Yes `TVMCPackage` (between the `compile` and `run` steps) sounds like what you
want. It's the deployable artifact. `TVMCModel` is the high level graph
definition. If you wanted to tune a model for a few different hardware targets
you could use the one `TVMCModel` to produce several `TVMCPackag
Ultimately, I'm trying to save off a tuned model as an executable (or something
similar). I'm wondering if this should be done between the `tune` and `compile`
steps, or between the `compile` and `run` steps. However, I'm a little confused
on the difference between the `TVMCModel` and `TVMCPac
Interesting findings! I think we should unify these two sets of APIs because
they show different behaviors and can confuse the users a lot. I did some
measurements on the VM executor recently and found that the code generated by
the second style(`relay.build_module.create_executor`) is much wo
Hello ! I have been reading the `custom_callback` function that autotvm uses to
train the XGBoost cost model.
There are a few things that I would like to ask for clarification if possible:
1. The `init` function checks if the model (bst) has a `best_score` attribute
which as I understand mea
Another thing is that I am still confused about the executors... There are
"graph", "debug" (interpreter), "vm", "aot" ...
Some executor cannot support dynamic shapes (i.e., graph). The default
optimization passes of them are not the same. I think any instructions on which
one should users p
Hi @yuchenj, thank you for your kind reply! I want to confirm some follow-up
questions and report some issues.
It seems in your mentioned line (`Optimize` function, `build_module.cc:303`), a
set of (default I think) passes are given. Is that the case: in `BuildRelay` we
will collect some **de
