[TVM Discuss] [Questions] [PattenLang]How to match op according to element type of input and output

[Lixiaoquan via TVM Discuss]

Thanks a lot for this detail sample!





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[TVM Discuss] [Questions] [PattenLang]How to match op according to element type of input and output

[Lixiaoquan via TVM Discuss]

I'm afraid I haven't made my point clear.  By using has_type, we can match to a 
specific dtype, but the shape of tensor is also fixed. By using wildcard(), we 
can match to (**AnyShape**, **AnyType**).  How to achieve something like 
has_type((**AnyShape**, 'float32'))?
```
in1 = wildcard()
in2 = wildcard()
pat = is_op('add')(in1, in2).has_type(relay.TensorType((10, 10), 'float32'))

x = relay.var('x', shape=(10, 10), dtype='float32')
pat.match(relay.add(x, x))
```
Thanks





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[TVM Discuss] [Questions] [PattenLang]How to match op according to element type of input and output

[Lixiaoquan via TVM Discuss]

Can it match shape other than (10,10)?





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[TVM Discuss] [Questions] [PattenLang]How to match op according to element type of input and output

[Lixiaoquan via TVM Discuss]

Current TypePattern requires type in pattern matches type in expr exactly. Is 
there a way to match only according to element type. For example, match a fp16 
*add*?





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[TVM Discuss] [Questions] How to serialize a Relay module?

[Lixiaoquan via TVM Discuss]

Is it possbile to serialize a Relay module (tvm.module.IRModule)?

If not, is there any plan to support this?

Thanks





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[TVM Discuss] [Questions] How does a Relay OP support variable length parameter list?

[Lixiaoquan via TVM Discuss]

I think the relay's convention is to convert multiple parameters into a tuple.





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