#pragma once #include int64_t cuda_version(); torch::Tensor ind2ptr(torch::Tensor ind, int64_t M); torch::Tensor ptr2ind(torch::Tensor ptr, int64_t E); torch::Tensor partition(torch::Tensor rowptr, torch::Tensor col, torch::optional optional_value, int64_t num_parts, bool recursive); std::tuple relabel(torch::Tensor col, torch::Tensor idx); torch::Tensor random_walk(torch::Tensor rowptr, torch::Tensor col, torch::Tensor start, int64_t walk_length); std::tuple subgraph(torch::Tensor idx, torch::Tensor rowptr, torch::Tensor row, torch::Tensor col); std::tuple sample_adj(torch::Tensor rowptr, torch::Tensor col, torch::Tensor rowcount, torch::Tensor idx, int64_t num_neighbors, bool replace); torch::Tensor spmm_sum(torch::optional opt_row, torch::Tensor rowptr, torch::Tensor col, torch::optional opt_value, torch::optional opt_colptr, torch::optional opt_csr2csc, torch::Tensor mat); torch::Tensor spmm_mean(torch::optional opt_row, torch::Tensor rowptr, torch::Tensor col, torch::optional opt_value, torch::optional opt_rowcount, torch::optional opt_colptr, torch::optional opt_csr2csc, torch::Tensor mat); std::tuple spmm_min(torch::Tensor rowptr, torch::Tensor col, torch::optional opt_value, torch::Tensor mat); std::tuple spmm_max(torch::Tensor rowptr, torch::Tensor col, torch::optional opt_value, torch::Tensor mat); std::tuple> spspmm_sum(torch::Tensor rowptrA, torch::Tensor colA, torch::optional optional_valueA, torch::Tensor rowptrB, torch::Tensor colB, torch::optional optional_valueB, int64_t K);