diff --git a/csrc/scheduler/reduction.cpp b/csrc/scheduler/reduction.cpp
index 283ab6a64b3..3dfc324af4c 100644
--- a/csrc/scheduler/reduction.cpp
+++ b/csrc/scheduler/reduction.cpp
@@ -63,14 +63,13 @@ void reduceProductTo(int64_t& z, int64_t& y, int64_t& x, const int64_t max) {
   }
 }
 
-std::unique_ptr < ReductionParams >
-    2dInnerReductionHeuristic(
-        const int64_t total_reduction_numel,
-        const int64_t total_iteration_numel,
-        const int64_t inner_most_dimension_numel,
-        const int64_t n_tensor_inputs,
-        const int64_t max_input_dtype_size,
-        const size_t vectorize_factor) {
+std::unique_ptr<ReductionParams> inner2dReductionHeuristic(
+    const int64_t total_reduction_numel,
+    const int64_t total_iteration_numel,
+    const int64_t inner_most_dimension_numel,
+    const int64_t n_tensor_inputs,
+    const int64_t max_input_dtype_size,
+    const size_t vectorize_factor) {
   // Set some targets for parallelization
 
   const int64_t n_elems = total_reduction_numel * total_iteration_numel;
@@ -493,7 +492,7 @@ std::unique_ptr < ReductionParams >
                 << (rparams->unroll_factor_inner_reduction > 1) << ", "
                 << rparams->cross_grid_inner_reduction << std::endl;
       }
-      return innerReductionHeuristic(
+      return inner2dReductionHeuristic(
           total_reduction_numel,
           total_iteration_numel,
           total_reduction_numel,
@@ -506,14 +505,13 @@ std::unique_ptr < ReductionParams >
   return rparams;
 }
 
-std::unique_ptr < ReductionParams >
-    3dInnerReductionHeuristic(
-        const int64_t total_reduction_numel,
-        const int64_t total_iteration_numel,
-        const int64_t inner_most_dimension_numel,
-        const int64_t n_tensor_inputs,
-        const int64_t max_input_dtype_size,
-        const size_t vectorize_factor) {
+std::unique_ptr<ReductionParams> inner3dReductionHeuristic(
+    const int64_t total_reduction_numel,
+    const int64_t total_iteration_numel,
+    const int64_t inner_most_dimension_numel,
+    const int64_t n_tensor_inputs,
+    const int64_t max_input_dtype_size,
+    const size_t vectorize_factor) {
   // Set some targets for parallelization
 
   const int64_t n_elems = total_reduction_numel * total_iteration_numel;
@@ -936,7 +934,7 @@ std::unique_ptr < ReductionParams >
                 << (rparams->unroll_factor_inner_reduction > 1) << ", "
                 << rparams->cross_grid_inner_reduction << std::endl;
       }
-      return innerReductionHeuristic(
+      return inner2dReductionHeuristic(
           total_reduction_numel,
           total_iteration_numel,
           total_reduction_numel,
@@ -1497,7 +1495,7 @@ std::unique_ptr<ReductionParams> reductionHeuristic(
     const size_t vectorize_factor) {
   if (fastest_dim_reduction) {
     if (total_reduction_numel == inner_most_dimension_numel) {
-      return 2dInnerReductionHeuristic(
+      return inner2dReductionHeuristic(
           total_reduction_numel,
           total_iteration_numel,
           inner_most_dimension_numel,
@@ -1505,7 +1503,7 @@ std::unique_ptr<ReductionParams> reductionHeuristic(
           (int64_t)max_input_dtype_size,
           vectorize_factor);
     } else {
-      return 3dInnerReductionHeuristic(
+      return inner3dReductionHeuristic(
           total_reduction_numel,
           total_iteration_numel,
           inner_most_dimension_numel,