public final class TrainingEpochs<
Samples: Collection,
Entropy: RandomNumberGenerator
>: Sequence, IteratorProtocol
An infinite sequence of collections of batch samples suitable for training a DNN when samples are uniform.
The batches in each epoch all have exactly the same size.
-
Creates an instance drawing samples from
samples
into batches of sizebatchSize
.Declaration
public init( samples: Samples, batchSize: Int, entropy: Entropy )
Parameters
entropy
a source of randomness used to shuffle sample ordering. It will be stored in
self
, so if it is only pseudorandom and has value semantics, the sequence of epochs is determinstic and not dependent on other operations. -
Returns the next epoch in sequence.
Declaration
public func next() -> Element?
-
Creates an instance drawing samples from
samples
into batches of sizebatchSize
.Declaration
public convenience init( samples: Samples, batchSize: Int )