Based on this line of code:
https://github.com/ufal/neuralmonkey/blob/master/neuralmonkey/decoders/output_projection.py#L125

Current implementation isn't flexible enough; if we train a "submodel" (e.g. decoder without attention - not containing any ctx_tensors) we cannot use the trained variables to initialize model with attention defined because the size of the dense layer matrix input become

Documentation of MMT CLI is lacking a lot of small information. Things like:

1. For this command to work:
   ./mmt import -e ENGINE -p SOURCE_FILE TARGET_FILE
   SOURCE_FILE and TARGET_FILE needs to end to language IDs.
   I tried importing files with .txt extension but the number of units in
   curl -X GET http://localhost:8045/memories/imports/00000000-0000-0000-0000-000000000001
   were 1/10th

This could be visualized in another table, where e.g. the confidence of the system across different documents could be compared and contrasted.

Document translation doesn't currently support the old Windows formats. Perhaps there's a quick Python plugin that we can use to perform a conversion on the fly back and forth. This would be best as an enable-able feature so that the library doesn't have to be installed

migrated from https://sourceforge.net/p/apertium/tickets/7/

Distro packaging guidelines prohibit coding language suffixes on binaries, so we might as well remove them from the repo itself to make it consistent.