@t-vi Sure, if you want to extend it, I'm okay with that. I'm not sure we need
an extra API, maybe just make the arbitrary value default?
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@t-vi Sorry for my delay, I had a lot of meetings today. I've finally read
through this enough to grok the problem. I'm not sure the Pattern Language is
the right tool for this pass.
As you said here:
[quote="t-vi, post:3, topic:7012"]
I’m always wondering whether I’m missing ready-made pass
Ah, yeah, this makes sense now.
The first LikeZapp pass will return this in certain cases:
```
tvm.relay.broadcast_to(data, list(res._checked_type_.shape))
```
Which doesn't have a type when it is constructed, but ZeroZapp later can find
that node and assume it does have a type. Thus, the prob
@matt-arm Can you give me an example? Is this just the partition issue we
talked about before, or something else?
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https://github.com/apache/incubator-tvm/pull/5760
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I'll throw together a PR with those extensions. Thanks!
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What do you guys thing? Which would be easier to use?
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Yeah, it's a bit complicated. The current pattern uses the tvm::ir::Type*
classes, so you can match number of versions of types, but as this question
reveals, we may want a finer granularity on some types.
Unfortunately, since we're using a lower level Type object, we won't be able to
embed
My apologies! I somehow missed this last week.
Yeah, the current TypePattern is matching the full type via StructuralEqual.
One possibility to clean this up slightly is to add a rule of:
1) If it's a TensorType
2) and the pattern's shape is ()
3) only check the dtype
That would only take a han
