auto comp = [](const llama_token_data & a, const llama_token_data & b) {
return a.logit > b.logit;
};
- if (k == (int) candidates->size) {
- std::sort(candidates->data, candidates->data + candidates->size, comp);
- } else {
+ if (k <= 128) {
std::partial_sort(candidates->data, candidates->data + k, candidates->data + candidates->size, comp);
+ } else {
+ constexpr int nbuckets = 128;
+ constexpr float bucket_low = -10.0f;
+ constexpr float bucket_high = 10.0f;
+ constexpr float bucket_scale = nbuckets/(bucket_high - bucket_low);
+ constexpr float bucker_inter = -bucket_low * bucket_scale;
+
+ std::vector<int> bucket_idx(candidates->size);
+ std::vector<int> histo(nbuckets, 0);
+
+ for (int i = 0; i < (int)candidates->size; ++i) {
+ const float val = candidates->data[i].logit;
+ int ib = int(bucket_scale * val + bucker_inter); //nbuckets * (val - bucket_low) / (bucket_high - bucket_low);
+ ib = std::max(0, std::min(nbuckets-1, ib));
+ bucket_idx[i] = ib;
+ ++histo[ib];
+ }
+ int nhave = 0;
+ int ib = nbuckets - 1;
+ for ( ; ib >= 0; --ib) {
+ nhave += histo[ib];
+ if (nhave >= k) break;
+ }
+ std::vector<llama_token_data> tmp_tokens(nhave);
+ auto ptr = tmp_tokens.data();
+ std::vector<llama_token_data*> bucket_ptrs;
+ bucket_ptrs.reserve(nbuckets - ib);
+ for (int j = nbuckets - 1; j >= ib; --j) {
+ bucket_ptrs.push_back(ptr);
+ ptr += histo[j];
+ }
+ for (int i = 0; i < (int)candidates->size; ++i) {
+ int j = bucket_idx[i];
+ if (j >= ib) {
+ *bucket_ptrs[nbuckets-1-j]++ = candidates->data[i];
+ }
+ }
+
+ ptr = tmp_tokens.data();
+ int ndone = 0;
+ for (int j = nbuckets-1; j > ib; --j) {
+ std::sort(ptr, ptr + histo[j], comp);
+ ptr += histo[j];
+ ndone += histo[j];
+ }
+ std::partial_sort(ptr, ptr + k - ndone, ptr + histo[ib], comp);
+
+ std::memcpy(candidates->data, tmp_tokens.data(), k*sizeof(llama_token_data));
+
}
candidates->sorted = true;
}