add VNNI unittest

tests/python/unittest/test_tir_schedule_tensorize.py

@@ -19,9 +19,10 @@
 import pytest
 import tvm
 import tvm.testing
-from tvm import tir
+from tvm import tir, te
 from tvm.script import tir as T
 from tvm.tir.schedule.testing import verify_trace_roundtrip
+from tvm.tir.tensor_intrin.vnni import INTRIN_NAME as VNNI_INTRIN
 
 # fmt: off
 # pylint: disable=no-member,invalid-name,unused-variable,line-too-long,redefined-outer-name,unexpected-keyword-arg,too-many-nested-blocks
@@ -531,5 +532,40 @@ def test_tensorize_with_annotation():
     verify_trace_roundtrip(sch=s, mod=func)
 
 
+def test_tensorize_vnni():
+    n, m, k = 128, 128, 128
+    X = te.placeholder((m, k), name="X", dtype="uint8")
+    packed_W = te.placeholder((n // 16, k // 4, 16, 4), name="packedW", dtype="int8")
+
+    ak = te.reduce_axis((0, k), name="k")
+    matmul = te.compute(
+        (m, n),
+        lambda i, j: te.sum(
+            X[i, ak].astype("int32")
+            * packed_W[
+                tvm.tir.indexdiv(j, 16), tvm.tir.indexdiv(ak, 4), j % 16, ak % 4
+            ].astype("int32"),
+            axis=ak,
+        ),
+        name="compute",
+    )
+
+    func = te.create_prim_func([X, packed_W, matmul])
+
+    sch = tir.Schedule(func, debug_mask="all")
+    block = sch.get_block("compute")
+    _, j, k = sch.get_loops(block)
+
+    _, ji = sch.split(j, factors=[None, 16])
+    ko, ki = sch.split(k, factors=[None, 4])
+    sch.reorder(ko, ji, ki)
+
+    sch.decompose_reduction(block, ko)
+    sch.tensorize(ji, VNNI_INTRIN)
+
+    verify_trace_roundtrip(sch=sch, mod=func)
+
+
 if __name__ == "__main__":
-    sys.exit(pytest.main([__file__] + sys.argv[1:]))
+    # sys.exit(pytest.main([__file__] + sys.argv[1:]))
+    test_tensorize_vnni()