I’m new to RASA and machine learning in general, meaning I got it up and running and created a relatively simple bot with it, but I’m still fuzzy on the details about how exactly it works.
Because the CPUs on my own computers do not support AVX, and I wanted to use the supervised pipeline, I am at the moment doing my development on a VPS.
I had the assumption that once I had trained a model I was happy with, I would then be able to deploy the bot (using the REST channel for instance) on my outdated laptops, in other words I assumed tensorflow would only be a requirement to train the bot, but not to make it run. So you can imagine I was slightly disappointed when
docker run -v $(pwd)/models:/app/models rasa/rasa:latest run
gave me the good old
The TensorFlow library was compiled to use AVX instructions, but these aren't available on your machine.
My question is therefore two fold:
- Could someone explain why is tensorflow required at runtime ?
- Is there anyway around it?
- Or as an alternative, could one have a RASA core runtime depending on a tensorflow version prior to 1.5 - so it would not need AVX support - (I checked on Github, couldn’t find one), but using a model trained by the latest stable version of RASA and tensorflow ?
Thank you for your time!