Method infer

src/python/handler/py_LDA.cpp:345–411

}

py::UniqueObj LDAModelObject::infer(PyObject* docObj, size_t iteration, float tolerance, size_t workers, tomoto::ParallelScheme ps, bool together, PyObject* transform) const
{
	auto* inst = getInst<tomoto::ILDAModel>();
	if (!isPrepared) throw py::RuntimeError{ "cannot infer with untrained model" };
	py::UniqueObj iter;
	if (PyObject_TypeCheck(docObj, py::Type<CorpusObject>))
	{
		auto cps = makeCorpus(docObj, transform);
		std::vector<tomoto::DocumentBase*> docs;
		for (auto& d : cps->docsMade) docs.emplace_back(d.get());
		auto ll = inst->infer(docs, iteration, tolerance, workers, ps, together);
		return py::buildPyTuple(cps, ll);
	}
	else if (auto* doc = py::checkType<DocumentObject>(docObj))
	{
		if (doc->corpus->tm.get() != py::getPObjectAddress(this)) throw py::ValueError{ "`doc` was from another model, not fit to this model" };
		if (doc->owner)
		{
			std::vector<tomoto::DocumentBase*> docs;
			docs.emplace_back((tomoto::DocumentBase*)doc->getBoundDoc());
			float ll = inst->infer(docs, iteration, tolerance, workers, ps, together)[0];
			doc->initialized = true;
			return py::buildPyTuple(py::buildPyValue(inst->getTopicsByDoc(doc->getBoundDoc())), ll);
		}
		else
		{
			return py::buildPyTuple(py::buildPyValue(inst->getTopicsByDoc(doc->getBoundDoc())), nullptr);
		}
	}
	else if (py::clearError(), (iter = py::UniqueObj{ PyObject_GetIter(docObj) }))
	{
		std::vector<tomoto::DocumentBase*> docs;
		std::vector<DocumentObject*> docObjs;
		py::UniqueObj item;
		while ((item = py::UniqueObj{ PyIter_Next(iter.get()) }))
		{
			auto* doc = py::checkType<DocumentObject>(item.get());
			if (!doc) throw py::ValueError{ "`doc` must be tomotopy.Document type or list of tomotopy.Document" };
			if (doc->corpus->tm.get() != py::getPObjectAddress(this)) throw py::ValueError{ "`doc` was from another model, not fit to this model" };
			docs.emplace_back((tomoto::DocumentBase*)doc->doc);
			docObjs.emplace_back(doc);
		}
		if (PyErr_Occurred()) throw py::ExcPropagation{};
		auto ll = inst->infer(docs, iteration, tolerance, workers, ps, together);
			
		for (auto doc : docObjs) doc->initialized = true;

		auto ret = py::UniqueObj{ PyList_New(docs.size()) };
		size_t i = 0;
		for (auto d : docs)
		{
			PyList_SetItem(ret.get(), i++, py::buildPyValue(inst->getTopicsByDoc(d)).release());
		}
		if (together)
		{
			return py::buildPyTuple(ret, ll[0]);
		}
		else