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I just this morning gave up trying to compile Tensorflow from sources with AVX. I'm sure I could do it given the time but after 5 minutes it was clearly a more complicated project. Shame it may break older CPUs though, I wonder what the challenge is in releasing two versions?
What is eager execution?
https://github.com/tensorflow/tensorflow/tree/r1.5/tensorflo... > Eager execution is an experimental interface to TensorFlow that provides an imperative programming style (à la NumPy). When you enable eager execution, TensorFlow operations execute immediately; you do not execute a pre-constructed graph with Session.run().
Good to see it, been running tf-nightly, cuda 9.1 nvidia gpu drivers with cuda 8. The entire dependency issues between drivers/apps/libraries have been incredibly annoying.
Good news for me: "Starting from 1.6 release, our prebuilt binaries will use AVX instructions. This may break TF on older CPUs." I just this morning gave up trying to compile Tensorflow from sources with AVX. I'm sure I could do it given the time but after 5 minutes it was clearly a more complicated project. Shame it may break older CPUs though, I wonder what the challenge is in releasing two versions?
https://gist.github.com/daniel-j-h/b410dd21d4949a54c83d0c386...
The build script needs slight adaptions between major TensorFlow releases; otherwise works great for me so far.
During boot time you can then figure out the instance architecture you are and fetch the appropriate wheel. Hope it helps.