Method sampleGlobalLevel

src/TopicModel/CTModel.hpp:130–161

		template<GlobalSampler _gs, typename _DocIter>
		void sampleGlobalLevel(ThreadPool* pool, _ModelState*, _RandGen* rgs, _DocIter first, _DocIter last) const
		{
			if (this->globalStep < this->burnIn || !this->optimInterval || (this->globalStep + 1) % this->optimInterval != 0) return;

			if (pool && pool->getNumWorkers() > 1)
			{
				std::vector<std::future<void>> res;
				const size_t chStride = pool->getNumWorkers() * 8;
				size_t dist = std::distance(first, last);
				for (size_t ch = 0; ch < chStride; ++ch)
				{
					auto b = first, e = first;
					std::advance(b, dist * ch / chStride);
					std::advance(e, dist * (ch + 1) / chStride);
					res.emplace_back(pool->enqueue([&, ch, chStride](size_t threadId, _DocIter b, _DocIter e)
					{
						for (auto doc = b; doc != e; ++doc)
						{
							updateBeta(*doc, rgs[threadId]);
						}
					}, b, e));
				}
				for (auto& r : res) r.get();
			}
			else
			{
				for (auto doc = first; doc != last; ++doc)
				{
					updateBeta(*doc, rgs[0]);
				}
			}
		}

		int restoreFromTrainingError(const exc::TrainingError& e, ThreadPool& pool, _ModelState* localData, _RandGen* rgs)
		{