DiskDataset

class bayesflow.datasets.DiskDataset(root: PathLike, *, pattern: str = '*.pkl', batch_size: int, load_fn: callable = None, adapter: Adapter | None, stage: str = 'training', **kwargs)

Bases: PyDataset

A dataset used to load pre-simulated files from disk. The training strategy will be offline.

By default, the expected file structure is as follows: root ├── … ├── sample_1.[ext] ├── … └── sample_n.[ext]

where each file contains a complete sample (e.g., a dictionary of numpy arrays) or is converted into a complete sample using a custom loader function.

on_epoch_end()

Method called at the end of every epoch.

property num_batches

Number of batches in the PyDataset.

Returns:

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

shuffle()

property max_queue_size

on_epoch_begin()

Method called at the beginning of every epoch.

property use_multiprocessing

property workers