Add PyCMAEvolutionStrategy for using pycma in ES emitters

[btjanaka]

Description

Currently, we only provide our custom implementation of CMA-ES for use with emitters like EvolutionStrategyEmitter. This PR instead makes it possible to use the pycma implementation of CMA-ES, which provides many more features.

In emitters, pycma can now be used by passing es="pycma_es" as an argument.

pycma can be installed separately with pip install cma; this PR also provides an extra for installing it with pip install ribs[pycma]. I have also added cma under the all extra; I believe it is a good idea to have the pycma extra and have cma under the all extra because pycma is fairly stable, so depending on it should be fine.

TODO

• [x] Add extra for installing pycma
• [x] Register pycma in ribs.emitters.opt
• [x] Implement PyCMAEvolutionStrategy
• [x] Benchmark PyCMA-ME on sphere -> tends to do slightly better but much slower
• [x] Write tests

Example Outputs

(These are fairly consistent across runs)

cma_me_imp (set the es parameter to cma_es or pycma_es inside sphere.py):

Our CMA-ES:

Create Scheduler for cma_me_imp with learning rate 1.0 and add mode batch, using solution dim 20, archive dims (500, 500), and 15 emitters.
Iteration 250 | Archive Coverage: 18.436% QD Score: 4422557.102
Iteration 500 | Archive Coverage: 29.236% QD Score: 6886947.626
Iteration 750 | Archive Coverage: 40.558% QD Score: 9295140.818
Iteration 1000 | Archive Coverage: 55.431% QD Score: 12105614.271
Iteration 1250 | Archive Coverage: 65.508% QD Score: 13774296.004
Iteration 1500 | Archive Coverage: 72.332% QD Score: 14767106.638
Iteration 1750 | Archive Coverage: 78.571% QD Score: 15628185.304
Iteration 2000 | Archive Coverage: 81.630% QD Score: 16075205.193
Iteration 2250 | Archive Coverage: 84.147% QD Score: 16391622.812
Iteration 2500 | Archive Coverage: 86.269% QD Score: 16764425.062
Iteration 2750 | Archive Coverage: 88.213% QD Score: 17039262.660
Iteration 3000 | Archive Coverage: 90.166% QD Score: 17342512.202
Iteration 3250 | Archive Coverage: 91.337% QD Score: 17505068.566
Iteration 3500 | Archive Coverage: 92.187% QD Score: 17611056.311
Iteration 3750 | Archive Coverage: 92.411% QD Score: 17638383.915
Iteration 4000 | Archive Coverage: 92.882% QD Score: 17685042.031
Iteration 4250 | Archive Coverage: 93.278% QD Score: 17764361.816
Iteration 4500 | Archive Coverage: 93.398% QD Score: 17792564.912
100%|███████████████████████████████████████████████████████| 4500/4500 [00:37<00:00, 121.04it/s]
Algorithm Time (Excludes Logging and Setup): 27.589414358139038s

With pycma CMA-ES:

Create Scheduler for cma_me_imp with learning rate 1.0 and add mode batch, using solution dim 20, archive dims (500, 500), and 15 emitters.
Iteration 250 | Archive Coverage: 18.369% QD Score: 4421017.381
Iteration 500 | Archive Coverage: 32.998% QD Score: 7718952.239
Iteration 750 | Archive Coverage: 47.248% QD Score: 10660291.659
Iteration 1000 | Archive Coverage: 61.361% QD Score: 13229427.018
Iteration 1250 | Archive Coverage: 71.946% QD Score: 14927574.916
Iteration 1500 | Archive Coverage: 79.135% QD Score: 16002255.296
Iteration 1750 | Archive Coverage: 84.764% QD Score: 16758346.119
Iteration 2000 | Archive Coverage: 89.135% QD Score: 17293875.851
Iteration 2250 | Archive Coverage: 92.056% QD Score: 17641038.587
Iteration 2500 | Archive Coverage: 93.736% QD Score: 17824591.298
Iteration 2750 | Archive Coverage: 94.524% QD Score: 17921700.563
Iteration 3000 | Archive Coverage: 95.107% QD Score: 18003408.425
Iteration 3250 | Archive Coverage: 95.278% QD Score: 18038041.474
Iteration 3500 | Archive Coverage: 95.574% QD Score: 18067125.317
Iteration 3750 | Archive Coverage: 95.867% QD Score: 18089722.810
Iteration 4000 | Archive Coverage: 95.971% QD Score: 18115817.866
Iteration 4250 | Archive Coverage: 96.054% QD Score: 18132526.811
Iteration 4500 | Archive Coverage: 96.167% QD Score: 18151481.017
100%|████████████████████████████████████████████████████████| 4500/4500 [01:31<00:00, 49.06it/s]
Algorithm Time (Excludes Logging and Setup): 81.55640316009521s

Status

• [x] I have read the guidelines in CONTRIBUTING.md
• [x] I have formatted my code using yapf
• [x] I have tested my code by running pytest
• [x] I have linted my code with pylint
• [x] I have added a one-line description of my change to the changelog in HISTORY.md
• [x] This PR is ready to go