BCOTrainer version upgrade fixes

[claralp]

What does this PR do?

This PR fixes to some issues that I identified with the BCOTrainer on the latest version upgrade:

• remove extra shuffles, super class already handles data shuffling. These destroy training reproducibility
• fix serialization of UDM classifier, not all parameters were saved previously
• accelerate.gather not hanging on empty lists anymore
• convert delta to tensor before logsigmoid, this led to numeric errors
• do not update delta value in eval mode

Let me know if you have any questions

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Who can review?

@kashif @qgallouedec

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[kashif]

@claralp we will need to add joblib as a dependency?

[claralp]

@kashif yes, but could use pickle as alternative if you prefer. Just BCO with UDM needs this

[PhilipMay]

Well, IMO using joblib is a good idea because it supports pickle with compression with just a line of code. So complexity is reduced. But it can also be a good idea to reduce the number of external dependencies. On the other side joblib is a very common dependency.

So @kashif should decide this. What do you think?

[PhilipMay]

Hey @kashif and @claralp - what about this PR. We should fix the missing dependency somehow. :-)

[PhilipMay]

@claralp since we do not get a response here my suggestion would be to just add joblib to the dependencies so the CI is green. A green CI hopefully then catches enough attention and some progress.

[claralp]

@kashif since I got no reply, I just added the job lib library now everywhere were sklearn is required as well

[kashif]

yes we can add the requirements to a EXTRAS in the setup.py? perhaps a bco?