For installation, see the installation instructions.

Poseidon Tutorial

Poseidon is designed to be able to run on a variety of different clusters. This tutorial contains two cluster examples: AWS and a private cluster.

In this tutorial, we will use CIFAR-10, which is a common benchmark in machine learning for image recognition using convolutional neural networks (CNN). The following url provides a description of TensorFlow’s implementation: https://www.tensorflow.org/versions/r1.0/tutorials/deep_cnn/.

Download the Model Script

The model we will use for Cifar10 is created by the TensorFlow team. Clone the git repository for each node you will use for Poseidon. Since Poseidon is currently set up for v1.0.1, we must also roll back the model repository (the repository isn’t versioned along with TensorFlow).

git clone https://github.com/tensorflow/models.git
git reset --hard 4364390adbf16b57c093a05217897831f48da7d3

For reference later, save the model directory that you just cloned into $TF_MODEL_HOME for reference later:

export TF_MODEL_HOME="`pwd`/models"

The script is designed to download Cifar10 automatically. To test everything is installed correctly (and download the data), we can run cifar10_train.py directly: python $TF_MODEL_HOME/tutorials/image/cifar10/cifar10_train.py

Data

Once you have tested cifar10_train.py with the above call, the data should have downloaded to /tmp/cifar10_data. Copy this data onto each node you wish to run Poseidon on to skip the download step during Poseidon execution.

Launch Poseidon

The first tutorial covers configurations specific to Amazon Web Service EC2 service. The second describes configurations when running on a local network.

• Poseidon on AWS Cluster
  • Training
  • Poseidon Logs
• Poseidon on a Private Cluster
  • Training
  • Poseidon Logs

Evaluating

Poseidon’s evaluating procedure is the same as TensorFlow’s. Run the evaluation script:

python $TF_MODEL_HOME/tutorials/image/cifar10/cifar10_eval.py