agda2train: An Agda backend to generate training data for machine learning

This is work in progress and a neural network trained on these data to provide premise selection is under way.

How to run

The agda2train package is published on Hackage, so one can simply:

$ cabal install agda2train
$ agda2train SomeFile.agda

Run agda2train --help to see the available flags; apart from the standard flags inherited by the agda executable we get the following backend-specific options:

$ agda2train --help
...
agda2train backend options
  -r      --recurse               Recurse into imports/dependencies.
  -x      --no-json               Skip generation of JSON files. (just debug print)
          --ignore-existing-json  Ignore existing JSON files. (i.e. always overwrite)
          --print-json            Print JSON output. (for debugging)
          --no-terms              Do not include definitions of things in scope
  -o DIR  --out-dir=DIR           Generate data at DIR. (default: project root)

Alternatively, assuming a working Haskell installation (cabal available), one can clone this repo and use the provided Makefile to build the package locally, as well as run our test suite:

$ git clone git@github.com:omelkonian/agda2train.git
$ cd agda2train
$ make build # build package
$ make install # install `agda2train` executable
$ make test # run the test-suite (based on golden files in `test/golden/*`)
$ make repl # REPL for developers
$ make allTests # extract JSON data from all example files in `test/*`
$ make stdlib # extract JSON data from Agda's standard library

Relevant Agda issues

• Type-on-hover #516
• Step-by-step evaluation #4747
• Reverting projection-like optimization #5142