct llm_build_context {
if (flash_attn) {
// NOTE: the V cache is not transposed when using flash attention
view_v_src = ggml_view_2d(ctx0, kv_self.v_l[il],
n_embd_v_gqa, nm,
n_embd_v_gqa, move.len,
ggml_row_size(kv_self.v_l[il]->type, n_embd_v_gqa),
ggml_row_size(kv_self.v_l[il]->type, n_embd_v_gqa*i));
ggml_row_size(kv_self.v_l[il]->type, n_embd_v_gqa*move.src));
view_v_dst = ggml_view_2d(ctx0, kv_self.v_l[il],
n_embd_v_gqa, nm,
n_embd_v_gqa, move.len,
ggml_row_size(kv_self.v_l[il]->type, n_embd_v_gqa),
ggml_row_size(kv_self.v_l[il]->type, n_embd_v_gqa*id));
ggml_row_size(kv_self.v_l[il]->type, n_embd_v_gqa*move.dst));
} else {
view_v_src = ggml_view_2d(ctx0, kv_self.v_l[il],
nm, n_embd_v_gqa,
move.len, n_embd_v_gqa,
ggml_row_size(kv_self.v_l[il]->type, kv_self.size),
ggml_row_size(kv_self.v_l[il]->type, i));
ggml_row_size(kv_self.v_l[il]->type, move.src));
view_v_dst = ggml_view_2d(ctx0, kv_self.v_l[il],
nm, n_embd_v_gqa,
move.len, n_embd_v_gqa,
ggml_row_size(kv_self.v_l[il]->type, kv_self.size),
ggml_row_size(kv_self.v_l[il]->type, id));
ggml_row_size(kv_self.v_l[il]->type, move.dst));
}
ggml_build_forward_expand(gf, ggml_cpy(ctx0, view_k_src, view_k_dst));
ggml_build_forward_expand(gf, ggml_cpy(ctx0, view_v_src, view_v_dst));
}
i += nm - 1;
}
//LLAMA_LOG_INFO("gf->n_nodes = %d\n", gf->n_nodes);
@ -17601,7 +17594,7 @@ struct llm_build_context {
}
};
static struct ggml_cgraph * llama_build_graph_defrag(llama_context & lctx, const std::vector<uint32_t> & ids) {
static struct ggml_cgraph * llama_build_graph_defrag(llama_context & lctx, const std::vector<struct llama_kv_defrag_move> & moves) {
llama_ubatch dummy = {};
dummy.equal_seqs = true;
@ -17611,7 +17604,7 @@ static struct ggml_cgraph * llama_build_graph_defrag(llama_context & lctx, const
llm.init();
struct ggml_cgraph * result = llm.build_defrag(ids);
struct ggml_cgraph * result = llm.build_defrag(moves);
llm.free();
@ -18627,7 +18620,12 @@ static int llama_decode_internal(
kv_self.head = 0;
}
const auto slot = llama_kv_cache_find_slot(kv_self, ubatch);
auto slot = llama_kv_cache_find_slot(kv_self, ubatch);
if (!slot) {
llama_kv_cache_defrag(kv_self);
llama_kv_cache_update(&lctx);
slot = llama_kv_cache_find_slot(kv_self, ubatch);
}
if (!slot) {
return 1;
}
@ -19030,8 +19028,8 @@ static void llama_kv_cache_defrag_internal(struct llama_context & lctx) {
//const int64_t t_start = ggml_time_us();
// number of cells moved
uint32_t n_moves = 0;
// groups of cells moved
std::vector<struct llama_kv_defrag_move> moves;
// each move requires 6*n_layer tensors (see build_defrag)
// - source view, destination view, copy operation
@ -19095,19 +19093,11 @@ static void llama_kv_cache_defrag_internal(struct llama_context & lctx) {
// are we moving a continuous block of memory?
bool cont = false;
// should we stop searching for the next move?
bool stop = false;
// go back and move the nf cells to the hole
for (; i1 < n_kv; ++i1) {
auto & cell1 = kv_self.cells[i1];
if (cell1.is_empty() || ids[i1] != n_kv) {
if (n_moves == max_moves) {
stop = true;
break;
}
cont = false;
continue;
}
@ -19123,8 +19113,10 @@ static void llama_kv_cache_defrag_internal(struct llama_context & lctx) {
kv_self.head = n_used;
if (!cont) {
n_moves++;
moves.push_back({i1, i0 + nf, 1});
cont = true;
} else {
moves.back().len++;
}
nf++;
@ -19134,22 +19126,16 @@ static void llama_kv_cache_defrag_internal(struct llama_context & lctx) {
}
}
if (stop || n_moves == max_moves) {
break;
}
//LLAMA_LOG_INFO("(tmp log) KV defrag: move [%u, %u) to [%u, %u)\n", is, i1 + 1, i0, i0 + nh);
i0 += nh - 1;
}
if (n_moves == 0) {
if (moves.size() == 0) {
return;
}
//LLAMA_LOG_INFO("(tmp log) KV defrag cell moves: %u\n", n_moves);
//LLAMA_LOG_INFO("expected gf nodes: %u\n", 6*n_moves*n_layer);
//LLAMA_LOG_INFO("(tmp log) KV defrag cell moves: %u\n", moves.size());
#if 0
// CPU defrag
@ -19224,11 +19210,18 @@ static void llama_kv_cache_defrag_internal(struct llama_context & lctx) {
#else
// ggml_graph defrag
for (std::size_t i = 0; i < moves.size(); i += max_moves) {
std::vector<struct llama_kv_defrag_move> chunk;
auto end = std::min(i + max_moves, moves.size());
chunk.assign(moves.begin() + i, moves.begin() + end);
ggml_backend_sched_reset(lctx.sched.get());
ggml_cgraph * gf = llama_build_graph_defrag(lctx, ids);
//LLAMA_LOG_INFO("expected gf nodes: %u\n", 6*chunk.size()*n_layer);
ggml_cgraph * gf = llama_build_graph_defrag(lctx, chunk);
llama_graph_compute(lctx, gf, lctx.cparams.n_threads, lctx.threadpool);
}
#endif
//const int64_t t_end = ggml_time_us();