[BugFix][MetaSchedule] MultiLevelTilingTensorCore generates inconsistent thread-binding sketch for batched matmul

Author: tsu-bin

src/meta_schedule/schedule_rule/multi_level_tiling.cc

@@ -190,7 +190,8 @@ std::pair<Array<tir::ExprRV>, Array<tir::LoopRV>> MultiLevelTilingNode::SplitLoo
   return {factors, splits};
 }
 
-std::vector<State> MultiLevelTilingNode::TileLoopNest(State state) const {
+std::vector<State> MultiLevelTilingNode::TileLoopNest(State state,
+                                                      int tile_inner_most_space_loop_num) const {
   Schedule& sch = state->sch;
   const BlockRV& block_rv = state->block_rv;
   // Step 1. Assuming trivial binding, pair the loops and their iter-var-types
@@ -199,6 +200,16 @@ std::vector<State> MultiLevelTilingNode::TileLoopNest(State state) const {
   ICHECK_EQ(loops.size(), iter_types.size());
   // Step 2. For each loop axis, tile it
   int64_t spatial_loop_product = 1;
+
+  int total_spatial_loop_num = 0;
+  std::for_each(iter_types.begin(), iter_types.end(), [&](const auto& iter_type) {
+    if (iter_type == IterVarType::kDataPar) total_spatial_loop_num++;
+  });
+  CHECK_GE(total_spatial_loop_num, tile_inner_most_space_loop_num);
+  if (tile_inner_most_space_loop_num < 0) tile_inner_most_space_loop_num = total_spatial_loop_num;
+  int outer_most_spatial_loop_skipped_num = total_spatial_loop_num - tile_inner_most_space_loop_num;
+
+  Array<LoopRV> skipped_outer_spatial_loops;
   std::vector<Array<LoopRV>> tiles(s_indices_.size() + r_indices_.size());
   state->tile_factors.resize(tiles.size());
   std::vector<Array<tir::ExprRV>> tile_factors;
@@ -208,6 +219,11 @@ std::vector<State> MultiLevelTilingNode::TileLoopNest(State state) const {
     const std::vector<int>* idx = nullptr;
 
     if (iter_types[i] == IterVarType::kDataPar) {
+      if (outer_most_spatial_loop_skipped_num > 0) {
+        skipped_outer_spatial_loops.push_back(loop);
+        outer_most_spatial_loop_skipped_num--;
+        continue;
+      }
       idx = &s_indices_;
       if (spatial_loop_product != -1) {
         if (const int64_t* extent = tir::GetLoopIntExtent(sch->Get(loop).get())) {
@@ -241,6 +257,11 @@ std::vector<State> MultiLevelTilingNode::TileLoopNest(State state) const {
   sch->Reorder(support::ConcatArrayList<LoopRV>(tiles.begin(), tiles.end()));
   // Step 4. Bind the tiles to threads
   int n_binds = std::min(tile_binds.size(), tiles.size());
+  if (skipped_outer_spatial_loops.size() && n_binds) {
+    auto& the_first_tile = tiles[0];
+    the_first_tile.insert(the_first_tile.begin(), skipped_outer_spatial_loops.begin(),
+                          skipped_outer_spatial_loops.end());
+  }
   for (int i = 0; i < n_binds; ++i) {
     LoopRV fused = sch->Fuse(tiles[i]);
     sch->Bind(fused, tile_binds[i]);

src/meta_schedule/schedule_rule/multi_level_tiling.h

@@ -162,7 +162,7 @@ class MultiLevelTilingNode : public ScheduleRuleNode {
   // SubRule 1. add write cache
   std::vector<State> AddWriteReuse(State state) const;
   // SubRule 2. tile the loop nest
-  std::vector<State> TileLoopNest(State state) const;
+  std::vector<State> TileLoopNest(State state, int tile_inner_most_space_loop_num = -1) const;
   // SubRule 3. add read cache
   std::vector<State> AddReadReuse(State state) const;
   // SubRule 4. add async pipeline

src/meta_schedule/schedule_rule/multi_level_tiling_tensor_core.cc

@@ -251,7 +251,7 @@ std::vector<State> MultiLevelTilingTensorCoreNode::ApplySubRules(std::vector<Sta
   });
   states = SubRule(std::move(states), [&](State state) {
     TensorCoreState tc_state = Downcast<TensorCoreState>(state);
-    return tc_state->is_mma ? MMATileLoopNest(tc_state) : TileLoopNest(state);
+    return tc_state->is_mma ? MMATileLoopNest(tc_state) : TileLoopNest(state, 2);
   });
   states = SubRule(std::move(states), [&](State state) {
     return TransformIntermediateOutputLayout(Downcast<TensorCoreState>(state));