Quick installation
You can install Quantus in various ways. The different options are listed in the following.
Installing via PyPI
If you already have PyTorch or TensorFlow installed on your machine, the most light-weight version of Quantus can be obtained from PyPI as follows (no additional explainability functionality or deep learning framework will be included):
pip install quantus
Alternatively, you can simply add the desired deep learning framework (in brackets) to have the package installed together with Quantus. To install Quantus with PyTorch, please run:
pip install "quantus[torch]"
For TensorFlow, please run:
pip install "quantus[tensorflow]"
Installing additional XAI Library support (PyPI only)
Most evaluation metrics in Quantus allow for a choice of either providing pre-computed explanations directly as an input, or instead making use of several wrappers implemented in quantus.explain
around common explainability libraries. The
following XAI Libraries are currently supported:
Captum
To enable the use of wrappers around Captum, you can run:
pip install "quantus[captum]"
tf-explain
To enable the use of wrappers around tf.explain, you can run:
pip install "quantus[tf-explain]"
Zennit
To use Quantus with support for the Zennit library, you can run:
pip install "quantus[zennit]"
Note that the three options above will also install the required frameworks (i.e., PyTorch or TensorFlow) respectively,
if they are not already installed in your environment. Note also, that not all explanation methods offered in Captum and tf-explain
are included in quantus.explain
.
Installing tutorial requirements
The Quantus tutorials have more requirements than the base package, which you can install by running
pip install "quantus[tutorials]"
Full installation
To simply install all of the above, you can run
pip install "quantus[full]"
Package requirements
The package requirements are as follows:
python>=3.8.0
torch>=1.11.0
tensorflow>=2.5.0
Please note that the exact PyTorch and/ or TensorFlow versions
to be installed depends on your Python version (3.8-3.11) and platform (darwin
, linux
, …).
See [project.optional-dependencies]
section in the pyproject.toml
file.