Hi JitteryCoyote63

So that I could simply do

task._update_requirements(".[train]")

but when I do this, the clearml agent (latest version) does not try to grab the matching cuda version, it only takes the cpu version. Is it a known bug?

The easiest way to go about is to add:
Task.add_requirements("torch", "==1.11.0") task = Task.init(...)Then it will auto detect your custom package, and will always add the torch version. The main issue with relying on the package requirements, is that the "torch" package will not be automatically get listed in the "installed packages" and the agent will not know it needs to resolve it (when pip resolves torch, it will default to the wrong cpu/cuda version)
wdyt?