MKL-DNN integration (in caffe2/mkl) implements only forward pass operators, although MKL-DNN itself provides primitives for both forward and backward pass. Implementation of ConvGradient operator would let Caffe2 use MKL-DNN for training on CPU, and support some models which need backprop (e.g. deep dream).
jspisak
commented
6 years ago
MKL-DNN integration (in caffe2/mkl) implements only forward pass operators, although MKL-DNN itself provides primitives for both forward and backward pass. Implementation of
ConvGradientoperator would let Caffe2 use MKL-DNN for training on CPU, and support some models which need backprop (e.g. deep dream).