object BatchStream
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- def fromFullBatch(features: STen, targets: STen, device: Device): BatchStream[(Variable, STen), Boolean, Unit]
Create a stream of a single full batch of features and targets
- def fromFunction[A, C](numBatches: Int, makeNonEmptyBatch: (Device) => Resource[IO, StreamControl[(A, STen)]]): BatchStream[(A, STen), Int, Unit]
- def fromFunctionWithBuffers[A, C](numBatches: Int, allocateBuffers1: (Device) => Resource[IO, C])(makeNonEmptyBatch: (C, Device) => Resource[IO, StreamControl[A]]): BatchStream[A, Int, C]
- def fromIndices[A, C](indices: Array[Array[Int]])(makeNonEmptyBatch: (Array[Int], Device) => Resource[IO, StreamControl[(A, STen)]]): BatchStream[(A, STen), Int, Unit]
Creates a stream from an array of indices and a lambda using a subset of those indexes to allocate the batch
Creates a stream from an array of indices and a lambda using a subset of those indexes to allocate the batch
The indices refer to some other external data structure
- def fromIndicesWithBuffers[A, C](indices: Array[Array[Int]], allocateBuffers1: (Device) => Resource[IO, C])(makeNonEmptyBatch: (Array[Int], C, Device) => Resource[IO, StreamControl[A]]): BatchStream[A, Int, C]
Creates a stream from an array of indices and a lambda using a subset of those indexes to allocate the batch
Creates a stream from an array of indices and a lambda using a subset of those indexes to allocate the batch
The indices refer to some other external data structure
- def fromVector[A](resources: Vector[Resource[IO, StreamControl[A]]]): BatchStream[A, Int, Unit]
Creates a stream from a vector of items
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- def minibatchesFromFull(minibatchSize: Int, dropLast: Boolean, features: STen, target: STen, rng: Random): BatchStream[(Variable, STen), Int, BufferPair]
Create a stream from the first dimension of a tensor
- final def ne(arg0: AnyRef): Boolean
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- final def notify(): Unit
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- final def notifyAll(): Unit
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- def single[A](resource: Resource[IO, StreamControl[A]]): BatchStream[A, Boolean, Unit]
Creates a stream from a single item
- def stagedFromIndices[A, B, C](indices: Array[Array[Int]], bucketSize: Int, allocateBuffers0: (Device) => Resource[IO, C])(loadInstancesToStaging: (Array[Int]) => Resource[IO, B], makeNonEmptyBatch: (B, Array[Int], C, Device) => Resource[IO, StreamControl[A]]): BatchStream[A, State[A, B], C]
A two stage data loader which first loads items of type B, then from B loads items of type A
A two stage data loader which first loads items of type B, then from B loads items of type A
Makes sense if loading B is quicker than loading an equivalent amount of A e.g. because B is a preformed batch of A-s on secondary medium
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- final def wait(arg0: Long, arg1: Int): Unit
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- Deprecated
(Since version 9)