patschmidt2 commented on issue #16566:
URL: https://github.com/apache/tvm/issues/16566#issuecomment-1943798326
Thanks, that definitely goes in the right direction! I have ported this over
to my local branch. I still get an error though:
```
Error message: The stmt tir.For#0 doesn't match the tensor intrin
The pattern attempting to be matched:
for j in range(512):
k = T.int32()
with T.block("res_update"):
v_j_i = T.axis.spatial(512, j)
v_k_i = T.axis.reduce(1024, k)
res = T.Buffer((1, 512), "int8")
v_i_o = T.int32()
a_in = T.Buffer((1, 1024), "int8")
b_in = T.Buffer((1024, 512), "int8")
T.reads(res[v_i_o, v_j_i], a_in[v_i_o, v_k_i], b_in[v_k_i, v_j_i])
T.writes(res[v_i_o, v_j_i])
res[v_i_o, v_j_i] = res[v_i_o, v_j_i] + a_in[v_i_o, v_k_i] *
b_in[v_k_i, v_j_i]
Does not match the tensorize description:
for j in range(512):
k = T.int32()
with T.block(""):
vii = T.axis.spatial(1, 0)
vjj = T.axis.spatial(512, j)
vkk = T.axis.reduce(1024, k)
C = T.Buffer((1, 512), "int8", offset_factor=1)
A = T.Buffer((1, 1024), "int8", offset_factor=1)
B = T.Buffer((1024, 512), "int8", offset_factor=1)
T.reads(C[0, vjj], A[0, vkk], B[vkk, vjj])
T.writes(C[0, vjj])
C[0, vjj] = C[0, vjj] + A[0, vkk] * B[vkk, vjj]
CompareArray array size mismatch. lhs.size()=2 vs rhs.size()=3
BlockRealizeNode iter_values do not match: op->iter_values=[j, k] vs
rhs->iter_values=[0, j, k]
```
It seems like the unit iterator is not actually deleted, but is still
preserved.
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