optimize sample_topp by filtering out small value elements up front

This works because we know that in worst case only 1 element will be selected
and therefore the remaining (n-1) elements have to split the remaining (1-topp)
probability. Probabilities smaller than that cannot be selected and can
be filtered out up front.

run.c

@@ -465,17 +465,24 @@ int sample_topp(float* probabilities, int n, float topp, ProbIndex* probindex) {
     // tokens that exceed probability topp. This way we never sample tokens that
     // have very low probabilities and are less likely to go "off the rails".
 
+    int n0 = 0;
     // quicksort indices in descending order of probabilities
+    // elements smaller than (1 - topp) / (n - 1) cannot be part of the result
+    // and can be filtered out directly
+    const float cutoff = (1.0f - topp) / (n - 1);
     for (int i = 0; i < n; i++) {
-        probindex[i].index = i;
-        probindex[i].prob = probabilities[i];
+        if (probabilities[i] >= cutoff) {
+            probindex[n0].index = i;
+            probindex[n0].prob = probabilities[i];
+            n0++;
+        }
     }
-    qsort(probindex, n, sizeof(ProbIndex), compare);
+    qsort(probindex, n0, sizeof(ProbIndex), compare);
 
     // truncate the list where cumulative probability exceeds topp
     float cumulative_prob = 0.0f;
-    int last_idx = 0;
-    for (int i = 0; i < n; i++) {
+    int last_idx = n0 - 1; // in case of rounding errors consider all elements
+    for (int i = 0; i < n0; i++) {
         cumulative_prob += probindex[i].prob;
         if (cumulative_prob > topp) {
             last_idx = i;