See: Description
Interface | Description |
---|---|
Dataset |
An interface to represent a set of sample data/label pairs to train a model.
|
Sampler |
An interface for sampling data items from a
RandomAccessDataset . |
Sampler.SubSampler |
An interface that samples a single data item at a time.
|
Class | Description |
---|---|
ArrayDataset | |
ArrayDataset.Builder |
The Builder to construct an
ArrayDataset . |
Batch |
A
Batch is used to hold multiple items (data and label pairs) from a Dataset . |
BatchSampler |
BatchSampler is a Sampler that returns a single epoch over the data. |
DataIterable |
DataIterable is a data loader that combines
Dataset , Batchifier , Pipeline , and Sampler to provide an iterable over the given RandomAccessDataset . |
RandomAccessDataset |
RandomAccessDataset represent the dataset that support random access reads.
|
RandomAccessDataset.BaseBuilder<T extends RandomAccessDataset.BaseBuilder<T>> |
The Builder to construct a
RandomAccessDataset . |
RandomSampler |
RandomSampler is an implementation of the Sampler.SubSampler interface. |
Record |
Record represents a single element of data and labels from Dataset . |
SequenceSampler |
SequenceSampler is an implementation of the Sampler.SubSampler interface. |
Enum | Description |
---|---|
Dataset.Usage |
An enum that indicates the mode - training, test or validation.
|
The central class to work with in this package is the Dataset
.
In practice, most of the implementations of Dataset
will actually
extend RandomAccessDataset
instead.