junrushao commented on code in PR #12572:
URL: https://github.com/apache/tvm/pull/12572#discussion_r953857171
##########
tests/python/unittest/test_tir_transform_lower_opaque_block.py:
##########
@@ -321,6 +321,47 @@ def test_annotated_loops():
tvm.ir.assert_structural_equal(attr3.value, tvm.tir.FloatImm("float32",
0.0))
+def test_annotated_block():
+ @T.prim_func
+ def annotated_block() -> None:
+ with T.block():
+ T.block_attr({"pragma_1": "str_value", "pragma_2": 1, "pragma_3":
0.0})
+ T.evaluate(0)
+
+ mod = tvm.IRModule.from_expr(annotated_block)
+ mod = tvm.tir.transform.LowerOpaqueBlock()(mod)
+ attr1 = mod["main"].body
+ attr2 = attr1.body
+ attr3 = attr2.body
+ assert attr1.attr_key == "pragma_1" and attr1.value == "str_value"
+ assert attr2.attr_key == "pragma_2"
+ tvm.ir.assert_structural_equal(attr2.value, tvm.tir.IntImm("int32", 1))
+ assert attr3.attr_key == "pragma_3"
+ tvm.ir.assert_structural_equal(attr3.value, tvm.tir.FloatImm("float32",
0.0))
+
+
+def test_preserved_annotations():
+ @T.prim_func
+ def before(A: T.Buffer[8, "float32"], B: T.Buffer[8, "float32"]):
+ for i in T.serial(8, annotations={"k_0": 1, "k_1": [2, 3], "k_2": 4}):
+ with T.block("block"):
+ T.block_attr({"k_3": 3.14, "k_4": ""})
+ B[i] = A[i] + 1.0
+
+ @T.prim_func
+ def after(A: T.Buffer[8, "float32"], B: T.Buffer[8, "float32"]):
+ for i in T.serial(8, annotations={"k_0": 1, "k_1": [2, 3]}):
+ for _ in range(1, annotations={"k_3": 3.14}):
Review Comment:
I'm a bit uncertain if haivng an AttrStmt might make sense in our workflow,
given it's something in the low-level TIR that we might want to minimize its
usage (CC: @tqchen). I'm aware that there could be any implications if we
directly remove a unit loop without preserving its annotation too. Not sure
what the best approach is.
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