Executing the Training in Parallel

Sometimes the training of the GMM-based models require a lot of time. However, the training procedures can be parallelized, i.e., by running the E-steps of the EM loop in parallel. For this purpose, we provide a set of scripts verify_gmm.py, verify_isv.py and verify_ivector.py. These scripts integrate perfectly into the bob.bio packages. Particularly, they have exactly the same set of options as documented in Running Biometric Recognition Experiments.

In fact, the scripts above only run in parallelized mode, i.e., either the --grid or --parallel option is required. During the submission of the jobs, several hundred jobs might be created (depending on the number_of_..._training_iterations that you specify in the bob.bio.gmm.algorithm.GMM constructor). However, after the training has finished, it is possible to use the normal verify.py script to run similar experiments, e.g., if you want to change the protocol of your experiment.

Todo

improve the documentation of the parallelized scripts.