In order this to work on AC922 you will need to:

lunch 4x containers only
docker run --runtime=nvidia -e NVIDIA_VISIBLE_DEVICES=0 ibmcom/powerai:1.6.0-pytorch-ubuntu18.04-py3 bash
docker run --runtime=nvidia -e NVIDIA_VISIBLE_DEVICES=1 ibmcom/powerai:1.6.0-pytorch-ubuntu18.04-py3 bash
docker run --runtime=nvidia -e NVIDIA_VISIBLE_DEVICES=2 ibmcom/powerai:1.6.0-pytorch-ubuntu18.04-py3 bash
docker run --runtime=nvidia -e NVIDIA_VISIBLE_DEVICES=3 ibmcom/powerai:1.6.0-pytorch-ubuntu18.04-py3 bash

1TB available RAM will allow expansion of your models for each GPU, up to 90% of the system capacity. With TF you may use 16x GPUs if you max limit the GPU memory utilization / session / container, however this is not available in PyTorch because PyTorch doesn’t pre-occupy the GPU’s entire memory.
Rgds,
FM