Implement non-greedy tokenizer that tries to maximize token lengths (#242)

* Implement non-greedy tokenizer that tries to maximize token lengths

* Insert single space in front of the prompt

- this is to match original llama tokenizer behavior

---------

Co-authored-by: Jakub Horak <redacted>

diff --git a/main.cpp b/main.cpp
index ca0fca8b364559f4d29e4cf51c82c07d9e4ec375..39c5d7b76b903cc1cb0cdfc70e06a485a906bebd 100644 (file)
--- a/main.cpp
+++ b/main.cpp
@@ -845,6 +845,8 @@ int main(int argc, char ** argv) {
 
     std::vector<float> logits;
 
+    // Add a space in front of the first character to match OG llama tokenizer behavior
+    params.prompt.insert(0, 1, ' ');
     // tokenize the prompt
     std::vector<gpt_vocab::id> embd_inp = ::llama_tokenize(vocab, params.prompt, true);
 

diff --git a/utils.cpp b/utils.cpp
index 9e50487efe7a6d107a550acfc822381906e32bd0..22ef593775c8c11a7975e1ef83111d976b2330f4 100644 (file)
--- a/utils.cpp
+++ b/utils.cpp
@@ -287,41 +287,57 @@ std::vector<gpt_vocab::id> gpt_tokenize(const gpt_vocab & vocab, const std::stri
     return tokens;
 }
 
+// TODO: Calculate this constant from the vocabulary
+#define MAX_TOKEN_LEN 18
+// SentencePiece implementation after https://guillaume-be.github.io/2020-05-30/sentence_piece
 std::vector<gpt_vocab::id> llama_tokenize(const gpt_vocab & vocab, const std::string & text, bool bos) {
-    //auto res = gpt_tokenize(vocab, text);
-
-    //if (bos) {
-    //    res.insert(res.begin(), 1); // TODO: replace with vocab.bos
-    //}
-
     std::vector<gpt_vocab::id> res;
-
-    if (bos) {
-        res.push_back(1); // TODO: replace with vocab.bos
-    }
-
-     //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;
+    std::vector<int> score;
+    std::vector<gpt_vocab::id> prev;
+    int len = text.length();
+
+    score.resize(len + 1);
+    prev.resize(len + 1);
+
+    // Forward pass
+    for (int i = 0; i < len; i++) {
+        int max_len = std::min(len - i, MAX_TOKEN_LEN);
+        for (int sub_len = 1; sub_len <= len - i; sub_len++) {
+            auto sub = text.substr(i, sub_len);
+            auto token = vocab.token_to_id.find(sub);
+            if (token != vocab.token_to_id.end()) {
+                int token_score = sub.length() * sub.length();
+                int local_score = score[i] + token_score;
+                int next = i + sub_len;
+                if (score[next] < local_score) {
+                    score[next] = local_score;
+                    prev[next] = (*token).second;
+                }
             }
         }
+    }
 
-        if (l == 0) {
-            break;
+    // Backward pass
+    int i = len;
+    while (i > 0) {
+        gpt_vocab::id token_id = prev[i];
+        if (token_id == 0) {
+           // TODO: Return error or something more meaningful
+            printf("failed to tokenize string!\n");
+           break;
         }
+        res.push_back(token_id);
+        auto token = (*vocab.id_to_token.find(token_id)).second;
+        i -= token.length();
+    }
 
-        res.push_back(t);
-        pos += l;
+    if (bos) {
+        res.push_back(1); // TODO: replace with vocab.bos
     }
 
+    // Pieces are in reverse order so correct that
+    std::reverse(res.begin(), res.end());
+
     return res;
 }