int n_tokens = text.length() + 2 * add_special;
std::vector<llama_token> result(n_tokens);
n_tokens = llama_tokenize(vocab, text.data(), text.length(), result.data(), result.size(), add_special, parse_special);
+ if (n_tokens == std::numeric_limits<int32_t>::min()) {
+ throw std::runtime_error("Tokenization failed: input text too large, tokenization result exceeds int32_t limit");
+ }
if (n_tokens < 0) {
result.resize(-n_tokens);
int check = llama_tokenize(vocab, text.data(), text.length(), result.data(), result.size(), add_special, parse_special);
/// @param tokens The tokens pointer must be large enough to hold the resulting tokens.
/// @return Returns the number of tokens on success, no more than n_tokens_max
/// @return Returns a negative number on failure - the number of tokens that would have been returned
+ /// @return Returns INT32_MIN on overflow (e.g., tokenization result size exceeds int32_t limit)
/// @param add_special Allow to add BOS and EOS tokens if model is configured to do so.
/// @param parse_special Allow tokenizing special and/or control tokens which otherwise are not exposed and treated
/// as plaintext. Does not insert a leading space.
bool add_special,
bool parse_special) const {
auto res = tokenize(std::string(text, text_len), add_special, parse_special);
+ if (res.size() >= static_cast<size_t>(std::numeric_limits<int32_t>::max())) {
+ LLAMA_LOG_ERROR("%s: tokenization result size %zu exceeds int32_t limit\n", __func__, res.size());
+ return std::numeric_limits<int32_t>::min();
+ }
+
if (n_tokens_max < (int) res.size()) {
// LLAMA_LOG_ERROR("%s: too many tokens\n", __func__);
return -((int) res.size());