1. Launch in main process if only 1 exp is passed
2. Launcher returns a list of stats for successful exps
3. More detailed logging for unsuccessful expos
4. Raise error if all runs were unsuccessful
5. DataclassPPrintMixin allows retrieving a pretty repr string
6. Minor improvements in docstrings
* Add class ExperimentCollection to improve usability
* Remove parameters from ExperimentBuilder.build
* Renamed ExperimentBuilder.build_default_seeded_experiments to build_seeded_collection,
changing the return type to ExperimentCollection
* Replace temp_config_mutation (which was not appropriate for the public API) with
method copy (which performs a safe deep copy)
* Remove flag `eval_mode` from Collector.collect
* Replace flag `is_eval` in BasePolicy with `is_within_training_step` (negating usages)
and set it appropriately in BaseTrainer
New method training_step, which
* collects training data (method _collect_training_data)
* performs "test in train" (method _test_in_train)
* performs policy update
The old method named train_step performed only the first two points
and was now split into two separate methods
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
# 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>
Closes: https://github.com/aai-institute/tianshou/issues/1116
### API Extensions
- Batch received new method: `to_torch_`. #1117
### Breaking Changes
- The method `to_torch` in `data.utils.batch.Batch` is not in-place
anymore. Instead, a new method `to_torch_` does the conversion in-place.
#1117
Closes: https://github.com/thu-ml/tianshou/issues/1086
### Api Extensions
- Batch received new method: `to_numpy_`. #1098
- `to_dict` in Batch supports also non-recursive conversion. #1098
- Batch `__eq__` now implemented, semantic equality check of batches is
now possible. #1098
### Breaking Changes
- The method `to_numpy` in `data.utils.batch.Batch` is not in-place
anymore. Instead, a new method `to_numpy_` does the conversion in-place.
#1098
Closes#952
- `SamplingConfig` supports `batch_size=None`. #1077
- tests and examples are covered by `mypy`. #1077
- `NetBase` is more used, stricter typing by making it generic. #1077
- `utils.net.common.Recurrent` now receives and returns a
`RecurrentStateBatch` instead of a dict. #1077
---------
Co-authored-by: Michael Panchenko <m.panchenko@appliedai.de>
Closes#917
### Internal Improvements
- Better variable names related to model outputs (logits, dist input
etc.). #1032
- Improved typing for actors and critics, using Tianshou classes like
`Actor`, `ActorProb`, etc.,
instead of just `nn.Module`. #1032
- Added interfaces for most `Actor` and `Critic` classes to enforce the
presence of `forward` methods. #1032
- Simplified `PGPolicy` forward by unifying the `dist_fn` interface (see
associated breaking change). #1032
- Use `.mode` of distribution instead of relying on knowledge of the
distribution type. #1032
### Breaking Changes
- Changed interface of `dist_fn` in `PGPolicy` and all subclasses to
take a single argument in both
continuous and discrete cases. #1032
---------
Co-authored-by: Arnau Jimenez <arnau.jimenez@zeiss.com>
Co-authored-by: Michael Panchenko <m.panchenko@appliedai.de>
Closes: #1058
### 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
### Internal Improvements
- `Collector`s rely less on state, the few stateful things are stored
explicitly instead of through a `.data` attribute. #1063
- Introduced a first iteration of a naming convention for vars in
`Collector`s. #1063
- Generally improved readability of Collector code and associated tests
(still quite some way to go). #1063
- Improved typing for `exploration_noise` and within Collector. #1063
### Breaking Changes
- Removed `.data` attribute from `Collector` and its child classes.
#1063
- Collectors no longer reset the environment on initialization. Instead,
the user might have to call `reset`
expicitly or pass `reset_before_collect=True` . #1063
- VectorEnvs now return an array of info-dicts on reset instead of a
list. #1063
- Fixed `iter(Batch(...)` which now behaves the same way as
`Batch(...).__iter__()`. Can be considered a bugfix. #1063
---------
Co-authored-by: Michael Panchenko <m.panchenko@appliedai.de>
changed all the occurrences where an action is selected deterministically
- **from**: using the outputs of the actor network.
- **to**: using the mode of the PyTorch distribution.
---------
Co-authored-by: Arnau Jimenez <arnau.jimenez@zeiss.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.
