Optimize alignments

[eu9ene]

• Add Moses tokenization of the corpus to reduce the vocabulary and increase accuracy
• Remap the calculated alignments back to whitespace-tokenized ones expected by OpusTrainer
• Use a fast C++ tokenizer
• Use parallelization with multiprocessing to speed things up

Known issues:

• I tested it on a student 400M corpus on 512GB machine without priors and it didn't OOM, but it took ~2 days to complete
• We can likely make it more scalable by using chunks, especially if we use the priors pre-calculated on the teacher step. However, it will not help with preemptions if we don't split it into multiple tasks
• To run it with existing teachers we'll need to separately run target: alignments-original to recalculate the priors with the new tokenization and then run it again with target: all and existing_tasks: { "alignments-original-src-trg": "<task_id>" }

fixes #507 fixes #663

[eu9ene]

The tests will fail due to https://github.com/mozilla/firefox-translations-training/issues/689

[eu9ene]

It turned out to be hard to restart only the alignments-original, so I added an extra task to recalculate the priors for the student alignments (in a separate branch). I'm testing it here for en-uk https://firefox-ci-tc.services.mozilla.com/tasks/groups/eZKkxqHISTCDwrsylAZZvA. This way we won't need to rerun things multiple times.