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FROM quay.io/pawsey/tensorflow:2.12.1.570-rocm5.6.0
To pull the image to your local desktop with Docker you can use:
$ docker pull quay.io/pawsey/tensorflow:2.12.1.570-rocm5.6.0
To know more about our recommendations of container builds with Docker and later translation into Singularity format for their use in Setonix please refer to the Containers Documentation.
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Here, the training distribution takes place on 16 GPUS (8 GPUs per node). Note the use of the TensorFlow environment variables TF_NUM_INTEROP_THREADS and TF_NUM_INTRAOP_THREADS to control the real number of threads to be used by the code (we recommend to leave them as 1). (Note that the resource request for GPU nodes is different from the usual Slurm allocation requests. Please refer to the page Example Slurm Batch Scripts for Setonix on GPU Compute Nodes for a detailed explanation of resource allocation on GPU nodes).
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