Hi @zhiics @comaniac,
I am using BYOC to offload transformers to external codegen tools. These
transformers are composite functions. I had been using this feature well with
my manually-generated annotation passes, but when I merge the latest changes to
go through the `AnnotateGraph -> PartitionGraph` passes, I found that codegen
fails because the generated function is wrong.
The transformer outputs a single value, and this value is used in three places
in the model. However, the generated function returns this value as a 3-tuple:
```
...
add(%268, %output_layernorm_bias2) /* ty=Tensor[(1, 64, 512), float32] */
};
%270 = %269(meta[relay.Constant][32] /* ty=Tensor[(512), float32] */ ...;
(%270, %270, %270)
}
```
The return value should just be `%270`.
After checking the output of `AnnotateTarget`, I found that the issue is that a
new `CompilerEnd` annotation is added each time this output is used. For
example:
```
%395 = annotation.compiler_end(%394, meta[relay.attrs.CompilerAttrs][105])
...
%444 = annotation.compiler_end(%394, meta[relay.attrs.CompilerAttrs][140])
...
%475 = annotation.compiler_end(%394, meta[relay.attrs.CompilerAttrs][162])
```
This definitely seems like a bug, and is causing my codegen to break since the
body of the function is a tuple rather than a call node. Is there a good
workaround, or easy way to fix this?
Thanks!
---
[Visit
Topic](https://discuss.tvm.ai/t/incorrect-generated-function-after-partitiongraph-pass/6380/1)
to respond.
You are receiving this because you enabled mailing list mode.
To unsubscribe from these emails, [click
here](https://discuss.tvm.ai/email/unsubscribe/109c6c25f713255145da94b4d3adee305876e587bca915341e2691fce1567e8d).
