[Apache TVM Discuss] [Development/RFC] [RFC] Refactor the compile_engine to expose a Relay -> TE translator
@Hzfengsy @spectrometerHBH I'd be interested to hear your thoughts on this as I imagine it could have some overlap with the work you're doing on TensorIR. --- [Visit Topic](https://discuss.tvm.apache.org/t/rfc-refactor-the-compile-engine-to-expose-a-relay-te-translator/8417/5) to respond. You are receiving this because you enabled mailing list mode. To unsubscribe from these emails, [click here](https://discuss.tvm.apache.org/email/unsubscribe/95b5dc4cc9876c1ed95a511e952f6b5daa18b1468ce97af60797d7b5b733605f).
[Apache TVM Discuss] [Development] Role of the LLVM autovectorizer in TVM
Yeah. In most cases we can do vectorize in TIR instead of relying on llvm. --- [Visit Topic](https://discuss.tvm.apache.org/t/role-of-the-llvm-autovectorizer-in-tvm/8388/3) to respond. You are receiving this because you enabled mailing list mode. To unsubscribe from these emails, [click here](https://discuss.tvm.apache.org/email/unsubscribe/c3ed85a45230fc0492438092e556ab4e2cb6733b65ac9a008d9880fc1cb61380).
[Apache TVM Discuss] [Development] Quantization and 3D convolution
Could you print out the lowered code? You can use `tvm.lower(s, args)` where `s` is the schedule. Also, if you provide a minimal example to run, I can take a look at it. --- [Visit Topic](https://discuss.tvm.apache.org/t/quantization-and-3d-convolution/8338/5) to respond. You are receiving this because you enabled mailing list mode. To unsubscribe from these emails, [click here](https://discuss.tvm.apache.org/email/unsubscribe/bc39afc4d027078cb076ffdfc75d52feca648126281010446a2c108336d92e56).
[Annoucement] Apache TVM Conference 2020
Dear Community: On behalf of the organizing committee. We are excited to announce that the registration of Apache TVM conference https://tvmconf.org/ is now open You can click the above link for the registration. TQ
[Apache TVM Discuss] [Development/RFC] [RFC] Refactor the compile_engine to expose a Relay -> TE translator
Another requirement I have for the general TE translator is to support an arbitrary Relay function, including the Relay function with more than one reduce op (e.g., conv2d). The current compile engine doesn't allow this pattern because it selects one schedule implementation per Relay function, but this should not be a limitation anymore if you are going to decouple the selection of compute and schedule. However, we probably don't have to cover it in this RFC if that's out of scope to you. --- [Visit Topic](https://discuss.tvm.apache.org/t/rfc-refactor-the-compile-engine-to-expose-a-relay-te-translator/8417/6) to respond. You are receiving this because you enabled mailing list mode. To unsubscribe from these emails, [click here](https://discuss.tvm.apache.org/email/unsubscribe/e4cf31aefab8e0821fa1159e82171e0eceb841adf776d15d17c11f93685e8f8d).
[Apache TVM Discuss] [Development/RFC] Expand Span for imported module
In this PR https://github.com/apache/incubator-tvm/pull/6885, node name is stored in Span.SourceName. Since Span.SourceName is supposed to represent name of source file, I'd suggest to add another field `hint` to Span to represent node or layer name which is common in models. And when model is imported, its name isn't kept by frontend, so Span.SourceName will be left empty in that case. `line`, `colume`, `end_line` and `end_colume` aren't needed too for imported model. @joshua19881228 @jroesch @tqchen @FrozenGene Please share your thought --- [Visit Topic](https://discuss.tvm.apache.org/t/expand-span-for-imported-module/8435/1) to respond. You are receiving this because you enabled mailing list mode. To unsubscribe from these emails, [click here](https://discuss.tvm.apache.org/email/unsubscribe/8798b0e796b8bf2340e3d238669a6923e861571f285f0620cc40da72bb754a2f).
