Great! Thanks for the reply @vinx13. At the moment we will rather try to avoid
using conv2d_transpose operators if possible. If this can't work for any
reason, I must look into adding this operator to the quantizer.
---
[Visit
Topic](https://discuss.tvm.ai/t/quantization-add-support-for-c
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
Hi all!
I'm using TVM for post training quantization and noticed that as of now,
**conv2d_transpose** operations **can not be quantized** and fall back to
float32.
* Is there a limitation behind this or is it simply a missing feature?
* If it's a missing feature, which parts of the code would
