Packages

  • package root
    Definition Classes
    root
  • package lamp

    Lamp provides utilities to build state of the art machine learning applications

    Lamp provides utilities to build state of the art machine learning applications

    Overview

    Notable types and packages:

    • lamp.STen is a memory managed wrapper around aten.ATen, an off the heap, native n-dimensionl array backed by libtorch.
    • lamp.autograd implements reverse mode automatic differentiation.
    • lamp.nn contains neural network building blocks, see e.g. lamp.nn.Linear.
    • lamp.data.IOLoops implements a training loop and other data related abstractions.
    • lamp.knn implements k-nearest neighbor search on the CPU and GPU
    • lamp.umap.Umap implements the UMAP dimension reduction algorithm
    • lamp.onnx implements serialization of computation graphs into ONNX format
    • lamp.io contains CSV and NPY readers
    How to get data into lamp

    Use one of the file readers in lamp.io or one of the factories in lamp.STen$.

    How to define a custom neural network layer

    See the documentation on lamp.nn.GenericModule

    How to compose neural network layers

    See the documentation on lamp.nn

    How to train models

    See the training loops in lamp.data.IOLoops

    Definition Classes
    root
  • package data
    Definition Classes
    lamp
  • CPU
  • CudaDevice
  • Device
  • DoublePrecision
  • FloatingPointPrecision
  • HalfPrecision
  • Movable
  • STen
  • STenOptions
  • Scope
  • SinglePrecision
  • TensorHelpers
c

lamp

CudaDevice

case class CudaDevice(i: Int) extends Device with Product with Serializable

Linear Supertypes
Serializable, Serializable, Product, Equals, Device, AnyRef, Any
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Inherited
  1. CudaDevice
  2. Serializable
  3. Serializable
  4. Product
  5. Equals
  6. Device
  7. AnyRef
  8. Any
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Visibility
  1. Public
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Instance Constructors

  1. new CudaDevice(i: Int)

Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int
    Definition Classes
    AnyRef → Any
  3. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  4. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  5. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  6. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  7. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  8. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  9. val i: Int
  10. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  11. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  12. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  13. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  14. def options[S](precision: FloatingPointPrecision)(implicit arg0: Sc[S]): STenOptions
    Definition Classes
    CudaDevice → Device
  15. def setSeed(seed: Long): Unit
    Definition Classes
    CudaDevice → Device
  16. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  17. def to(t: Tensor): Tensor
    Definition Classes
    CudaDevice → Device
  18. def to[S](t: STenOptions)(implicit arg0: Sc[S]): STenOptions
    Definition Classes
    CudaDevice → Device
  19. def to[S](t: STen)(implicit arg0: Sc[S]): STen
    Definition Classes
    Device
  20. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  21. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  22. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  23. def withOtherStreamThenSync[A](synchronizeBefore: Boolean)(f: ⇒ A): A

    Executes f on a new stream f must not switch to other threads Restores the stream to the default stream

    Executes f on a new stream f must not switch to other threads Restores the stream to the default stream

    Definition Classes
    CudaDevice → Device

Inherited from Serializable

Inherited from Serializable

Inherited from Product

Inherited from Equals

Inherited from Device

Inherited from AnyRef

Inherited from Any

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