c1c31db36facdf8d557f4dcc69866ac86814b83f,pynndescent/pynndescent_.py,NNDescent,_init_search_graph,#NNDescent#,900

Before Change

        // Preserve any distance 0 points
        diversified_data[diversified_data == 0.0] = FLOAT32_EPS

        self._search_graph.rows[:] = diversified_rows.tolist()
        self._search_graph.data[:] = diversified_data.tolist()

        // Get rid of any -1 index entries
        self._search_graph = self._search_graph.tocsr()

After Change

            del self._rp_forest
            self._search_forest = [
                convert_tree_format(tree, self._raw_data.shape[0])
                for tree in best_trees
            ]

        if self._is_sparse:

Instances