Skrl

Changed
- Update loader and utils for OmniIsaacGymEnvs 2022.2.1.0
- Update Omniverse Isaac Gym real-world examples

Fixed
- TensorBoard writer instantiation when `write_interval` is zero

Added
- Isaac Orbit environment loader
- Wrap an Isaac Orbit environment
- Gaussian-Deterministic shared model instantiator

Added
- Utility for downloading models from Hugging Face Hub

Fixed
- Initialization of agent components if they have not been defined
- Manual trainer `train`/`eval` method default arguments

Added
- Support for Farama Gymnasium interface
- Wrapper for robosuite environments
- Weights & Biases integration
- Set the running mode (training or evaluation) of the agents
- Allow clipping the gradient norm for DDPG, TD3 and SAC agents
- Initialize model biases
- Add RNN (RNN, LSTM, GRU and any other variant) support for A2C, DDPG, PPO, SAC, TD3 and TRPO agents
- Allow disabling training/evaluation progressbar
- Farama Shimmy and robosuite examples
- KUKA LBR iiwa real-world example

Changed (breaking changes)
- Forward model inputs as a Python dictionary
- Returns a Python dictionary with extra output values in model calls

Changed
- Adopt the implementation of `terminated` and `truncated` over `done` for all environments

Fixed
- Omniverse Isaac Gym simulation speed for the Franka Emika real-world example
- Call agents' method `record_transition` instead of parent method
to allow storing samples in memories during evaluation
- Move TRPO policy optimization out of the value optimization loop
- Access to the categorical model distribution
- Call reset only once for Gym/Gymnasium vectorized environments

Removed
- Deprecated method `start` in trainers

Added
- AMP agent for physics-based character animation
- Manual trainer
- Gaussian model mixin
- Support for creating shared models
- Parameter `role` to model methods
- Wrapper compatibility with the new OpenAI Gym environment API
- Internal library colored logger
- Migrate checkpoints/models from other RL libraries to skrl models/agents
- Configuration parameter `store_separately` to agent configuration dict
- Save/load agent modules (models, optimizers, preprocessors)
- Set random seed and configure deterministic behavior for reproducibility
- Benchmark results for Isaac Gym and Omniverse Isaac Gym on the GitHub discussion page
- Franka Emika real-world example

Changed (breaking changes)
- Models implementation as Python mixin

Changed
- Multivariate Gaussian model (`GaussianModel` until 0.7.0) to `MultivariateGaussianMixin`
- Trainer's `cfg` parameter position and default values
- Show training/evaluation display progress using `tqdm`
- Update Isaac Gym and Omniverse Isaac Gym examples

Fixed
- Missing recursive arguments during model weights initialization
- Tensor dimension when computing preprocessor parallel variance
- Models' clip tensors dtype to `float32`

Removed
- Parameter `inference` from model methods
- Configuration parameter `checkpoint_policy_only` from agent configuration dict