mir-am / lambdanet

Probabilistic Type Inference using Graph Neural Networks

This is the source code repo for the ICLR paper LambdaNet: Probabilistic Type Inference using Graph Neural Networks.

After cloning this repo, here are the steps to reproduce our experimental results (todo: provide scripts for these actions):

• download the Typescript projects used in our experiments
• filter and prepare the TS projects into a serialization format
• start the training

Our main results are present in the paper. The Typescript files used for manual comparison with JSNice are put under the directory data/comparison/.

Instructions

Running trained models

To run pre-trained LambdaNet models, check the file src/main/scala/lambdanet/RunTrainedModel.scala and change the parameters under the todo comments depending on which model you want to run and where your target TS files are located, then run program with this class as the main class (sbt "runMain lambdanet.RunTrainedModel").

Model weights can be downloaded here (todo).