Allow the user to reach the search algorithm's internal optimizer

[engintoklu]

With this pull request, algorithms inheriting from the base class GaussianSearchAlgorithm now have a read-only property (named optimizer) that allows the user to reach the internal optimizer object employed by the search algorithm.

By reaching this internal optimizer, the user can now read or modify its hyperparameters.

For example, the learning rate of an internal optimizer (e.g. of Adam or ClipUp) can be retrieved like this:

from evotorch.algorithms import PGPE

my_search_algorithm = PGPE(
    optimizer="adam",  # can also be "sgd" or "clipup"
    ...
)

lr = my_search_algorithm.optimizer.param_groups[0]["lr"]

If one wishes to update the learning rate, the following is possible:

my_search_algorithm.optimizer.param_groups[0]["lr"] = new_lr

[codecov]

Codecov Report

Attention: 20 lines in your changes are missing coverage. Please review.

Comparison is base (9d31d59) 77.83% compared to head (e79e1bc) 77.66%.

Additional details and impacted files

@@            Coverage Diff             @@
##           master      #89      +/-   ##
==========================================
- Coverage   77.83%   77.66%   -0.18%     
==========================================
  Files          49       49              
  Lines        7332     7373      +41     
==========================================
+ Hits         5707     5726      +19     
- Misses       1625     1647      +22     

Files	Coverage Δ
src/evotorch/algorithms/distributed/gaussian.py	83.00% <66.66%> (-0.25%)	⬇️
src/evotorch/optimizers.py	77.20% <50.00%> (-10.55%)	⬇️

... and 1 file with indirect coverage changes

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