chore: import upstream snapshot with attribution

dgl_sparse/include/sparse/sddmm.h

@@ -0,0 +1,44 @@
+/**
+ *  Copyright (c) 2022 by Contributors
+ * @file sparse/sddmm.h
+ * @brief DGL C++ SDDMM operator.
+ */
+#ifndef SPARSE_SDDMM_H_
+#define SPARSE_SDDMM_H_
+
+#include <sparse/sparse_matrix.h>
+#include <torch/script.h>
+
+namespace dgl {
+namespace sparse {
+
+/**
+ * @brief Perform a sampled matrix multiplication of a sparse matrix and two
+ * dense matrices. It calculates `sparse_mat * (mat1 @ mat2)`. The SDDMM can be
+ * batched, where the batch dimension is the last dimension for all input
+ * matrices.
+ *
+ * There are four cases for the input and output matrix shapes:
+ *   (1) (n, m), (n, k), (k, m), and (n, m);
+ *   (2) (n, m), (n,), and (m,), and (n, m);
+ *   (3) (n, m, b), (n, k, b), (k, m, b), and (n, m, b);
+ *   (4) (n, m), (n, k, b), (k, m, b), and (n, m, b);
+ *
+ * This function supports autograd for `mat1` and `mat2` but does not support
+ * high order gradient.
+ *
+ *
+ * @param sparse_mat The sparse matrix.
+ * @param mat1 The first dense matrix.
+ * @param mat2 The second dense matrix.
+ *
+ * @return SparseMatrix
+ */
+c10::intrusive_ptr<SparseMatrix> SDDMM(
+    const c10::intrusive_ptr<SparseMatrix>& sparse_mat, torch::Tensor mat1,
+    torch::Tensor mat2);
+
+}  // namespace sparse
+}  // namespace dgl
+
+#endif  // SPARSE_SDDMM_H_