OfflineDataset

class bayesflow.datasets.OfflineDataset(data: Mapping[str, ndarray], batch_size: int, adapter: Adapter | None, num_samples: int = None, *, stage: str = 'training', **kwargs)

Bases: PyDataset

A dataset that is pre-simulated and stored in memory. When storing and loading data from disk, it is recommended to save any pre-simulated data in raw form and create the OfflineDataset object only after loading in the raw data. See the DiskDataset class for handling large datasets that are split into multiple smaller files.

property num_batches: int | None

Number of batches in the PyDataset.

Returns:

The number of batches in the PyDataset or None to indicate that the dataset is infinite.

on_epoch_end() → None

Method called at the end of every epoch.

shuffle() → None

Shuffle the dataset in-place.

property max_queue_size

on_epoch_begin()

Method called at the beginning of every epoch.

property use_multiprocessing

property workers