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cosmopolitan/third_party/ggml/common.cc

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Introduce prompt caching so prompts load instantly This change also introduces an ephemeral status line in non-verbose mode to display a load percentage status when slow operations are happening.
2023-04-28 23:15:26 +00:00
/*-*-mode:c++;indent-tabs-mode:nil;c-basic-offset:4;tab-width:8;coding:utf-8-*-│
│vi: set net ft=c++ ts=4 sts=4 sw=4 fenc=utf-8 :vi│
Import llama.cpp https://github.com/ggerganov/llama.cpp 0b2da20538d01926b77ea237dd1c930c4d20b686 See third_party/ggml/README.cosmo for changes
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╚──────────────────────────────────────────────────────────────────────────────╝
│ │
Use Companion AI in llama.com by default
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│ llama.com │
│ Copyright (c) 2023 Justine Alexandra Roberts Tunney │
Import llama.cpp https://github.com/ggerganov/llama.cpp 0b2da20538d01926b77ea237dd1c930c4d20b686 See third_party/ggml/README.cosmo for changes
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│ Copyright (c) 2023 Georgi Gerganov │
│ │
│ Permission is hereby granted, free of charge, to any person obtaining │
│ a copy of this software and associated documentation files (the │
│ "Software"), to deal in the Software without restriction, including │
│ without limitation the rights to use, copy, modify, merge, publish, │
│ distribute, sublicense, and/or sell copies of the Software, and to │
│ permit persons to whom the Software is furnished to do so, subject to │
│ the following conditions: │
│ │
│ The above copyright notice and this permission notice shall be │
│ included in all copies or substantial portions of the Software. │
│ │
│ THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, │
│ EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF │
│ MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. │
│ IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY │
│ CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, │
│ TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE │
│ SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. │
│ │
╚─────────────────────────────────────────────────────────────────────────────*/
Use Companion AI in llama.com by default
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#include "third_party/ggml/common.h"
#include "libc/runtime/runtime.h"
#include "libc/str/str.h"
#include "third_party/libcxx/algorithm"
#include "third_party/libcxx/cassert"
#include "third_party/libcxx/cstring"
#include "third_party/libcxx/fstream"
#include "third_party/libcxx/iterator"
#include "third_party/libcxx/string"
STATIC_YOINK("zipos");
Import llama.cpp https://github.com/ggerganov/llama.cpp 0b2da20538d01926b77ea237dd1c930c4d20b686 See third_party/ggml/README.cosmo for changes
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asm(".ident\t\"\\n\\n\
llama.cpp (MIT License)\\n\
Copyright (c) 2023 Georgi Gerganov\"");
asm(".include \"libc/disclaimer.inc\"");
// clang-format off
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static bool is_integer_str(const char *s) {
if (*s == '-') ++s;
if (!*s) return false;
while (isdigit(*s)) ++s;
return !*s;
}
Import llama.cpp https://github.com/ggerganov/llama.cpp 0b2da20538d01926b77ea237dd1c930c4d20b686 See third_party/ggml/README.cosmo for changes
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static std::string replace_all(std::string const& original,
std::string const& before,
std::string const& after) {
// https://stackoverflow.com/a/7724536/1653720
std::string retval;
std::string::const_iterator end = original.end();
std::string::const_iterator current = original.begin();
std::string::const_iterator next =
std::search(current, end, before.begin(), before.end());
while (next != end) {
retval.append(current, next);
retval.append(after);
current = next + before.size();
next = std::search(current, end, before.begin(), before.end());
}
retval.append(current, next);
return retval;
}
Import llama.cpp https://github.com/ggerganov/llama.cpp 0b2da20538d01926b77ea237dd1c930c4d20b686 See third_party/ggml/README.cosmo for changes
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Use Companion AI in llama.com by default
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static bool append_file_to_prompt(const char *path, gpt_params & params) {
std::ifstream file(path);
if (!file) {
fprintf(stderr, "error: failed to open file '%s'\n", path);
return false;
}
std::copy(std::istreambuf_iterator<char>(file), std::istreambuf_iterator<char>(), back_inserter(params.prompt));
if (params.prompt.back() == '\n') {
params.prompt.pop_back();
}
return true;
}
Import llama.cpp https://github.com/ggerganov/llama.cpp 0b2da20538d01926b77ea237dd1c930c4d20b686 See third_party/ggml/README.cosmo for changes
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bool gpt_params_parse(int argc, char ** argv, gpt_params & params) {
Use Companion AI in llama.com by default
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params.n_threads = std::min(20, std::max(1, (int)(_getcpucount() * 0.75)));
Import llama.cpp https://github.com/ggerganov/llama.cpp 0b2da20538d01926b77ea237dd1c930c4d20b686 See third_party/ggml/README.cosmo for changes
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bool invalid_param = false;
std::string arg;
gpt_params default_params;
for (int i = 1; i < argc; i++) {
arg = argv[i];
if (arg == "-s" || arg == "--seed") {
if (++i >= argc) {
invalid_param = true;
break;
}
params.seed = std::stoi(argv[i]);
Make shell usability improvements to llama.cpp - Introduce -v and --verbose flags - Don't print stats / diagnostics unless -v is passed - Reduce --top_p default from 0.95 to 0.70 - Change --reverse-prompt to no longer imply --interactive - Permit --reverse-prompt specifying custom EOS if non-interactive
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} else if (arg == "-v" || arg == "--verbose") {
++params.verbose;
Import llama.cpp https://github.com/ggerganov/llama.cpp 0b2da20538d01926b77ea237dd1c930c4d20b686 See third_party/ggml/README.cosmo for changes
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} else if (arg == "-t" || arg == "--threads") {
if (++i >= argc) {
invalid_param = true;
break;
}
params.n_threads = std::stoi(argv[i]);
} else if (arg == "-p" || arg == "--prompt") {
if (++i >= argc) {
invalid_param = true;
break;
}
params.prompt = argv[i];
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} else if (arg == "-C" || arg == "--prompt_cache") {
Import llama.cpp https://github.com/ggerganov/llama.cpp 0b2da20538d01926b77ea237dd1c930c4d20b686 See third_party/ggml/README.cosmo for changes
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if (++i >= argc) {
invalid_param = true;
break;
}
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params.prompt_path = argv[i];
} else if (arg == "-f" || arg == "--file") {
if (++i >= argc) {
Import llama.cpp https://github.com/ggerganov/llama.cpp 0b2da20538d01926b77ea237dd1c930c4d20b686 See third_party/ggml/README.cosmo for changes
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invalid_param = true;
break;
}
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if (!append_file_to_prompt(argv[i], params)) {
invalid_param = true;
break;
Import llama.cpp https://github.com/ggerganov/llama.cpp 0b2da20538d01926b77ea237dd1c930c4d20b686 See third_party/ggml/README.cosmo for changes
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}
} else if (arg == "-n" || arg == "--n_predict") {
if (++i >= argc) {
invalid_param = true;
break;
}
params.n_predict = std::stoi(argv[i]);
} else if (arg == "--top_k") {
if (++i >= argc) {
invalid_param = true;
break;
}
params.top_k = std::stoi(argv[i]);
} else if (arg == "-c" || arg == "--ctx_size") {
if (++i >= argc) {
invalid_param = true;
break;
}
params.n_ctx = std::stoi(argv[i]);
} else if (arg == "--memory_f32") {
params.memory_f16 = false;
} else if (arg == "--top_p") {
if (++i >= argc) {
invalid_param = true;
break;
}
params.top_p = std::stof(argv[i]);
} else if (arg == "--temp") {
if (++i >= argc) {
invalid_param = true;
break;
}
params.temp = std::stof(argv[i]);
} else if (arg == "--repeat_last_n") {
if (++i >= argc) {
invalid_param = true;
break;
}
params.repeat_last_n = std::stoi(argv[i]);
} else if (arg == "--repeat_penalty") {
if (++i >= argc) {
invalid_param = true;
break;
}
params.repeat_penalty = std::stof(argv[i]);
} else if (arg == "-b" || arg == "--batch_size") {
if (++i >= argc) {
invalid_param = true;
break;
}
params.n_batch = std::stoi(argv[i]);
params.n_batch = std::min(512, params.n_batch);
} else if (arg == "--keep") {
if (++i >= argc) {
invalid_param = true;
break;
}
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params.n_keep_str = argv[i];
if (is_integer_str(argv[i])) {
params.n_keep = std::stoi(params.n_keep_str);
if (!params.n_keep) {
params.n_keep_str = "";
}
}
Import llama.cpp https://github.com/ggerganov/llama.cpp 0b2da20538d01926b77ea237dd1c930c4d20b686 See third_party/ggml/README.cosmo for changes
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} else if (arg == "-m" || arg == "--model") {
if (++i >= argc) {
invalid_param = true;
break;
}
params.model = argv[i];
} else if (arg == "--lora") {
if (++i >= argc) {
invalid_param = true;
break;
}
params.lora_adapter = argv[i];
params.use_mmap = false;
} else if (arg == "--lora-base") {
if (++i >= argc) {
invalid_param = true;
break;
}
params.lora_base = argv[i];
} else if (arg == "-i" || arg == "--interactive") {
params.interactive = true;
} else if (arg == "--embedding") {
params.embedding = true;
} else if (arg == "--interactive-first") {
params.interactive_first = true;
} else if (arg == "-ins" || arg == "--instruct") {
params.instruct = true;
} else if (arg == "--color") {
params.use_color = true;
} else if (arg == "--mlock") {
params.use_mlock = true;
} else if (arg == "--no-mmap") {
params.use_mmap = false;
} else if (arg == "--mtest") {
params.mem_test = true;
} else if (arg == "--verbose-prompt") {
params.verbose_prompt = true;
} else if (arg == "-r" || arg == "--reverse-prompt") {
if (++i >= argc) {
invalid_param = true;
break;
}
params.antiprompt.push_back(argv[i]);
} else if (arg == "--perplexity") {
params.perplexity = true;
} else if (arg == "--ignore-eos") {
params.ignore_eos = true;
} else if (arg == "--n_parts") {
if (++i >= argc) {
invalid_param = true;
break;
}
params.n_parts = std::stoi(argv[i]);
} else if (arg == "-h" || arg == "--help") {
gpt_print_usage(argc, argv, default_params);
exit(0);
} else if (arg == "--random-prompt") {
params.random_prompt = true;
} else if (arg == "--in-prefix") {
if (++i >= argc) {
invalid_param = true;
break;
}
params.input_prefix = argv[i];
} else {
fprintf(stderr, "error: unknown argument: %s\n", arg.c_str());
gpt_print_usage(argc, argv, default_params);
exit(1);
}
}
if (invalid_param) {
fprintf(stderr, "error: invalid parameter for argument: %s\n", arg.c_str());
gpt_print_usage(argc, argv, default_params);
exit(1);
}
Use Companion AI in llama.com by default
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// if no prompt is specified, then use companion ai
if (params.prompt.empty()) {
if (params.verbose) {
fprintf(stderr, "%s: No prompt specified\n", __func__);
fprintf(stderr, "%s: Loading CompanionAI\n", __func__);
}
append_file_to_prompt("/zip/companionai.txt", params);
const char *user;
user = getenv("USER");
if (!user || !*user) {
user = "Cosmo";
}
params.prompt = replace_all(params.prompt, "USER_NAME", user);
std::string user_prompt;
user_prompt.append(user);
user_prompt.append(":");
params.antiprompt.push_back(user_prompt);
params.repeat_penalty = 1.17647;
params.repeat_last_n = 256;
params.interactive = true;
params.ignore_eos = true;
params.n_predict = -1;
params.n_ctx = 2048;
params.n_keep = 0;
params.n_keep_str = "\n\n\n";
params.top_k = 40;
params.top_p = .5;
params.temp = 0.4;
}
Import llama.cpp https://github.com/ggerganov/llama.cpp 0b2da20538d01926b77ea237dd1c930c4d20b686 See third_party/ggml/README.cosmo for changes
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return true;
}
void gpt_print_usage(int /*argc*/, char ** argv, const gpt_params & params) {
fprintf(stderr, "usage: %s [options]\n", argv[0]);
fprintf(stderr, "\n");
fprintf(stderr, "options:\n");
fprintf(stderr, " -h, --help show this help message and exit\n");
Use Companion AI in llama.com by default
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fprintf(stderr, " -v, --verbose print plenty of helpful information, e.g. prompt\n");
Import llama.cpp https://github.com/ggerganov/llama.cpp 0b2da20538d01926b77ea237dd1c930c4d20b686 See third_party/ggml/README.cosmo for changes
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fprintf(stderr, " -i, --interactive run in interactive mode\n");
fprintf(stderr, " --interactive-first run in interactive mode and wait for input right away\n");
fprintf(stderr, " -ins, --instruct run in instruction mode (use with Alpaca models)\n");
fprintf(stderr, " -r PROMPT, --reverse-prompt PROMPT\n");
fprintf(stderr, " run in interactive mode and poll user input upon seeing PROMPT (can be\n");
fprintf(stderr, " specified more than once for multiple prompts).\n");
fprintf(stderr, " --color colorise output to distinguish prompt and user input from generations\n");
fprintf(stderr, " -s SEED, --seed SEED RNG seed (default: -1, use random seed for <= 0)\n");
fprintf(stderr, " -t N, --threads N number of threads to use during computation (default: %d)\n", params.n_threads);
fprintf(stderr, " -p PROMPT, --prompt PROMPT\n");
Use Companion AI in llama.com by default
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fprintf(stderr, " prompt to start generation with (default: Companion AI)\n");
Import llama.cpp https://github.com/ggerganov/llama.cpp 0b2da20538d01926b77ea237dd1c930c4d20b686 See third_party/ggml/README.cosmo for changes
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fprintf(stderr, " --random-prompt start with a randomized prompt.\n");
fprintf(stderr, " --in-prefix STRING string to prefix user inputs with (default: empty)\n");
fprintf(stderr, " -f FNAME, --file FNAME\n");
Use Companion AI in llama.com by default
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fprintf(stderr, " text file containing prompt (default: Companion AI)\n");
fprintf(stderr, " -C FNAME, --prompt_cache FNAME\n");
fprintf(stderr, " path of cache for fast prompt reload (default: .prompt.jtlp)\n");
Import llama.cpp https://github.com/ggerganov/llama.cpp 0b2da20538d01926b77ea237dd1c930c4d20b686 See third_party/ggml/README.cosmo for changes
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fprintf(stderr, " -n N, --n_predict N number of tokens to predict (default: %d, -1 = infinity)\n", params.n_predict);
fprintf(stderr, " --top_k N top-k sampling (default: %d)\n", params.top_k);
fprintf(stderr, " --top_p N top-p sampling (default: %.1f)\n", (double)params.top_p);
fprintf(stderr, " --repeat_last_n N last n tokens to consider for penalize (default: %d)\n", params.repeat_last_n);
fprintf(stderr, " --repeat_penalty N penalize repeat sequence of tokens (default: %.1f)\n", (double)params.repeat_penalty);
fprintf(stderr, " -c N, --ctx_size N size of the prompt context (default: %d)\n", params.n_ctx);
fprintf(stderr, " --ignore-eos ignore end of stream token and continue generating\n");
fprintf(stderr, " --memory_f32 use f32 instead of f16 for memory key+value\n");
fprintf(stderr, " --temp N temperature (default: %.1f)\n", (double)params.temp);
fprintf(stderr, " --n_parts N number of model parts (default: -1 = determine from dimensions)\n");
fprintf(stderr, " -b N, --batch_size N batch size for prompt processing (default: %d)\n", params.n_batch);
fprintf(stderr, " --perplexity compute perplexity over the prompt\n");
Use Companion AI in llama.com by default
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fprintf(stderr, " --keep NUM|STR number of tokens to keep from the initial prompt, or substring\n");
fprintf(stderr, " to search for within prompt that divides the actual prompt from\n");
fprintf(stderr, " its initial example text (default: %d, -1 = all)\n", params.n_keep);
Import llama.cpp https://github.com/ggerganov/llama.cpp 0b2da20538d01926b77ea237dd1c930c4d20b686 See third_party/ggml/README.cosmo for changes
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if (llama_mlock_supported()) {
fprintf(stderr, " --mlock force system to keep model in RAM rather than swapping or compressing\n");
}
if (llama_mmap_supported()) {
fprintf(stderr, " --no-mmap do not memory-map model (slower load but may reduce pageouts if not using mlock)\n");
}
fprintf(stderr, " --mtest compute maximum memory usage\n");
fprintf(stderr, " --verbose-prompt print prompt before generation\n");
fprintf(stderr, " --lora FNAME apply LoRA adapter (implies --no-mmap)\n");
fprintf(stderr, " --lora-base FNAME optional model to use as a base for the layers modified by the LoRA adapter\n");
fprintf(stderr, " -m FNAME, --model FNAME\n");
fprintf(stderr, " model path (default: %s)\n", params.model.c_str());
fprintf(stderr, "\n");
}
std::string gpt_random_prompt(std::mt19937 & rng) {
const int r = rng() % 10;
switch (r) {
case 0: return "So";
case 1: return "Once upon a time";
case 2: return "When";
case 3: return "The";
case 4: return "After";
case 5: return "If";
case 6: return "import";
case 7: return "He";
case 8: return "She";
case 9: return "They";
default: return "To";
}
return "The";
}
// TODO: not great allocating this every time
std::vector<llama_token> llama_tokenize(struct llama_context * ctx, const std::string & text, bool add_bos) {
// initialize to prompt numer of chars, since n_tokens <= n_prompt_chars
std::vector<llama_token> res(text.size() + (int)add_bos);
int n = llama_tokenize(ctx, text.c_str(), res.data(), res.size(), add_bos);
assert(n >= 0);
res.resize(n);
return res;
}
/* Keep track of current color of output, and emit ANSI code if it changes. */
void set_console_color(console_state & con_st, console_color_t color) {
if (con_st.use_color && con_st.color != color) {
switch(color) {
case CONSOLE_COLOR_DEFAULT:
printf(ANSI_COLOR_RESET);
break;
case CONSOLE_COLOR_PROMPT:
printf(ANSI_COLOR_YELLOW);
break;
case CONSOLE_COLOR_USER_INPUT:
printf(ANSI_BOLD ANSI_COLOR_GREEN);
break;
}
con_st.color = color;
}
Use Companion AI in llama.com by default
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fflush(stdout);
Import llama.cpp https://github.com/ggerganov/llama.cpp 0b2da20538d01926b77ea237dd1c930c4d20b686 See third_party/ggml/README.cosmo for changes
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}
#if defined (_WIN32)
void win32_console_init(bool enable_color) {
unsigned long dwMode = 0;
void* hConOut = GetStdHandle((unsigned long)-11); // STD_OUTPUT_HANDLE (-11)
if (!hConOut || hConOut == (void*)-1 || !GetConsoleMode(hConOut, &dwMode)) {
hConOut = GetStdHandle((unsigned long)-12); // STD_ERROR_HANDLE (-12)
if (hConOut && (hConOut == (void*)-1 || !GetConsoleMode(hConOut, &dwMode))) {
hConOut = 0;
}
}
if (hConOut) {
// Enable ANSI colors on Windows 10+
if (enable_color && !(dwMode & 0x4)) {
SetConsoleMode(hConOut, dwMode | 0x4); // ENABLE_VIRTUAL_TERMINAL_PROCESSING (0x4)
}
// Set console output codepage to UTF8
SetConsoleOutputCP(CP_UTF8);
}
void* hConIn = GetStdHandle((unsigned long)-10); // STD_INPUT_HANDLE (-10)
if (hConIn && hConIn != (void*)-1 && GetConsoleMode(hConIn, &dwMode)) {
// Set console input codepage to UTF16
_setmode(_fileno(stdin), _O_WTEXT);
}
}
// Convert a wide Unicode string to an UTF8 string
void win32_utf8_encode(const std::wstring & wstr, std::string & str) {
int size_needed = WideCharToMultiByte(CP_UTF8, 0, &wstr[0], (int)wstr.size(), NULL, 0, NULL, NULL);
std::string strTo(size_needed, 0);
WideCharToMultiByte(CP_UTF8, 0, &wstr[0], (int)wstr.size(), &strTo[0], size_needed, NULL, NULL);
str = strTo;
}
#endif
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