llama : more tokenizer fixes (#2810)

* tests : write a Python tokenizer test (wip)

* llama : prefix input text for tokenization with whitespace

* llama : distinguish pieces from decoded text + fix detokenization

* common : add comments

* examples : no longer manually add leading space when tokenizing

* tests : use Python to generate tokenizer tests for C++

* tests : add option to tokenize text files

ggml-ci

* tests : add test-tokenizer-1.py

* llama.cpp : fix LF token

* hellaswag : move the concat space for clarity

* tests : add falcon tests (py + cpp, currently do not pass Unicode)

ggml-ci

* common : temporary separate llama_detokenize calls for SPM and BPE

---------

Co-authored-by: klosax <[email protected]>

Author: ggerganov

common/common.cpp

@@ -733,16 +733,49 @@ std::vector<llama_token> llama_tokenize(
     return result;
 }
 
-std::string llama_token_to_str(const struct llama_context * ctx, llama_token token) {
+std::string llama_token_to_piece(const struct llama_context * ctx, llama_token token) {
     std::vector<char> result(8, 0);
-    const int n_tokens = llama_token_to_str(ctx, token, result.data(), result.size());
+    const int n_tokens = llama_token_to_piece(ctx, token, result.data(), result.size());
     if (n_tokens < 0) {
         result.resize(-n_tokens);
-        int check = llama_token_to_str(ctx, token, result.data(), result.size());
+        int check = llama_token_to_piece(ctx, token, result.data(), result.size());
         GGML_ASSERT(check == -n_tokens);
     } else {
         result.resize(n_tokens);
     }
 
     return std::string(result.data(), result.size());
 }
+
+std::string llama_detokenize_spm(llama_context * ctx, const std::vector<llama_token> & tokens) {
+    const llama_token bos_id = llama_token_bos(ctx);
+
+    std::string piece;
+    std::string result;
+
+    for (size_t i = 0; i < tokens.size(); ++i) {
+        piece = llama_token_to_piece(ctx, tokens[i]);
+
+        // remove the leading space of the first non-BOS token
+        if (((tokens[0] == bos_id && i == 1) || (tokens[0] != bos_id && i == 0)) && piece[0] == ' ') {
+            piece = piece.substr(1);
+        }
+
+        result += piece;
+    }
+
+    return result;
+}
+
+std::string llama_detokenize_bpe(llama_context * ctx, const std::vector<llama_token> & tokens) {
+    std::string piece;
+    std::string result;
+
+    for (size_t i = 0; i < tokens.size(); ++i) {
+        piece = llama_token_to_piece(ctx, tokens[i]);
+
+        result += piece;
+    }
+
+    return result;
+}

common/common.h

@@ -116,11 +116,31 @@ struct llama_context_params llama_context_params_from_gpt_params(const gpt_param
 // Vocab utils
 //
 
+// tokenizes a string into a vector of tokens
+// should work similar to Python's `tokenizer.encode`
 std::vector<llama_token> llama_tokenize(
         struct llama_context * ctx,
            const std::string & text,
                         bool   add_bos);
 
-std::string llama_token_to_str(
+// tokenizes a token into a piece
+// should work similar to Python's `tokenizer.id_to_piece`
+std::string llama_token_to_piece(
         const struct llama_context * ctx,
                        llama_token   token);
+
+// TODO: these should be moved in llama.h C-style API under single `llama_detokenize` function
+//       that takes into account the tokenizer type and decides how to handle the leading space
+//
+// detokenizes a vector of tokens into a string
+// should work similar to Python's `tokenizer.decode`
+// removes the leading space from the first non-BOS token
+std::string llama_detokenize_spm(
+                         llama_context * ctx,
+        const std::vector<llama_token> & tokens);
+
+// detokenizes a vector of tokens into a string
+// should work similar to Python's `tokenizer.decode`
+std::string llama_detokenize_bpe(
+                         llama_context * ctx,
+        const std::vector<llama_token> & tokens);

examples/beam_search/beam_search.cpp

@@ -35,7 +35,7 @@ struct ostream_beam_view {
 std::ostream& operator<<(std::ostream& os, const ostream_beam_view & obv) {
     os << "p(" << obv.beam_view.p << ") eob(" << std::boolalpha << obv.beam_view.eob << ") tokens(";
     for (size_t i = 0 ; i < obv.beam_view.n_tokens ; ++i) {
-        os << llama_token_to_str(obv.ctx, obv.beam_view.tokens[i]);
+        os << llama_token_to_piece(obv.ctx, obv.beam_view.tokens[i]);
     }
     return os << ')';
 }
@@ -156,7 +156,7 @@ int main(int argc, char ** argv)
 
     for( auto id : tokens_list )
     {
-        std::cout << llama_token_to_str(ctx, id);
+        std::cout << llama_token_to_piece(ctx, id);
     }
     std::cout << std::flush;
 
@@ -175,7 +175,7 @@ int main(int argc, char ** argv)
 
     std::cout << "\n\n";
     for (llama_token const token_id : callback_data.response) {
-        std::cout << llama_token_to_str(ctx,token_id);
+        std::cout << llama_token_to_piece(ctx,token_id);
     }
     std::cout << std::endl;
 

examples/embd-input/embd-input-lib.cpp

@@ -214,7 +214,7 @@ const char * sampling(struct MyModel * mymodel) {
     if (id == llama_token_eos(ctx)) {
         ret = "</s>";
     } else {
-        ret = llama_token_to_str(ctx, id);
+        ret = llama_token_to_piece(ctx, id);
     }
     eval_id(mymodel, id);
     return ret.c_str();

examples/embedding/embedding.cpp

@@ -56,9 +56,6 @@ int main(int argc, char ** argv) {
 
     int n_past = 0;
 
-    // Add a space in front of the first character to match OG llama tokenizer behavior
-    params.prompt.insert(0, 1, ' ');
-
     // tokenize the prompt
     auto embd_inp = ::llama_tokenize(ctx, params.prompt, true);
 
@@ -67,7 +64,7 @@ int main(int argc, char ** argv) {
         fprintf(stderr, "%s: prompt: '%s'\n", __func__, params.prompt.c_str());
         fprintf(stderr, "%s: number of tokens in prompt = %zu\n", __func__, embd_inp.size());
         for (int i = 0; i < (int) embd_inp.size(); i++) {
-            fprintf(stderr, "%6d -> '%s'\n", embd_inp[i], llama_token_to_str(ctx, embd_inp[i]).c_str());
+            fprintf(stderr, "%6d -> '%s'\n", embd_inp[i], llama_token_to_piece(ctx, embd_inp[i]).c_str());
         }
         fprintf(stderr, "\n");
     }

examples/main/main.cpp

@@ -195,11 +195,6 @@ int main(int argc, char ** argv) {
     // tokenize the prompt
     std::vector<llama_token> embd_inp;
 
-    if (llama_vocab_type(ctx) == LLAMA_VOCAB_TYPE_SPM) {
-        // Add a space in front of the first character to match OG llama tokenizer behavior
-        params.prompt.insert(0, 1, ' ');
-    }
-
     if (params.interactive_first || params.instruct || !params.prompt.empty() || session_tokens.empty()) {
         embd_inp = ::llama_tokenize(ctx, params.prompt, add_bos);
     } else {
@@ -216,7 +211,6 @@ int main(int argc, char ** argv) {
     int guidance_offset = 0;
     int original_prompt_len = 0;
     if (ctx_guidance) {
-        params.cfg_negative_prompt.insert(0, 1, ' ');
         guidance_inp = ::llama_tokenize(ctx_guidance, params.cfg_negative_prompt, add_bos);
 
         std::vector<llama_token> original_inp = ::llama_tokenize(ctx, params.prompt, add_bos);
@@ -285,22 +279,22 @@ int main(int argc, char ** argv) {
         fprintf(stderr, "%s: prompt: '%s'\n", __func__, params.prompt.c_str());
         fprintf(stderr, "%s: number of tokens in prompt = %zu\n", __func__, embd_inp.size());
         for (int i = 0; i < (int) embd_inp.size(); i++) {
-            fprintf(stderr, "%6d -> '%s'\n", embd_inp[i], llama_token_to_str(ctx, embd_inp[i]).c_str());
+            fprintf(stderr, "%6d -> '%s'\n", embd_inp[i], llama_token_to_piece(ctx, embd_inp[i]).c_str());
         }
 
         if (ctx_guidance) {
             fprintf(stderr, "\n");
             fprintf(stderr, "%s: negative prompt: '%s'\n", __func__, params.cfg_negative_prompt.c_str());
             fprintf(stderr, "%s: number of tokens in negative prompt = %zu\n", __func__, guidance_inp.size());
             for (int i = 0; i < (int) guidance_inp.size(); i++) {
-                fprintf(stderr, "%6d -> '%s'\n", guidance_inp[i], llama_token_to_str(ctx, guidance_inp[i]).c_str());
+                fprintf(stderr, "%6d -> '%s'\n", guidance_inp[i], llama_token_to_piece(ctx, guidance_inp[i]).c_str());
             }
         }
 
         if (params.n_keep > 0) {
         fprintf(stderr, "%s: static prompt based on n_keep: '", __func__);
             for (int i = 0; i < params.n_keep; i++) {
-                fprintf(stderr, "%s", llama_token_to_str(ctx, embd_inp[i]).c_str());
+                fprintf(stderr, "%s", llama_token_to_piece(ctx, embd_inp[i]).c_str());
             }
             fprintf(stderr, "'\n");
         }
@@ -456,7 +450,7 @@ int main(int argc, char ** argv) {
                 //printf("\n---\n");
                 //printf("resetting: '");
                 //for (int i = 0; i < (int) embd.size(); i++) {
-                //    printf("%s", llama_token_to_str(ctx, embd[i]));
+                //    printf("%s", llama_token_to_piece(ctx, embd[i]));
                 //}
                 //printf("'\n");
                 //printf("\n---\n");
@@ -509,7 +503,7 @@ int main(int argc, char ** argv) {
                     input_size = embd_guidance.size();
                     //fprintf(stderr, "\n---------------------\n");
                     //for (int i = 0; i < (int) embd_guidance.size(); i++) {
-                        //fprintf(stderr, "%s", llama_token_to_str(ctx, embd_guidance[i]));
+                        //fprintf(stderr, "%s", llama_token_to_piece(ctx, embd_guidance[i]));
                     //}
                     //fprintf(stderr, "\n---------------------\n");
                 } else {
@@ -673,7 +667,7 @@ int main(int argc, char ** argv) {
         // display text
         if (input_echo) {
             for (auto id : embd) {
-                printf("%s", llama_token_to_str(ctx, id).c_str());
+                printf("%s", llama_token_to_piece(ctx, id).c_str());
             }
             fflush(stdout);
         }
@@ -689,7 +683,7 @@ int main(int argc, char ** argv) {
             if (params.antiprompt.size()) {
                 std::string last_output;
                 for (auto id : last_n_tokens) {
-                    last_output += llama_token_to_str(ctx, id);
+                    last_output += llama_token_to_piece(ctx, id);
                 }
 
                 is_antiprompt = false;

examples/perplexity/perplexity.cpp

@@ -392,7 +392,7 @@ void hellaswag_score(llama_context * ctx, const gpt_params & params) {
         hs_data[i].context = prompt_lines[idx*6];
         hs_data[i].gold_ending_idx = std::stoi( prompt_lines[idx*6+1] );
         for (size_t j=0; j < 4; j++) {
-            hs_data[i].ending[j] = " " + prompt_lines[idx*6+2+j];
+            hs_data[i].ending[j] = prompt_lines[idx*6+2+j];
         }
 
         // Delete the selected random example from the prompt
@@ -417,7 +417,7 @@ void hellaswag_score(llama_context * ctx, const gpt_params & params) {
         size_t context_size = context_embd.size();
 
         for (int i = 0; i < 4; ++i) {
-            ending_tokens[i] = ::llama_tokenize(ctx, hs_data[task_idx].context + hs_data[task_idx].ending[i], add_bos);
+            ending_tokens[i] = ::llama_tokenize(ctx, hs_data[task_idx].context + " " + hs_data[task_idx].ending[i], add_bos);
             for (int k = 0; k < int(context_size); ++k) {
                 if (ending_tokens[i][k] != context_embd[k]) {
                     fprintf(stderr, "Oops: ending %d of task %d differs from context at position %d\n",i,int(task_idx),k);

examples/save-load-state/save-load-state.cpp

@@ -87,7 +87,7 @@ int main(int argc, char ** argv) {
         }
         llama_token_data_array candidates_p = { candidates.data(), candidates.size(), false };
         auto next_token = llama_sample_token(ctx, &candidates_p);
-        auto next_token_str = llama_token_to_str(ctx, next_token);
+        auto next_token_str = llama_token_to_piece(ctx, next_token);
         last_n_tokens_data.push_back(next_token);
 
         printf("%s", next_token_str.c_str());
@@ -147,7 +147,7 @@ int main(int argc, char ** argv) {
         }
         llama_token_data_array candidates_p = { candidates.data(), candidates.size(), false };
         auto next_token = llama_sample_token(ctx2, &candidates_p);
-        auto next_token_str = llama_token_to_str(ctx2, next_token);
+        auto next_token_str = llama_token_to_piece(ctx2, next_token);
         last_n_tokens_data.push_back(next_token);
 
         printf("%s", next_token_str.c_str());

examples/server/server.cpp

@@ -94,7 +94,7 @@ static std::string tokens_to_str(llama_context *ctx, Iter begin, Iter end)
     std::string ret;
     for (; begin != end; ++begin)
     {
-        ret += llama_token_to_str(ctx, *begin);
+        ret += llama_token_to_piece(ctx, *begin);
     }
     return ret;
 }
@@ -123,7 +123,7 @@ static void server_log(const char *level, const char *function, int line,
 // format incomplete utf-8 multibyte character for output
 static std::string tokens_to_output_formatted_string(const llama_context *ctx, const llama_token token)
 {
-    std::string out = token == -1 ? "" : llama_token_to_str(ctx, token);
+    std::string out = token == -1 ? "" : llama_token_to_piece(ctx, token);
     // if the size is 1 and first bit is 1, meaning it's a partial character
     //   (size > 1 meaning it's already a known token)
     if (out.size() == 1 && (out[0] & 0x80) == 0x80)
@@ -286,7 +286,6 @@ struct llama_server_context
                     std::vector<llama_token> p;
                     if (first)
                     {
-                        s.insert(0, 1, ' '); // add a space if it's the first
                         p = ::llama_tokenize(ctx, s, add_bos);
                         first = false;
                     }
@@ -309,7 +308,6 @@ struct llama_server_context
         else
         {
             auto s = json_prompt.template get<std::string>();
-            s.insert(0, 1, ' '); // always add a first space
             prompt_tokens = ::llama_tokenize(ctx, s, add_bos);
         }
 
@@ -566,7 +564,7 @@ struct llama_server_context
 
         if (!embd.empty() && embd.back() == llama_token_eos(ctx))
         {
-            // stopping_word = llama_token_to_str(ctx, embd.back());
+            // stopping_word = llama_token_to_piece(ctx, embd.back());
             has_next_token = false;
             stopped_eos = true;
             LOG_VERBOSE("eos token found", {});
@@ -613,7 +611,7 @@ struct llama_server_context
     {
         const completion_token_output token_with_probs = nextToken();
 
-        const std::string token_text = token_with_probs.tok == -1 ? "" : llama_token_to_str(ctx, token_with_probs.tok);
+        const std::string token_text = token_with_probs.tok == -1 ? "" : llama_token_to_piece(ctx, token_with_probs.tok);
         generated_text += token_text;
 
         if (params.n_probs > 0)
@@ -1254,7 +1252,7 @@ void beam_search_callback(void * callback_data, llama_beams_state beams_state) {
 
 struct token_translator {
     llama_context * ctx;
-    std::string operator()(llama_token tok) const { return llama_token_to_str(ctx, tok); }
+    std::string operator()(llama_token tok) const { return llama_token_to_piece(ctx, tok); }
     std::string operator()(completion_token_output cto) const { return (*this)(cto.tok); }
 };
 
@@ -1364,7 +1362,7 @@ int main(int argc, char **argv)
 
                 while (llama.has_next_token) {
                     const completion_token_output token_with_probs = llama.doCompletion();
-                    const std::string token_text = token_with_probs.tok == -1 ? "" : llama_token_to_str(llama.ctx, token_with_probs.tok);
+                    const std::string token_text = token_with_probs.tok == -1 ? "" : llama_token_to_piece(llama.ctx, token_with_probs.tok);
 
                     stop_pos = llama.findStoppingStrings(llama.generated_text,
                         token_text.size(), STOP_FULL);
@@ -1395,7 +1393,7 @@ int main(int argc, char **argv)
                     if (token_with_probs.tok == -1 || llama.multibyte_pending > 0) {
                         continue;
                     }
-                    const std::string token_text = llama_token_to_str(llama.ctx, token_with_probs.tok);
+                    const std::string token_text = llama_token_to_piece(llama.ctx, token_with_probs.tok);
 
                     size_t pos = std::min(sent_count, llama.generated_text.size());
 

examples/simple/simple.cpp

@@ -63,7 +63,7 @@ int main(int argc, char ** argv) {
     fprintf(stderr, "\n\n");
 
     for (auto id : tokens_list) {
-        fprintf(stderr, "%s", llama_token_to_str(ctx, id).c_str());
+        fprintf(stderr, "%s", llama_token_to_piece(ctx, id).c_str());
     }
 
     fflush(stderr);
@@ -112,7 +112,7 @@ int main(int argc, char ** argv) {
         }
 
         // print the new token :
-        printf("%s", llama_token_to_str(ctx, new_token_id).c_str());
+        printf("%s", llama_token_to_piece(ctx, new_token_id).c_str());
         fflush(stdout);
 
         // push this new token for next evaluation

examples/train-text-from-scratch/train-text-from-scratch.cpp

@@ -1964,7 +1964,7 @@ void print_matrix(struct ggml_tensor * probs) {
 
 
 void print_token(struct llama_context * ctx, llama_token token) {
-    printf("%s", llama_token_to_str(ctx, token).c_str());
+    printf("%s", llama_token_to_piece(ctx, token).c_str());
 }
 
 void print_tokens(struct llama_context* ctx, struct ggml_tensor * tokens) {
@@ -2202,7 +2202,7 @@ int tokenize_file(struct llama_context * lctx, const char * filename, std::vecto
         const char * in  = buf.data();
         const char * end = buf.data() + buf.size();
         for (int i = 0; i < (int) out.size(); ++i) {
-            std::string s = llama_token_to_str(lctx, out[i]);
+            std::string s = llama_token_to_piece(lctx, out[i]);
             int len = s.length();
             if (in >= end) {
                 printf("%s: unexpected end of original text.\n", __func__);