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I'm trying to get an inception-resnet-v2 network running on the movidius stick, but it gives me a NaN result.
I'm using caffe for this one, not tensorflow. Gotten from https://github.com/soeaver/caffe-model/blob/master/cls/inception/deploy_inception-resnet-v2.prototxt
I'm using it pretrained, and replaced the final fully connected layer to train it on our own data. All other weights are not changed during training.
I tried pinpointing where it goes wrong and the Eltwise layer 'inception_resnet_v2_a1_residual_eltwise' seems to be the first where the result of caffe and the result of ncs seem to differ significantly (180%, compared to 0.5% the layers before). Which eventually leads to consistent NaN outputs at the end of the network.
This is my prototxt:
This is the pretrained network: