[GitHub] [tvm] comaniac commented on a change in pull request #7497: [Tensorize] Support conds depend on outer loop vars inside tensorize scope

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

comaniac commented on a change in pull request #7497:
URL: https://github.com/apache/tvm/pull/7497#discussion_r585804702



##########
File path: tests/python/unittest/test_te_schedule_tensorize.py
##########
@@ -18,14 +18,22 @@
 from tvm import te
 
 
-def intrin_vadd(n):
+def intrin_vadd(xo, m, n):
     x = te.placeholder((n,), name="vx")
     y = te.placeholder((n,), name="vy")
-    z = te.compute(x.shape, lambda i: x[i] + y[i], name="z")
+    if m % n == 0:
+        body = lambda i: x[i] + y[i]
+    else:
+        body = lambda i: tvm.tir.Select(
+            xo * n + i < m, x[i] + y[i], tvm.tir.const(0, dtype=x.dtype)
+        )
+    z = te.compute(x.shape, body, name="z")
 
     def intrin_func(ins, outs):
         xx, yy = ins
         zz = outs[0]
+        # special handle needed to tackle tail loop part when m % n != 0
+        # here is tvm.min(n, m - xo * n)

Review comment:
       Is that possible to also improve `vadd` in this PR so that you can reuse the `check` function for both test cases?




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