Using multiple executors

You will be aware that there are many features of TensorFlow, including computational graphs that lend themselves naturally to being computed in parallel. Computational graphs can be split over different processors as well as in processing different batches. We will address how to access different processors on the same machine in this recipe.

Getting ready

For this recipe, we will show you how to access multiple devices on the same system and train on them. This is a very common occurrence: along with a CPU, a machine may have one or more GPUs that can share the computational load. If TensorFlow can access these devices, it will automatically distribute the computations to multiple devices via a greedy...