first try to intergrate sentencepiece

.gitignore

@@ -21,3 +21,4 @@ models/*
 
 arm_neon.h
 compile_commands.json
+*.dSYM/

Makefile

@@ -30,9 +30,9 @@ endif
 # Compile flags
 #
 
-CFLAGS   = -I.              -O3 -DNDEBUG -std=c11   -fPIC
-CXXFLAGS = -I. -I./examples -O3 -DNDEBUG -std=c++11 -fPIC
-LDFLAGS  =
+CFLAGS   = -I.              -O3 -DNDEBUG -std=c11   -fPIC -g -I/opt/homebrew/include
+CXXFLAGS = -I. -I./examples -O3 -DNDEBUG -std=c++11 -fPIC -g -I/opt/homebrew/include
+LDFLAGS  = -L/opt/homebrew/lib -lsentencepiece
 
 # OS specific
 # TODO: support Windows

main.cpp

@@ -10,6 +10,12 @@
 #include <map>
 #include <string>
 #include <vector>
+#include <sentencepiece_processor.h>
+#include <stdexcept>
+#include <iostream>
+#include <bitset>
+#include <sstream>
+#include <regex>
 
 #include <signal.h>
 #include <unistd.h>
@@ -82,7 +88,7 @@ struct llama_model {
 };
 
 // load the model's weights from a file
-bool llama_model_load(const std::string & fname, llama_model & model, gpt_vocab & vocab, int n_ctx) {
+bool llama_model_load(const std::string & fname, llama_model & model, sentencepiece::SentencePieceProcessor & sp, gpt_vocab & vocab, int n_ctx) {
     printf("%s: loading model from '%s' - please wait ...\n", __func__, fname.c_str());
 
     auto fin = std::ifstream(fname, std::ios::binary);
@@ -144,6 +150,8 @@ bool llama_model_load(const std::string & fname, llama_model & model, gpt_vocab
             return false;
         }
 
+        printf("total pieces: %d", sp.GetPieceSize());
+
         std::string word;
         for (int i = 0; i < n_vocab; i++) {
             uint32_t len;
@@ -152,8 +160,9 @@ bool llama_model_load(const std::string & fname, llama_model & model, gpt_vocab
             word.resize(len);
             fin.read((char *) word.data(), len);
 
-            vocab.token_to_id[word] = i;
-            vocab.id_to_token[i] = word;
+            std::string wordx = sp.IdToPiece(i);
+            vocab.token_to_id[wordx] = i;
+            vocab.id_to_token[i] = wordx;
 
             //if (i < 30000) {
             //    printf("%s: vocab[%d] = '%s'\n", __func__, i, word.c_str());
@@ -764,6 +773,9 @@ int main(int argc, char ** argv) {
     gpt_params params;
     params.model = "models/llama-7B/ggml-model.bin";
 
+    sentencepiece::SentencePieceProcessor sp;
+    sp.Load("./models/tokenizer.model");
+
     if (gpt_params_parse(argc, argv, params) == false) {
         return 1;
     }
@@ -791,7 +803,7 @@ int main(int argc, char ** argv) {
     {
         const int64_t t_start_us = ggml_time_us();
 
-        if (!llama_model_load(params.model, model, vocab, 512)) {  // TODO: set context from user input ??
+        if (!llama_model_load(params.model, model, sp, vocab, 512)) {  // TODO: set context from user input ??
             fprintf(stderr, "%s: failed to load model from '%s'\n", __func__, params.model.c_str());
             return 1;
         }

utils.cpp

@@ -4,6 +4,7 @@
 #include <cstring>
 #include <fstream>
 #include <regex>
+#include <sentencepiece_processor.h>
 #include <iostream>
 #include <iterator>
 #include <string>
@@ -281,33 +282,30 @@ std::vector<gpt_vocab::id> llama_tokenize(const gpt_vocab & vocab, const std::st
 
     std::vector<gpt_vocab::id> res;
 
-    if (bos) {
-        res.push_back(1); // TODO: replace with vocab.bos
+    // if (bos) {
+    //     res.push_back(1); // TODO: replace with vocab.bos
+    // }
+
+    sentencepiece::SentencePieceProcessor sp;
+    sp.Load("./models/tokenizer.model");
+
+    std::vector<std::string> pieces;
+    return sp.EncodeAsIds(text);
+/*
+    for (const auto & piece : pieces) {
+        printf("piece: %s\n", piece.c_str());
+        if (vocab.token_to_id.count(piece) > 0) {
+            res.push_back(vocab.token_to_id.at(piece));
+        } else {
+            // handle unknown token
+        }
     }
 
-     //find the longest token that matches the text
-    int pos = 0;
-    while (true) {
-        int l = 0;
-        int t = 0;
-        for (const auto & kv : vocab.id_to_token) {
-            if (kv.second.size() < l) continue;
-            if (kv.second.size() > text.size() - pos) continue;
-            if (text.substr(pos, kv.second.size()) == kv.second) {
-                l = kv.second.size();
-                t = kv.first;
-            }
-        }
-
-        if (l == 0) {
-            break;
-        }
-
-        res.push_back(t);
-        pos += l;
+    for (const auto& id : res) {
+        printf("%d\n", id);
     }
 
-    return res;
+    return res;*/
 }
 
 bool gpt_vocab_init(const std::string & fname, gpt_vocab & vocab) {