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We rely on the ASL paper's code here and have included it below just to make the process easier.

Installation

Install all ASL paper dependencies.

pip install git+https://github.com/mapillary/[email protected]

Running the experiments

You can use the scripts run-bsl.sh and run-dft.sh to train the BSL and DFT models, correspondingly. Set the SEED environment variable to change the random state.

export SEED=0
mkdir -p logs
./run-bsl.sh
./run-dft.sh

Verifying results

# Verification via the LP is parallelisable (the larger you can afford to make NUM_PROC, the better)
export MLBL_NUM_PROC=10
./eval.sh