hope51607 commented on PR #11507:
URL: https://github.com/apache/tvm/pull/11507#issuecomment-1143520351
Hi @AndrewZhaoLuo, thanks for your reply.
Consider the testing relay graph
```
def @main(%in: Tensor[(1, 10), float32], %shape: Tensor[(2), int64]) {
%0 = dyn.reshape(%in, %shape, newshape=[]);
nn.softmax(%0, axis=1)
}
```
I found that when the target is cuda, the TIR lowering from softmax contains
```
allocate(T_softmax_exp: Pointer(warp float32), float32, [any_dim_3]),
storage_scope = warp;
```
which seems to allocate warp memory with any.
I am not sure why the reason behind the problem is that cuda's softmax does
not support dynamic shapes? or is it a softmax schedule issue?
I think this issue seems to be out of scope of this PR.
Maybe I should mark skip in these softmax tests with dynamic shapes when
target is cuda.
Can anyone give me some hints?
Thanks.
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