# Changes
## Dependencies
- New extra "eval"
## Api Extension
- `Experiment` and `ExperimentConfig` now have a `name`, that can
however be overridden when `Experiment.run()` is called
- When building an `Experiment` from an `ExperimentConfig`, the user has
the option to add info about seeds to the name.
- New method in `ExperimentConfig` called
`build_default_seeded_experiments`
- `SamplingConfig` has an explicit training seed, `test_seed` is
inferred.
- New `evaluation` package for repeating the same experiment with
multiple seeds and aggregating the results (important extension!).
Currently in alpha state.
- Loggers can now restore the logged data into python by using the new
`restore_logged_data`
## Breaking Changes
- `AtariEnvFactory` (in examples) now receives explicit train and test
seeds
- `EnvFactoryRegistered` now requires an explicit `test_seed`
- `BaseLogger.prepare_dict_for_logging` is now abstract
---------
Co-authored-by: Maximilian Huettenrauch <m.huettenrauch@appliedai.de>
Co-authored-by: Michael Panchenko <m.panchenko@appliedai.de>
Co-authored-by: Michael Panchenko <35432522+MischaPanch@users.noreply.github.com>
The high-level examples were all broken by changes made to make mypy
pass.
This PR fixes them, making a type change in logging.run_cli instead to
make mypy happy.
Addresses part of #1015
### Dependencies
- move jsonargparse and docstring-parser to dependencies to run hl
examples without dev
- create mujoco-py extra for legacy mujoco envs
- updated atari extra
- removed atari-py and gym dependencies
- added ALE-py, autorom, and shimmy
- created robotics extra for HER-DDPG
### Mac specific
- only install envpool when not on mac
- mujoco-py not working on macOS newer than Monterey
(https://github.com/openai/mujoco-py/issues/777)
- D4RL also fails due to dependency on mujoco-py
(https://github.com/Farama-Foundation/D4RL/issues/232)
### Other
- reduced training-num/test-num in example files to a number ≤ 20
(examples with 100 led to too many open files)
- rendering for Mujoco envs needs to be fixed on gymnasium side
(https://github.com/Farama-Foundation/Gymnasium/issues/749)
---------
Co-authored-by: Maximilian Huettenrauch <m.huettenrauch@appliedai.de>
Co-authored-by: Michael Panchenko <35432522+MischaPanch@users.noreply.github.com>
(should be dev dependency only) by introducing a new
place where jsonargparse can be configured:
logging.run_cli, which is also slightly more convenient
of number of environments in SamplingConfig is used
(values are now passed to factory method)
This is clearer and removes the need to pass otherwise
unnecessary configuration to environment factories at
construction
* Add common based class for A2C and PPO agent factories
* Add default for dist_fn parameter, adding corresponding factories
* Add example mujoco_a2c_hl
* Use prefix convention (subclasses have superclass names as prefix) to
facilitate discoverability of relevant classes via IDE autocompletion
* Use dual naming, adding an alternative concise name that omits the
precise OO semantics and retains only the essential part of the name
(which can be more pleasing to users not accustomed to
convoluted OO naming)
* Created mixins for agent factories to reduce code duplication
* Further factorised params & mixins for experiment factories
* Additional parameter abstractions
* Implement high-level MuJoCo TD3 example
