Tensorflow benchmarks cause error when running run_forward_backward

[atinzad]

Tensorflow benchmarks cause error when running run_forward_backward

[jbalma]

This might not help, but worth a try. I've seen this in a bunch of the models from the tensorflow/models repo after upgrading to tensorflow-v1.0, but it looks like you're using 0.12 anyways. For me, I was seeing this Shapes(n,m,1,1) and (1,1) are incompatible. It seemed to me to be related changes to argument ordering made in tensorflow-v1.0 to some of the routines, including loss and one of the softmax routines. So I'm immediately suspicious of that tf.concat() call needing the arguments swapped or something added/removed. I had to rearrange arguments for a few routines if I recall.

Where did you get your benchmark_alexnet.py? If was built with a tf-v1.0 instead of 0.12, this might explain it. I believe the tensorflow guys have a script for making other python scripts v1.0 compatible. You could try upgrading to tensorflow-v1 and see if this fixes the problem.

In benchmark_alexnet.py, try changing the order of the loss arguments, or use slim (I've had luck with this approach):

import tensorflow.contrib.slim as slim

See available functions here: https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/slim

Good luck