mirror of https://github.com/llvm/torch-mlir
b6e551c7b8
For static tests (that is when the shape is know) for example: ``` @annotate_args([None, ([3, 18, 2, 2], torch.float32, True)]) ``` The e2e passes. But only if the replacement op's return type is set as undefined (optional shape and type must be explicitly made unset), otherwise there's a error about the function return type. For dynamic cases, for example if the above is replaced with ``` @annotate_args([None, ([-1, -1, -1, -1], torch.float32, True)]) ``` There is a failure to lower to linalg from torch ("view op explicitly labelled as illegal"). This seems to be because the support for lowering from torch to linalg with dynamic shapes is limited. |
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main.py | ||
xfail_sets.py |