chore: import upstream snapshot with attribution

dgl_sparse/include/sparse/spmm.h

@@ -0,0 +1,40 @@
+/**
+ *  Copyright (c) 2022 by Contributors
+ * @file sparse/spmm.h
+ * @brief DGL C++ SpMM operator.
+ */
+#ifndef SPARSE_SPMM_H_
+#define SPARSE_SPMM_H_
+
+#include <sparse/sparse_matrix.h>
+#include <torch/script.h>
+
+namespace dgl {
+namespace sparse {
+
+/**
+ * @brief Perform a matrix multiplication of the sparse matrix and dense
+ * matrix. The SpMM can be batched, where the batch dimension is the last
+ * dimension for both sparse and dense matrices.
+ *
+ * There are three cases for sparse, dense, and output matrix shapes:
+ *   (1) (n, m), (m, k), and (n, k);
+ *   (2) (n, m), (m,), and (n,);
+ *   (3) (n, m, b), (m, k, b), and (n, k, b).
+ *
+ * This function supports autograd for both the sparse and dense matrix but does
+ * not support higher order gradient.
+ *
+ * @param sparse_mat The sparse matrix.
+ * @param dense_mat The dense matrix.
+ *
+ * @return Dense matrix.
+ */
+torch::Tensor SpMM(
+    const c10::intrusive_ptr<SparseMatrix>& sparse_mat,
+    torch::Tensor dense_mat);
+
+}  // namespace sparse
+}  // namespace dgl
+
+#endif  // SPARSE_SPMM_H_