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ADAPT is the open source white-box testing framework for deep neural networks

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ADAPT

ADAPT is an open source white-box testing framework for deep neural networks, which is first introduced in Effective White-Box Testing for Deep Neural Networks with Adaptive Neuron-Selection Strategy.

Docker

ADAPT offers a docker image with pre-installed ADAPT. If you want to install docker, please see here. Instructions for GPU support for Docker can be found in here. Following command will download an image.

$ docker pull ghcr.io/kupl/adapt

You can see the downloaded image with the following command.

$ docker images
REPOSITORY              TAG                           IMAGE ID            CREATED             SIZE
ghcr.io/kupl/adapt      latest                        ...

Docker container

To open a bash using the docker image, use the following command.

$ docker run --rm -it ghcr.io/kupl/adapt bash

If no commands are pass to docker, jupyter notebook server will be launched. The command will open a server at http://localhost:8888/. If you are using a server, replace localhost with the ip address (or domain) of your server.

$ docker run -p 8888:8888 ghcr.io/kupl/adapt

Build docker image

If you want to build your docker image by yourself, the following command will download this repository and create a docker image with a tag of adapt.

$ git clone https://github.com/kupl/adapt.git
$ cd adapt
$ docker build . --tag adapt

Local Installation

If you do not prefer docker, or want to implement your own idea based on ADAPT, you can install ADAPT in your local machine. First, download this repository using git.

$ git clone https://github.com/kupl/adapt.git
$ cd adapt

ADAPT uses Tensorflow 2.0. To install Tensorflow 2.0, you need a pip>=19.0. The following commands will create a virtual environment and update pip with the Ubuntu machine. If you successfully create a virtual environment, your shell will be prefixed by (venv). Updating system pip using pip can cause some problems, so using virtual enviroment is highly recommended. More detailed instructions, including instructions about setting GPU acceleration, can be found in here.

$ sudo apt update
$ sudo apt install python3-dev python3-pip python3-venv
$ python3 -m venv --system-site-packages ./venv
$ source ./venv/bin/activate
(venv) $ pip install --upgrade pip

Install ADAPT with the following command. ADAPT will automatically install all dependancies, including tensorflow.

(venv) $ pip install .

To deactivate the virtual environment, type the following command. Then, (venv) in front of your shell will disappear.

(venv) $ deactivate

Jupyter notebook

The following command will install jupyter notebook in your virtual environment.

(venv) $ pip install notebook

To launch jupyter notebook server, type the following command.

(venv) $ jupyter notebook
# If you are using a server machine, use following command instead of above one, and visit http://(your server's ip address or domain):8888.
(venv) $ jupyter notebook --ip 0.0.0.0

If your machine have jupyter notebook installed in system-wide, you can install a kernel with the following commands.

(venv) $ pip install -I ipykernel
(venv) $ python -m ipykernel install --user --name adapt --display-name ADAPT

Now, you can see the ADAPT entry when you create a new notebook.

Tutorial

ADAPT offeres some tutorials at tutorial.

Issues

We are welcome any issues. Please, leave them in the Issues tab.

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ADAPT is the open source white-box testing framework for deep neural networks

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