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Add back top_k (#56)
* Add back top_k * Update utils.cpp * Update utils.h --------- Co-authored-by: Bill Hamilton <bill.hamilton@shopify.com> Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
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3 changed files with 12 additions and 89 deletions
3
main.cpp
3
main.cpp
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@ -825,6 +825,7 @@ int main(int argc, char ** argv) {
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if (i >= embd_inp.size()) {
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// sample next token
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const float top_k = params.top_k;
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const float top_p = params.top_p;
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const float temp = params.temp;
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const float repeat_penalty = params.repeat_penalty;
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@ -836,7 +837,7 @@ int main(int argc, char ** argv) {
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{
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const int64_t t_start_sample_us = ggml_time_us();
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id = llama_sample_top_p(vocab, logits.data() + (logits.size() - n_vocab), last_n_tokens, repeat_penalty, top_p, temp, rng);
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id = llama_sample_top_p_top_k(vocab, logits.data() + (logits.size() - n_vocab), last_n_tokens, repeat_penalty, top_k, top_p, temp, rng);
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last_n_tokens.erase(last_n_tokens.begin());
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last_n_tokens.push_back(id);
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79
utils.cpp
79
utils.cpp
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@ -301,25 +301,8 @@ bool gpt_vocab_init(const std::string & fname, gpt_vocab & vocab) {
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return true;
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}
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gpt_vocab::id gpt_sample_top_k_top_p(
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const gpt_vocab & vocab,
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const float * logits,
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int top_k,
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double top_p,
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double temp,
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std::mt19937 & rng) {
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int n_logits = vocab.id_to_token.size();
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std::vector<std::pair<double, gpt_vocab::id>> logits_id;
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logits_id.reserve(n_logits);
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{
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const double scale = 1.0/temp;
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for (int i = 0; i < n_logits; ++i) {
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logits_id.push_back(std::make_pair(logits[i]*scale, i));
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}
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}
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void sample_top_k(std::vector<std::pair<double, gpt_vocab::id>> & logits_id, int top_k) {
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// find the top K tokens
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std::partial_sort(
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logits_id.begin(),
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@ -329,63 +312,14 @@ gpt_vocab::id gpt_sample_top_k_top_p(
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});
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logits_id.resize(top_k);
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double maxl = -INFINITY;
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for (const auto & kv : logits_id) {
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maxl = std::max(maxl, kv.first);
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}
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// compute probs for the top K tokens
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std::vector<double> probs;
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probs.reserve(logits_id.size());
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double sum = 0.0;
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for (const auto & kv : logits_id) {
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double p = exp(kv.first - maxl);
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probs.push_back(p);
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sum += p;
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}
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// normalize the probs
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for (auto & p : probs) {
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p /= sum;
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}
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if (top_p < 1.0f) {
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double cumsum = 0.0f;
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for (int i = 0; i < top_k; i++) {
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cumsum += probs[i];
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if (cumsum >= top_p) {
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top_k = i + 1;
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probs.resize(top_k);
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logits_id.resize(top_k);
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break;
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}
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}
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cumsum = 1.0/cumsum;
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for (int i = 0; i < (int) probs.size(); i++) {
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probs[i] *= cumsum;
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}
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}
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//printf("\n");
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//for (int i = 0; i < (int) probs.size(); i++) {
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// printf("%d: '%s' %f\n", i, vocab.id_to_token.at(logits_id[i].second).c_str(), probs[i]);
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//}
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//exit(0);
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std::discrete_distribution<> dist(probs.begin(), probs.end());
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int idx = dist(rng);
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return logits_id[idx].second;
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}
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gpt_vocab::id llama_sample_top_p(
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gpt_vocab::id llama_sample_top_p_top_k(
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const gpt_vocab & vocab,
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const float * logits,
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std::vector<gpt_vocab::id> & last_n_tokens,
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double repeat_penalty,
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int top_k,
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double top_p,
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double temp,
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std::mt19937 & rng) {
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@ -412,12 +346,7 @@ gpt_vocab::id llama_sample_top_p(
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}
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}
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std::sort(
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logits_id.begin(),
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logits_id.end(),
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[](const std::pair<double, gpt_vocab::id> & a, const std::pair<double, gpt_vocab::id> & b) {
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return a.first > b.first;
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});
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sample_top_k(logits_id, top_k);
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double maxl = -INFINITY;
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for (const auto & kv : logits_id) {
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19
utils.h
19
utils.h
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@ -19,7 +19,7 @@ struct gpt_params {
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int32_t repeat_last_n = 64; // last n tokens to penalize
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// sampling parameters
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int32_t top_k = 40; // unused
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int32_t top_k = 40;
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float top_p = 0.95f;
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float temp = 0.80f;
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float repeat_penalty = 1.30f;
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@ -77,25 +77,18 @@ bool gpt_vocab_init(const std::string & fname, gpt_vocab & vocab);
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// - consider only the top K tokens
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// - from them, consider only the top tokens with cumulative probability > P
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//
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// TODO: not sure if this implementation is correct
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// TODO: temperature is not implemented
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//
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gpt_vocab::id gpt_sample_top_k_top_p(
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gpt_vocab::id llama_sample_top_p_top_k(
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const gpt_vocab & vocab,
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const float * logits,
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std::vector<gpt_vocab::id> & last_n_tokens,
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double repeat_penalty,
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int top_k,
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double top_p,
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double temp,
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std::mt19937 & rng);
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gpt_vocab::id llama_sample_top_p(
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const gpt_vocab & vocab,
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const float * logits,
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std::vector<gpt_vocab::id> & last_n_tokens,
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double repeat_penalty,
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double top_p,
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double temp,
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std::mt19937 & rng);
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// filer to top K tokens from list of logits
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void sample_top_k(std::vector<std::pair<double, gpt_vocab::id>> & logits_id, int top_k);
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//
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// Quantization
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