v0.3.0

Breaking changes

• The functions collect, collect_exhaust_source and sample_feedforward_collect_and_make_source return one additional object. The additional object is a dictionary containing information of the unrolling process of the environment.

# BEFORE
sample = collect(env, controller)
# AFTER
sample, loop_result = collect(env, controller)

• The function make_dataloader expects either SupervisedDataset, SupervisedDatasetWithWeights or UnsupervisedDataset instead of PyTree. These three new dataset objects are simply NamedTuple's.

# BEFORE
make_dataloader((X, y),...)
# AFTER
make_dataloader(SupervisedDataset(X,y),...)

New features

• loop_observer-module. They can be used to record additional trial information such as physical quantities like angles over time. Works with collect, collect_exhaust_source and sample_feedforward_collect_and_make_source. Output is stored in the new dictionary output (see above).

• LOSS_FN_MODEL in combination with SupervisedDatasetWithWeights can be used to weigh the loss term during model training on a per-sample basis.