I work in an environment in which computational resources are shared, i.e., we have a few server machines equipped with a few Nvidia Titan X GPUs each.
For small to m
Shameless plug: If you install the GPU supported Tensorflow, the session will first allocate all GPU whether you set it to use only CPU or GPU. I may add my tip that even you set the graph to use CPU only you should set the same configuration(as answered above:) ) to prevent the unwanted GPU occupation.
And in an interactive interface like IPython and Jupyter, you should also set that configure, otherwise, it will allocate all memory and left almost none for others. This is sometimes hard to notice.