A compiler of a Differentiable Functional Language.
I am providing code in the repository to you under an open source license. Because this is my personal repository, the license you receive to my code is from me and not my employer (Facebook).
The goal of this project is to explore relation between programs and structures of neural networks.
There clearly is a correspondence between execution of a program, written in functional paradigm, and flow of data in a neural network. I've already applied this idea to design of sophisticated networks (see the FNN language), which could learn non-trivial algorithms.
This repository is a next iteration of the research. I'll try to implement a compiler of a differentiable functional language with a haskell-like syntax.
Currently the project is under development, but one can check it out, build and test:
stack build # Build the project
stack test # Run tests
stack haddock # Build documentation
stack run my_file.dfl # Run the compiler
stack run my_file.dfl -- -d # Run the compiler and produce
# debug output for every step of
# compilation
This project is licensed under the MIT License - see the LICENSE file for details.