Make TIR minimal.

Author: zxybazh

tests/python/unittest/test_tir_transform_lower_tvm_builtin.py

@@ -174,40 +174,16 @@ def build_tir():
 
 def test_lower_overflow_int32():
     @T.prim_func
-    def variance4(
-        rxplaceholder: T.Buffer((T.int64(1), T.int64(32), T.int64(25690112)), "float32"),
-        T_divide: T.Buffer((T.int64(1), T.int64(32), T.int64(1)), "float32"),
-    ):
+    def variance4(rxplaceholder: T.Buffer((T.int64(1), T.int64(32), T.int64(25690112)), "float32")):
         T.func_attr({"global_symbol": "variance4", "tir.noalias": True})
         rxplaceholder_red = T.allocate([32], "float32", "global")
         T_subtract = T.allocate([822083584], "float32", "global")
         rxplaceholder_red_1 = T.Buffer((T.int64(32),), data=rxplaceholder_red)
         rxplaceholder_1 = T.Buffer((T.int64(822083584),), data=rxplaceholder.data)
-        for ax1, k2 in T.grid(32, 25690112):
-            if k2 == 0:
-                rxplaceholder_red_1[ax1] = T.float32(0)
-            rxplaceholder_red_1[ax1] = (
-                rxplaceholder_red_1[ax1] + rxplaceholder_1[ax1 * 25690112 + k2]
-            )
-        rxplaceholder_red_2 = T.Buffer((T.int64(32),), data=rxplaceholder_red)
-        for ax1 in range(32):
-            rxplaceholder_red_2[ax1] = rxplaceholder_red_1[ax1] * T.float32(3.8925482302295915e-08)
         T_subtract_1 = T.Buffer((T.int64(822083584),), data=T_subtract)
         for ax1, ax2 in T.grid(32, 25690112):
             cse_var_1: T.int32 = ax1 * 25690112 + ax2
-            T_subtract_1[cse_var_1] = rxplaceholder_1[cse_var_1] - rxplaceholder_red_2[ax1]
-        T_subtract_2 = T.Buffer((T.int64(822083584),), data=T_subtract)
-        for ax1, ax2 in T.grid(32, 25690112):
-            cse_var_2: T.int32 = ax1 * 25690112 + ax2
-            T_subtract_2[cse_var_2] = T_subtract_1[cse_var_2] * T_subtract_1[cse_var_2]
-        rxplaceholder_red_3 = T.Buffer((T.int64(32),), data=rxplaceholder_red)
-        for ax1, k2 in T.grid(32, 25690112):
-            if k2 == 0:
-                rxplaceholder_red_3[ax1] = T.float32(0)
-            rxplaceholder_red_3[ax1] = rxplaceholder_red_3[ax1] + T_subtract_2[ax1 * 25690112 + k2]
-        for ax1 in range(32):
-            T_divide_1 = T.Buffer((T.int64(32),), data=T_divide.data)
-            T_divide_1[ax1] = rxplaceholder_red_3[ax1] * T.float32(3.8925482302295915e-08)
+            T_subtract_1[cse_var_1] = rxplaceholder_1[cse_var_1] - rxplaceholder_red_1[ax1]
 
     func = variance4
     tvm.build(func, target="llvm")  # should not crash