transpose scheduler fix: reduction IterDomain on input tensors

csrc/scheduler/transpose.cpp

@@ -127,6 +127,27 @@ void TransposeScheduler::computeHeuristics(
 
 namespace {
 
+// propagation could miss trivial reduction iterdomain on input tensors, since
+// that doesn't have any dependency and doesn't map to anything, we can naively
+// just reorder them so they won't interfere with tiling.
+// See https://github.com/NVIDIA/Fuser/issues/1659#issuecomment-1907053830
+void cleanInnerNDLeafDomain(TensorView* tv, int n) {
+  if (!tv->isFusionInput()) {
+    return;
+  }
+
+  std::unordered_map<int, int> old2new;
+
+  int target = 0;
+  for (int i = 0; i < n; i++) {
+    if (tv->axis(-1 - i)->isReduction()) {
+      old2new[-1 - i] = target++;
+    }
+  }
+
+  tv->reorder(old2new);
+}
+
 // TransposeViewPropagator doesn't propagate anything. It simply walks across
 // the path of potential propagation checking if there's any incompatible
 // propagation that would not be resolved.
@@ -1236,6 +1257,7 @@ void scheduleTranspose(Fusion* fusion, TransposeParams params) {
 
   int pos = (int)reference2->nDims() - 2;
   // [..., tile1, tile2]
+  cleanInnerNDLeafDomain(reference2, 2);
   reference2->merge(pos);
   reference2->split(pos, params.vectorize_factor2);
   reference2->split(pos, params.getThreadsPerBlock());
@@ -1321,6 +1343,7 @@ void scheduleTranspose(Fusion* fusion, TransposeParams params) {
   reference1->reorder({{-2, -1}});
   // [..., tile2, tile1]
   pos = (int)reference1->nDims() - 2;
+  cleanInnerNDLeafDomain(reference1, 2);
   reference1->merge(pos);
   reference1->split(pos, params.vectorize_factor1);
   reference1->split(pos, params.getThreadsPerBlock());

test/test_gpu_transpose.cpp

@@ -1335,4 +1335,56 @@ TEST_F(TransposeTest, TransposeSplitAggregatedVectorizationWidth) {
   NVF_CHECK(ref.equal(cg_outputs.at(0)));
 }
 
+// Testing transpose scheduler to handle trivial reduction IterDomain produced
+// by segmented fusion, see issue 1659 for details
+TEST_F(TransposeTest, TrivialReductionIterDomainOnInputsIssueRepro1659) {
+  auto fusion = std::make_unique<Fusion>();
+  auto fusion_ptr = fusion.get();
+  FusionGuard fg(fusion_ptr);
+
+  auto tv0 = TensorViewBuilder()
+                 .ndims(3)
+                 .contiguity({true, true, std::nullopt})
+                 .shape({-1, -1, 1})
+                 .dtype(DataType::Float)
+                 .build();
+  fusion->addInput(tv0);
+  auto tv1 = TensorViewBuilder()
+                 .ndims(3)
+                 .contiguity({true, std::nullopt, true})
+                 .shape({-1, 1, -1})
+                 .dtype(DataType::Float)
+                 .build();
+  fusion->addInput(tv1);
+  auto tv2 = sum(tv0, {1});
+  auto tv3 = squeeze(tv1, std::vector<int64_t>{1});
+  auto tv4 = add(tv2, tv3);
+  fusion->addOutput(tv4);
+
+  auto options = at::TensorOptions().dtype(at::kFloat).device(at::kCUDA, 0);
+
+  auto t0 = at::randn({1024, 512, 1}, options);
+  auto t1 = at::randn({1024, 1, 512}, options);
+  std::vector<c10::IValue> aten_inputs({t0, t1});
+
+  FusionExecutorCache executor_cache(std::move(fusion));
+  auto cg_outputs = executor_cache.runFusionWithInputs(aten_inputs);
+
+  auto runtime = executor_cache.getMostRecentKernelRuntime();
+  NVF_CHECK(runtime->isSegmented(), "Segmentation expected");
+  auto heuristic0 =
+      runtime->schedulerHeuristics()->heuristicsList().at(0).get()->heuristic();
+  NVF_CHECK(
+      heuristic0 == ScheduleHeuristic::Reduction,
+      "Unexpected heuristic: ",
+      heuristic0);
+  auto heuristic1 =
+      runtime->schedulerHeuristics()->heuristicsList().at(1).get()->heuristic();
+  NVF_CHECK(
+      heuristic1 == ScheduleHeuristic::Transpose,
+      "Unexpected heuristic: ",
+      heuristic1);
+  testValidate(fusion_ptr, cg_outputs, {t0, t1}, __LINE__, __FILE__);
+}
+
 } // namespace nvfuser