Move “common” part to new project biosignal/software/basetorch>

The key idea is to apply DRY to software packages that use PyTorch inside the biosignal/software group. Example packages are:

• biosignal/software/ptbench>
• biosignal/software/deepdraw>

There are several elements that can be shared between these two packages. Most notably:

• Resource monitoring and logging (GPU/CPU utilisation, log files)
• Training and evaluation loops
• Image loading and transformations when applicable
• Base data loading for composed datasets (everything inside the data submodule)
• Common analysis code

One key point to keep track relates to using Pytorch-lightning as base software to implement monitoring, logging and training/evaluation loops. One must decide if we do this now, or later. If done later, we risk to redo and remove common API work to be done now. If done now, at this stage, then one must make sure to implement this through various MRs, each addressing only one aspect so we can keep track of changes.

assigned to @dcarron

Advice: take 30 minutes to 1 hour everyday to study PyTorch-lightning so we can make an informed decision.

mentioned in issue #22