Recently, TVM has supported the incoming MXNet 2.0 frontend via a series of PRs: #6054, #6699. This enables the new GluonNLP 1.0, which has upgraded from MXNet 1.x to MXNet 2.0 to convert to TVM graph (as added in dmlc/gluon-nlp#1390). However, I noticed that there are three missing operators when I profile against the BART model.
- _npi_subtract_scalar
- _npi_stack
- _npi_advanced_indexing_multiple
The first two operators are pretty straightforward to support while the _npi_advanced_indexing_multiple is more complicated and is triggered when we call a[idx1, idx2]. The MXNet-side implementation of _npi_advanced_indexing_multiple is here: https://github.com/apache/incubator-mxnet/blob/6bbd53107aa16fc41e8d462cf5dc46fb70d592df/src/operator/numpy/np_indexing_op.cc#L479-L491
Since I do not have the bandwidth in supporting this operator. Help is really appreciated.