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Improve change log #1129

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Dominik Jain 2024-04-30 17:47:06 +02:00
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CHANGELOG.md
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## Release 1.1.0
### Api Extensions
- Batch received two new methods: `to_dict` and `to_list_of_dicts`. #1063
- `Collector`s can now be closed, and their reset is more granular. #1063
- Trainers can control whether collectors should be reset prior to training. #1063
- Convenience constructor for `CollectStats` called `with_autogenerated_stats`. #1063
- `SamplingConfig` supports `batch_size=None`. #1077
- Batch received new methods: `to_numpy_` and `to_torch_`. #1098, #1117
- `to_dict` in Batch supports also non-recursive conversion. #1098
- Batch `__eq__` implemented, semantic equality check of batches is now possible. #1098
- `data`:
- `Batch`:
- Add methods `to_dict` and `to_list_of_dicts`. #1063 #1098
- Add methods `to_numpy_` and `to_torch_`. #1098, #1117
- Add `__eq__` (semantic equality check). #1098
- `data.collector`:
- `Collector`:
- Add method `close` #1063
- Method `reset` is now more granular (new flags controlling behavior). #1063
- `CollectStats`: Add convenience constructor `with_autogenerated_stats`. #1063
- `trainer`:
- Trainers can now control whether collectors should be reset prior to training. #1063
- `Batch.keys()` deprecated in favor of `Batch.get_keys()` (needed to make iteration consistent with naming) #1105.
- `highlevel.experiment`:
- `Experiment` now has a `name` attribute, which can be set using `ExperimentBuilder.with_name` and
which determines the default run name and therefore the persistence subdirectory.
It can still be overridden in `Experiment.run()`, the new parameter name being `run_name` rather than
`experiment_name` (although the latter will still be interpreted correctly). #1074 #1131
- Add class `ExperimentCollection` for the convenient execution of multiple experiment runs #1131
- `ExperimentBuilder`:
- Add method `build_seeded_collection` for the sound creation of multiple
experiments with varying random seeds #1131
- Add method `copy` to facilitate the creation of multiple experiments from a single builder #1131
- `SamplingConfig` has an explicit training seed, `test_seed` is inferred. #1074
- New `evaluation` package for repeating the same experiment with multiple seeds and aggregating the results (important extension!).
Launchers for parallelization currently in alpha state. #1074
- `highlevel`:
- `SamplingConfig`:
- Add support for `batch_size=None`. #1077
- Add `training_seed` for explicit seeding of training and test environments, the `test_seed` is inferred from `training_seed`. #1074
- `highlevel.experiment`:
- `Experiment` now has a `name` attribute, which can be set using `ExperimentBuilder.with_name` and
which determines the default run name and therefore the persistence subdirectory.
It can still be overridden in `Experiment.run()`, the new parameter name being `run_name` rather than
`experiment_name` (although the latter will still be interpreted correctly). #1074 #1131
- Add class `ExperimentCollection` for the convenient execution of multiple experiment runs #1131
- `ExperimentBuilder`:
- Add method `build_seeded_collection` for the sound creation of multiple
experiments with varying random seeds #1131
- Add method `copy` to facilitate the creation of multiple experiments from a single builder #1131
- `evaluation`: New package for repeating the same experiment with multiple seeds and aggregating the results. #1074
- The module `evaluation.launchers` for parallelization is currently in alpha state.
- Loggers can now restore the logged data into python by using the new `restore_logged_data` method. #1074
- `continuous.Critic`:
- Add flag `apply_preprocess_net_to_obs_only` to allow the
preprocessing network to be applied to the observations only (without
the actions concatenated), which is essential for the case where we want
to reuse the actor's preprocessing network #1128
- `utils.net`:
- `continuous.Critic`:
- Add flag `apply_preprocess_net_to_obs_only` to allow the
preprocessing network to be applied to the observations only (without
the actions concatenated), which is essential for the case where we want
to reuse the actor's preprocessing network #1128
### Fixes
- `CriticFactoryReuseActor`: Enable the Critic flag `apply_preprocess_net_to_obs_only` for continuous critics,