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  • NVIDIA
    UNet Medical for TensorFlow2
    Resource
    NVIDIA
    UNet Medical for TensorFlow2

    U-Net allows for seamless segmentation of 2D images, with high accuracy and performance.

  • Changelog

    June 2020

    • Updated training and inference accuracy with A100 results
    • Updated training and inference performance with A100 results

    February 2020

    • Initial release

    Known issues

    • Some set-ups suffer from a ncclCommInitRank failed: unhandled system error. This is a known issue with NCCL 2.7.5. The issue is solved in NCCL 2.7.8, which can be applied by changing the first line the Dockerfile from ARG FROM_IMAGE_NAME=nvcr.io/nvidia/tensorflow:20.06-tf2-py3 to ARG FROM_IMAGE_NAME=nvcr.io/nvidia/tensorflow:20.08-tf2-py3 and rebuilding the docker image.
    • For TensorFlow 2.0 the training performance using AMP and XLA is around 30% lower than reported here. The issue was solved in TensorFlow 2.1.

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