| | #if defined(_MSC_VER) |
| | #define _SILENCE_CXX17_CODECVT_HEADER_DEPRECATION_WARNING |
| | #endif |
| |
|
| | #include "ggml.h" |
| | #include "gguf.h" |
| |
|
| | #include "common.h" |
| | #include "log.h" |
| | #include "build-info.h" |
| | #include "log.cpp" |
| | |
| | #define JSON_ASSERT GGML_ASSERT |
| | #include "json.hpp" |
| | #include "json-schema-to-grammar.cpp" |
| | #include "llama.h" |
| | #include "chat.cpp" |
| |
|
| | #include <algorithm> |
| | #include <cinttypes> |
| | #include <climits> |
| | #include <cmath> |
| | #include <codecvt> |
| | #include <cstdarg> |
| | #include <cstring> |
| | #include <ctime> |
| | #include <filesystem> |
| | #include <fstream> |
| | #include <iostream> |
| | #include <iterator> |
| | #include <regex> |
| | #include <sstream> |
| | #include <string> |
| | #include <thread> |
| | #include <unordered_map> |
| | #include <unordered_set> |
| | #include <vector> |
| |
|
| | #if defined(__APPLE__) && defined(__MACH__) |
| | #include <sys/types.h> |
| | #include <sys/sysctl.h> |
| | #endif |
| |
|
| | #if defined(_WIN32) |
| | #define WIN32_LEAN_AND_MEAN |
| | #ifndef NOMINMAX |
| | # define NOMINMAX |
| | #endif |
| | #include <locale> |
| | #include <windows.h> |
| | #include <fcntl.h> |
| | #include <io.h> |
| | #else |
| | #include <sys/ioctl.h> |
| | #include <sys/stat.h> |
| | #include <unistd.h> |
| | #endif |
| | #if defined(LLAMA_USE_CURL) |
| | #include <curl/curl.h> |
| | #include <curl/easy.h> |
| | #include <future> |
| | #endif |
| |
|
| | #if defined(_MSC_VER) |
| | #pragma warning(disable: 4244 4267) |
| | #endif |
| |
|
| | #if defined(LLAMA_USE_CURL) |
| | #ifdef __linux__ |
| | #include <linux/limits.h> |
| | #elif defined(_WIN32) |
| | # if !defined(PATH_MAX) |
| | # define PATH_MAX MAX_PATH |
| | # endif |
| | #else |
| | #include <sys/syslimits.h> |
| | #endif |
| | #define LLAMA_CURL_MAX_URL_LENGTH 2084 |
| |
|
| | |
| | |
| | |
| |
|
| | using curl_ptr = std::unique_ptr<CURL, decltype(&curl_easy_cleanup)>; |
| |
|
| | |
| | struct curl_slist_ptr { |
| | struct curl_slist * ptr = nullptr; |
| | ~curl_slist_ptr() { |
| | if (ptr) { |
| | curl_slist_free_all(ptr); |
| | } |
| | } |
| | }; |
| | #endif |
| |
|
| | using json = nlohmann::ordered_json; |
| |
|
| | |
| | |
| | |
| |
|
| | int32_t cpu_get_num_physical_cores() { |
| | #ifdef __linux__ |
| | |
| | std::unordered_set<std::string> siblings; |
| | for (uint32_t cpu=0; cpu < UINT32_MAX; ++cpu) { |
| | std::ifstream thread_siblings("/sys/devices/system/cpu/cpu" |
| | + std::to_string(cpu) + "/topology/thread_siblings"); |
| | if (!thread_siblings.is_open()) { |
| | break; |
| | } |
| | std::string line; |
| | if (std::getline(thread_siblings, line)) { |
| | siblings.insert(line); |
| | } |
| | } |
| | if (!siblings.empty()) { |
| | return static_cast<int32_t>(siblings.size()); |
| | } |
| | #elif defined(__APPLE__) && defined(__MACH__) |
| | int32_t num_physical_cores; |
| | size_t len = sizeof(num_physical_cores); |
| | int result = sysctlbyname("hw.perflevel0.physicalcpu", &num_physical_cores, &len, NULL, 0); |
| | if (result == 0) { |
| | return num_physical_cores; |
| | } |
| | result = sysctlbyname("hw.physicalcpu", &num_physical_cores, &len, NULL, 0); |
| | if (result == 0) { |
| | return num_physical_cores; |
| | } |
| | #elif defined(_WIN32) && (_WIN32_WINNT >= 0x0601) && !defined(__MINGW64__) |
| | |
| | unsigned int n_threads_win = std::thread::hardware_concurrency(); |
| | unsigned int default_threads = n_threads_win > 0 ? (n_threads_win <= 4 ? n_threads_win : n_threads_win / 2) : 4; |
| |
|
| | DWORD buffer_size = 0; |
| | if (!GetLogicalProcessorInformationEx(RelationProcessorCore, nullptr, &buffer_size)) { |
| | if (GetLastError() != ERROR_INSUFFICIENT_BUFFER) { |
| | return default_threads; |
| | } |
| | } |
| |
|
| | std::vector<char> buffer(buffer_size); |
| | if (!GetLogicalProcessorInformationEx(RelationProcessorCore, reinterpret_cast<PSYSTEM_LOGICAL_PROCESSOR_INFORMATION_EX>(buffer.data()), &buffer_size)) { |
| | return default_threads; |
| | } |
| |
|
| | int32_t num_physical_cores = 0; |
| | PSYSTEM_LOGICAL_PROCESSOR_INFORMATION_EX info = reinterpret_cast<PSYSTEM_LOGICAL_PROCESSOR_INFORMATION_EX>(buffer.data()); |
| | while (buffer_size > 0) { |
| | if (info->Relationship == RelationProcessorCore) { |
| | num_physical_cores += info->Processor.GroupCount; |
| | } |
| | buffer_size -= info->Size; |
| | info = reinterpret_cast<PSYSTEM_LOGICAL_PROCESSOR_INFORMATION_EX>(reinterpret_cast<char*>(info) + info->Size); |
| | } |
| |
|
| | return num_physical_cores > 0 ? num_physical_cores : default_threads; |
| | #endif |
| | unsigned int n_threads = std::thread::hardware_concurrency(); |
| | return n_threads > 0 ? (n_threads <= 4 ? n_threads : n_threads / 2) : 4; |
| | } |
| |
|
| | #if defined(__x86_64__) && defined(__linux__) && !defined(__ANDROID__) |
| | #include <pthread.h> |
| |
|
| | static void cpuid(unsigned leaf, unsigned subleaf, |
| | unsigned *eax, unsigned *ebx, unsigned *ecx, unsigned *edx) { |
| | __asm__("movq\t%%rbx,%%rsi\n\t" |
| | "cpuid\n\t" |
| | "xchgq\t%%rbx,%%rsi" |
| | : "=a"(*eax), "=S"(*ebx), "=c"(*ecx), "=d"(*edx) |
| | : "0"(leaf), "2"(subleaf)); |
| | } |
| |
|
| | static int pin_cpu(int cpu) { |
| | cpu_set_t mask; |
| | CPU_ZERO(&mask); |
| | CPU_SET(cpu, &mask); |
| | return pthread_setaffinity_np(pthread_self(), sizeof(mask), &mask); |
| | } |
| |
|
| | static bool is_hybrid_cpu(void) { |
| | unsigned eax, ebx, ecx, edx; |
| | cpuid(7, 0, &eax, &ebx, &ecx, &edx); |
| | return !!(edx & (1u << 15)); |
| | } |
| |
|
| | static bool is_running_on_efficiency_core(void) { |
| | unsigned eax, ebx, ecx, edx; |
| | cpuid(0x1a, 0, &eax, &ebx, &ecx, &edx); |
| | int intel_atom = 0x20; |
| | int core_type = (eax & 0xff000000u) >> 24; |
| | return core_type == intel_atom; |
| | } |
| |
|
| | static int cpu_count_math_cpus(int n_cpu) { |
| | int result = 0; |
| | for (int cpu = 0; cpu < n_cpu; ++cpu) { |
| | if (pin_cpu(cpu)) { |
| | return -1; |
| | } |
| | if (is_running_on_efficiency_core()) { |
| | continue; |
| | } |
| | ++cpu; |
| | ++result; |
| | } |
| | return result; |
| | } |
| |
|
| | #endif |
| |
|
| | |
| | |
| | |
| | int32_t cpu_get_num_math() { |
| | #if defined(__x86_64__) && defined(__linux__) && !defined(__ANDROID__) |
| | int n_cpu = sysconf(_SC_NPROCESSORS_ONLN); |
| | if (n_cpu < 1) { |
| | return cpu_get_num_physical_cores(); |
| | } |
| | if (is_hybrid_cpu()) { |
| | cpu_set_t affinity; |
| | if (!pthread_getaffinity_np(pthread_self(), sizeof(affinity), &affinity)) { |
| | int result = cpu_count_math_cpus(n_cpu); |
| | pthread_setaffinity_np(pthread_self(), sizeof(affinity), &affinity); |
| | if (result > 0) { |
| | return result; |
| | } |
| | } |
| | } |
| | #endif |
| | return cpu_get_num_physical_cores(); |
| | } |
| |
|
| | |
| |
|
| | #if defined(_WIN32) |
| |
|
| | bool set_process_priority(enum ggml_sched_priority prio) { |
| | if (prio == GGML_SCHED_PRIO_NORMAL) { |
| | return true; |
| | } |
| |
|
| | DWORD p = NORMAL_PRIORITY_CLASS; |
| | switch (prio) { |
| | case GGML_SCHED_PRIO_NORMAL: p = NORMAL_PRIORITY_CLASS; break; |
| | case GGML_SCHED_PRIO_MEDIUM: p = ABOVE_NORMAL_PRIORITY_CLASS; break; |
| | case GGML_SCHED_PRIO_HIGH: p = HIGH_PRIORITY_CLASS; break; |
| | case GGML_SCHED_PRIO_REALTIME: p = REALTIME_PRIORITY_CLASS; break; |
| | } |
| |
|
| | if (!SetPriorityClass(GetCurrentProcess(), p)) { |
| | LOG_WRN("failed to set process priority class %d : (%d)\n", prio, (int) GetLastError()); |
| | return false; |
| | } |
| |
|
| | return true; |
| | } |
| |
|
| | #else |
| | #include <sys/types.h> |
| | #include <sys/resource.h> |
| |
|
| | bool set_process_priority(enum ggml_sched_priority prio) { |
| | if (prio == GGML_SCHED_PRIO_NORMAL) { |
| | return true; |
| | } |
| |
|
| | int p = 0; |
| | switch (prio) { |
| | case GGML_SCHED_PRIO_NORMAL: p = 0; break; |
| | case GGML_SCHED_PRIO_MEDIUM: p = -5; break; |
| | case GGML_SCHED_PRIO_HIGH: p = -10; break; |
| | case GGML_SCHED_PRIO_REALTIME: p = -20; break; |
| | } |
| |
|
| | if (!setpriority(PRIO_PROCESS, 0, p)) { |
| | LOG_WRN("failed to set process priority %d : %s (%d)\n", prio, strerror(errno), errno); |
| | return false; |
| | } |
| | return true; |
| | } |
| |
|
| | #endif |
| |
|
| | |
| | |
| | |
| |
|
| |
|
| | void postprocess_cpu_params(cpu_params& cpuparams, const cpu_params* role_model) { |
| | int32_t n_set = 0; |
| |
|
| | if (cpuparams.n_threads < 0) { |
| | |
| | if (role_model != nullptr) { |
| | cpuparams = *role_model; |
| | } else { |
| | cpuparams.n_threads = cpu_get_num_math(); |
| | } |
| | } |
| |
|
| | for (int32_t i = 0; i < GGML_MAX_N_THREADS; i++) { |
| | if (cpuparams.cpumask[i]) { |
| | n_set++; |
| | } |
| | } |
| |
|
| | if (n_set && n_set < cpuparams.n_threads) { |
| | |
| | LOG_WRN("Not enough set bits in CPU mask (%d) to satisfy requested thread count: %d\n", n_set, cpuparams.n_threads); |
| | } |
| | } |
| |
|
| | bool parse_cpu_range(const std::string & range, bool (&boolmask)[GGML_MAX_N_THREADS]) { |
| | size_t dash_loc = range.find('-'); |
| | if (dash_loc == std::string::npos) { |
| | LOG_ERR("Format of CPU range is invalid! Expected [<start>]-[<end>].\n"); |
| | return false; |
| | } |
| |
|
| | size_t start_i; |
| | size_t end_i; |
| |
|
| | if (dash_loc == 0) { |
| | start_i = 0; |
| | } else { |
| | start_i = std::stoull(range.substr(0, dash_loc)); |
| | if (start_i >= GGML_MAX_N_THREADS) { |
| | LOG_ERR("Start index out of bounds!\n"); |
| | return false; |
| | } |
| | } |
| |
|
| | if (dash_loc == range.length() - 1) { |
| | end_i = GGML_MAX_N_THREADS - 1; |
| | } else { |
| | end_i = std::stoull(range.substr(dash_loc + 1)); |
| | if (end_i >= GGML_MAX_N_THREADS) { |
| | LOG_ERR("End index out of bounds!\n"); |
| | return false; |
| | } |
| | } |
| |
|
| | for (size_t i = start_i; i <= end_i; i++) { |
| | boolmask[i] = true; |
| | } |
| |
|
| | return true; |
| | } |
| |
|
| | bool parse_cpu_mask(const std::string & mask, bool (&boolmask)[GGML_MAX_N_THREADS]) { |
| | |
| | size_t start_i = 0; |
| | if (mask.length() >= 2 && mask.substr(0, 2) == "0x") { |
| | start_i = 2; |
| | } |
| |
|
| | size_t num_digits = mask.length() - start_i; |
| | if (num_digits > 128) num_digits = 128; |
| |
|
| | size_t end_i = num_digits + start_i; |
| |
|
| | for (size_t i = start_i, n = (num_digits*4 - 1); i < end_i; i++, n-=4) { |
| | char c = mask.at(i); |
| | int8_t id = c; |
| |
|
| | if ((c >= '0' && c <= '9')) { |
| | id -= '0'; |
| | } else if (c >= 'a' && c <= 'f') { |
| | id -= 'a' - 10; |
| | } else if (c >= 'A' && c <= 'F') { |
| | id -= 'A' - 10; |
| | } else { |
| | LOG_ERR("Invalid hex character '%c' at position %d\n", c, int32_t(i)); |
| | return false; |
| | } |
| |
|
| | boolmask[ n ] = boolmask[ n ] || ((id & 8) != 0); |
| | boolmask[n - 1] = boolmask[n - 1] || ((id & 4) != 0); |
| | boolmask[n - 2] = boolmask[n - 2] || ((id & 2) != 0); |
| | boolmask[n - 3] = boolmask[n - 3] || ((id & 1) != 0); |
| | } |
| |
|
| | return true; |
| | } |
| |
|
| | void common_init() { |
| | llama_log_set([](ggml_log_level level, const char * text, void * ) { |
| | if (LOG_DEFAULT_LLAMA <= common_log_verbosity_thold) { |
| | common_log_add(common_log_main(), level, "%s", text); |
| | } |
| | }, NULL); |
| |
|
| | #ifdef NDEBUG |
| | const char * build_type = ""; |
| | #else |
| | const char * build_type = " (debug)"; |
| | #endif |
| |
|
| | LOG_INF("build: %d (%s) with %s for %s%s\n", LLAMA_BUILD_NUMBER, LLAMA_COMMIT, LLAMA_COMPILER, LLAMA_BUILD_TARGET, build_type); |
| | } |
| |
|
| | std::string common_params_get_system_info(const common_params & params) { |
| | std::ostringstream os; |
| |
|
| | os << "system_info: n_threads = " << params.cpuparams.n_threads; |
| | if (params.cpuparams_batch.n_threads != -1) { |
| | os << " (n_threads_batch = " << params.cpuparams_batch.n_threads << ")"; |
| | } |
| | #if defined(_WIN32) && (_WIN32_WINNT >= 0x0601) && !defined(__MINGW64__) |
| | |
| | DWORD logicalProcessorCount = GetActiveProcessorCount(ALL_PROCESSOR_GROUPS); |
| | os << " / " << logicalProcessorCount << " | " << llama_print_system_info(); |
| | #else |
| | os << " / " << std::thread::hardware_concurrency() << " | " << llama_print_system_info(); |
| | #endif |
| |
|
| | return os.str(); |
| | } |
| |
|
| | |
| | |
| | |
| |
|
| | std::string string_format(const char * fmt, ...) { |
| | va_list ap; |
| | va_list ap2; |
| | va_start(ap, fmt); |
| | va_copy(ap2, ap); |
| | int size = vsnprintf(NULL, 0, fmt, ap); |
| | GGML_ASSERT(size >= 0 && size < INT_MAX); |
| | std::vector<char> buf(size + 1); |
| | int size2 = vsnprintf(buf.data(), size + 1, fmt, ap2); |
| | GGML_ASSERT(size2 == size); |
| | va_end(ap2); |
| | va_end(ap); |
| | return std::string(buf.data(), size); |
| | } |
| |
|
| | std::string string_strip(const std::string & str) { |
| | size_t start = 0; |
| | size_t end = str.size(); |
| | while (start < end && std::isspace(str[start])) { |
| | start++; |
| | } |
| | while (end > start && std::isspace(str[end - 1])) { |
| | end--; |
| | } |
| | return str.substr(start, end - start); |
| | } |
| |
|
| | std::string string_get_sortable_timestamp() { |
| | using clock = std::chrono::system_clock; |
| |
|
| | const clock::time_point current_time = clock::now(); |
| | const time_t as_time_t = clock::to_time_t(current_time); |
| | char timestamp_no_ns[100]; |
| | std::strftime(timestamp_no_ns, 100, "%Y_%m_%d-%H_%M_%S", std::localtime(&as_time_t)); |
| |
|
| | const int64_t ns = std::chrono::duration_cast<std::chrono::nanoseconds>( |
| | current_time.time_since_epoch() % 1000000000).count(); |
| | char timestamp_ns[11]; |
| | snprintf(timestamp_ns, 11, "%09" PRId64, ns); |
| |
|
| | return std::string(timestamp_no_ns) + "." + std::string(timestamp_ns); |
| | } |
| |
|
| | void string_replace_all(std::string & s, const std::string & search, const std::string & replace) { |
| | if (search.empty()) { |
| | return; |
| | } |
| | std::string builder; |
| | builder.reserve(s.length()); |
| | size_t pos = 0; |
| | size_t last_pos = 0; |
| | while ((pos = s.find(search, last_pos)) != std::string::npos) { |
| | builder.append(s, last_pos, pos - last_pos); |
| | builder.append(replace); |
| | last_pos = pos + search.length(); |
| | } |
| | builder.append(s, last_pos, std::string::npos); |
| | s = std::move(builder); |
| | } |
| |
|
| | std::string regex_escape(const std::string & s) { |
| | static const std::regex special_chars("[.^$|()*+?\\[\\]{}\\\\]"); |
| | return std::regex_replace(s, special_chars, "\\$0"); |
| | } |
| |
|
| | std::string string_join(const std::vector<std::string> & values, const std::string & separator) { |
| | std::ostringstream result; |
| | for (size_t i = 0; i < values.size(); ++i) { |
| | if (i > 0) { |
| | result << separator; |
| | } |
| | result << values[i]; |
| | } |
| | return result.str(); |
| | } |
| |
|
| | std::vector<std::string> string_split(const std::string & str, const std::string & delimiter) { |
| | std::vector<std::string> parts; |
| | size_t start = 0; |
| | size_t end = str.find(delimiter); |
| |
|
| | while (end != std::string::npos) { |
| | parts.push_back(str.substr(start, end - start)); |
| | start = end + delimiter.length(); |
| | end = str.find(delimiter, start); |
| | } |
| |
|
| | parts.push_back(str.substr(start)); |
| |
|
| | return parts; |
| | } |
| |
|
| | std::string string_repeat(const std::string & str, size_t n) { |
| | if (n == 0) { |
| | return ""; |
| | } |
| |
|
| | std::string result; |
| | result.reserve(str.length() * n); |
| |
|
| | for (size_t i = 0; i < n; ++i) { |
| | result += str; |
| | } |
| |
|
| | return result; |
| | } |
| |
|
| | std::string string_from(bool value) { |
| | return value ? "true" : "false"; |
| | } |
| |
|
| | std::string string_from(const std::vector<int> & values) { |
| | std::stringstream buf; |
| |
|
| | buf << "[ "; |
| | bool first = true; |
| | for (auto e : values) { |
| | if (first) { |
| | first = false; |
| | } else { |
| | buf << ", "; |
| | } |
| | buf << std::to_string(e); |
| | } |
| | buf << " ]"; |
| |
|
| | return buf.str(); |
| | } |
| |
|
| | std::string string_from(const struct llama_context * ctx, const std::vector<llama_token> & tokens) { |
| | std::stringstream buf; |
| |
|
| | buf << "[ "; |
| |
|
| | bool first = true; |
| | for (const auto & token : tokens) { |
| | if (!first) { |
| | buf << ", "; |
| | } else { |
| | first = false; |
| | } |
| |
|
| | auto detokenized = common_token_to_piece(ctx, token); |
| |
|
| | detokenized.erase( |
| | std::remove_if( |
| | detokenized.begin(), |
| | detokenized.end(), |
| | [](const unsigned char c) { return !std::isprint(c); }), |
| | detokenized.end()); |
| |
|
| | buf << "'" << detokenized << "'" |
| | << ":" << std::to_string(token); |
| | } |
| |
|
| | buf << " ]"; |
| |
|
| | return buf.str(); |
| | } |
| |
|
| | std::string string_from(const struct llama_context * ctx, const struct llama_batch & batch) { |
| | std::stringstream buf; |
| |
|
| | buf << "[ "; |
| |
|
| | bool first = true; |
| | for (int i = 0; i < batch.n_tokens; ++i) { |
| | if (!first) { |
| | buf << ", "; |
| | } else { |
| | first = false; |
| | } |
| |
|
| | auto detokenized = common_token_to_piece(ctx, batch.token[i]); |
| |
|
| | detokenized.erase( |
| | std::remove_if( |
| | detokenized.begin(), |
| | detokenized.end(), |
| | [](const unsigned char c) { return !std::isprint(c); }), |
| | detokenized.end()); |
| |
|
| | buf << "\n" << std::to_string(i) |
| | << ", token '" << detokenized << "'" |
| | << ", pos " << std::to_string(batch.pos[i]) |
| | << ", n_seq_id " << std::to_string(batch.n_seq_id[i]) |
| | << ", seq_id " << std::to_string(batch.seq_id[i][0]) |
| | << ", logits " << std::to_string(batch.logits[i]); |
| | } |
| |
|
| | buf << " ]"; |
| |
|
| | return buf.str(); |
| | } |
| |
|
| | void string_process_escapes(std::string & input) { |
| | std::size_t input_len = input.length(); |
| | std::size_t output_idx = 0; |
| |
|
| | for (std::size_t input_idx = 0; input_idx < input_len; ++input_idx) { |
| | if (input[input_idx] == '\\' && input_idx + 1 < input_len) { |
| | switch (input[++input_idx]) { |
| | case 'n': input[output_idx++] = '\n'; break; |
| | case 'r': input[output_idx++] = '\r'; break; |
| | case 't': input[output_idx++] = '\t'; break; |
| | case '\'': input[output_idx++] = '\''; break; |
| | case '\"': input[output_idx++] = '\"'; break; |
| | case '\\': input[output_idx++] = '\\'; break; |
| | case 'x': |
| | |
| | if (input_idx + 2 < input_len) { |
| | const char x[3] = { input[input_idx + 1], input[input_idx + 2], 0 }; |
| | char *err_p = nullptr; |
| | const long val = std::strtol(x, &err_p, 16); |
| | if (err_p == x + 2) { |
| | input_idx += 2; |
| | input[output_idx++] = char(val); |
| | break; |
| | } |
| | } |
| | |
| | default: input[output_idx++] = '\\'; |
| | input[output_idx++] = input[input_idx]; break; |
| | } |
| | } else { |
| | input[output_idx++] = input[input_idx]; |
| | } |
| | } |
| |
|
| | input.resize(output_idx); |
| | } |
| |
|
| | bool string_parse_kv_override(const char * data, std::vector<llama_model_kv_override> & overrides) { |
| | const char * sep = strchr(data, '='); |
| | if (sep == nullptr || sep - data >= 128) { |
| | LOG_ERR("%s: malformed KV override '%s'\n", __func__, data); |
| | return false; |
| | } |
| | llama_model_kv_override kvo; |
| | std::strncpy(kvo.key, data, sep - data); |
| | kvo.key[sep - data] = 0; |
| | sep++; |
| | if (strncmp(sep, "int:", 4) == 0) { |
| | sep += 4; |
| | kvo.tag = LLAMA_KV_OVERRIDE_TYPE_INT; |
| | kvo.val_i64 = std::atol(sep); |
| | } else if (strncmp(sep, "float:", 6) == 0) { |
| | sep += 6; |
| | kvo.tag = LLAMA_KV_OVERRIDE_TYPE_FLOAT; |
| | kvo.val_f64 = std::atof(sep); |
| | } else if (strncmp(sep, "bool:", 5) == 0) { |
| | sep += 5; |
| | kvo.tag = LLAMA_KV_OVERRIDE_TYPE_BOOL; |
| | if (std::strcmp(sep, "true") == 0) { |
| | kvo.val_bool = true; |
| | } else if (std::strcmp(sep, "false") == 0) { |
| | kvo.val_bool = false; |
| | } else { |
| | LOG_ERR("%s: invalid boolean value for KV override '%s'\n", __func__, data); |
| | return false; |
| | } |
| | } else if (strncmp(sep, "str:", 4) == 0) { |
| | sep += 4; |
| | kvo.tag = LLAMA_KV_OVERRIDE_TYPE_STR; |
| | if (strlen(sep) > 127) { |
| | LOG_ERR("%s: malformed KV override '%s', value cannot exceed 127 chars\n", __func__, data); |
| | return false; |
| | } |
| | strncpy(kvo.val_str, sep, 127); |
| | kvo.val_str[127] = '\0'; |
| | } else { |
| | LOG_ERR("%s: invalid type for KV override '%s'\n", __func__, data); |
| | return false; |
| | } |
| | overrides.emplace_back(std::move(kvo)); |
| | return true; |
| | } |
| |
|
| | |
| | |
| | |
| |
|
| | |
| | |
| | bool fs_validate_filename(const std::string & filename) { |
| | if (!filename.length()) { |
| | |
| | return false; |
| | } |
| | if (filename.length() > 255) { |
| | |
| | |
| | |
| | return false; |
| | } |
| |
|
| | std::u32string filename_utf32; |
| | try { |
| | #if defined(__clang__) |
| | |
| | # pragma clang diagnostic push |
| | # pragma clang diagnostic ignored "-Wdeprecated-declarations" |
| | #endif |
| | std::wstring_convert<std::codecvt_utf8<char32_t>, char32_t> converter; |
| |
|
| | #if defined(__clang__) |
| | # pragma clang diagnostic pop |
| | #endif |
| |
|
| | filename_utf32 = converter.from_bytes(filename); |
| |
|
| | |
| | |
| | std::string filename_reencoded = converter.to_bytes(filename_utf32); |
| | if (filename_reencoded != filename) { |
| | return false; |
| | } |
| | } catch (const std::exception &) { |
| | return false; |
| | } |
| |
|
| | |
| | |
| | |
| | |
| | |
| | |
| | |
| | for (char32_t c : filename_utf32) { |
| | if (c <= 0x1F |
| | || c == 0x7F |
| | || (c >= 0x80 && c <= 0x9F) |
| | || c == 0xFF0E |
| | || c == 0x2215 |
| | || c == 0x2216 |
| | || (c >= 0xD800 && c <= 0xDFFF) |
| | || c == 0xFFFD |
| | || c == 0xFEFF |
| | || c == '/' || c == '\\' || c == ':' || c == '*' |
| | || c == '?' || c == '"' || c == '<' || c == '>' || c == '|') { |
| | return false; |
| | } |
| | } |
| |
|
| | |
| | |
| | if (filename.front() == ' ' || filename.back() == ' ' || filename.back() == '.') { |
| | return false; |
| | } |
| |
|
| | |
| | if (filename.find("..") != std::string::npos) { |
| | return false; |
| | } |
| |
|
| | |
| | if (filename == ".") { |
| | return false; |
| | } |
| |
|
| | return true; |
| | } |
| |
|
| | |
| | bool fs_create_directory_with_parents(const std::string & path) { |
| | #ifdef _WIN32 |
| | std::wstring_convert<std::codecvt_utf8<wchar_t>> converter; |
| | std::wstring wpath = converter.from_bytes(path); |
| |
|
| | |
| | const DWORD attributes = GetFileAttributesW(wpath.c_str()); |
| | if ((attributes != INVALID_FILE_ATTRIBUTES) && (attributes & FILE_ATTRIBUTE_DIRECTORY)) { |
| | return true; |
| | } |
| |
|
| | size_t pos_slash = 0; |
| |
|
| | |
| | while ((pos_slash = path.find('\\', pos_slash)) != std::string::npos) { |
| | const std::wstring subpath = wpath.substr(0, pos_slash); |
| | const wchar_t * test = subpath.c_str(); |
| |
|
| | const bool success = CreateDirectoryW(test, NULL); |
| | if (!success) { |
| | const DWORD error = GetLastError(); |
| |
|
| | |
| | if (error == ERROR_ALREADY_EXISTS) { |
| | const DWORD attributes = GetFileAttributesW(subpath.c_str()); |
| | if (attributes == INVALID_FILE_ATTRIBUTES || !(attributes & FILE_ATTRIBUTE_DIRECTORY)) { |
| | return false; |
| | } |
| | } else { |
| | return false; |
| | } |
| | } |
| |
|
| | pos_slash += 1; |
| | } |
| |
|
| | return true; |
| | #else |
| | |
| | struct stat info; |
| | if (stat(path.c_str(), &info) == 0) { |
| | return S_ISDIR(info.st_mode); |
| | } |
| |
|
| | size_t pos_slash = 1; |
| |
|
| | |
| | while ((pos_slash = path.find('/', pos_slash)) != std::string::npos) { |
| | const std::string subpath = path.substr(0, pos_slash); |
| | struct stat info; |
| |
|
| | |
| | if (stat(subpath.c_str(), &info) == 0) { |
| | if (!S_ISDIR(info.st_mode)) { |
| | return false; |
| | } |
| | } else { |
| | |
| | const int ret = mkdir(subpath.c_str(), 0755); |
| | if (ret != 0) { |
| | return false; |
| | } |
| | } |
| |
|
| | pos_slash += 1; |
| | } |
| |
|
| | return true; |
| | #endif |
| | } |
| |
|
| | std::string fs_get_cache_directory() { |
| | std::string cache_directory = ""; |
| | auto ensure_trailing_slash = [](std::string p) { |
| | |
| | if (p.back() != DIRECTORY_SEPARATOR) { |
| | p += DIRECTORY_SEPARATOR; |
| | } |
| | return p; |
| | }; |
| | if (getenv("LLAMA_CACHE")) { |
| | cache_directory = std::getenv("LLAMA_CACHE"); |
| | } else { |
| | #ifdef __linux__ |
| | if (std::getenv("XDG_CACHE_HOME")) { |
| | cache_directory = std::getenv("XDG_CACHE_HOME"); |
| | } else { |
| | cache_directory = std::getenv("HOME") + std::string("/.cache/"); |
| | } |
| | #elif defined(__APPLE__) |
| | cache_directory = std::getenv("HOME") + std::string("/Library/Caches/"); |
| | #elif defined(_WIN32) |
| | cache_directory = std::getenv("LOCALAPPDATA"); |
| | #endif |
| | cache_directory = ensure_trailing_slash(cache_directory); |
| | cache_directory += "llama.cpp"; |
| | } |
| | return ensure_trailing_slash(cache_directory); |
| | } |
| |
|
| | std::string fs_get_cache_file(const std::string & filename) { |
| | GGML_ASSERT(filename.find(DIRECTORY_SEPARATOR) == std::string::npos); |
| | std::string cache_directory = fs_get_cache_directory(); |
| | const bool success = fs_create_directory_with_parents(cache_directory); |
| | if (!success) { |
| | throw std::runtime_error("failed to create cache directory: " + cache_directory); |
| | } |
| | return cache_directory + filename; |
| | } |
| |
|
| |
|
| | |
| | |
| | |
| | struct common_init_result common_init_from_params(common_params & params) { |
| | common_init_result iparams; |
| | auto mparams = common_model_params_to_llama(params); |
| |
|
| | llama_model * model = nullptr; |
| |
|
| | if (!params.hf_repo.empty() && !params.hf_file.empty()) { |
| | model = common_load_model_from_hf(params.hf_repo, params.hf_file, params.model, params.hf_token, mparams); |
| | } else if (!params.model_url.empty()) { |
| | model = common_load_model_from_url(params.model_url, params.model, params.hf_token, mparams); |
| | } else { |
| | model = llama_model_load_from_file(params.model.c_str(), mparams); |
| | } |
| |
|
| | if (model == NULL) { |
| | LOG_ERR("%s: failed to load model '%s'\n", __func__, params.model.c_str()); |
| | return iparams; |
| | } |
| |
|
| | const llama_vocab * vocab = llama_model_get_vocab(model); |
| |
|
| | if (params.reranking) { |
| | bool ok = true; |
| |
|
| | if (llama_vocab_bos(vocab) == LLAMA_TOKEN_NULL) { |
| | LOG_WRN("%s: warning: vocab does not have a BOS token, reranking will not work\n", __func__); |
| | ok = false; |
| | } |
| |
|
| | if (llama_vocab_eos(vocab) == LLAMA_TOKEN_NULL) { |
| | LOG_WRN("%s: warning: vocab does not have an EOS token, reranking will not work\n", __func__); |
| | ok = false; |
| | } |
| |
|
| | if (llama_vocab_sep(vocab) == LLAMA_TOKEN_NULL) { |
| | LOG_WRN("%s: warning: vocab does not have a SEP token, reranking will not work\n", __func__); |
| | ok = false; |
| | } |
| |
|
| | if (!ok) { |
| | llama_model_free(model); |
| |
|
| | return iparams; |
| | } |
| | } |
| |
|
| | auto cparams = common_context_params_to_llama(params); |
| |
|
| | llama_context * lctx = llama_init_from_model(model, cparams); |
| | if (lctx == NULL) { |
| | LOG_ERR("%s: failed to create context with model '%s'\n", __func__, params.model.c_str()); |
| | llama_model_free(model); |
| | return iparams; |
| | } |
| |
|
| | if (params.ctx_shift && !llama_kv_cache_can_shift(lctx)) { |
| | LOG_WRN("%s: KV cache shifting is not supported for this model, disabling KV cache shifting\n", __func__); |
| | params.ctx_shift = false; |
| | } |
| |
|
| | if (!params.control_vectors.empty()) { |
| | if (params.control_vector_layer_start <= 0) params.control_vector_layer_start = 1; |
| | if (params.control_vector_layer_end <= 0) params.control_vector_layer_end = llama_model_n_layer(model); |
| |
|
| | const auto cvec = common_control_vector_load(params.control_vectors); |
| | if (cvec.n_embd == -1) { |
| | llama_free(lctx); |
| | llama_model_free(model); |
| |
|
| | return iparams; |
| | } |
| |
|
| | int err = llama_apply_adapter_cvec( |
| | lctx, |
| | cvec.data.data(), |
| | cvec.data.size(), |
| | cvec.n_embd, |
| | params.control_vector_layer_start, |
| | params.control_vector_layer_end); |
| | if (err) { |
| | llama_free(lctx); |
| | llama_model_free(model); |
| |
|
| | return iparams; |
| | } |
| | } |
| |
|
| | |
| | for (auto & la : params.lora_adapters) { |
| | llama_adapter_lora_ptr lora; |
| | lora.reset(llama_adapter_lora_init(model, la.path.c_str())); |
| | if (lora == nullptr) { |
| | LOG_ERR("%s: failed to apply lora adapter '%s'\n", __func__, la.path.c_str()); |
| | llama_free(lctx); |
| | llama_model_free(model); |
| | return iparams; |
| | } |
| |
|
| | la.ptr = lora.get(); |
| | iparams.lora.emplace_back(std::move(lora)); |
| | } |
| |
|
| | if (!params.lora_init_without_apply) { |
| | common_set_adapter_lora(lctx, params.lora_adapters); |
| | } |
| |
|
| | if (params.sampling.ignore_eos && llama_vocab_eos(vocab) == LLAMA_TOKEN_NULL) { |
| | LOG_WRN("%s: warning: vocab does not have an EOS token, ignoring --ignore-eos\n", __func__); |
| | params.sampling.ignore_eos = false; |
| | } |
| |
|
| | if (params.sampling.ignore_eos) { |
| | for (llama_token i = 0; i < llama_vocab_n_tokens(vocab); i++) { |
| | if (llama_vocab_is_eog(vocab, i)) { |
| | LOG_INF("%s: added %s logit bias = %f\n", __func__, common_token_to_piece(lctx, i).c_str(), -INFINITY); |
| | params.sampling.logit_bias.push_back({i, -INFINITY}); |
| | } |
| | } |
| | } |
| |
|
| | if (params.sampling.penalty_last_n == -1) { |
| | LOG_INF("%s: setting penalty_last_n to ctx_size = %d\n", __func__, llama_n_ctx(lctx)); |
| | params.sampling.penalty_last_n = llama_n_ctx(lctx); |
| | } |
| |
|
| | if (params.sampling.dry_penalty_last_n == -1) { |
| | LOG_INF("%s: setting dry_penalty_last_n to ctx_size = %d\n", __func__, llama_n_ctx(lctx)); |
| | params.sampling.dry_penalty_last_n = llama_n_ctx(lctx); |
| | } |
| |
|
| | if (params.warmup) { |
| | LOG_WRN("%s: warming up the model with an empty run - please wait ... (--no-warmup to disable)\n", __func__); |
| |
|
| | std::vector<llama_token> tmp; |
| | llama_token bos = llama_vocab_bos(vocab); |
| | llama_token eos = llama_vocab_eos(vocab); |
| |
|
| | |
| | if (bos != LLAMA_TOKEN_NULL) { |
| | tmp.push_back(bos); |
| | } |
| | if (eos != LLAMA_TOKEN_NULL) { |
| | tmp.push_back(eos); |
| | } |
| | if (tmp.empty()) { |
| | tmp.push_back(0); |
| | } |
| |
|
| | if (llama_model_has_encoder(model)) { |
| | llama_encode(lctx, llama_batch_get_one(tmp.data(), tmp.size())); |
| | llama_token decoder_start_token_id = llama_model_decoder_start_token(model); |
| | if (decoder_start_token_id == LLAMA_TOKEN_NULL) { |
| | decoder_start_token_id = bos; |
| | } |
| | tmp.clear(); |
| | tmp.push_back(decoder_start_token_id); |
| | } |
| | if (llama_model_has_decoder(model)) { |
| | llama_decode(lctx, llama_batch_get_one(tmp.data(), std::min(tmp.size(), (size_t) params.n_batch))); |
| | } |
| | llama_kv_cache_clear(lctx); |
| | llama_synchronize(lctx); |
| | llama_perf_context_reset(lctx); |
| | } |
| |
|
| | iparams.model.reset(model); |
| | iparams.context.reset(lctx); |
| |
|
| | return iparams; |
| | } |
| |
|
| | void common_set_adapter_lora(struct llama_context * ctx, std::vector<common_adapter_lora_info> & lora) { |
| | llama_clear_adapter_lora(ctx); |
| | for (auto & la : lora) { |
| | if (la.scale != 0.0f) { |
| | llama_set_adapter_lora(ctx, la.ptr, la.scale); |
| | } |
| | } |
| | } |
| |
|
| | struct llama_model_params common_model_params_to_llama(common_params & params) { |
| | auto mparams = llama_model_default_params(); |
| |
|
| | if (!params.devices.empty()) { |
| | mparams.devices = params.devices.data(); |
| | } |
| | if (params.n_gpu_layers != -1) { |
| | mparams.n_gpu_layers = params.n_gpu_layers; |
| | } |
| | mparams.main_gpu = params.main_gpu; |
| | mparams.split_mode = params.split_mode; |
| | mparams.tensor_split = params.tensor_split; |
| | mparams.use_mmap = params.use_mmap; |
| | mparams.use_mlock = params.use_mlock; |
| | mparams.check_tensors = params.check_tensors; |
| | if (params.kv_overrides.empty()) { |
| | mparams.kv_overrides = NULL; |
| | } else { |
| | GGML_ASSERT(params.kv_overrides.back().key[0] == 0 && "KV overrides not terminated with empty key"); |
| | mparams.kv_overrides = params.kv_overrides.data(); |
| | } |
| |
|
| | return mparams; |
| | } |
| |
|
| | struct llama_context_params common_context_params_to_llama(const common_params & params) { |
| | auto cparams = llama_context_default_params(); |
| |
|
| | cparams.n_ctx = params.n_ctx; |
| | cparams.n_seq_max = params.n_parallel; |
| | cparams.n_batch = params.n_batch; |
| | cparams.n_ubatch = params.n_ubatch; |
| | cparams.n_threads = params.cpuparams.n_threads; |
| | cparams.n_threads_batch = params.cpuparams_batch.n_threads == -1 ? |
| | params.cpuparams.n_threads : params.cpuparams_batch.n_threads; |
| | cparams.logits_all = params.logits_all; |
| | cparams.embeddings = params.embedding; |
| | cparams.rope_scaling_type = params.rope_scaling_type; |
| | cparams.rope_freq_base = params.rope_freq_base; |
| | cparams.rope_freq_scale = params.rope_freq_scale; |
| | cparams.yarn_ext_factor = params.yarn_ext_factor; |
| | cparams.yarn_attn_factor = params.yarn_attn_factor; |
| | cparams.yarn_beta_fast = params.yarn_beta_fast; |
| | cparams.yarn_beta_slow = params.yarn_beta_slow; |
| | cparams.yarn_orig_ctx = params.yarn_orig_ctx; |
| | cparams.pooling_type = params.pooling_type; |
| | cparams.attention_type = params.attention_type; |
| | cparams.defrag_thold = params.defrag_thold; |
| | cparams.cb_eval = params.cb_eval; |
| | cparams.cb_eval_user_data = params.cb_eval_user_data; |
| | cparams.offload_kqv = !params.no_kv_offload; |
| | cparams.flash_attn = params.flash_attn; |
| | cparams.no_perf = params.no_perf; |
| |
|
| | if (params.reranking) { |
| | cparams.embeddings = true; |
| | cparams.pooling_type = LLAMA_POOLING_TYPE_RANK; |
| | } |
| |
|
| | cparams.type_k = params.cache_type_k; |
| | cparams.type_v = params.cache_type_v; |
| |
|
| | return cparams; |
| | } |
| |
|
| | struct ggml_threadpool_params ggml_threadpool_params_from_cpu_params(const cpu_params & params) { |
| | struct ggml_threadpool_params tpp; |
| |
|
| | ggml_threadpool_params_init(&tpp, params.n_threads); |
| |
|
| | if (params.mask_valid) { |
| | std::memcpy(&tpp.cpumask, ¶ms.cpumask, GGML_MAX_N_THREADS); |
| | } |
| |
|
| | tpp.prio = params.priority; |
| | tpp.poll = params.poll; |
| | tpp.strict_cpu = params.strict_cpu; |
| |
|
| | return tpp; |
| | } |
| |
|
| | #ifdef LLAMA_USE_CURL |
| |
|
| | #define CURL_MAX_RETRY 3 |
| | #define CURL_RETRY_DELAY_SECONDS 2 |
| |
|
| | static bool curl_perform_with_retry(const std::string & url, CURL * curl, int max_attempts, int retry_delay_seconds) { |
| | int remaining_attempts = max_attempts; |
| |
|
| | while (remaining_attempts > 0) { |
| | LOG_INF("%s: Trying to download from %s (attempt %d of %d)...\n", __func__ , url.c_str(), max_attempts - remaining_attempts + 1, max_attempts); |
| |
|
| | CURLcode res = curl_easy_perform(curl); |
| | if (res == CURLE_OK) { |
| | return true; |
| | } |
| |
|
| | int exponential_backoff_delay = std::pow(retry_delay_seconds, max_attempts - remaining_attempts) * 1000; |
| | LOG_WRN("%s: curl_easy_perform() failed: %s, retrying after %d milliseconds...\n", __func__, curl_easy_strerror(res), exponential_backoff_delay); |
| |
|
| | remaining_attempts--; |
| | std::this_thread::sleep_for(std::chrono::milliseconds(exponential_backoff_delay)); |
| | } |
| |
|
| | LOG_ERR("%s: curl_easy_perform() failed after %d attempts\n", __func__, max_attempts); |
| |
|
| | return false; |
| | } |
| |
|
| | static bool common_download_file(const std::string & url, const std::string & path, const std::string & hf_token) { |
| | |
| | curl_ptr curl(curl_easy_init(), &curl_easy_cleanup); |
| | curl_slist_ptr http_headers; |
| | if (!curl) { |
| | LOG_ERR("%s: error initializing libcurl\n", __func__); |
| | return false; |
| | } |
| |
|
| | bool force_download = false; |
| |
|
| | |
| | curl_easy_setopt(curl.get(), CURLOPT_URL, url.c_str()); |
| | curl_easy_setopt(curl.get(), CURLOPT_FOLLOWLOCATION, 1L); |
| |
|
| | |
| | if (!hf_token.empty()) { |
| | std::string auth_header = "Authorization: Bearer " + hf_token; |
| | http_headers.ptr = curl_slist_append(http_headers.ptr, auth_header.c_str()); |
| | curl_easy_setopt(curl.get(), CURLOPT_HTTPHEADER, http_headers.ptr); |
| | } |
| |
|
| | #if defined(_WIN32) |
| | |
| | |
| | curl_easy_setopt(curl.get(), CURLOPT_SSL_OPTIONS, CURLSSLOPT_NATIVE_CA); |
| | #endif |
| |
|
| | |
| | auto file_exists = std::filesystem::exists(path); |
| |
|
| | |
| | std::string metadata_path = path + ".json"; |
| | nlohmann::json metadata; |
| | std::string etag; |
| | std::string last_modified; |
| |
|
| | if (file_exists) { |
| | |
| | std::ifstream metadata_in(metadata_path); |
| | if (metadata_in.good()) { |
| | try { |
| | metadata_in >> metadata; |
| | LOG_INF("%s: previous metadata file found %s: %s\n", __func__, metadata_path.c_str(), metadata.dump().c_str()); |
| | if (metadata.contains("url") && metadata.at("url").is_string()) { |
| | auto previous_url = metadata.at("url").get<std::string>(); |
| | if (previous_url != url) { |
| | LOG_ERR("%s: Model URL mismatch: %s != %s\n", __func__, url.c_str(), previous_url.c_str()); |
| | return false; |
| | } |
| | } |
| | if (metadata.contains("etag") && metadata.at("etag").is_string()) { |
| | etag = metadata.at("etag"); |
| | } |
| | if (metadata.contains("lastModified") && metadata.at("lastModified").is_string()) { |
| | last_modified = metadata.at("lastModified"); |
| | } |
| | } catch (const nlohmann::json::exception & e) { |
| | LOG_ERR("%s: error reading metadata file %s: %s\n", __func__, metadata_path.c_str(), e.what()); |
| | return false; |
| | } |
| | } |
| | } else { |
| | LOG_INF("%s: no previous model file found %s\n", __func__, path.c_str()); |
| | } |
| |
|
| | |
| | struct common_load_model_from_url_headers { |
| | std::string etag; |
| | std::string last_modified; |
| | }; |
| |
|
| | common_load_model_from_url_headers headers; |
| |
|
| | { |
| | typedef size_t(*CURLOPT_HEADERFUNCTION_PTR)(char *, size_t, size_t, void *); |
| | auto header_callback = [](char * buffer, size_t , size_t n_items, void * userdata) -> size_t { |
| | common_load_model_from_url_headers * headers = (common_load_model_from_url_headers *) userdata; |
| |
|
| | static std::regex header_regex("([^:]+): (.*)\r\n"); |
| | static std::regex etag_regex("ETag", std::regex_constants::icase); |
| | static std::regex last_modified_regex("Last-Modified", std::regex_constants::icase); |
| |
|
| | std::string header(buffer, n_items); |
| | std::smatch match; |
| | if (std::regex_match(header, match, header_regex)) { |
| | const std::string & key = match[1]; |
| | const std::string & value = match[2]; |
| | if (std::regex_match(key, match, etag_regex)) { |
| | headers->etag = value; |
| | } else if (std::regex_match(key, match, last_modified_regex)) { |
| | headers->last_modified = value; |
| | } |
| | } |
| | return n_items; |
| | }; |
| |
|
| | curl_easy_setopt(curl.get(), CURLOPT_NOBODY, 1L); |
| | curl_easy_setopt(curl.get(), CURLOPT_NOPROGRESS, 1L); |
| | curl_easy_setopt(curl.get(), CURLOPT_HEADERFUNCTION, static_cast<CURLOPT_HEADERFUNCTION_PTR>(header_callback)); |
| | curl_easy_setopt(curl.get(), CURLOPT_HEADERDATA, &headers); |
| |
|
| | bool was_perform_successful = curl_perform_with_retry(url, curl.get(), CURL_MAX_RETRY, CURL_RETRY_DELAY_SECONDS); |
| | if (!was_perform_successful) { |
| | return false; |
| | } |
| |
|
| | long http_code = 0; |
| | curl_easy_getinfo(curl.get(), CURLINFO_RESPONSE_CODE, &http_code); |
| | if (http_code != 200) { |
| | |
| | |
| | force_download = true; |
| | LOG_ERR("%s: HEAD invalid http status code received: %ld\n", __func__, http_code); |
| | } |
| | } |
| |
|
| | bool should_download = !file_exists || force_download; |
| | if (!should_download) { |
| | if (!etag.empty() && etag != headers.etag) { |
| | LOG_WRN("%s: ETag header is different (%s != %s): triggering a new download\n", __func__, etag.c_str(), headers.etag.c_str()); |
| | should_download = true; |
| | } else if (!last_modified.empty() && last_modified != headers.last_modified) { |
| | LOG_WRN("%s: Last-Modified header is different (%s != %s): triggering a new download\n", __func__, last_modified.c_str(), headers.last_modified.c_str()); |
| | should_download = true; |
| | } |
| | } |
| | if (should_download) { |
| | std::string path_temporary = path + ".downloadInProgress"; |
| | if (file_exists) { |
| | LOG_WRN("%s: deleting previous downloaded file: %s\n", __func__, path.c_str()); |
| | if (remove(path.c_str()) != 0) { |
| | LOG_ERR("%s: unable to delete file: %s\n", __func__, path.c_str()); |
| | return false; |
| | } |
| | } |
| |
|
| | |
| |
|
| | struct FILE_deleter { |
| | void operator()(FILE * f) const { |
| | fclose(f); |
| | } |
| | }; |
| |
|
| | std::unique_ptr<FILE, FILE_deleter> outfile(fopen(path_temporary.c_str(), "wb")); |
| | if (!outfile) { |
| | LOG_ERR("%s: error opening local file for writing: %s\n", __func__, path.c_str()); |
| | return false; |
| | } |
| |
|
| | typedef size_t(*CURLOPT_WRITEFUNCTION_PTR)(void * data, size_t size, size_t nmemb, void * fd); |
| | auto write_callback = [](void * data, size_t size, size_t nmemb, void * fd) -> size_t { |
| | return fwrite(data, size, nmemb, (FILE *)fd); |
| | }; |
| | curl_easy_setopt(curl.get(), CURLOPT_NOBODY, 0L); |
| | curl_easy_setopt(curl.get(), CURLOPT_WRITEFUNCTION, static_cast<CURLOPT_WRITEFUNCTION_PTR>(write_callback)); |
| | curl_easy_setopt(curl.get(), CURLOPT_WRITEDATA, outfile.get()); |
| |
|
| | |
| | curl_easy_setopt(curl.get(), CURLOPT_NOPROGRESS, 0L); |
| |
|
| | |
| | auto llama_download_hide_password_in_url = [](const std::string & url) -> std::string { |
| | std::size_t protocol_pos = url.find("://"); |
| | if (protocol_pos == std::string::npos) { |
| | return url; |
| | } |
| |
|
| | std::size_t at_pos = url.find('@', protocol_pos + 3); |
| | if (at_pos == std::string::npos) { |
| | return url; |
| | } |
| |
|
| | return url.substr(0, protocol_pos + 3) + "********" + url.substr(at_pos); |
| | }; |
| |
|
| | |
| | LOG_INF("%s: trying to download model from %s to %s (server_etag:%s, server_last_modified:%s)...\n", __func__, |
| | llama_download_hide_password_in_url(url).c_str(), path.c_str(), headers.etag.c_str(), headers.last_modified.c_str()); |
| | bool was_perform_successful = curl_perform_with_retry(url, curl.get(), CURL_MAX_RETRY, CURL_RETRY_DELAY_SECONDS); |
| | if (!was_perform_successful) { |
| | return false; |
| | } |
| |
|
| | long http_code = 0; |
| | curl_easy_getinfo (curl.get(), CURLINFO_RESPONSE_CODE, &http_code); |
| | if (http_code < 200 || http_code >= 400) { |
| | LOG_ERR("%s: invalid http status code received: %ld\n", __func__, http_code); |
| | return false; |
| | } |
| |
|
| | |
| | outfile.reset(); |
| |
|
| | |
| | metadata.update({ |
| | {"url", url}, |
| | {"etag", headers.etag}, |
| | {"lastModified", headers.last_modified} |
| | }); |
| | std::ofstream(metadata_path) << metadata.dump(4); |
| | LOG_INF("%s: file metadata saved: %s\n", __func__, metadata_path.c_str()); |
| |
|
| | if (rename(path_temporary.c_str(), path.c_str()) != 0) { |
| | LOG_ERR("%s: unable to rename file: %s to %s\n", __func__, path_temporary.c_str(), path.c_str()); |
| | return false; |
| | } |
| | } |
| |
|
| | return true; |
| | } |
| |
|
| | struct llama_model * common_load_model_from_url( |
| | const std::string & model_url, |
| | const std::string & local_path, |
| | const std::string & hf_token, |
| | const struct llama_model_params & params) { |
| | |
| | if (model_url.empty()) { |
| | LOG_ERR("%s: invalid model_url\n", __func__); |
| | return NULL; |
| | } |
| |
|
| | if (!common_download_file(model_url, local_path, hf_token)) { |
| | return NULL; |
| | } |
| |
|
| | |
| | int n_split = 0; |
| | { |
| | struct gguf_init_params gguf_params = { |
| | true, |
| | NULL, |
| | }; |
| | auto * ctx_gguf = gguf_init_from_file(local_path.c_str(), gguf_params); |
| | if (!ctx_gguf) { |
| | LOG_ERR("\n%s: failed to load input GGUF from %s\n", __func__, local_path.c_str()); |
| | return NULL; |
| | } |
| |
|
| | auto key_n_split = gguf_find_key(ctx_gguf, LLM_KV_SPLIT_COUNT); |
| | if (key_n_split >= 0) { |
| | n_split = gguf_get_val_u16(ctx_gguf, key_n_split); |
| | } |
| |
|
| | gguf_free(ctx_gguf); |
| | } |
| |
|
| | if (n_split > 1) { |
| | char split_prefix[PATH_MAX] = {0}; |
| | char split_url_prefix[LLAMA_CURL_MAX_URL_LENGTH] = {0}; |
| |
|
| | |
| | |
| | { |
| | if (!llama_split_prefix(split_prefix, sizeof(split_prefix), local_path.c_str(), 0, n_split)) { |
| | LOG_ERR("\n%s: unexpected model file name: %s n_split=%d\n", __func__, local_path.c_str(), n_split); |
| | return NULL; |
| | } |
| |
|
| | if (!llama_split_prefix(split_url_prefix, sizeof(split_url_prefix), model_url.c_str(), 0, n_split)) { |
| | LOG_ERR("\n%s: unexpected model url: %s n_split=%d\n", __func__, model_url.c_str(), n_split); |
| | return NULL; |
| | } |
| | } |
| |
|
| | |
| | std::vector<std::future<bool>> futures_download; |
| | for (int idx = 1; idx < n_split; idx++) { |
| | futures_download.push_back(std::async(std::launch::async, [&split_prefix, &split_url_prefix, &n_split, hf_token](int download_idx) -> bool { |
| | char split_path[PATH_MAX] = {0}; |
| | llama_split_path(split_path, sizeof(split_path), split_prefix, download_idx, n_split); |
| |
|
| | char split_url[LLAMA_CURL_MAX_URL_LENGTH] = {0}; |
| | llama_split_path(split_url, sizeof(split_url), split_url_prefix, download_idx, n_split); |
| |
|
| | return common_download_file(split_url, split_path, hf_token); |
| | }, idx)); |
| | } |
| |
|
| | |
| | for (auto & f : futures_download) { |
| | if (!f.get()) { |
| | return NULL; |
| | } |
| | } |
| | } |
| |
|
| | return llama_model_load_from_file(local_path.c_str(), params); |
| | } |
| |
|
| | struct llama_model * common_load_model_from_hf( |
| | const std::string & repo, |
| | const std::string & remote_path, |
| | const std::string & local_path, |
| | const std::string & hf_token, |
| | const struct llama_model_params & params) { |
| | |
| | |
| | |
| | |
| | |
| | |
| | |
| | |
| |
|
| | std::string model_url = "https://huggingface.co/"; |
| | model_url += repo; |
| | model_url += "/resolve/main/"; |
| | model_url += remote_path; |
| |
|
| | return common_load_model_from_url(model_url, local_path, hf_token, params); |
| | } |
| |
|
| | |
| | |
| | |
| | |
| | |
| | |
| | |
| | |
| | |
| | |
| | |
| | std::pair<std::string, std::string> common_get_hf_file(const std::string & hf_repo_with_tag, const std::string & hf_token) { |
| | auto parts = string_split<std::string>(hf_repo_with_tag, ':'); |
| | std::string tag = parts.size() > 1 ? parts.back() : "latest"; |
| | std::string hf_repo = parts[0]; |
| | if (string_split<std::string>(hf_repo, '/').size() != 2) { |
| | throw std::invalid_argument("error: invalid HF repo format, expected <user>/<model>[:quant]\n"); |
| | } |
| |
|
| | |
| | json model_info; |
| | curl_ptr curl(curl_easy_init(), &curl_easy_cleanup); |
| | curl_slist_ptr http_headers; |
| | std::string res_str; |
| | std::string url = "https://huggingface.co/v2/" + hf_repo + "/manifests/" + tag; |
| | curl_easy_setopt(curl.get(), CURLOPT_URL, url.c_str()); |
| | curl_easy_setopt(curl.get(), CURLOPT_NOPROGRESS, 1L); |
| | typedef size_t(*CURLOPT_WRITEFUNCTION_PTR)(void * ptr, size_t size, size_t nmemb, void * data); |
| | auto write_callback = [](void * ptr, size_t size, size_t nmemb, void * data) -> size_t { |
| | static_cast<std::string *>(data)->append((char * ) ptr, size * nmemb); |
| | return size * nmemb; |
| | }; |
| | curl_easy_setopt(curl.get(), CURLOPT_WRITEFUNCTION, static_cast<CURLOPT_WRITEFUNCTION_PTR>(write_callback)); |
| | curl_easy_setopt(curl.get(), CURLOPT_WRITEDATA, &res_str); |
| | #if defined(_WIN32) |
| | curl_easy_setopt(curl.get(), CURLOPT_SSL_OPTIONS, CURLSSLOPT_NATIVE_CA); |
| | #endif |
| | if (!hf_token.empty()) { |
| | std::string auth_header = "Authorization: Bearer " + hf_token; |
| | http_headers.ptr = curl_slist_append(http_headers.ptr, auth_header.c_str()); |
| | } |
| | |
| | http_headers.ptr = curl_slist_append(http_headers.ptr, "User-Agent: llama-cpp"); |
| | http_headers.ptr = curl_slist_append(http_headers.ptr, "Accept: application/json"); |
| | curl_easy_setopt(curl.get(), CURLOPT_HTTPHEADER, http_headers.ptr); |
| |
|
| | CURLcode res = curl_easy_perform(curl.get()); |
| |
|
| | if (res != CURLE_OK) { |
| | throw std::runtime_error("error: cannot make GET request to HF API"); |
| | } |
| |
|
| | long res_code; |
| | curl_easy_getinfo(curl.get(), CURLINFO_RESPONSE_CODE, &res_code); |
| | if (res_code == 200) { |
| | model_info = json::parse(res_str); |
| | } else if (res_code == 401) { |
| | throw std::runtime_error("error: model is private or does not exist; if you are accessing a gated model, please provide a valid HF token"); |
| | } else { |
| | throw std::runtime_error(string_format("error from HF API, response code: %ld, data: %s", res_code, res_str.c_str())); |
| | } |
| |
|
| | |
| | if (!model_info.contains("ggufFile")) { |
| | throw std::runtime_error("error: model does not have ggufFile"); |
| | } |
| | json & gguf_file = model_info.at("ggufFile"); |
| | if (!gguf_file.contains("rfilename")) { |
| | throw std::runtime_error("error: ggufFile does not have rfilename"); |
| | } |
| |
|
| | return std::make_pair(hf_repo, gguf_file.at("rfilename")); |
| | } |
| |
|
| | #else |
| |
|
| | struct llama_model * common_load_model_from_url( |
| | const std::string & , |
| | const std::string & , |
| | const std::string & , |
| | const struct llama_model_params & ) { |
| | LOG_WRN("%s: llama.cpp built without libcurl, downloading from an url not supported.\n", __func__); |
| | return nullptr; |
| | } |
| |
|
| | struct llama_model * common_load_model_from_hf( |
| | const std::string & , |
| | const std::string & , |
| | const std::string & , |
| | const std::string & , |
| | const struct llama_model_params & ) { |
| | LOG_WRN("%s: llama.cpp built without libcurl, downloading from Hugging Face not supported.\n", __func__); |
| | return nullptr; |
| | } |
| |
|
| | std::pair<std::string, std::string> common_get_hf_file(const std::string &, const std::string &) { |
| | LOG_WRN("%s: llama.cpp built without libcurl, downloading from Hugging Face not supported.\n", __func__); |
| | return std::make_pair("", ""); |
| | } |
| |
|
| | #endif |
| |
|
| | |
| | |
| | |
| |
|
| | void common_batch_clear(struct llama_batch & batch) { |
| | batch.n_tokens = 0; |
| | } |
| |
|
| | void common_batch_add( |
| | struct llama_batch & batch, |
| | llama_token id, |
| | llama_pos pos, |
| | const std::vector<llama_seq_id> & seq_ids, |
| | bool logits) { |
| | GGML_ASSERT(batch.seq_id[batch.n_tokens] && "llama_batch size exceeded"); |
| |
|
| | batch.token [batch.n_tokens] = id; |
| | batch.pos [batch.n_tokens] = pos; |
| | batch.n_seq_id[batch.n_tokens] = seq_ids.size(); |
| | for (size_t i = 0; i < seq_ids.size(); ++i) { |
| | batch.seq_id[batch.n_tokens][i] = seq_ids[i]; |
| | } |
| | batch.logits [batch.n_tokens] = logits; |
| |
|
| | batch.n_tokens++; |
| | } |
| |
|
| | |
| | |
| | |
| |
|
| | size_t common_lcp(const llama_tokens & a, const llama_tokens & b) { |
| | size_t i; |
| | for (i = 0; i < a.size() && i < b.size() && a[i] == b[i]; i++) {} |
| |
|
| | return i; |
| | } |
| |
|
| | size_t common_lcs(const llama_tokens & a, const llama_tokens & b) { |
| | |
| | if (a.empty() || b.empty()) { |
| | return 0; |
| | } |
| |
|
| | |
| | size_t a_len = a.size(); |
| | size_t b_len = b.size(); |
| |
|
| | |
| | size_t max_length = 0; |
| |
|
| | |
| | std::vector<size_t> prev_row(b_len + 1, 0); |
| | std::vector<size_t> curr_row(b_len + 1, 0); |
| |
|
| | |
| | for (size_t i = 1; i <= a_len; i++) { |
| | |
| | for (size_t j = 1; j <= b_len; j++) { |
| | |
| | if (a[i - 1] == b[j - 1]) { |
| | |
| | if (i == 1 || j == 1) { |
| | curr_row[j] = 1; |
| | } else { |
| | |
| | curr_row[j] = prev_row[j - 1] + 1; |
| | } |
| |
|
| | |
| | if (curr_row[j] > max_length) { |
| | max_length = curr_row[j]; |
| | } |
| | } else { |
| | |
| | curr_row[j] = 0; |
| | } |
| | } |
| |
|
| | |
| | prev_row = curr_row; |
| | } |
| |
|
| | |
| | return max_length; |
| | } |
| |
|
| | |
| | |
| | |
| |
|
| | std::vector<llama_token> common_tokenize( |
| | const struct llama_context * ctx, |
| | const std::string & text, |
| | bool add_special, |
| | bool parse_special) { |
| | const llama_model * model = llama_get_model(ctx); |
| | const llama_vocab * vocab = llama_model_get_vocab(model); |
| | return common_tokenize(vocab, text, add_special, parse_special); |
| | } |
| |
|
| | std::vector<llama_token> common_tokenize( |
| | const struct llama_vocab * vocab, |
| | const std::string & text, |
| | bool add_special, |
| | bool parse_special) { |
| | |
| | int n_tokens = text.length() + 2 * add_special; |
| | std::vector<llama_token> result(n_tokens); |
| | n_tokens = llama_tokenize(vocab, text.data(), text.length(), result.data(), result.size(), add_special, parse_special); |
| | if (n_tokens < 0) { |
| | result.resize(-n_tokens); |
| | int check = llama_tokenize(vocab, text.data(), text.length(), result.data(), result.size(), add_special, parse_special); |
| | GGML_ASSERT(check == -n_tokens); |
| | } else { |
| | result.resize(n_tokens); |
| | } |
| | return result; |
| | } |
| |
|
| | std::string common_token_to_piece(const struct llama_context * ctx, llama_token token, bool special) { |
| | const llama_model * model = llama_get_model(ctx); |
| | const llama_vocab * vocab = llama_model_get_vocab(model); |
| | return common_token_to_piece(vocab, token, special); |
| | } |
| |
|
| | std::string common_token_to_piece(const struct llama_vocab * vocab, llama_token token, bool special) { |
| | std::string piece; |
| | piece.resize(piece.capacity()); |
| | const int n_chars = llama_token_to_piece(vocab, token, &piece[0], piece.size(), 0, special); |
| | if (n_chars < 0) { |
| | piece.resize(-n_chars); |
| | int check = llama_token_to_piece(vocab, token, &piece[0], piece.size(), 0, special); |
| | GGML_ASSERT(check == -n_chars); |
| | } |
| | else { |
| | piece.resize(n_chars); |
| | } |
| |
|
| | return piece; |
| | } |
| |
|
| | std::string common_detokenize(const struct llama_context * ctx, const std::vector<llama_token> & tokens, bool special) { |
| | const llama_model * model = llama_get_model(ctx); |
| | const llama_vocab * vocab = llama_model_get_vocab(model); |
| | return common_detokenize(vocab, tokens, special); |
| | } |
| |
|
| | std::string common_detokenize(const struct llama_vocab * vocab, const std::vector<llama_token> & tokens, bool special) { |
| | std::string text; |
| | text.resize(std::max(text.capacity(), tokens.size())); |
| | int32_t n_chars = llama_detokenize(vocab, tokens.data(), (int32_t)tokens.size(), &text[0], (int32_t)text.size(), false, special); |
| | if (n_chars < 0) { |
| | text.resize(-n_chars); |
| | n_chars = llama_detokenize(vocab, tokens.data(), (int32_t)tokens.size(), &text[0], (int32_t)text.size(), false, special); |
| | GGML_ASSERT(n_chars <= (int32_t)text.size()); |
| | } |
| |
|
| | text.resize(n_chars); |
| |
|
| | |
| | return text; |
| | } |
| |
|
| | |
| | |
| | |
| |
|
| | void common_kv_cache_dump_view(const llama_kv_cache_view & view, int row_size) { |
| | static const char slot_chars[] = ".123456789ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz+"; |
| |
|
| | printf("=== Dumping KV cache. total cells %d, max sequences per cell %d, populated cells %d, total tokens in cache %d, largest empty slot=%d @ %d", |
| | view.n_cells, view.n_seq_max, view.used_cells, view.token_count, view.max_contiguous, view.max_contiguous_idx); |
| |
|
| | llama_kv_cache_view_cell * c_curr = view.cells; |
| | llama_seq_id * cs_curr = view.cells_sequences; |
| |
|
| | for (int i = 0; i < view.n_cells; i++, c_curr++, cs_curr += view.n_seq_max) { |
| | if (i % row_size == 0) { |
| | printf("\n%5d: ", i); |
| | } |
| | int seq_count = 0; |
| | for (int j = 0; j < view.n_seq_max; j++) { |
| | if (cs_curr[j] >= 0) { seq_count++; } |
| | } |
| | putchar(slot_chars[std::min(sizeof(slot_chars) - 2, size_t(seq_count))]); |
| | } |
| |
|
| | printf("\n=== Done dumping\n"); |
| | } |
| |
|
| | void common_kv_cache_dump_view_seqs(const llama_kv_cache_view & view, int row_size) { |
| | static const char slot_chars[] = "0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz"; |
| |
|
| | printf("=== Dumping KV cache. total cells %d, max sequences per cell %d, populated cells %d, total tokens in cache %d, largest empty slot=%d @ %d\n", |
| | view.n_cells, view.n_seq_max, view.used_cells, view.token_count, view.max_contiguous, view.max_contiguous_idx); |
| |
|
| | std::unordered_map<llama_seq_id, size_t> seqs; |
| | llama_kv_cache_view_cell * c_curr = view.cells; |
| | llama_seq_id * cs_curr = view.cells_sequences; |
| |
|
| | for (int i = 0; i < view.n_cells; i++, c_curr++, cs_curr += view.n_seq_max) { |
| | for (int j = 0; j < view.n_seq_max; j++) { |
| | if (cs_curr[j] < 0) { continue; } |
| | if (seqs.find(cs_curr[j]) == seqs.end()) { |
| | if (seqs.size() + 1 >= sizeof(slot_chars)) { break; } |
| | const size_t sz = seqs.size(); |
| | seqs[cs_curr[j]] = sz; |
| | } |
| | } |
| | if (seqs.size() + 1 >= sizeof(slot_chars)) { break; } |
| | } |
| |
|
| | printf("=== Sequence legend: "); |
| | for (const auto & it : seqs) { |
| | printf("%zu=%d, ", it.second, it.first); |
| | } |
| | printf("'+'=other sequence ids"); |
| |
|
| | c_curr = view.cells; |
| | cs_curr = view.cells_sequences; |
| | for (int i = 0; i < view.n_cells; i++, c_curr++, cs_curr += view.n_seq_max) { |
| | if (i % row_size == 0) { |
| | printf("\n%5d: ", i); |
| | } |
| | for (int j = 0; j < view.n_seq_max; j++) { |
| | if (cs_curr[j] >= 0) { |
| | const auto & it = seqs.find(cs_curr[j]); |
| | putchar(it != seqs.end() ? int(slot_chars[it->second]) : '+'); |
| | } else { |
| | putchar('.'); |
| | } |
| | } |
| | putchar(' '); |
| | } |
| |
|
| | printf("\n=== Done dumping\n"); |
| | } |
| |
|
| | |
| | |
| | |
| |
|
| | void common_embd_normalize(const float * inp, float * out, int n, int embd_norm) { |
| | double sum = 0.0; |
| |
|
| | switch (embd_norm) { |
| | case -1: |
| | sum = 1.0; |
| | break; |
| | case 0: |
| | for (int i = 0; i < n; i++) { |
| | if (sum < std::abs(inp[i])) { |
| | sum = std::abs(inp[i]); |
| | } |
| | } |
| | sum /= 32760.0; |
| | break; |
| | case 2: |
| | for (int i = 0; i < n; i++) { |
| | sum += inp[i] * inp[i]; |
| | } |
| | sum = std::sqrt(sum); |
| | break; |
| | default: |
| | for (int i = 0; i < n; i++) { |
| | sum += std::pow(std::abs(inp[i]), embd_norm); |
| | } |
| | sum = std::pow(sum, 1.0 / embd_norm); |
| | break; |
| | } |
| |
|
| | const float norm = sum > 0.0 ? 1.0 / sum : 0.0f; |
| |
|
| | for (int i = 0; i < n; i++) { |
| | out[i] = inp[i] * norm; |
| | } |
| | } |
| |
|
| | float common_embd_similarity_cos(const float * embd1, const float * embd2, int n){ |
| | double sum = 0.0; |
| | double sum1 = 0.0; |
| | double sum2 = 0.0; |
| |
|
| | for (int i = 0; i < n; i++) { |
| | sum += embd1[i] * embd2[i]; |
| | sum1 += embd1[i] * embd1[i]; |
| | sum2 += embd2[i] * embd2[i]; |
| | } |
| |
|
| | |
| | if (sum1 == 0.0 || sum2 == 0.0) { |
| | if (sum1 == 0.0 && sum2 == 0.0) { |
| | return 1.0f; |
| | } |
| | return 0.0f; |
| | } |
| |
|
| | return sum / (sqrt(sum1) * sqrt(sum2)); |
| | } |
| |
|
| | |
| | |
| | |
| |
|
| | static common_control_vector_data common_control_vector_load_one(const common_control_vector_load_info & load_info) { |
| | common_control_vector_data result = { -1, {} }; |
| |
|
| | ggml_context * ctx = nullptr; |
| | struct gguf_init_params meta_gguf_params = { |
| | false, |
| | &ctx, |
| | }; |
| | struct gguf_context * ctx_gguf = gguf_init_from_file(load_info.fname.c_str(), meta_gguf_params); |
| | if (!ctx_gguf) { |
| | LOG_ERR("%s: failed to load control vector file from %s\n", __func__, load_info.fname.c_str()); |
| | return result; |
| | } |
| |
|
| | int32_t n_tensors = gguf_get_n_tensors(ctx_gguf); |
| | if (n_tensors == 0) { |
| | LOG_WRN("%s: no direction tensors found in %s\n", __func__, load_info.fname.c_str()); |
| | } |
| |
|
| | for (int i = 0; i < n_tensors; i++) { |
| | std::string name = gguf_get_tensor_name(ctx_gguf, i); |
| |
|
| | int layer_idx = -1; |
| |
|
| | |
| | size_t dotpos = name.find('.'); |
| | if (dotpos != std::string::npos && name.substr(0, dotpos) == "direction") { |
| | try { |
| | layer_idx = std::stoi(name.substr(dotpos + 1)); |
| | } catch (...) { |
| | layer_idx = -1; |
| | } |
| | } |
| | if (layer_idx < 0) { |
| | LOG_ERR("%s: invalid/unparsable direction tensor layer index in %s\n", __func__, load_info.fname.c_str()); |
| | result.n_embd = -1; |
| | break; |
| | } else if (layer_idx == 0) { |
| | LOG_ERR("%s: invalid (zero) direction tensor layer index in %s\n", __func__, load_info.fname.c_str()); |
| | result.n_embd = -1; |
| | break; |
| | } |
| |
|
| | struct ggml_tensor * tensor = ggml_get_tensor(ctx, name.c_str()); |
| | if (tensor->type != GGML_TYPE_F32) { |
| | LOG_ERR("%s: invalid (non-F32) direction tensor type in %s\n", __func__, load_info.fname.c_str()); |
| | result.n_embd = -1; |
| | break; |
| | } |
| | if (ggml_n_dims(tensor) != 1) { |
| | LOG_ERR("%s: invalid (non-1D) direction tensor shape in %s\n", __func__, load_info.fname.c_str()); |
| | result.n_embd = -1; |
| | break; |
| | } |
| |
|
| | if (result.n_embd == -1) { |
| | result.n_embd = ggml_nelements(tensor); |
| | } else if (ggml_nelements(tensor) != result.n_embd) { |
| | LOG_ERR("%s: direction tensor in %s does not match previous dimensions\n", __func__, load_info.fname.c_str()); |
| | result.n_embd = -1; |
| | break; |
| | } |
| |
|
| | |
| | result.data.resize(std::max(result.data.size(), static_cast<size_t>(result.n_embd * layer_idx)), 0.0f); |
| |
|
| | const float * src = (const float *) tensor->data; |
| | float * dst = result.data.data() + result.n_embd * (layer_idx - 1); |
| | for (int j = 0; j < result.n_embd; j++) { |
| | dst[j] += src[j] * load_info.strength; |
| | } |
| |
|
| | } |
| |
|
| | if (result.n_embd == -1) { |
| | LOG_WRN("%s: skipping %s due to invalid direction tensors\n", __func__, load_info.fname.c_str()); |
| | result.data.clear(); |
| | } |
| |
|
| | gguf_free(ctx_gguf); |
| | ggml_free(ctx); |
| |
|
| | return result; |
| | } |
| |
|
| | common_control_vector_data common_control_vector_load(const std::vector<common_control_vector_load_info> & load_infos) { |
| | common_control_vector_data result = { -1, {} }; |
| |
|
| | for (const auto & info : load_infos) { |
| | auto cur = common_control_vector_load_one(info); |
| |
|
| | if (cur.n_embd == -1) { |
| | result.n_embd = -1; |
| | break; |
| | } |
| | if (result.n_embd != -1 && result.n_embd != cur.n_embd) { |
| | LOG_ERR("%s: control vectors in %s does not match previous dimensions\n", __func__, info.fname.c_str()); |
| | result.n_embd = -1; |
| | break; |
| | } |
| |
|
| | if (result.n_embd == -1) { |
| | result = std::move(cur); |
| | } else { |
| | result.data.resize(std::max(result.data.size(), cur.data.size()), 0.0f); |
| | for (size_t i = 0; i < cur.data.size(); i++) { |
| | result.data[i] += cur.data[i]; |
| | } |
| | } |
| | } |
| |
|
| | if (result.n_embd == -1) { |
| | LOG_ERR("%s: no valid control vector files passed\n", __func__); |
| | result.data.clear(); |
| | } |
| |
|
| | return result; |
| | } |
| |
|
| | template <> |
| | json common_grammar_trigger::to_json() const { |
| | json out { |
| | {"type", (int) type}, |
| | {"value", value}, |
| | }; |
| | if (type == COMMON_GRAMMAR_TRIGGER_TYPE_TOKEN) { |
| | out["token"] = (int) token; |
| | } |
| | return out; |
| | } |
| |
|
| | template <> |
| | common_grammar_trigger common_grammar_trigger::from_json(const json & in) { |
| | common_grammar_trigger out; |
| | out.type = (common_grammar_trigger_type) in.at("type").get<int>(); |
| | out.value = in.at("value").get<std::string>(); |
| | if (out.type == COMMON_GRAMMAR_TRIGGER_TYPE_TOKEN) { |
| | out.token = (llama_token) in.at("token").get<int>(); |
| | } |
| | return out; |
| | } |
| |
|