Installation instructions

Installation instructions#

DeepSensor is a Python package that can be installed in a number of ways. In this section we will describe the two main ways to install the package.

Install DeepSensor from PyPI#

If you want to use the latest stable release of DeepSensor and do not want/need access to the worked examples or the package’s source code, we recommend installing from PyPI.

This is the easiest way to install DeepSensor.

pip install deepsensor

Note

We advise installing DeepSensor and its dependencies in a python virtual environment using a tool such as venv or conda (other virtual environment managers are available).

Install DeepSensor from source#

Note

You will want to use this method if you intend on contributing to the source code of DeepSensor.

If you want to keep up with the latest changes to DeepSensor, or want/need easy access to the worked examples or the package’s source code, we recommend installing from source.

This method will create a DeepSensor directory on your machine which will contain all the source code, docs and worked examples.

  • Clone the repository:

    git clone https://github.com/alan-turing-institute/deepsensor

  • Install DeepSensor:

    pip install -v -e .

Install PyTorch or TensorFlow#

The next step, if you intend to use any of DeepSensor’s deep learning modelling functionality, is to install the deep learning backend of your choice. Currently, DeepSensor supports PyTorch or TensorFlow.

The quickest way to install these packages is with pip (see below), although this doesn’t guarantee GPU functionality will work (asssuming you have a GPU). To access GPU support, you may need to follow the installation instructions of these libraries (PyTorch: https://pytorch.org/, TensorFlow: https://www.tensorflow.org/install).

To install tensorflow via pip:

pip install tensorflow
pip install tensorflow_probability[tf]

To install pytorch via pip:

pip install torch
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