mirror of https://github.com/alibaba/MNN.git
1eaa7a632b
When converting a caffe model, `ReductionTransform` thinks there're always 4 dims in the input of a `Reduction` layer. However, when forwarding `OpCommonUtils::computeReduceDims` had an assumption that dim numbers wouldn't exceed `inputs[0]->dimensions()`. So, MNN would write unexpected addresses and then crash, if a Reduction op follows a Reshape / InnerProduct op, since both ops may output a tensor of 2 dimensions. _Comment_: I know `TransformInnerProduct` often converts caffe's InnerProduct into 1x1 Convolution, but Reshape can also cause a tensor has only 2 dimensions, so this still deserves a fix. |
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| geometry | ||
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