I’m currently testing a pre-trained ResNet101 model and I’m interested in profile it and deploy it using CPU only. So my focus is on optimizing the model as much as possible.
I’ve installed MXNet with MKL support and everything seems to work properly. But anytime I set MXNET_SUBGRAPH_BACKEND=MKLDNN, inference time increase almost by 3 times compared to inference without subgraph optimization.
Moreover, I’ve noticed that disabling one specific type of fusion (MXNET_DISABLE_MKLDNN_FUSE_CONV_BN=1) solves the issue. Of course, by disabling the fusion, there’s no improvement on the inference time.
What could be the root cause of this issue?