mirror of https://github.com/llvm/torch-mlir
dcb48dd46c
The LpNormalization lowering was previously just computing the norm, which is incorrect. This computes the norm then divides the input tensor by it's norm. I've tested this against some simple onnx models locally. I'll look into adding a test case for this in an external test suite. |
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CAPI | ||
Conversion | ||
Dialect | ||
RefBackend | ||
python | ||
CMakeLists.txt | ||
lit.cfg.py | ||
lit.site.cfg.py.in |