SIANA TensorFlow/Keras Docker for CPU-Host

This repo is used to build a docker image for deep-learning development targeting TensorFlow 2.0 with Keras.

At its core, it includes the lastest versions of TensorFlow and Keras. In addition, several typical packages are included to help with parsing data (images and audio, refer to the Dockerfile for details.)

Pre-requisites

Notes:

• the following instructions were tested on Linux/Ubuntu 18.04
• the following instructions assumed the root path under: ~/docker-tf2-cpu

You will need:

• to install Docker Engine

Running the container

To run the container, simply run:

foo@bar: ~/docker-tf2-cpu$ make bash

From the terminal, you can then run your TensorFlow/Keras python scripts.

The doker container maps /src/workspace/ to your ~/docker-keras-cpu folder on the host side.

Note: review the Makefile targets for different runtime options.

Building the image

Open a terminal into your ~/docker-keras-cpu and run:

 foo@bar: ~/docker-tf2-cpu$ make build

Docker will launch and proceed to build a new image named: "docker-tf2-cpu"

On completion, you should see the new image listed:

foo@bar: ~/docker-tf2-cpu$ docker image list