grain.experimental.RepeatIterDataset

class grain.experimental.RepeatIterDataset(parent, num_epochs=None)

Repeats the underlying dataset for num_epochs.

If num_epochs is None, repeats indefinitely. Note that unlike RepeatMapDataset, RepeatIterDataset does not support re-seeding for each epoch. Each epoch will be identical.

Parameters:

• parent (IterDataset[T])

• num_epochs (int | None)

__init__(parent, num_epochs=None)

Parameters:

• parent (IterDataset[T])

• num_epochs (int | None)

Methods

__init__(parent[, num_epochs])
apply(transformations)	Returns a dataset with the given transformation(s) applied.
batch(batch_size, *[, drop_remainder, batch_fn])	Returns a dataset of elements batched along a new first dimension.
filter(transform)	Returns a dataset containing only the elements that match the filter.
map(transform)	Returns a dataset containing the elements transformed by transform.
map_with_index(transform)	Returns a dataset of the elements transformed by the transform.
mp_prefetch([options, worker_init_fn, ...])	Returns a dataset prefetching elements in multiple processes.
pipe(func, /, *args, **kwargs)	Syntactic sugar for applying a callable to this dataset.
prefetch(multiprocessing_options)	Deprecated, use mp_prefetch instead.
random_map(transform, *[, seed])	Returns a dataset containing the elements transformed by transform.
seed(seed)	Returns a dataset that uses the seed for default seed generation.

Attributes

parents