braindecode.training.iter_trial_prediction_chunks#
- braindecode.training.iter_trial_prediction_chunks(module, dataset, *, windows_per_chunk, return_targets=True, batch_size=1, num_workers=0, loader_kwargs=None)[source]#
Yield predictions in chunks of at most
windows_per_chunkwindows.Takes the arguments of
iter_trial_predictions()and has the same lifecycle. A chunk never spans two trials and overlap removal carries across chunks, so concatenating a trial’s chunks along axis 1 gives itsiter_trial_predictions()output exactly. Memory depends on the chunk size, not on the trial length.- Parameters:
windows_per_chunk (int) – Maximum number of source windows per chunk.
module – As in
iter_trial_predictions().dataset – As in
iter_trial_predictions().return_targets – As in
iter_trial_predictions().batch_size – As in
iter_trial_predictions().num_workers – As in
iter_trial_predictions().loader_kwargs – As in
iter_trial_predictions().
- Yields:
chunk (TrialPredictionChunk)