svm training improvement 2

[franklevasseur]

About

This PR is part of a sequence of PR's with name svm training improvement $n that presents few improvements or combination of improvements as attempts to make training faster and consume less memory.

⚠️⚠️ Do not merge this PR as we first need to compare with other attempts first. ⚠️⚠️

Description

This PR mixes #88 with the following improvement:

We train one intent classifier per context. Currently all those classifiers are trained sequentially. However, there is no arm in training them concurrently as the amount of concurrent trainings is limited by the MLThreadPool class located in ml-thread-pool/index.ts file:

const maxMLThreads = Math.max(os.cpus().length - 1, 1) // ncpus - webworker
const userMlThread = process.env.BP_NUM_ML_THREADS ? Number(process.env.BP_NUM_ML_THREADS) : 4
const numMLThreads = Math.min(maxMLThreads, userMlThread)

Performance

On clinc150 using local lang server with dimension 100:

branch	memory used (mb)	time to train (s)
master	~800	101
this	~700	240

On John Doe* using remote lang server https://lang-01.botpress.io

branch	memory used (gb)	time to train (min)
master	~40	20
this	<2	38

• John Doe is an internally-known really big bot

Overall, it's fair to say that there is no major speed improvement from #88.