The model requires:
If you want to run sockeye on a GPU you need to make sure your version of Apache MXNet Incubating contains the GPU bindings. Depending on your version of CUDA you can do this by running the following:
> pip install -r requirements/requirements.gpu-cu${CUDA_VERSION}.txt
> pip install .
To train the LDGCN model, run (e.g., for AMR2015):
./train_amr15gc.sh
When we finish the training, we can use the trained model to decode on the test set, run:
./decode_amr15.sh
This will use the last checkpoint by default. Use --checkpoints
to specify a model checkpoint file.
We use BPE code. In the postprocessing stage, we need to merge them into natural language sequence for evaluation, run:
./merge_amr15.sh
For BLEU score evaluation, run:
./eval_amr15_bleu.sh