inline size_t sample_discrete (
rng_t & rng,
size_t dim,
const float * probs)
{
float t = sample_unif01(rng);
for (size_t i = 0; DIST_LIKELY(i < dim - 1); ++i) {
t -= probs[i];
if (DIST_UNLIKELY(t < 0)) {
return i;
}
}
return dim - 1;
}
bool add_value(
const Model & model,
size_t groupid,
count_t count = 1) {
const bool add_group = driver_.add_value(model, groupid, count);
if (DIST_UNLIKELY(add_group)) {
shifted_scores_.packed_add();
_update_empty_groups(model);
}
_update_nonempty_group(model, groupid);
return add_group;
}
bool remove_value(
const Model & model,
size_t groupid,
count_t count = 1) {
const bool remove_group =
driver_.remove_value(model, groupid, count);
if (DIST_UNLIKELY(remove_group)) {
shifted_scores_.packed_remove(groupid);
_update_empty_groups(model);
} else {
_update_nonempty_group(model, groupid);
}
return remove_group;
}
inline size_t sample_from_likelihoods (
rng_t & rng,
const std::vector<float, Alloc> & likelihoods,
float total_likelihood)
{
const size_t size = likelihoods.size();
float t = total_likelihood * sample_unif01(rng);
for (size_t i = 0; DIST_LIKELY(i < size); ++i) {
t -= likelihoods[i];
if (DIST_UNLIKELY(t < 0)) {
return i;
}
}
return size - 1;
}
