mirror of https://github.com/llvm/torch-mlir
993338a12d
Specifically, we use unranked memrefs which get passed as a fixed-size set of arguments/returns. One big caveat about this is that returning results isn't going to work. See TODO in LowerTensorLoadOp. This is far from enough runtime-wise, but it starts to demarcate a plausible layering. Notice for example how this removes the runtime-dependence from LowerRankedShapes. Eventually, we want to have an `npcomp_rt` or `npcomp_hal` dialect with its own set of runtime types that will supercede this. See comments in LowerTensorLoadOp for more direction about where this is going to evolve. |
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| .. | ||
| Conversion | ||
| Dialect | ||
| E2E | ||
| CMakeLists.txt | ||
| lit.cfg.py | ||
| lit.site.cfg.py.in | ||