Welcome to pythae’s documentation!¶
This library aims at gathering some of the common (Variational) Autoencoders implementations so that we can conduct benchmark analysis and reproducible research!
News 📢
As of v0.1.0, Pythae now supports distributed training using PyTorch’s DDP). You can now train your favorite VAE faster and on larger datasets, still with a few lines of code. See Distributed Training with Pythae.
Setup¶
To install the latest stable release of this library run the following using pip
$ pip install pythae
To install the latest version of this library run the following using pip
$ pip install git+https://github.com/clementchadebec/benchmark_VAE.git
or alternatively you can clone the github repo to access to tests, tutorials and scripts.
$ git clone https://github.com/clementchadebec/benchmark_VAE.git
and install the library
$ cd benchmark_VAE
$ pip install -e .
If you clone the pythae’s repository you will access to the following:
docs
: The folder in which the documentation can be retrieved.tests
: pythae’s unit-testing using pytest.examples
: A list ofipynb
tutorials and script describing the main functionalities of pythae.src/pythae
: The main library which can be installed withpip
.