| ================== | |
| Installation | |
| ================== | |
| ``EasyTPP`` provides an open-source library for `Neural TPP`, with a fully automated pipeline for model training and prediction. | |
| Requirements | |
| ============= | |
| .. code-block:: bash | |
| PyTorch version >= 1.8.0 | |
| Python version >= 3.7 | |
| Tensorflow version >= 1.13.1 (only needed when using Tensorflow backend) | |
| First, we need a python environment whose version is at least greater than 3.7.0. If you don’t have one, please refer to the `Documentation <https://docs.anaconda.com/anaconda/install/>`_ to install and configure the Anaconda environment. | |
| .. code-block:: bash | |
| conda create -n easytpp python=3.8 | |
| conda activate easytpp | |
| Then, install Pytorch and keep the version at least greater than 1.8.0. | |
| .. code-block:: bash | |
| pip install torch | |
| By default, we assume to use PyTorch. If one wants to use Tensorflow backend, please install tensorflow additionally. Both Tensorflow 1.13.1 and 2.x are supported. | |
| .. code-block:: bash | |
| pip install tensorflow | |
| Install | |
| ===================== | |
| Install with pip | |
| -------------------------- | |
| .. code-block:: bash | |
| pip install easy-tpp | |
| Install with the source | |
| -------------------------- | |
| Setup from the source: | |
| .. code-block:: bash | |
| git clone https://github.com/ant-research/EasyTemporalPointProcess.git | |
| cd EasyTemporalPointProcess | |
| python setup.py install | |