This repo contains sample code for updating Deep Learning models with particle filters.
Details on how to run the notebook are given below, in the Implementation section.
Depend on Docker, a.k.a as {Do}, is an easy to use project template that helps start working quickly on any of your projects. It lets you embed the knowledge you have about your software into a container that hides away complexities and makes it easy to build, ship, and run on Linux or Windows, locally, in a data center, and on any cloud. To accomplish all of it, the only dependency you need is Docker!
Knowing that we don't want to have to set-up the environment for building probabilistic models every time we mode to a different machine, we've package all the necessary dependencies - chiefly Tensorflow and Tensorflow Probability - into our image. Running the Jupyter notebooks become very simple: ./run.sh will get you your own Jupyter Notebook server! After that, simply open Chrome and browse to http://localhost:5555.
For now the project has been built to run CPU only, we'll get to the GPU enabled project soon, hang on tight.
If you're into having the full experience, by building your own image, read-on or click the {Do} link below for the full documentation.
How to {Do} For ease of use, all Docker commands required to use this project have been embedded into intuitively named native shell scripts.
Build Linux: ./build.sh Builds the Docker container image and tags it using the registry and version tag settings specified in your environment file
Ship (push and pull) Linux: ./push.sh or ./pull.sh Pushes or pulls the Docker container image to of from the registry specified in your environment file
Run Linux: ./run.sh [command] Creates a docker container and, if no argument is specified, executes the startup script. If a command line is specified as an argument to the run script, this command line is executed in the container in place of the default startup script.
Logs Linux: ./logs.sh Tails the output of the command executed inside the container. Use Ctrl-C to stop the tail.
Exec Linux: ./exec.sh [command] This script requires a running container to exist. It executes the specified command in the running container. If no command is specified as an argument, then a default command is executed to open a new interactive shell within the container.
Status Linux: ./status.sh This script shows the current status of the Docker container including any mapped ports.
Stop Linux: ./stop.sh Stops the container and cleans up its files.