scripts

Experiments

Data filtering, split and pre-processing

Run the following command. This will clean the raw NL2Bash corpus and apply filtering, create the train/dev/test splits and preprocess the data into the formats taken by the Tensorflow models.

make data

To change the data-processing workflow, go to data and modify the utility scripts.

Train the models

make train

Generate evaluation table using pre-trained models

Decode the pre-trained models and print the evaluation summary table.

make decode

Skip the decoding step and print the evaluation summary table from the predictions saved on disk.

make gen_manual_evaluation_table

By default, the decoding and evaluation steps will print sanity checking messages. You may set verbose to False in the following source files to suppress those messages.

encoder_decoder/decode_tools.py
eval/eval_tools.py