Apply lint with clang-format

dmlc · Apr 17, 2024 · a8ae77c · a8ae77c
1 parent fdc5108
commit a8ae77c
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Showing 3 changed files with 139 additions and 148 deletions.
diff --git a/src/array/cuda/spmm.cu b/src/array/cuda/spmm.cu
@@ -3,9 +3,10 @@
  * @file array/cuda/spmm.cu
  * @brief SPMM C APIs and definitions.
  */
-#include <cstdlib>
 #include <dgl/array.h>
 
+#include <cstdlib>
+
 #include "../../runtime/cuda/cuda_common.h"
 #include "./functor.cuh"
 #include "./ge_spmm.cuh"
@@ -23,15 +24,14 @@ namespace aten {
  *       no broadcast, use dgl's kernel in other cases.
  */
 template <int XPU, typename IdType, typename DType>
-void SpMMCsr(
-    const std::string& op, const std::string& reduce, const BcastOff& bcast,
-    const CSRMatrix& csr, NDArray ufeat, NDArray efeat, NDArray out,
-    std::vector<NDArray> out_aux) {
+void SpMMCsr(const std::string& op, const std::string& reduce,
+             const BcastOff& bcast, const CSRMatrix& csr, NDArray ufeat,
+             NDArray efeat, NDArray out, std::vector<NDArray> out_aux) {
   bool is_scalar_efeat = efeat.NumElements() == csr.indices->shape[0];
   bool use_efeat = op != "copy_lhs";
   bool use_deterministic_alg_only = false;
   if (NULL != std::getenv("USE_DETERMINISTIC_ALG"))
-      use_deterministic_alg_only = true;
+    use_deterministic_alg_only = true;
 
   if (reduce == "sum") {
     bool more_nnz = (csr.indices->shape[0] > csr.num_rows * csr.num_cols);
@@ -42,9 +42,8 @@ void SpMMCsr(
       CusparseCsrmm2<DType, IdType>(
           ufeat->ctx, csr, static_cast<DType*>(ufeat->data), nullptr,
           static_cast<DType*>(out->data), x_length, use_deterministic_alg_only);
-    } else if (
-        op == "mul" && is_scalar_efeat &&
-        cusparse_available<DType, IdType>(more_nnz)) {
+    } else if (op == "mul" && is_scalar_efeat &&
+               cusparse_available<DType, IdType>(more_nnz)) {
       // cusparse
       int64_t x_length = 1;
       for (int i = 1; i < ufeat->ndim; ++i) x_length *= ufeat->shape[i];
@@ -80,10 +79,9 @@ void SpMMCsr(
  * @brief CUDA implementation of g-SpMM on Coo format.
  */
 template <int XPU, typename IdType, typename DType>
-void SpMMCoo(
-    const std::string& op, const std::string& reduce, const BcastOff& bcast,
-    const COOMatrix& coo, NDArray ufeat, NDArray efeat, NDArray out,
-    std::vector<NDArray> out_aux) {
+void SpMMCoo(const std::string& op, const std::string& reduce,
+             const BcastOff& bcast, const COOMatrix& coo, NDArray ufeat,
+             NDArray efeat, NDArray out, std::vector<NDArray> out_aux) {
   if (reduce == "sum") {
     SWITCH_OP(op, Op, {
       cuda::SpMMCoo<IdType, DType, Op, cuda::reduce::Sum<IdType, DType, true> >(