mirror of
https://github.com/LostRuins/koboldcpp.git
synced 2025-09-15 11:29:43 +00:00
Merge branch 'master' into concedo_experimental
# Conflicts: # README.md
This commit is contained in:
commit
700951dbd4
16 changed files with 470 additions and 143 deletions
309
llama.cpp
309
llama.cpp
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@ -76,6 +76,7 @@
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#include <thread>
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#include <unordered_map>
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#include <set>
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#include <forward_list>
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#if defined(_MSC_VER)
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#pragma warning(disable: 4244 4267) // possible loss of data
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@ -1188,6 +1189,8 @@ struct llama_vocab {
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std::unordered_map<token, id> token_to_id;
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std::vector<token_data> id_to_token;
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std::unordered_map<token, id> special_tokens_cache;
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std::map<std::pair<std::string, std::string>, int> bpe_ranks;
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// default LLaMA special tokens
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@ -2131,7 +2134,7 @@ static void llm_load_hparams(
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}
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// TODO: This should probably be in llama.h
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static std::vector<llama_vocab::id> llama_tokenize_internal(const llama_vocab & vocab, std::string raw_text, bool bos);
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static std::vector<llama_vocab::id> llama_tokenize_internal(const llama_vocab & vocab, std::string raw_text, bool bos, bool special = false);
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static llama_token llama_byte_to_token(const llama_vocab & vocab, uint8_t ch);
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static void llm_load_vocab(
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@ -2247,6 +2250,101 @@ static void llm_load_vocab(
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GGUF_GET_KEY(ctx, vocab.special_unk_id, gguf_get_val_u32, GGUF_TYPE_UINT32, false, kv(LLM_KV_TOKENIZER_UNK_ID));
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GGUF_GET_KEY(ctx, vocab.special_sep_id, gguf_get_val_u32, GGUF_TYPE_UINT32, false, kv(LLM_KV_TOKENIZER_SEP_ID));
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GGUF_GET_KEY(ctx, vocab.special_pad_id, gguf_get_val_u32, GGUF_TYPE_UINT32, false, kv(LLM_KV_TOKENIZER_PAD_ID));
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// build special tokens cache
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{
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// TODO: It is unclear (to me) at this point, whether special tokes are guaranteed to be of a deterministic type,
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// and will always be correctly labeled in 'added_tokens.json' etc.
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// The assumption is, since special tokens aren't meant to be exposed to end user, they are designed
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// to be unmatchable by the tokenizer, therefore tokens from the vocab, which are unmatchable by the tokenizer
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// are special tokens.
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// From testing, this appears to corelate 1:1 with special tokens.
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//
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// Counting special tokens and verifying in only one direction
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// is sufficient to detect difference in those two sets.
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//
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uint32_t special_tokens_count_by_type = 0;
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uint32_t special_tokens_count_from_verification = 0;
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bool special_tokens_definition_mismatch = false;
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for (const auto & t : vocab.token_to_id) {
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const auto & token = t.first;
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const auto & id = t.second;
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// Count all non-normal tokens in the vocab while iterating
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if (vocab.id_to_token[id].type != LLAMA_TOKEN_TYPE_NORMAL) {
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special_tokens_count_by_type++;
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}
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// Skip single character tokens
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if (token.length() > 1) {
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bool is_tokenizable = false;
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// Split token string representation in two, in all possible ways
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// and check if both halves can be matched to a valid token
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for (unsigned i = 1; i < token.length();) {
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const auto left = token.substr(0, i);
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const auto right = token.substr(i);
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// check if we didnt partition in the middle of a utf sequence
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auto utf = utf8_len(left.at(left.length() - 1));
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if (utf == 1) {
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if (vocab.token_to_id.find(left) != vocab.token_to_id.end() &&
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vocab.token_to_id.find(right) != vocab.token_to_id.end() ) {
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is_tokenizable = true;
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break;
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}
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i++;
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} else {
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// skip over the rest of multibyte utf sequence
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i += utf - 1;
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}
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}
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if (!is_tokenizable) {
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// Some tokens are multibyte, but they are utf sequences with equivalent text length of 1
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// it's faster to re-filter them here, since there are way less candidates now
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// Calculate a total "utf" length of a token string representation
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size_t utf8_str_len = 0;
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for (unsigned i = 0; i < token.length();) {
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utf8_str_len++;
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i += utf8_len(token.at(i));
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}
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// And skip the ones which are one character
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if (utf8_str_len > 1) {
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// At this point what we have left are special tokens only
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vocab.special_tokens_cache[token] = id;
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// Count manually found special tokens
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special_tokens_count_from_verification++;
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// If this manually found special token is not marked as such, flag a mismatch
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if (vocab.id_to_token[id].type == LLAMA_TOKEN_TYPE_NORMAL) {
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special_tokens_definition_mismatch = true;
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}
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}
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}
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}
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}
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if (special_tokens_definition_mismatch || special_tokens_count_from_verification != special_tokens_count_by_type) {
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LLAMA_LOG_WARN("%s: mismatch in special tokens definition ( %u/%zu vs %u/%zu ).\n",
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__func__,
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special_tokens_count_from_verification, vocab.id_to_token.size(),
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special_tokens_count_by_type, vocab.id_to_token.size()
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);
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} else {
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LLAMA_LOG_INFO("%s: special tokens definition check successful ( %u/%zu ).\n",
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__func__,
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special_tokens_count_from_verification, vocab.id_to_token.size()
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);
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}
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}
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}
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static void llm_load_print_meta(llama_model_loader & ml, llama_model & model) {
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@ -5811,6 +5909,13 @@ static int llama_decode_internal(
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ggml_allocr_alloc_graph(lctx.alloc, gf);
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struct ggml_tensor * res = gf->nodes[gf->n_nodes - 1];
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struct ggml_tensor * embeddings = gf->nodes[gf->n_nodes - 2];
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GGML_ASSERT(strcmp(res->name, "result_output") == 0);
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GGML_ASSERT(strcmp(embeddings->name, "result_norm") == 0);
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#ifdef GGML_USE_CUBLAS
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for (int i = 0; i < gf->n_leafs; i++) {
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ggml_tensor * node = gf->leafs[i];
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@ -5828,6 +5933,12 @@ static int llama_decode_internal(
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}
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ggml_cuda_set_mul_mat_q(cparams.mul_mat_q);
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// HACK: ggml-alloc may change the tensor backend when reusing a parent, so force output to be on the CPU here if needed
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if (!lctx.embedding.empty()) {
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embeddings->backend = GGML_BACKEND_CPU;
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}
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res->backend = GGML_BACKEND_CPU;
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#endif
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// LLAMA_LOG_INFO("graph build time: %.3f ms (%d nodes, %d leafs)\n", (ggml_time_us() - t_start_us)/1000.0, gf->n_nodes, gf->n_leafs);
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@ -5852,12 +5963,6 @@ static int llama_decode_internal(
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n_threads = 1;
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}
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struct ggml_tensor * res = gf->nodes[gf->n_nodes - 1];
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struct ggml_tensor * embeddings = gf->nodes[gf->n_nodes - 2];
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GGML_ASSERT(strcmp(res->name, "result_output") == 0);
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GGML_ASSERT(strcmp(embeddings->name, "result_norm") == 0);
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#if GGML_USE_MPI
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const int64_t n_layer = hparams.n_layer;
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ggml_mpi_graph_compute_pre(lctx.ctx_mpi, gf, n_layer);
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@ -6470,7 +6575,137 @@ private:
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llm_bigram_bpe::queue work_queue;
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};
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static std::vector<llama_vocab::id> llama_tokenize_internal(const llama_vocab & vocab, std::string raw_text, bool bos) {
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typedef enum FRAGMENT_BUFFER_VARIANT_TYPE{
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FRAGMENT_BUFFER_VARIANT_TYPE_TOKEN,
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FRAGMENT_BUFFER_VARIANT_TYPE_RAW_TEXT
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} FRAGMENT_BUFFER_VARIANT_TYPE;
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struct fragment_buffer_variant{
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fragment_buffer_variant(llama_vocab::id _token)
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:
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type(FRAGMENT_BUFFER_VARIANT_TYPE_TOKEN),
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token(_token),
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raw_text(_dummy),
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offset(0),
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length(0){}
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fragment_buffer_variant(const std::string & _raw_text, int64_t _offset, int64_t _length)
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:
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type(FRAGMENT_BUFFER_VARIANT_TYPE_RAW_TEXT),
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token((llama_vocab::id)-1),
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raw_text(_raw_text),
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offset(_offset),
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length(_length){
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GGML_ASSERT( _offset >= 0 );
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GGML_ASSERT( _length >= 1 );
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GGML_ASSERT( offset + length <= raw_text.length() );
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}
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const FRAGMENT_BUFFER_VARIANT_TYPE type;
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const llama_vocab::id token;
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const std::string _dummy;
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const std::string & raw_text;
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const uint64_t offset;
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const uint64_t length;
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};
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// #define PRETOKENIZERDEBUG
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static void tokenizer_st_partition(const llama_vocab & vocab, std::forward_list<fragment_buffer_variant> & buffer)
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{
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// for each special token
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for (const auto & st: vocab.special_tokens_cache) {
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const auto & special_token = st.first;
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const auto & special_id = st.second;
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// for each text fragment
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std::forward_list<fragment_buffer_variant>::iterator it = buffer.begin();
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while (it != buffer.end()) {
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auto & fragment = (*it);
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// if a fragment is text ( not yet processed )
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if (fragment.type == FRAGMENT_BUFFER_VARIANT_TYPE_RAW_TEXT) {
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auto * raw_text = &(fragment.raw_text);
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auto raw_text_base_offset = fragment.offset;
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auto raw_text_base_length = fragment.length;
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// loop over the text
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while (true) {
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// find the first occurence of a given special token in this fragment
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// passing offset argument only limit the "search area" but match coordinates
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// are still relative to the source full raw_text
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auto match = raw_text->find(special_token, raw_text_base_offset);
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// no occurences found, stop processing this fragment for a given special token
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if (match == std::string::npos) break;
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// check if match is within bounds of offset <-> length
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if (match + special_token.length() > raw_text_base_offset + raw_text_base_length) break;
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#ifdef PRETOKENIZERDEBUG
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fprintf(stderr, "FF: (%ld %ld %ld) '%s'\n", raw_text->length(), raw_text_base_offset, raw_text_base_length, raw_text->substr(raw_text_base_offset, raw_text_base_length).c_str());
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#endif
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auto source = std::distance(buffer.begin(), it);
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// if match is further than base offset
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// then we have some text to the left of it
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if (match > raw_text_base_offset) {
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// left
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const int64_t left_reminder_offset = raw_text_base_offset + 0;
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const int64_t left_reminder_length = match - raw_text_base_offset;
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buffer.emplace_after(it, (*raw_text), left_reminder_offset, left_reminder_length);
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#ifdef PRETOKENIZERDEBUG
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fprintf(stderr, "FL: (%ld %ld) '%s'\n", left_reminder_offset, left_reminder_length, raw_text->substr(left_reminder_offset, left_reminder_length).c_str());
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#endif
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it++;
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}
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// special token
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buffer.emplace_after(it, special_id);
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it++;
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// right
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if (match + special_token.length() < raw_text_base_offset + raw_text_base_length) {
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const int64_t right_reminder_offset = match + special_token.length();
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const int64_t right_reminder_length = raw_text_base_length - ((match - raw_text_base_offset) + special_token.length());
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buffer.emplace_after(it, (*raw_text), right_reminder_offset, right_reminder_length);
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#ifdef PRETOKENIZERDEBUG
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fprintf(stderr, "FR: (%ld %ld) '%s'\n", right_reminder_offset, right_reminder_length, raw_text->substr(right_reminder_offset, right_reminder_length).c_str());
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#endif
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it++;
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if (source == 0) {
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buffer.erase_after(buffer.before_begin());
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} else {
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buffer.erase_after(std::next(buffer.begin(), (source-1)));
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}
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// repeat for the right side
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raw_text_base_offset = right_reminder_offset;
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raw_text_base_length = right_reminder_length;
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#ifdef PRETOKENIZERDEBUG
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fprintf(stderr, "RR: (%ld %ld) '%s'\n", raw_text_base_offset, raw_text_base_length, raw_text->substr(raw_text_base_offset, raw_text_base_length).c_str());
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#endif
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} else {
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if (source == 0) {
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buffer.erase_after(buffer.before_begin());
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} else {
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buffer.erase_after(std::next(buffer.begin(), (source-1)));
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}
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break;
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}
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}
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}
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it++;
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}
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}
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}
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static std::vector<llama_vocab::id> llama_tokenize_internal(const llama_vocab & vocab, std::string raw_text, bool bos, bool special) {
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std::vector<llama_vocab::id> output;
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// OG tokenizer behavior:
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@ -6486,20 +6721,58 @@ static std::vector<llama_vocab::id> llama_tokenize_internal(const llama_vocab &
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return output;
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}
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std::forward_list<fragment_buffer_variant> fragment_buffer;
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fragment_buffer.emplace_front( raw_text, 0, raw_text.length() );
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if (special) tokenizer_st_partition( vocab, fragment_buffer );
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switch (vocab.type) {
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case LLAMA_VOCAB_TYPE_SPM:
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{
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// without adding this leading whitespace, we do not get the same results as the original tokenizer
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raw_text = " " + raw_text;
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for (const auto & fragment: fragment_buffer)
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{
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if (fragment.type == FRAGMENT_BUFFER_VARIANT_TYPE_RAW_TEXT)
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{
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// without adding this leading whitespace, we do not get the same results as the original tokenizer
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llm_tokenizer_spm tokenizer(vocab);
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llama_escape_whitespace(raw_text);
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tokenizer.tokenize(raw_text, output);
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// TODO: It's likely possible to get rid of this string copy entirely
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// by modifying llm_tokenizer_x to operate with string offsets like pre-tokenizer
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// and passing 'add space prefix' as bool argument
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//
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auto raw_text = (special ? "" : " ") + fragment.raw_text.substr(fragment.offset, fragment.length);
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#ifdef PRETOKENIZERDEBUG
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fprintf(stderr,"TT: (%ld %ld %ld) '%s'\n", raw_text.length(), fragment.offset, fragment.length, raw_text.c_str());
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#endif
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llm_tokenizer_spm tokenizer(vocab);
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llama_escape_whitespace(raw_text);
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tokenizer.tokenize(raw_text, output);
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}
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else // if (fragment.type == FRAGMENT_BUFFER_VARIANT_TYPE_TOKEN)
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{
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output.push_back(fragment.token);
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}
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}
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} break;
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case LLAMA_VOCAB_TYPE_BPE:
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{
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llm_tokenizer_bpe tokenizer(vocab);
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tokenizer.tokenize(raw_text, output);
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for (const auto & fragment: fragment_buffer)
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{
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if (fragment.type == FRAGMENT_BUFFER_VARIANT_TYPE_RAW_TEXT)
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{
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auto raw_text = fragment.raw_text.substr(fragment.offset, fragment.length);
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#ifdef PRETOKENIZERDEBUG
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fprintf(stderr,"TT: (%ld %ld %ld) '%s'\n", raw_text.length(), fragment.offset, fragment.length, raw_text.c_str());
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#endif
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llm_tokenizer_bpe tokenizer(vocab);
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tokenizer.tokenize(raw_text, output);
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}
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else // if (fragment.type == FRAGMENT_BUFFER_VARIANT_TYPE_TOKEN)
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{
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output.push_back(fragment.token);
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}
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}
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} break;
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}
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@ -9416,15 +9689,15 @@ llama_token llama_token_eot(const struct llama_context * ctx) {
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return ctx->model.vocab.special_eot_id;
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}
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int llama_tokenize(
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const struct llama_model * model,
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const char * text,
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int text_len,
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llama_token * tokens,
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int n_max_tokens,
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bool add_bos) {
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auto res = llama_tokenize_internal(model->vocab, std::string(text, text_len), add_bos);
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bool add_bos,
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bool special) {
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auto res = llama_tokenize_internal(model->vocab, std::string(text, text_len), add_bos, special);
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if (n_max_tokens < (int) res.size()) {
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// LLAMA_LOG_ERROR("%s: too many tokens\n", __func__);
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