@tqchen, I tried to add ONNX as target, but since target codegen receives
lowered IRModule with PrimFunc nodes, I am not able to convert those to ONNX.
However, as in the case of external codegen lowering is deferred to external
codegens, I am receiving IRModule without PrimFunc nodes and I am
Thanks for sharing the ideas.
https://discuss.tvm.ai/t/discuss-module-based-model-runtime-interface/5025 is
the current proposed way for universal packaging, and that should resolve most
of the current concerns.
While it is always possible to introduce another layer of abstraction for
packag
Hi All!
**Introduction:**
In this RFC, i like to propose an independent module inside TVM which will have
key responsibility towards handling all the deliverables from TVM
compiler(Relay Build) and offer an user friendly way to save, upload, reuse an
TVM compiled library.
**Motivation/Backg
It is a missing feature. Rules should be added to
https://github.com/apache/incubator-tvm/blob/master/python/tvm/relay/quantize/_annotate.py
and
https://github.com/apache/incubator-tvm/blob/master/src/relay/quantize/calibrate.cc
For performance part, you might also need to take a look of `conv
