Docker Images

Valohai utilizes Docker images to package your dependencies. This means that the platform is capable of running any code from C to Python as long as it can run inside a Docker container.

You can use any Docker image accessible through the Internet or build your own.

We recommend hosting your images on Docker Hub but you can use any Docker repository.

Here are the most common Docker images currently used on the platform:

  • tensorflow/tensorflow:1.8.0-devel
  • tensorflow/tensorflow:1.8.0-devel-py3
  • tensorflow/tensorflow:1.8.0-devel-gpu
  • tensorflow/tensorflow:1.8.0-devel-gpu-py3
  • tensorflow/tensorflow:1.7.0-devel-gpu-py3
  • tensorflow/tensorflow:1.7.0-devel-gpu
  • tensorflow/tensorflow:1.7.0-devel-py3
  • tensorflow/tensorflow:1.7.0-devel
  • tensorflow/tensorflow:1.6.0-devel-gpu-py3
  • tensorflow/tensorflow:1.6.0-devel-gpu
  • tensorflow/tensorflow:1.6.0-devel-py3
  • tensorflow/tensorflow:1.6.0-devel
  • valohai/keras:2.1.4-theano1.0.1-python3.6-cuda9.0-cudnn7-devel-ubuntu16.04
  • valohai/keras:2.1.3-tensorflow1.4.0-python3.5-cuda8.0-cudnn6-devel-ubuntu14.04
  • valohai/keras:2.0.0-tensorflow1.0.1-python3.6-cuda8.0-cudnn5-devel-ubuntu16.04
  • valohai/keras:2.0.0-theano0.9.0rc4-python3.6-cuda8.0-cudnn5-devel-ubuntu16.04
  • valohai/keras:2.0.0-theano0.8.2-python3.6-cuda8.0-cudnn5-devel-ubuntu16.04
  • valohai/darknet:62b781a-cuda8.0-cudnn5-devel-ubuntu16.04
  • valohai/darknet:b61bcf5-cuda8.0-cudnn5-devel-ubuntu16.04
  • r-base:3.4.2
  • python:3.6.5
  • python:3.6
  • python:3
  • python:2.7.14
  • python:2.7
  • python:2

Tip

Using these images will result in faster executions since they’re cached on workers.