WIP: add Diversity is All You Need implementation

[kinalmehta]

Description

Adds implementation of Diversity is All You Need paper. It is an unsupervised option learning framework which can later be used for transfer learning.

To-Do

• [x] Implement unsupervised skill learning
• [ ] implement model saving and loading logic
• [ ] use the pre-trained model to train on a task from paper to benchmark
• [ ] add documentation and benchmarks

Types of changes

• [ ] Bug fix
• [ ] New feature
• [x] New algorithm
• [ ] Documentation

Checklist:

• [x] I've read the CONTRIBUTION guide (required).
• [x] I have ensured pre-commit run --all-files passes (required).
• [ ] I have updated the documentation and previewed the changes via mkdocs serve.
• [ ] I have updated the tests accordingly (if applicable).

If you are adding new algorithms or your change could result in performance difference, you may need to (re-)run tracked experiments. See https://github.com/vwxyzjn/cleanrl/pull/137 as an example PR.

• [ ] I have contacted vwxyzjn to obtain access to the openrlbenchmark W&B team (required).
• [ ] I have tracked applicable experiments in openrlbenchmark/cleanrl with --capture-video flag toggled on (required).
• [ ] I have added additional documentation and previewed the changes via mkdocs serve.
  • [ ] I have explained note-worthy implementation details.
  • [ ] I have explained the logged metrics.
  • [ ] I have added links to the original paper and related papers (if applicable).
  • [ ] I have added links to the PR related to the algorithm.
  • [ ] I have created a table comparing my results against those from reputable sources (i.e., the original paper or other reference implementation).
  • [ ] I have added the learning curves (in PNG format with width=500 and height=300).
  • [ ] I have added links to the tracked experiments.
  • [ ] I have updated the overview sections at the docs and the repo
• [ ] I have updated the tests accordingly (if applicable).

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Name	Status	Preview	Updated
cleanrl	✅ Ready (Inspect)	Visit Preview	Dec 9, 2022 at 7:05PM (UTC)