[GitHub] [tvm] yzh119 commented on a change in pull request #10420: [fix] Change the rule of determining compact dataflow.

[GitBox <gi...@apache.org>]

yzh119 commented on a change in pull request #10420:
URL: https://github.com/apache/tvm/pull/10420#discussion_r817268218



##########
File path: src/tir/schedule/analysis/analysis.cc
##########
@@ -363,6 +363,26 @@ void CheckCompleteOrReductionBlock(const ScheduleState& self, const StmtSRef& bl
                                          reduction_block_error_code);
 }
 
+StmtSRef GetInnermostDominantSubBlockSRef(const ScheduleState& self, const StmtSRef& block_sref) {
+  // return the innermost dominant sub-block.
+  const BlockNode* block = TVM_SREF_TO_BLOCK(block, block_sref);
+  bool all_iter_vars_data_parallel = true;
+  for (const IterVar& iter_var : block->iter_vars) {
+    if (iter_var->iter_type != kDataPar) {
+      all_iter_vars_data_parallel = false;
+    }
+  }
+  Array<StmtSRef> child_block_srefs = GetChildBlockSRefOnSRefTree(self, block_sref);
+  if (!block->init.defined() && child_block_srefs.size() == 1 && all_iter_vars_data_parallel) {
+    const StmtSRef& child_block_sref = child_block_srefs[0];
+    if (IsDominantBlock(self->GetBlockScope(block_sref), child_block_sref)) {

Review comment:
       This is to avoid something like:
   ```
   with T.block("outer"):
       vi, vj = T.axis.remap("SS", [i, j])
       b[vi, vj, 0] = b[vi, vj, 1] + b[vi, vj, 2]
       for k, l in T.grid(16, 16):
           with T.block("inner"):
               vk, vl = T.axis.remap("SR", [k, l])
               with T.init():
                   b[vi, vj, vk] = 0.0
               b[vi, vj, vk] = b[vi, vj, vk] + a[vi, vj, vk, vl]
   ```
   
   But unfortunately the `IsDominantBlock` return true here...




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