avalanche.benchmarks.utils.data_loader.GroupBalancedInfiniteDataLoader

class avalanche.benchmarks.utils.data_loader.GroupBalancedInfiniteDataLoader(datasets: typing.Sequence[avalanche.benchmarks.utils.avalanche_dataset.AvalancheDataset], collate_mbatches=<function _default_collate_mbatches_fn>, **kwargs)

Data loader that balances data from multiple datasets emitting an infinite stream.

__init__(datasets: typing.Sequence[avalanche.benchmarks.utils.avalanche_dataset.AvalancheDataset], collate_mbatches=<function _default_collate_mbatches_fn>, **kwargs)

Data loader that balances data from multiple datasets emitting an infinite stream.

Mini-batches emitted by this dataloader are created by collating together mini-batches from each group. It may be used to balance data among classes, experiences, tasks, and so on.

Parameters

• datasets – an instance of AvalancheDataset.

• collate_mbatches – function that given a sequence of mini-batches (one for each task) combines them into a single mini-batch. Used to combine the mini-batches obtained separately from each task.

• kwargs – data loader arguments used to instantiate the loader for each group separately. See pytorch DataLoader.

Methods

__init__(datasets[, collate_mbatches])

Data loader that balances data from multiple datasets emitting an infinite stream.