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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| .. | ||
| CMakeLists.txt | ||
| acap_dispatch.cpp | ||
| acap_dispatch.h | ||
| debug.cpp | ||
| debug.h | ||
| func_builder.cpp | ||
| func_builder.h | ||
| module_builder.cpp | ||
| module_builder.h | ||
| python_bindings.cpp | ||