FrozenGene commented on issue #4828: [QNN][TFLite] TFLite rounding mode support URL: https://github.com/apache/incubator-tvm/pull/4828#issuecomment-596177857 > > CI's LLVM is LLVM 4.0. I think we should supply `quantized add` so that we avoid it is just a lucky. > > Just tested, it's a lucky case indeed. > BTW, is it possible to follow tensorflow to have a specific llvm version for each tvm release to avoid > certain problems like this? To avoid lucky case, when we support TFLite rounding, we could change the `data = get_real_image(224, 224)` to ```python np.random.seed(0) data = np.random.random_integers(low=0, high=128, size=(1, 224, 224, 3)).astype('uint8') ``` back. For LLVM version, I think we can not at least currently. We support different LLVM versions on TVM. We have the check in `FindLLVM.cmake` to make sure the minimal requirement is 4.0. Could you dig it more? If we can make sure it is the bug of LLVM, we then can discuss how to deal with this case.
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