mirror of https://github.com/llvm/torch-mlir
0c73c535d6
* This is sufficient to capture the forward and backward pass and gradients of a convolutional model with an nllloss. * As with the forward conv, the backward conv is a special case wrapped in an enigma on the PyTorch side. There aren't many like it, so special casing is just what we do. * When I traced this, I found that the copy_ op is not yet boxing compatible so I had to map it manually. If there are many more like this, I'll probably do something a bit more clever to reduce duplication. * This exposes new signature patterns that will need to be handled by the ATen lowering. Will take care of that next: It will be nice to have an e2e of a non-trivial case with full gradients. * Fixes #97. |
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| .. | ||
| pytorch | ||
| CMakeLists.txt | ||
| README.md | ||
| __init__.py | ||
README.md
NPComp - Frontends
NPComp maintains in-tree frontends for various popular numeric-python based frameworks. In general these are:
- Considered optional components
- Target dialects maintained at the top-level of the project
- Maintained in isolation so as to facilitate moving them out to dedicated projects at an appropriate point of the lifecycle (i.e. if NPComp is successful as a general purpose target for such frameworks, then it may make sense to contribute/build each frontend to their respective up-stream project).
Frontends try to stylistically fit into the outer project except for when it is more clear/advantageous to align them with the conventions of the source project. This is approached on a case by case basis as needed. Deviations should be documented in a local style guide for the frontend.