Welcome to RET (ROCm Enablement Tool)

RET is a comprehensive checking, set up, installation, testing and benchmarking tool which does carry out the installation of ROCm suite ranging from dependencies, drivers and toolchain to framework and benchmark. RET makes the process of carrying out automated ROCm installation incredibly simple and provides a more user friendly and faster installation experience.

• INSTALL OS
• RUN ret
• RUN your Tensorflow benchmark OR TRAIN your own model with tensorflow

Hardware Support and supported GPU

please refer to ROCm main repository at https://rocm.github.io/ROCmInstall.html.

Getting started

Supported OS

• Ubuntu:
  • 16.04
  • 18.04
• CentOS 7.6 # Tensorflow run on Docker

Prerequisites

Note: it is required to start with a clean system

Formatting a hard drive along with the install of a new OS is the best option after the instllation you will need git to download the RET source

  sudo apt -y install git

Note: DO NOT update and upgrade your system

Clone repository

   git clone https://github.com/rocmsys/RET.git

Usage:

sudo ./ret  <command\> <option>
e.g.
sudo ./ret install rocm or sudo ./ret install tensorflow
sudo reboot
rocminfo

• command:

  •       [install] <package>              : Install ROCm or ML Framework TF/PT
          [remove]  <package>              : Remove ROCm or ML Framework TF/PT
          [benchmark] <Packages> <Model>   : Run benchmark for specific ML Framework${END}"
    

  • packages:

    •    [rocm]                      : ROCm-dkms packages
         [tensorflow]                : Tensorflow framework
      

  • Model:

    • [vgg16]                      : vgg16 model${END}"
      [alexnet]                    : alexnet model${END}"
      [resnet50]                    : resnet50 model. Default Model${END}"
      

• Options:

  •        [-py2|-py3]                     : ${FG_LIGHT_BLUE}: Python version. Default is Python3${END}"
           [-h|--help]                     : Show this help message
           [-v|--version]                  : Show version of this package
           [-V|--verbose]                  : Be verbose
           [-b|--benchmark]                : Run benchmark
    

RUN RET:

   cd RET
   sudo ./ret install rocm         # install ROCm stack
   sudo reboot
   sudo ./ret install tensorflow   # install Tensorflow

Tensorflow's tf_cnn_benchmarks

Details on the tf_cnn_benchmarks can be found at this Link.

Here are the basic instructions:

sudo ./ret benchmark tensorflow resnet50  # run it direct

OR
# Download your Benchmark
# Grab the repo
cd $HOME
git clone -b cnn_tf_v1.13_compatible https://github.com/tensorflow/benchmarks.git
cd benchmarks
# Run the training benchmark (e.g. ResNet-50)
python3 ./scripts/tf_cnn_benchmarks/tf_cnn_benchmarks.py --model=resnet50  --batch_size=256 --num_batches=50 --use_fp16=True --datasets_use_prefetch=False --display_every=10

**Note:** You may need to add your GPU number --num_gpus=<your GPU number>