Backend libraries

Fully supported

Every component implements this backend

NumPy

numpy provides a powerful yet flexible implementation of n-dimension arrays, and is used as a base by most of the other libraries. It is required by dockerasmus.pdb, since Protein instances have properties and methods that directly return numpy.ndarray objects.

NumPy can only perform computations on the CPU.

Theano

theano is a library which can defined, evaluate, compile and optimise n-dimension array computations. It works seamlessly with NumPy array, but is a lot more efficient than interpreted computations while adding only a light overhead. Theano is very useful to compute the same mathematical expression a lot of times, which is what happend with a scoring function.

Theano can perform computations on the GPU using a configuration file. Read the official documentation to find out how.

Partially supported

Only some components implement these backend

MXNet

mxnet is a deep-learning library developed that supports both symbolic and imperative programming in order to perform efficient computations. It is maintained by the developers previously behind minerva, cxxnet and purine2.

Tensorflow

Considered

Could possibly be implemented as backends

• PyTorch
• PyCUDA

Hint

Know a library not listed here that works well for your other projects ? Submit a feature request to the issue tracker or even better, fork the project, try implementing a backend, add a test, and submit a merge request !