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			577 lines
		
	
	
		
			19 KiB
		
	
	
	
		
			C++
		
	
	
	
	
	
			
		
		
	
	
			577 lines
		
	
	
		
			19 KiB
		
	
	
	
		
			C++
		
	
	
	
	
	
| #include "utils.h"
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| 
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| #include <cassert>
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| #include <cstring>
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| #include <fstream>
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| #include <regex>
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| #include <iostream>
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| #include <iterator>
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| #include <string>
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| #include <math.h>
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| 
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|  #if defined(_MSC_VER) || defined(__MINGW32__)
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|  #include <malloc.h> // using malloc.h with MSC/MINGW
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|  #elif !defined(__FreeBSD__) && !defined(__NetBSD__)
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|  #include <alloca.h>
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|  #endif
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| 
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| bool gpt_params_parse(int argc, char ** argv, gpt_params & params) {
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|     // determine sensible default number of threads.
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|     // std::thread::hardware_concurrency may not be equal to the number of cores, or may return 0.
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| #ifdef __linux__
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|     std::ifstream cpuinfo("/proc/cpuinfo");
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|     params.n_threads = std::count(std::istream_iterator<std::string>(cpuinfo),
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|                                   std::istream_iterator<std::string>(),
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|                                   std::string("processor"));
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| #endif
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|     if (params.n_threads == 0) {
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|         params.n_threads = std::max(1, (int32_t) std::thread::hardware_concurrency());
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|     }
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| 
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|     for (int i = 1; i < argc; i++) {
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|         std::string arg = argv[i];
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| 
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|         if (arg == "-s" || arg == "--seed") {
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|             params.seed = std::stoi(argv[++i]);
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|         } else if (arg == "-t" || arg == "--threads") {
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|             params.n_threads = std::stoi(argv[++i]);
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|         } else if (arg == "-p" || arg == "--prompt") {
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|             params.prompt = argv[++i];
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|         } else if (arg == "-f" || arg == "--file") {
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|             std::ifstream file(argv[++i]);
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|             std::copy(std::istreambuf_iterator<char>(file), std::istreambuf_iterator<char>(), back_inserter(params.prompt));
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|             if (params.prompt.back() == '\n') {
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|                 params.prompt.pop_back();
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|             }
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|         } else if (arg == "-n" || arg == "--n_predict") {
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|             params.n_predict = std::stoi(argv[++i]);
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|         } else if (arg == "--top_k") {
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|             params.top_k = std::stoi(argv[++i]);
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|         } else if (arg == "-c" || arg == "--ctx_size") {
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|             params.n_ctx = std::stoi(argv[++i]);
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|         } else if (arg == "--top_p") {
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|             params.top_p = std::stof(argv[++i]);
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|         } else if (arg == "--temp") {
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|             params.temp = std::stof(argv[++i]);
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|         } else if (arg == "--repeat_last_n") {
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|             params.repeat_last_n = std::stoi(argv[++i]);
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|         } else if (arg == "--repeat_penalty") {
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|             params.repeat_penalty = std::stof(argv[++i]);
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|         } else if (arg == "-b" || arg == "--batch_size") {
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|             params.n_batch = std::stoi(argv[++i]);
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|         } else if (arg == "-m" || arg == "--model") {
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|             params.model = argv[++i];
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|         } else if (arg == "-i" || arg == "--interactive") {
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|             params.interactive = true;
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|         } else if (arg == "-ins" || arg == "--instruct") {
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|             params.instruct = true;
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|         } else if (arg == "--color") {
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|             params.use_color = true;
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|         } else if (arg == "-r" || arg == "--reverse-prompt") {
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|             params.antiprompt = argv[++i];
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|         } else if (arg == "-h" || arg == "--help") {
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|             gpt_print_usage(argc, argv, params);
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|             exit(0);
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|         } else {
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|             fprintf(stderr, "error: unknown argument: %s\n", arg.c_str());
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|             gpt_print_usage(argc, argv, params);
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|             exit(0);
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|         }
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|     }
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| 
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|     return true;
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| }
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| 
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| void gpt_print_usage(int /*argc*/, char ** argv, const gpt_params & params) {
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|     fprintf(stderr, "usage: %s [options]\n", argv[0]);
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|     fprintf(stderr, "\n");
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|     fprintf(stderr, "options:\n");
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|     fprintf(stderr, "  -h, --help            show this help message and exit\n");
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|     fprintf(stderr, "  -i, --interactive     run in interactive mode\n");
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|     fprintf(stderr, "  -ins, --instruct      run in instruction mode (use with Alpaca models)\n");
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|     fprintf(stderr, "  -r PROMPT, --reverse-prompt PROMPT\n");
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|     fprintf(stderr, "                        in interactive mode, poll user input upon seeing PROMPT\n");
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|     fprintf(stderr, "  --color               colorise output to distinguish prompt and user input from generations\n");
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|     fprintf(stderr, "  -s SEED, --seed SEED  RNG seed (default: -1)\n");
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|     fprintf(stderr, "  -t N, --threads N     number of threads to use during computation (default: %d)\n", params.n_threads);
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|     fprintf(stderr, "  -p PROMPT, --prompt PROMPT\n");
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|     fprintf(stderr, "                        prompt to start generation with (default: random)\n");
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|     fprintf(stderr, "  -f FNAME, --file FNAME\n");
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|     fprintf(stderr, "                        prompt file to start generation.\n");
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|     fprintf(stderr, "  -n N, --n_predict N   number of tokens to predict (default: %d)\n", params.n_predict);
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|     fprintf(stderr, "  --top_k N             top-k sampling (default: %d)\n", params.top_k);
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|     fprintf(stderr, "  --top_p N             top-p sampling (default: %.1f)\n", params.top_p);
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|     fprintf(stderr, "  --repeat_last_n N     last n tokens to consider for penalize (default: %d)\n", params.repeat_last_n);
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|     fprintf(stderr, "  --repeat_penalty N    penalize repeat sequence of tokens (default: %.1f)\n", params.repeat_penalty);
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|     fprintf(stderr, "  -c N, --ctx_size N    size of the prompt context (default: %d)\n", params.n_ctx);
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|     fprintf(stderr, "  --temp N              temperature (default: %.1f)\n", params.temp);
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|     fprintf(stderr, "  -b N, --batch_size N  batch size for prompt processing (default: %d)\n", params.n_batch);
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|     fprintf(stderr, "  -m FNAME, --model FNAME\n");
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|     fprintf(stderr, "                        model path (default: %s)\n", params.model.c_str());
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|     fprintf(stderr, "\n");
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| }
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| 
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| std::string gpt_random_prompt(std::mt19937 & rng) {
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|     const int r = rng() % 10;
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|     switch (r) {
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|         case 0: return "So";
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|         case 1: return "Once upon a time";
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|         case 2: return "When";
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|         case 3: return "The";
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|         case 4: return "After";
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|         case 5: return "If";
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|         case 6: return "import";
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|         case 7: return "He";
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|         case 8: return "She";
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|         case 9: return "They";
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|         default: return "To";
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|     }
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| 
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|     return "The";
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| }
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| 
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| void replace(std::string & str, const std::string & needle, const std::string & replacement) {
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|     size_t pos = 0;
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|     while ((pos = str.find(needle, pos)) != std::string::npos) {
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|         str.replace(pos, needle.length(), replacement);
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|         pos += replacement.length();
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|     }
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| }
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| 
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| std::map<std::string, int32_t> json_parse(const std::string & fname) {
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|     std::map<std::string, int32_t> result;
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| 
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|     // read file into string
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|     std::string json;
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|     {
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|         std::ifstream ifs(fname);
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|         if (!ifs) {
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|             fprintf(stderr, "Failed to open %s\n", fname.c_str());
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|             exit(1);
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|         }
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| 
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|         json = std::string((std::istreambuf_iterator<char>(ifs)),
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|                 (std::istreambuf_iterator<char>()));
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|     }
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| 
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|     if (json[0] != '{') {
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|         return result;
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|     }
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| 
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|     // parse json
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|     {
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|         bool has_key  = false;
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|         bool in_token = false;
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| 
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|         std::string str_key = "";
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|         std::string str_val = "";
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| 
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|         int n = json.size();
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|         for (int i = 1; i < n; ++i) {
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|             if (!in_token) {
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|                 if (json[i] == ' ') continue;
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|                 if (json[i] == '"') {
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|                     in_token = true;
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|                     continue;
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|                 }
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|             } else {
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|                 if (json[i] == '\\' && i+1 < n) {
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|                     if (has_key == false) {
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|                         str_key += json[i];
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|                     } else {
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|                         str_val += json[i];
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|                     }
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|                     ++i;
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|                 } else if (json[i] == '"') {
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|                     if (has_key == false) {
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|                         has_key = true;
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|                         ++i;
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|                         while (json[i] == ' ') ++i;
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|                         ++i; // :
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|                         while (json[i] == ' ') ++i;
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|                         if (json[i] != '\"') {
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|                             while (json[i] != ',' && json[i] != '}') {
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|                                 str_val += json[i++];
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|                             }
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|                             has_key = false;
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|                         } else {
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|                             in_token = true;
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|                             continue;
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|                         }
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|                     } else {
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|                         has_key = false;
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|                     }
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| 
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|                     ::replace(str_key, "\\u0120", " " ); // \u0120 -> space
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|                     ::replace(str_key, "\\u010a", "\n"); // \u010a -> new line
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|                     ::replace(str_key, "\\\"",    "\""); // \\\"   -> "
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| 
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|                     try {
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|                         result[str_key] = std::stoi(str_val);
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|                     } catch (...) {
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|                         //fprintf(stderr, "%s: ignoring key '%s' with value '%s'\n", fname.c_str(), str_key.c_str(), str_val.c_str());
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| 
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|                     }
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|                     str_key = "";
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|                     str_val = "";
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|                     in_token = false;
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|                     continue;
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|                 }
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|                 if (has_key == false) {
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|                     str_key += json[i];
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|                 } else {
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|                     str_val += json[i];
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|                 }
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|             }
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|         }
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|     }
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| 
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|     return result;
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| }
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| 
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| std::vector<gpt_vocab::id> gpt_tokenize(const gpt_vocab & vocab, const std::string & text) {
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|     std::vector<std::string> words;
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| 
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|     // first split the text into words
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|     {
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|         std::string str = text;
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|         std::string pat = R"('s|'t|'re|'ve|'m|'ll|'d| ?[[:alpha:]]+| ?[[:digit:]]+| ?[^\s[:alpha:][:digit:]]+|\s+(?!\S)|\s+)";
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| 
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|         std::regex re(pat);
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|         std::smatch m;
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| 
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|         while (std::regex_search(str, m, re)) {
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|             for (auto x : m) {
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|                 words.push_back(x);
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|             }
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|             str = m.suffix();
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|         }
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|     }
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| 
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|     // find the longest tokens that form the words:
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|     std::vector<gpt_vocab::id> tokens;
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|     for (const auto & word : words) {
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|         if (word.size() == 0) continue;
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| 
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|         int i = 0;
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|         int n = word.size();
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|         while (i < n) {
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|             int j = n;
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|             while (j > i) {
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|                 auto it = vocab.token_to_id.find(word.substr(i, j-i));
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|                 if (it != vocab.token_to_id.end()) {
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|                     tokens.push_back(it->second);
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|                     i = j;
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|                     break;
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|                 }
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|                 --j;
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|             }
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|             if (i == n) {
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|                 break;
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|             }
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|             if (j == i) {
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|                 auto sub = word.substr(i, 1);
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|                 if (vocab.token_to_id.find(sub) != vocab.token_to_id.end()) {
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|                     tokens.push_back(vocab.token_to_id.at(sub));
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|                 } else {
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|                     fprintf(stderr, "%s: unknown token '%s'\n", __func__, sub.data());
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|                 }
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|                 ++i;
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|             }
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|         }
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|     }
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| 
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|     return tokens;
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| }
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| 
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| // TODO: Calculate this constant from the vocabulary
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| #define MAX_TOKEN_LEN 18
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| // SentencePiece implementation after https://guillaume-be.github.io/2020-05-30/sentence_piece
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| std::vector<gpt_vocab::id> llama_tokenize(const gpt_vocab & vocab, const std::string & text, bool bos) {
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|     std::vector<gpt_vocab::id> res;
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|     std::vector<int> score;
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|     std::vector<gpt_vocab::id> prev;
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|     int len = text.length();
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| 
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|     score.resize(len + 1);
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|     prev.resize(len + 1);
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| 
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|     // Forward pass
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|     for (int i = 0; i < len; i++) {
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|         int max_len = std::min(len - i, MAX_TOKEN_LEN);
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|         for (int sub_len = 1; sub_len <= max_len; sub_len++) {
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|             auto sub = text.substr(i, sub_len);
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|             auto token = vocab.token_to_id.find(sub);
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|             if (token != vocab.token_to_id.end()) {
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|                 int token_score = sub.length() * sub.length();
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|                 int local_score = score[i] + token_score;
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|                 int next = i + sub_len;
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|                 if (score[next] < local_score) {
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|                     score[next] = local_score;
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|                     prev[next] = (*token).second;
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|                 }
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|             }
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|         }
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|     }
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| 
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|     // Backward pass
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|     int i = len;
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|     while (i > 0) {
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|         gpt_vocab::id token_id = prev[i];
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|         if (token_id == 0) {
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| 	    // TODO: Return error or something more meaningful
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|             printf("failed to tokenize string!\n");
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| 	    break;
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|         }
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|         res.push_back(token_id);
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|         auto token = (*vocab.id_to_token.find(token_id)).second;
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|         i -= token.length();
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|     }
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| 
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|     if (bos) {
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|         res.push_back(1); // TODO: replace with vocab.bos
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|     }
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| 
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|     // Pieces are in reverse order so correct that
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|     std::reverse(res.begin(), res.end());
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| 
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|     return res;
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| }
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| 
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| bool gpt_vocab_init(const std::string & fname, gpt_vocab & vocab) {
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|     printf("%s: loading vocab from '%s'\n", __func__, fname.c_str());
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| 
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|     vocab.token_to_id = ::json_parse(fname);
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| 
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|     for (const auto & kv : vocab.token_to_id) {
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|         vocab.id_to_token[kv.second] = kv.first;
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|     }
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| 
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|     printf("%s: vocab size = %d\n", __func__, (int) vocab.token_to_id.size());
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| 
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|     // print the vocabulary
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|     //for (auto kv : vocab.token_to_id) {
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|     //    printf("'%s' -> %d\n", kv.first.data(), kv.second);
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|     //}
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| 
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|     return true;
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| }
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| 
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| 
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| void sample_top_k(std::vector<std::pair<double, gpt_vocab::id>> & logits_id, int top_k) {
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|     // find the top K tokens
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|     std::partial_sort(
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|             logits_id.begin(),
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|             logits_id.begin() + top_k, logits_id.end(),
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|             [](const std::pair<double, gpt_vocab::id> & a, const std::pair<double, gpt_vocab::id> & b) {
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|         return a.first > b.first;
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|     });
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| 
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|     logits_id.resize(top_k);
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| }
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| 
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| gpt_vocab::id llama_sample_top_p_top_k(
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|         const gpt_vocab & vocab,
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|         const float * logits,
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|         std::vector<gpt_vocab::id> & last_n_tokens,
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|         double repeat_penalty,
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|         int top_k,
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|         double top_p,
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|         double temp,
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|         std::mt19937 & rng) {
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|     int n_logits = vocab.id_to_token.size();
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| 
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|     std::vector<std::pair<double, gpt_vocab::id>> logits_id;
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|     logits_id.reserve(n_logits);
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| 
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|     {
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|         const double scale = 1.0/temp;
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|         for (int i = 0; i < n_logits; ++i) {
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|             // repetition penalty from CTRL paper (https://arxiv.org/abs/1909.05858)
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|             // credit https://github.com/facebookresearch/llama/compare/main...shawwn:llama:main
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|             if (std::find(last_n_tokens.begin(), last_n_tokens.end(), i) != last_n_tokens.end()) {
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|                 // if score < 0 then repetition penalty has to multiplied to reduce the previous token probability
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|                 if (logits[i] < 0.0) {
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|                     logits_id.push_back(std::make_pair(logits[i]*scale*repeat_penalty, i));
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|                 } else {
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|                     logits_id.push_back(std::make_pair(logits[i]*scale/repeat_penalty, i));
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|                 }
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|             } else {
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|                 logits_id.push_back(std::make_pair(logits[i]*scale, i));
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|             }
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|         }
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|     }
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| 
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|     sample_top_k(logits_id, top_k);
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| 
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|     double maxl = -INFINITY;
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|     for (const auto & kv : logits_id) {
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|         maxl = std::max(maxl, kv.first);
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|     }
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| 
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|     // compute probs for the top K tokens
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|     std::vector<double> probs;
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|     probs.reserve(logits_id.size());
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| 
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|     double sum = 0.0;
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|     for (const auto & kv : logits_id) {
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|         double p = exp(kv.first - maxl);
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|         probs.push_back(p);
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|         sum += p;
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|     }
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| 
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|     // normalize the probs
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|     for (auto & p : probs) {
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|         p /= sum;
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|     }
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| 
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|     if (top_p < 1.0f) {
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|         double cumsum = 0.0f;
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|         for (int i = 0; i < (int) probs.size(); i++) {
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|             cumsum += probs[i];
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|             if (cumsum >= top_p) {
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|                 probs.resize(i + 1);
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|                 logits_id.resize(i + 1);
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|                 break;
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|             }
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|         }
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| 
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|         cumsum = 1.0/cumsum;
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|         for (int i = 0; i < (int) probs.size(); i++) {
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|             probs[i] *= cumsum;
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|         }
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|     }
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| 
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|     //printf("\n");
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|     //for (int i = 0; i < (int) 10; i++) {
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|     //    printf("%d: '%s' %f\n", i, vocab.id_to_token.at(logits_id[i].second).c_str(), probs[i]);
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|     //}
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|     //printf("\n\n");
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|     //exit(0);
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| 
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|     std::discrete_distribution<> dist(probs.begin(), probs.end());
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|     int idx = dist(rng);
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| 
 | |
|     return logits_id[idx].second;
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| }
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| 
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| 
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| size_t ggml_quantize_q4_0(float * src, void * dst, int n, int k, int qk, int64_t * hist) {
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|     const int nb = k / qk;
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|     const size_t bs = (sizeof(float) + sizeof(uint8_t)*qk/2);
 | |
|     const size_t row_size = nb*bs;
 | |
| 
 | |
|     assert(k % qk == 0);
 | |
| 
 | |
|     const size_t pp_size = qk / 2;
 | |
|     uint8_t *pp = static_cast<uint8_t*>(alloca(pp_size));
 | |
| 
 | |
|     char * pdst = (char *) dst;
 | |
| 
 | |
|     for (int j = 0; j < n; j += k) {
 | |
|         uint8_t * pd = (uint8_t *) (pdst + (j/k)*row_size + 0*bs);
 | |
|         uint8_t * pb = (uint8_t *) (pdst + (j/k)*row_size + 0*bs + sizeof(float));
 | |
| 
 | |
|         for (int i = 0; i < nb; i++) {
 | |
|             float amax = 0.0f; // absolute max
 | |
| 
 | |
|             {
 | |
|                 for (int l = 0; l < qk; l++) {
 | |
|                     const float v = src[j + i*qk + l];
 | |
|                     amax = std::max(amax, fabsf(v));
 | |
|                 }
 | |
| 
 | |
|                 const float d = amax / ((1 << 3) - 1);
 | |
|                 const float id = d ? 1.0f/d : 0.0f;
 | |
| 
 | |
|                 *(float *) pd = d;
 | |
|                 pd += bs;
 | |
| 
 | |
|                 for (int l = 0; l < qk; l += 2) {
 | |
|                     const float v0 = (src[j + i*qk + l + 0])*id;
 | |
|                     const float v1 = (src[j + i*qk + l + 1])*id;
 | |
| 
 | |
|                     const uint8_t vi0 = ((int8_t) (round(v0))) + 8;
 | |
|                     const uint8_t vi1 = ((int8_t) (round(v1))) + 8;
 | |
| 
 | |
|                     assert(vi0 >= 0 && vi0 < 16);
 | |
|                     assert(vi1 >= 0 && vi1 < 16);
 | |
| 
 | |
|                     hist[vi0]++;
 | |
|                     hist[vi1]++;
 | |
| 
 | |
|                     pp[l/2] = vi0 | (vi1 << 4);
 | |
|                 }
 | |
| 
 | |
|                 memcpy(pb, pp, pp_size);
 | |
|                 pb += bs;
 | |
|             }
 | |
|         }
 | |
|     }
 | |
| 
 | |
|     return (n/k)*row_size;
 | |
| }
 | |
| 
 | |
| size_t ggml_quantize_q4_1(float * src, void * dst, int n, int k, int qk, int64_t * hist) {
 | |
|     const int nb = k / qk;
 | |
|     const size_t bs = (2*sizeof(float) + sizeof(uint8_t)*qk/2);
 | |
|     const size_t row_size = nb*bs;
 | |
| 
 | |
|     assert(k % qk == 0);
 | |
| 
 | |
|     const size_t pp_size = qk / 2;
 | |
|     uint8_t *pp = static_cast<uint8_t*>(alloca(pp_size));
 | |
| 
 | |
|     char * pdst = (char *) dst;
 | |
| 
 | |
|     for (int j = 0; j < n; j += k) { 
 | |
|         uint8_t * pd = (uint8_t *) (pdst + (j/k)*row_size + 0*bs);
 | |
|         uint8_t * pm = (uint8_t *) (pdst + (j/k)*row_size + 0*bs +   sizeof(float));
 | |
|         uint8_t * pb = (uint8_t *) (pdst + (j/k)*row_size + 0*bs + 2*sizeof(float));
 | |
| 
 | |
|         //printf("n = %d, k = %d, nb = %d, row_size = %d, j = %d, pm = %p, pd = %p, pb = %p\n", n, k, nb, row_size, j, pm, pd, pb);
 | |
| 
 | |
|         for (int i = 0; i < nb; i++) {
 | |
|             float min = std::numeric_limits<float>::max();
 | |
|             float max = std::numeric_limits<float>::min();
 | |
| 
 | |
|             {
 | |
|                 for (int l = 0; l < qk; l++) {
 | |
|                     const float v = src[j + i*qk + l];
 | |
|                     if (v < min) min = v;
 | |
|                     if (v > max) max = v;
 | |
|                 }
 | |
| 
 | |
|                 const float d = (max - min) / ((1 << 4) - 1);
 | |
|                 const float id = d ? 1.0f/d : 0.0f;
 | |
| 
 | |
|                 *(float *) pd = d;
 | |
|                 *(float *) pm = min;
 | |
|                 pd += bs; 
 | |
|                 pm += bs;
 | |
| 
 | |
|                 for (int l = 0; l < qk; l += 2) {
 | |
|                     const float v0 = (src[j + i*qk + l + 0] - min)*id;
 | |
|                     const float v1 = (src[j + i*qk + l + 1] - min)*id;
 | |
| 
 | |
|                     const uint8_t vi0 = round(v0);
 | |
|                     const uint8_t vi1 = round(v1);
 | |
| 
 | |
|                     assert(vi0 >= 0 && vi0 < 16);
 | |
|                     assert(vi1 >= 0 && vi1 < 16);
 | |
| 
 | |
|                     hist[vi0]++;
 | |
|                     hist[vi1]++;
 | |
| 
 | |
|                     pp[l/2] = vi0 | (vi1 << 4);
 | |
|                 }
 | |
| 
 | |
|                 memcpy(pb, pp, pp_size);
 | |
|                 pb += bs;
 | |
|             }
 | |
|         }
 | |
|     }
 | |
| 
 | |
|     return (n/k)*row_size;
 | |
| }
 | 
