In our use-case, we believe we can benefit from modifying the
native_client source code to include orthographical rules about how the alphabet is to be used (e.g. our phonemes always comes in consonant-vowel pairs).
We would like to enforce these rules by modifying the C++ code underlying the native client, but in order to test and deploy these changes we first have to be able to build the native client from scratch.
My understanding is that the only way to do this is to compile tensorflow from scratch locally, and then have it build the native client from the source code. So far, building tensorflow has been a mission, even on a fairly regular GPU instance on AWS. In our team, we use Docker as standard, so we are planning to containerise the tensorflow build as well.
Up until now, we’ve been grabbing tensorflow from taskcluster, but if we need to build from scratch this no longer works.
My questions are:
- Has anyone else tried to build the native client from scratch?
- Does this sound like the correct approach for what we want to achieve?
- Any tips about how to do this well?
- How should we think about following changes to the mozilla fork of tensorflow? Is it fairly stable/safe to update from, or should we expect occasional major changes resulting in a lot of work on our end to re-sync things if we want to stay up to date (e.g. with respect to Paddle Paddle CTC updates etc)