add DataLoader related parameters to fit() and predict()

[BohdanBilonoh]

Checklist before merging this PR:

• Mentioned all issues that this PR fixes or addresses.
• Summarized the updates of this PR under Summary.
• Added an entry under Unreleased in the Changelog.

Summary

Add torch.utils.data.DataLoader related parameters to fit() and predict() of TorchForecastingModel

[codecov]

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 93.77%. Comparing base (0a72bf6) to head (719b7ab).

Additional details and impacted files

@@            Coverage Diff             @@
##           master    #2295      +/-   ##
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- Coverage   93.79%   93.77%   -0.02%     
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  Files         138      138              
  Lines       14288    14274      -14     
==========================================
- Hits        13401    13386      -15     
- Misses        887      888       +1     

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[madtoinou]

Hi @BohdanBilonoh,

It looks great, however to make it easier to maintain and more exhaustive, I think that it would be great to just add an argument called dataloader_kwargs, then check that the argument explicitly used by Darts are not redundant/overwritten and then pass this argument down to the DataLoader constructor.

It will allow users to specify more than just prefetch_factor, persistent_workers and pin_memory, while limiting copy-pasting from other library documentation (putting a link to the torch.DataLoader page does sound like a good idea for this argument however)

PS: Apologies for taking so long with the review of this PR.

[joshua-xia]

Hi @BohdanBilonoh, Would you please add multiprocessing_context parameter for Dataloader, it is useful when we use multi-workers for dataloader, Thanks!

[joshua-xia]

Hi @BohdanBilonoh, Would you please add multiprocessing_context parameter for Dataloader, it is useful when we use multi-workers for dataloader, Thanks!

@BohdanBilonoh refer to #2375

[joshua-xia]

Hi @BohdanBilonoh, Would you please add multiprocessing_context parameter for Dataloader, it is useful when we use multi-workers for dataloader, Thanks!

@BohdanBilonoh refer to #2375

@BohdanBilonoh My bad, it is good idea from @madtoinou to add dataloader_kwargs to let user input dataloader parameters as wish freely, not need to support special multiprocessing_context parameter forcibly