[GitHub] [tvm] shingjan commented on a diff in pull request #13579: [TIR] Add preserve_unit_iters option to blockize/tensorize

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

shingjan commented on code in PR #13579:
URL: https://github.com/apache/tvm/pull/13579#discussion_r1043725708


##########
src/tir/schedule/primitive/blockize_tensorize.cc:
##########
@@ -427,7 +430,8 @@ Stmt MakeLoopNest(Stmt stmt, const std::vector<const ForNode*>& loops) {
 }
 
 BlockRealize BlockizeImpl(const ScheduleState& self, const StmtSRef& loop_sref,
-                          Map<Block, Block>* block_sref_reuse, arith::Analyzer* analyzer) {
+                          bool preserve_unit_iters, Map<Block, Block>* block_sref_reuse,

Review Comment:
   nit: put preserve_unit_iters at the end of argument like other functions with preserve_unit_iters introduced.



##########
src/arith/iter_affine_map.cc:
##########
@@ -1812,18 +1812,26 @@ class SubspaceDivider {
     // extent of inner
     PrimExpr inner_extent;
 
+    // The kind of the division result.
+    enum class Kind {

Review Comment:
   This looks much cleaner with enum!



##########
tests/python/unittest/test_meta_schedule_runner.py:
##########
@@ -690,6 +690,8 @@ def _check_correct_add(args_before: List[np.ndarray], args_after: List[np.ndarra
         a_before, b_before, c_before = args_before
         a_after, b_after, c_after = args_after
         c_before = a_before + b_before
+        print(a_before)

Review Comment:
   remove the print



##########
tests/python/unittest/test_meta_schedule_schedule_rule_mlt_intrin.py:
##########
@@ -74,16 +74,16 @@ def vnni_conv2d_nchwc_0(placeholder: T.Buffer[(1, 4, 56, 56, 16), "uint8"], plac
         for i0_0, i1_0, i2_0, i3_0, i4_0_0, i0_1, i1_1, i2_1, i3_1, i4_0_1 in T.grid(1, 8, 28, 56, 1, 1, 2, 1, 1, 1):
             for i5_0, i6_0, i7_0, i8_0, i9_0_0, i0_2, i1_2, i2_2, i3_2, i4_0_2, i5_1, i6_1, i7_1, i8_1, i9_0_1, i0_3, i1_3, i2_3, i3_3, i4_0_3 in T.grid(1, 1, 1, 4, 1, 1, 1, 2, 1, 1, 1, 1, 4, 1, 1, 1, 1, 1, 1, 1):
                 with T.block("conv2d_NCHWc_int8_o"):
-                    n = T.axis.spatial(1, 0)
+                    n = T.axis.spatial(1, i0_2 + i0_3 + i0_0 + i0_1)

Review Comment:
   This is the result of trivial iters being preserved instead of simplified right? 



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