mirror of https://github.com/llvm/torch-mlir
895f490cf5
Torch-to-linalg pass fails for `EmbeddingBag` when the training only specific properties of the operator are set to `true.` For instance, this operator's `sparse` input/property is training-specific, and if the value of this property is `true,` the existing lowering bails out. However, we don't need to check for training-specific parameters and bailout from the legalization since we don't care about these properties during the eval/inference mode. --------- Co-authored-by: Hanumanth Hanumantharayappa <hhanuman@ah-hhanuman-l.dhcp.mathworks.com> |
||
|---|---|---|
| .. | ||
| CAPI | ||
| Conversion | ||
| Dialect | ||
| RefBackend | ||
| python | ||
| CMakeLists.txt | ||
| lit.cfg.py | ||
| lit.site.cfg.py.in | ||