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test-llama-archs : generate dummy test vocab (#29084)

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Assisted-by: pi:llama.cpp/DeepSeek-V4-Flash-Vision-Exp
This commit is contained in:
Georgi Gerganov
2026-09-19 11:27:46 +03:00
committed by GitHub
parent 59fc5a1ca3
commit efa28e950e
4 changed files with 85 additions and 14 deletions
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include/llama.h
+1
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@@ -77,6 +77,7 @@ extern "C" {
LLAMA_VOCAB_TYPE_UGM = 4, // T5 tokenizer based on Unigram LLAMA_VOCAB_TYPE_UGM = 4, // T5 tokenizer based on Unigram
LLAMA_VOCAB_TYPE_RWKV = 5, // RWKV tokenizer based on greedy tokenization LLAMA_VOCAB_TYPE_RWKV = 5, // RWKV tokenizer based on greedy tokenization
LLAMA_VOCAB_TYPE_PLAMO2 = 6, // PLaMo-2 tokenizer based on Aho-Corasick with dynamic programming LLAMA_VOCAB_TYPE_PLAMO2 = 6, // PLaMo-2 tokenizer based on Aho-Corasick with dynamic programming
LLAMA_VOCAB_TYPE_TEST = 7, // Dummy tokenizer for testing: rolling hash of fixed-size chunks -> tokens, tokens -> hex
}; };
enum llama_rope_type { enum llama_rope_type {
src/llama-model-saver.cpp
+13 -13
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@@ -387,13 +387,13 @@ void llama_model_saver::add_kv_from_model() {
add_kv(LLM_KV_TOKENIZER_SCORES, scores); add_kv(LLM_KV_TOKENIZER_SCORES, scores);
add_kv(LLM_KV_TOKENIZER_MERGES, vocab.get_bpe_merges()); add_kv(LLM_KV_TOKENIZER_MERGES, vocab.get_bpe_merges());
// FIXME llama_token is type i32 but when reading in a GGUF file u32 is expected, not an issue for writing though // FIXME llama_token is type i32 but when reading in a GGUF file u32 is expected, not an issue for writing though
add_kv(LLM_KV_TOKENIZER_BOS_ID, uint32_t(vocab.token_bos())); if (vocab.token_bos() != LLAMA_TOKEN_NULL) { add_kv(LLM_KV_TOKENIZER_BOS_ID, uint32_t(vocab.token_bos())); }
add_kv(LLM_KV_TOKENIZER_EOS_ID, uint32_t(vocab.token_eos())); if (vocab.token_eos() != LLAMA_TOKEN_NULL) { add_kv(LLM_KV_TOKENIZER_EOS_ID, uint32_t(vocab.token_eos())); }
add_kv(LLM_KV_TOKENIZER_EOT_ID, uint32_t(vocab.token_eot())); if (vocab.token_eot() != LLAMA_TOKEN_NULL) { add_kv(LLM_KV_TOKENIZER_EOT_ID, uint32_t(vocab.token_eot())); }
add_kv(LLM_KV_TOKENIZER_EOM_ID, uint32_t(vocab.token_eom())); if (vocab.token_eom() != LLAMA_TOKEN_NULL) { add_kv(LLM_KV_TOKENIZER_EOM_ID, uint32_t(vocab.token_eom())); }
add_kv(LLM_KV_TOKENIZER_UNK_ID, uint32_t(vocab.token_unk())); if (vocab.token_unk() != LLAMA_TOKEN_NULL) { add_kv(LLM_KV_TOKENIZER_UNK_ID, uint32_t(vocab.token_unk())); }
add_kv(LLM_KV_TOKENIZER_SEP_ID, uint32_t(vocab.token_sep())); if (vocab.token_sep() != LLAMA_TOKEN_NULL) { add_kv(LLM_KV_TOKENIZER_SEP_ID, uint32_t(vocab.token_sep())); }
add_kv(LLM_KV_TOKENIZER_PAD_ID, uint32_t(vocab.token_pad())); if (vocab.token_pad() != LLAMA_TOKEN_NULL) { add_kv(LLM_KV_TOKENIZER_PAD_ID, uint32_t(vocab.token_pad())); }
// add_kv(LLM_KV_TOKENIZER_CLS_ID, uint32_t(vocab.token_bos())); // deprecated // add_kv(LLM_KV_TOKENIZER_CLS_ID, uint32_t(vocab.token_bos())); // deprecated
// add_kv(LLM_KV_TOKENIZER_MASK_ID, ???); // add_kv(LLM_KV_TOKENIZER_MASK_ID, ???);
add_kv(LLM_KV_TOKENIZER_ADD_BOS, vocab.get_add_bos()); add_kv(LLM_KV_TOKENIZER_ADD_BOS, vocab.get_add_bos());
@@ -404,12 +404,12 @@ void llama_model_saver::add_kv_from_model() {
add_kv(LLM_KV_TOKENIZER_PRECOMPILED_CHARSMAP, vocab.get_precompiled_charsmap()); add_kv(LLM_KV_TOKENIZER_PRECOMPILED_CHARSMAP, vocab.get_precompiled_charsmap());
// add_kv(LLM_KV_TOKENIZER_HF_JSON, ???); // add_kv(LLM_KV_TOKENIZER_HF_JSON, ???);
// add_kv(LLM_KV_TOKENIZER_RWKV, ???); // add_kv(LLM_KV_TOKENIZER_RWKV, ???);
add_kv(LLM_KV_TOKENIZER_FIM_PRE_ID, uint32_t(vocab.token_fim_pre())); if (vocab.token_fim_pre() != LLAMA_TOKEN_NULL) { add_kv(LLM_KV_TOKENIZER_FIM_PRE_ID, uint32_t(vocab.token_fim_pre())); }
add_kv(LLM_KV_TOKENIZER_FIM_SUF_ID, uint32_t(vocab.token_fim_suf())); if (vocab.token_fim_suf() != LLAMA_TOKEN_NULL) { add_kv(LLM_KV_TOKENIZER_FIM_SUF_ID, uint32_t(vocab.token_fim_suf())); }
add_kv(LLM_KV_TOKENIZER_FIM_MID_ID, uint32_t(vocab.token_fim_mid())); if (vocab.token_fim_mid() != LLAMA_TOKEN_NULL) { add_kv(LLM_KV_TOKENIZER_FIM_MID_ID, uint32_t(vocab.token_fim_mid())); }
add_kv(LLM_KV_TOKENIZER_FIM_PAD_ID, uint32_t(vocab.token_fim_pad())); if (vocab.token_fim_pad() != LLAMA_TOKEN_NULL) { add_kv(LLM_KV_TOKENIZER_FIM_PAD_ID, uint32_t(vocab.token_fim_pad())); }
add_kv(LLM_KV_TOKENIZER_FIM_REP_ID, uint32_t(vocab.token_fim_rep())); if (vocab.token_fim_rep() != LLAMA_TOKEN_NULL) { add_kv(LLM_KV_TOKENIZER_FIM_REP_ID, uint32_t(vocab.token_fim_rep())); }
add_kv(LLM_KV_TOKENIZER_FIM_SEP_ID, uint32_t(vocab.token_fim_sep())); if (vocab.token_fim_sep() != LLAMA_TOKEN_NULL) { add_kv(LLM_KV_TOKENIZER_FIM_SEP_ID, uint32_t(vocab.token_fim_sep())); }
// TODO: implement LoRA support // TODO: implement LoRA support
// add_kv(LLM_KV_ADAPTER_TYPE, ???); // add_kv(LLM_KV_ADAPTER_TYPE, ???);
src/llama-vocab.cpp
+58
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@@ -2087,6 +2087,16 @@ void llama_vocab::impl::load(llama_model_loader & ml, const LLM_KV & kv) {
special_unk_id = LLAMA_TOKEN_NULL; special_unk_id = LLAMA_TOKEN_NULL;
special_sep_id = LLAMA_TOKEN_NULL; special_sep_id = LLAMA_TOKEN_NULL;
special_pad_id = LLAMA_TOKEN_NULL; special_pad_id = LLAMA_TOKEN_NULL;
} else if (tokenizer_model == "test") {
type = LLAMA_VOCAB_TYPE_TEST;
// default special tokens
special_bos_id = LLAMA_TOKEN_NULL;
special_eos_id = LLAMA_TOKEN_NULL;
special_unk_id = LLAMA_TOKEN_NULL;
special_sep_id = LLAMA_TOKEN_NULL;
special_pad_id = LLAMA_TOKEN_NULL;
special_mask_id = LLAMA_TOKEN_NULL;
} else if (tokenizer_model == "plamo2") { } else if (tokenizer_model == "plamo2") {
type = LLAMA_VOCAB_TYPE_PLAMO2; type = LLAMA_VOCAB_TYPE_PLAMO2;
@@ -3134,6 +3144,7 @@ std::string llama_vocab::impl::type_name() const{
case LLAMA_VOCAB_TYPE_UGM: return "UGM"; case LLAMA_VOCAB_TYPE_UGM: return "UGM";
case LLAMA_VOCAB_TYPE_RWKV: return "RWKV"; case LLAMA_VOCAB_TYPE_RWKV: return "RWKV";
case LLAMA_VOCAB_TYPE_PLAMO2: return "PLaMo2"; case LLAMA_VOCAB_TYPE_PLAMO2: return "PLaMo2";
case LLAMA_VOCAB_TYPE_TEST: return "TEST";
default: return "unknown"; default: return "unknown";
} }
} }
@@ -3222,6 +3233,9 @@ void llama_vocab::impl::init_tokenizer(enum llama_vocab_type type) {
case LLAMA_VOCAB_TYPE_PLAMO2: case LLAMA_VOCAB_TYPE_PLAMO2:
tokenizer = std::make_unique<llm_tokenizer_plamo2>(vocab); tokenizer = std::make_unique<llm_tokenizer_plamo2>(vocab);
break; break;
case LLAMA_VOCAB_TYPE_TEST:
tokenizer = std::make_unique<llm_tokenizer>();
break;
default: default:
GGML_ABORT("unsupported vocab type"); GGML_ABORT("unsupported vocab type");
} }
@@ -3595,6 +3609,42 @@ std::vector<llama_token> llama_vocab::impl::tokenize(
} }
} }
} break; } break;
case LLAMA_VOCAB_TYPE_TEST:
{
const uint32_t n_vocab = vocab.n_tokens();
constexpr size_t chunk_size = 5;
// reserve output to avoid repeated reallocations
size_t n_tokens = 0;
for (const auto & fragment : fragment_buffer) {
if (fragment.type == FRAGMENT_BUFFER_VARIANT_TYPE_RAW_TEXT) {
n_tokens += (fragment.length + chunk_size - 1) / chunk_size;
} else {
++n_tokens;
}
}
output.reserve(output.size() + n_tokens);
for (const auto & fragment : fragment_buffer) {
if (fragment.type == FRAGMENT_BUFFER_VARIANT_TYPE_RAW_TEXT) {
const auto & text = fragment.raw_text;
const size_t begin = fragment.offset;
const size_t end = begin + fragment.length;
size_t pos = begin;
while (pos < end) {
const size_t n = std::min(chunk_size, end - pos);
uint64_t hash = 0;
for (size_t i = 0; i < n; ++i) {
hash = hash*31 + (uint8_t) text[pos + i];
}
output.push_back((llama_token)(hash % n_vocab));
pos += n;
}
} else { // if (fragment.type == FRAGMENT_BUFFER_VARIANT_TYPE_TOKEN)
output.push_back(fragment.token);
}
}
} break;
case LLAMA_VOCAB_TYPE_NONE: case LLAMA_VOCAB_TYPE_NONE:
GGML_ABORT("fatal error"); GGML_ABORT("fatal error");
} }
@@ -3693,6 +3743,11 @@ int32_t llama_vocab::impl::token_to_piece(llama_token token, char * buf, int32_t
memcpy(buf, result.data(), result.size()); memcpy(buf, result.data(), result.size());
return (int)result.size(); return (int)result.size();
} }
case LLAMA_VOCAB_TYPE_TEST: {
// tokens -> text: simply stringify the token id in hex
std::string result = format("%x", token);
return _try_copy(result.data(), result.size());
}
case LLAMA_VOCAB_TYPE_PLAMO2: { case LLAMA_VOCAB_TYPE_PLAMO2: {
// PLaMo-2 uses similar token handling as BPE/SPM // PLaMo-2 uses similar token handling as BPE/SPM
if (vocab.is_byte(token)) { if (vocab.is_byte(token)) {
@@ -3963,6 +4018,9 @@ llama_token llama_vocab::byte_to_token(uint8_t ch) const {
snprintf(hex_str, sizeof(hex_str), "<0x%02X>", ch); snprintf(hex_str, sizeof(hex_str), "<0x%02X>", ch);
return pimpl->token_to_id.at(hex_str); return pimpl->token_to_id.at(hex_str);
} }
case LLAMA_VOCAB_TYPE_TEST:
// TEST tokens have no byte-level mapping
return LLAMA_TOKEN_NULL;
default: default:
GGML_ABORT("fatal error"); GGML_ABORT("fatal error");
} }
tests/test-llama-archs.cpp
+13 -1
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@@ -338,7 +338,19 @@ static gguf_context_ptr get_gguf_ctx(const llm_arch arch, const bool moe) {
ms.add_kv(LLM_KV_SWIGLU_CLAMP_EXP, 7.0f); ms.add_kv(LLM_KV_SWIGLU_CLAMP_EXP, 7.0f);
} }
ms.add_kv(LLM_KV_TOKENIZER_MODEL, "no_vocab"); // dummy tokenizer: token ids are derived from fixed-size chunks and detokenized as hex ids
{
std::vector<std::string> tokenizer_list(n_vocab);
std::vector<float> tokenizer_scores(n_vocab, 0.0f);
ms.add_kv(LLM_KV_TOKENIZER_MODEL, "test");
for (uint32_t i = 0; i < n_vocab; i++) {
tokenizer_list[i] = "tok_" + std::to_string(i);
}
ms.add_kv(LLM_KV_TOKENIZER_LIST, tokenizer_list);
ms.add_kv(LLM_KV_TOKENIZER_SCORES, tokenizer_scores);
}
// ms.add_kv(LLM_KV_DENSE_2_FEAT_OUT, n_embd); // ms.add_kv(LLM_KV_DENSE_2_FEAT_OUT, n_embd);
// ms.add_kv(LLM_KV_DENSE_3_FEAT_IN, n_embd); // ms.add_kv(LLM_KV_DENSE_3_FEAT_IN, n_embd);