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I've been working with Keras and Tensorflow for about a year now, but I'm fairly new to the NCS, and have basically only been building and running the examples on the stick. I have a simple MNIST example built and trained using Keras up and running, but as soon as I start adding more complex layers, such as BatchNormalization it breaks. I have seen many tricks involving manually traversing the graph and removing offending nodes or changing types of nodes, but none of those solutions have worked for me. (To be fair, I really don't know what I'm doing...) I built a super simple example project that demonstrates the problem: https://github.com/kajohansson/keras_ncs_batchnorm_fail
If anyone can point me in the right direction I'd be very happy! Perhaps an end-to-end implementation of mobilnet v1 in Keras that is known to run on NCS? Or should I learn Caffe? Any pointers welcome!
My end goal is to have a network based on mobilenet v1, pretrained on imagenet, with the output completely replaced by something else than the normal classifier.
Thanks in advance!