Added hyperparameter tuning for RecurrentPPO

[technocrat13]

Hyperparameter tuning for RecurrentPPO was non-existent as hyperparams_opt.py did not accept 'ppo_lstm' as a valid argument

Description

• Extended sample_ppo_params() to be called by sample_ppo_lstm_params(), trail is then updated with some lstm specific hyperparams, and "policy_kwargs" is updated
• Added "tiny" to sample_ppo_params() to support smaller neural nets for the LSTM (solution 2 in issue #409)

Motivation and Context

• closes #409
• ReccurentPPO's hyperparameters can not be tuned by passing "ppo_lstm" to -optimize
• [x] I have raised an issue to propose this change (required for new features and bug fixes)

Types of changes

• [x] Bug fix (non-breaking change which fixes an issue)
• [x] New feature (non-breaking change which adds functionality)
• [ ] Breaking change (fix or feature that would cause existing functionality to change)
• [ ] Documentation (update in the documentation)

Checklist:

• [x] I've read the CONTRIBUTION guide (required)
• [x] I have updated the changelog accordingly (required).
• [ ] My change requires a change to the documentation.
• [x] I have updated the tests accordingly (required for a bug fix or a new feature).
• [ ] I have updated the documentation accordingly.
• [x] I have reformatted the code using make format (required)
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[technocrat13]

updated changelog, let me know if anything else is required, I can add you as a contributor, seems a little late to create a branch (I will keep this in mind next time)