Struct burn_core::data::dataset::transform::SamplerDataset

pub struct SamplerDataset<D, I> { /* private fields */ }

Sample items from a dataset.

This is an convenient way of modeling a dataset as a probability distribution of a fixed size. You have multiple options to instantiate the dataset sampler.

• With replacement (Default): This is the most efficient way of using the sampler because no state is required to keep indices that have been selected.

• Without replacement: This has a similar effect to using a shuffled dataset, but with more flexibility since you can set the dataset to an arbitrary size. Once every item has been used, a new cycle is created with a new random suffle.

Implementations

impl<D, I> SamplerDataset<D, I>

where D: Dataset<I>, I: Send + Sync,

pub fn new(dataset: D, size: usize) -> SamplerDataset<D, I>

Creates a new sampler dataset with replacement.

pub fn with_replacement(dataset: D, size: usize) -> SamplerDataset<D, I>

Creates a new sampler dataset with replacement.

pub fn without_replacement(dataset: D, size: usize) -> SamplerDataset<D, I>

Creates a new sampler dataset without replacement.

Trait Implementations

impl<D, I> Dataset<I> for SamplerDataset<D, I>

where D: Dataset<I>, I: Send + Sync,

fn get(&self, index: usize) -> Option<I>

Gets the item at the given index.

fn len(&self) -> usize

Gets the number of items in the dataset.

fn is_empty(&self) -> bool

Checks if the dataset is empty.

fn iter(&self) -> DatasetIterator<'_, I>

where Self: Sized,

Returns an iterator over the dataset.