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2 changes: 2 additions & 0 deletions src/generators.cpp
Original file line number Diff line number Diff line change
Expand Up @@ -420,6 +420,8 @@ void Generator::InitializeSamplingMethod(const GeneratorParams& params) {
throw std::runtime_error("top_p must be between 0.0 and 1.0");
if (search.top_k < 0)
throw std::runtime_error("top_k must be 0 or greater");
if (search.top_k > params.config.model.vocab_size)
throw std::runtime_error("top_k (" + std::to_string(search.top_k) + ") must be less than or equal to vocab_size (" + std::to_string(params.config.model.vocab_size) + ")");
if (search.top_p > 0.0f && search.top_p < 1.0f && search.top_k > 1) {
sampling_method_ = SamplingMethod::kTopKTopP;
} else if (search.top_k > 1) {
Expand Down
4 changes: 4 additions & 0 deletions src/search.cpp
Original file line number Diff line number Diff line change
Expand Up @@ -170,6 +170,7 @@ void GreedySearch_Cpu::SelectTop() {

void GreedySearch_Cpu::SampleTopK(int k, float temperature) {
const int vocab_size = params_->config.model.vocab_size;
k = std::min(k, vocab_size);
std::vector<int> indices(vocab_size);
std::vector<float> top_k_scores(k);

Expand Down Expand Up @@ -329,6 +330,9 @@ void GreedySearch_Cpu::SampleTopP(float p, float temperature) {
void GreedySearch_Cpu::SampleTopKTopP(int k, float p, float temperature) {
assert(temperature > 0.0f);

// Clamp k to vocab_size to prevent out-of-bounds access in partial_sort
k = std::min(k, params_->config.model.vocab_size);

// --- Buffers allocated once to avoid re-allocations in the batch loop ---
std::vector<int32_t> indices(params_->config.model.vocab_size);

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14 changes: 14 additions & 0 deletions test/sampling_tests.cpp
Original file line number Diff line number Diff line change
Expand Up @@ -460,6 +460,19 @@ TEST(SamplingTests, RepetitionPenaltyCorrectnessCpu) {
<< " Unpenalized per-token avg=" << unpenalized_avg;
}

TEST(SamplingTests, TopKExceedingVocabSizeIsRejected) {
auto config = OgaConfig::Create(MODEL_PATH "hf-internal-testing/tiny-random-gpt2-fp32");
config->ClearProviders();
auto model = OgaModel::Create(*config);

auto params = OgaGeneratorParams::Create(*model);
params->SetSearchOption("max_length", 25);
params->SetSearchOptionBool("do_sample", true);
params->SetSearchOption("top_k", 5000); // vocab_size is 1000

EXPECT_THROW(OgaGenerator::Create(*model, *params), std::runtime_error);
}

#if USE_CUDA
TEST(SamplingTests, BatchedSamplingTopPCuda) {
std::vector<int32_t> input_ids{0, 1, 2, 3};
Expand All @@ -480,6 +493,7 @@ TEST(SamplingTests, BatchedSamplingTopPCuda) {
auto params = OgaGeneratorParams::Create(*model);
params->SetSearchOption("max_length", 10);
params->SetSearchOptionBool("do_sample", true);
params->SetSearchOption("top_k", 1);
params->SetSearchOption("top_p", 0.25f);
params->SetSearchOption("batch_size", batch_size);

Expand Down
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