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new d33a44702c [Tests] Update test_adaptive_pooling_window expected IR for
const-int-bound fix (#20023)
d33a44702c is described below
commit d33a44702c23dccb8d9f850032d703f22a35af4a
Author: Syeam Bin Abdullah <[email protected]>
AuthorDate: Sat Jul 18 00:14:25 2026 +0930
[Tests] Update test_adaptive_pooling_window expected IR for const-int-bound
fix (#20023)
Followup to #19978: the const-int-bound modular-set fix correctly
prevents the simplifier from over-folding the adaptive pool window
extent. The previous expected IR used the simplified closed form `(v_ax2
% 3 * 4 + 16) // 12 + 1`, which was only reachable because the buggy
bound let `CanProve` prove an invalid predicate. After the fix the
generated IR retains the correct `T.Select` form, so update the expected
IR to match and remove the `xfail` marker that was added in #19978.
This branch is based on current main so the `xfail` removal is explicit
(addressing feedback from @tlopex on the previous attempt in #19995).
---
tests/python/te/test_te_create_primfunc.py | 11 +++--------
1 file changed, 3 insertions(+), 8 deletions(-)
diff --git a/tests/python/te/test_te_create_primfunc.py
b/tests/python/te/test_te_create_primfunc.py
index e3fd003f31..38eef4f795 100644
--- a/tests/python/te/test_te_create_primfunc.py
+++ b/tests/python/te/test_te_create_primfunc.py
@@ -911,11 +911,6 @@ def test_loop_aware_reducer_combiner():
_check_workload(te_workload, tir_workload)
[email protected](
- reason="const-int-bound fix (apache/tvm#19978) simplifies the adaptive "
- "pool window extent; the expected IR below still encodes the old "
- "(pre-fix) T.Select form and needs updating as a followup"
-)
def test_adaptive_pooling_window():
@T.prim_func(s_tir=True)
def tir_workload(
@@ -926,11 +921,11 @@ def test_adaptive_pooling_window():
# fmt: off
adaptive_pool_sum = T.sblock_alloc_buffer((1, 1024, 12, 30))
for ax0, ax1, ax2, ax3 in T.grid(1, 1024, 12, 30):
- with T.sblock("adaptive_pool_sum_1"):
+ with T.sblock("adaptive_pool_sum_l1"):
v_ax0, v_ax1, v_ax2, v_ax3 = T.axis.remap("SSSS", [ax0, ax1,
ax2, ax3])
T.reads(x[v_ax0, v_ax1, v_ax2 * 16 // 12:v_ax2 * 16 // 12 +
((v_ax2 % 3 * 4 + 16) // 12 + 1), v_ax3 * 40 // 30:v_ax3 * 40 // 30 + ((v_ax3 %
3 * 10 + 40) // 30 + 1)])
T.writes(adaptive_pool_sum[v_ax0, v_ax1, v_ax2, v_ax3])
- for rv0, rv1 in T.grid((v_ax2 % 3 * 4 + 16) // 12 + 1, (v_ax3
% 3 * 10 + 40) // 30 + 1):
+ for rv0, rv1 in T.grid(T.Select((v_ax2 * 16 + 4) % 12 == 0,
(v_ax2 * 16 + 16) // 12, (v_ax2 * 16 + 16) // 12 + 1) - v_ax2 * 16 // 12,
T.Select((v_ax3 * 40 + 10) % 30 == 0, (v_ax3 * 40 + 40) // 30, (v_ax3 * 40 +
40) // 30 + 1) - v_ax3 * 40 // 30):
with T.sblock("adaptive_pool_sum"):
v_ax0_1 = T.axis.spatial((v_ax0, v_ax0 + 1), v_ax0)
v_ax1_1 = T.axis.spatial((v_ax1, v_ax1 + 1), v_ax1)
@@ -948,7 +943,7 @@ def test_adaptive_pooling_window():
T.reads(adaptive_pool_sum[v_ax0, v_ax1, v_ax2, v_ax3])
T.writes(adaptive_pool_avg[v_ax0, v_ax1, v_ax2, v_ax3])
T.sblock_attr({"schedule_rule":
"meta_schedule.adaptive_pool_avg"})
- adaptive_pool_avg[v_ax0, v_ax1, v_ax2, v_ax3] =
adaptive_pool_sum[v_ax0, v_ax1, v_ax2, v_ax3] / (T.Cast("float32", (v_ax2 % 3 *
4 + 16) // 12 + 1) * T.Cast("float32", (v_ax3 % 3 * 10 + 40) // 30 + 1))
+ adaptive_pool_avg[v_ax0, v_ax1, v_ax2, v_ax3] =
adaptive_pool_sum[v_ax0, v_ax1, v_ax2, v_ax3] / (T.Cast("float32",
T.Select((v_ax2 * 16 + 4) % 12 == 0, (v_ax2 * 16 + 16) // 12, (v_ax2 * 16 + 16)
// 12 + 1) - v_ax2 * 16 // 12) * T.Cast("float32", T.Select((v_ax3 * 40 + 10) %
30 == 0, (v_ax3 * 40 + 40) // 30, (v_ax3 * 40 + 40) // 30 + 1) - v_ax3 * 40 //
30))
# fmt: on
def te_workload():
