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 nn

    Provides building blocks for neural networks

    Provides building blocks for neural networks

    Notable types:

    Optimizers:

    Modules facilitating composing other modules:

    • nn.Sequential composes a homogenous list of modules (analogous to List)
    • nn.sequence composes a heterogeneous list of modules (analogous to tuples)
    • nn.EitherModule composes two modules in a scala.Either

    Examples of neural network building blocks, layers etc:

    Definition Classes
    lamp
  • package graph
    Definition Classes
    nn
  • GCN
  • Graph
  • GraphAttention
  • MPNN
  • VertexPooling

case class MPNN[M1 <: Module, M2 <: Module](messageTransform: M1 with Module, vertexTransform: M2 with Module, degreeNormalizeI: Boolean = true, degreeNormalizeJ: Boolean = true, aggregateJ: Boolean = true) extends GraphModule with Product with Serializable

Linear Supertypes
Serializable, Product, Equals, GenericModule[Graph, Graph], AnyRef, Any
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Inherited
  1. MPNN
  2. Serializable
  3. Product
  4. Equals
  5. GenericModule
  6. AnyRef
  7. Any
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Visibility
  1. Public
  2. Protected

Instance Constructors

  1. new MPNN(messageTransform: M1 with Module, vertexTransform: M2 with Module, degreeNormalizeI: Boolean = true, degreeNormalizeJ: Boolean = true, aggregateJ: Boolean = true)

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. val aggregateJ: Boolean
  5. def apply[S](a: Graph)(implicit arg0: Sc[S]): Graph

    Alias of forward

    Alias of forward

    Definition Classes
    GenericModule
  6. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  7. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.CloneNotSupportedException]) @native() @IntrinsicCandidate()
  8. val degreeNormalizeI: Boolean
  9. val degreeNormalizeJ: Boolean
  10. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  11. def forward[S](x: Graph)(implicit arg0: Sc[S]): Graph

    The implementation of the function.

    The implementation of the function.

    In addition of x it can also use all the state to compute its value.

    Definition Classes
    MPNNGenericModule
  12. final def getClass(): Class[_ <: AnyRef]
    Definition Classes
    AnyRef → Any
    Annotations
    @native() @IntrinsicCandidate()
  13. final def gradients(loss: Variable, zeroGrad: Boolean = true): Seq[Option[STen]]

    Computes the gradient of loss with respect to the parameters.

    Computes the gradient of loss with respect to the parameters.

    Definition Classes
    GenericModule
  14. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  15. final def learnableParameters: Long

    Returns the total number of optimizable parameters.

    Returns the total number of optimizable parameters.

    Definition Classes
    GenericModule
  16. val messageTransform: M1 with Module
  17. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  18. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @IntrinsicCandidate()
  19. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @IntrinsicCandidate()
  20. final def parameters: Seq[(Constant, PTag)]

    Returns the state variables which need gradient computation.

    Returns the state variables which need gradient computation.

    Definition Classes
    GenericModule
  21. def productElementNames: Iterator[String]
    Definition Classes
    Product
  22. def state: Seq[(Constant, PTag)]

    List of optimizable, or non-optimizable, but stateful parameters

    List of optimizable, or non-optimizable, but stateful parameters

    Stateful means that the state is carried over the repeated forward calls.

    Definition Classes
    MPNNGenericModule
  23. final def synchronized[T0](arg0: => T0): T0
    Definition Classes
    AnyRef
  24. val vertexTransform: M2 with Module
  25. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException])
  26. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException]) @native()
  27. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException])
  28. final def zeroGrad(): Unit
    Definition Classes
    GenericModule

Deprecated Value Members

  1. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.Throwable]) @Deprecated
    Deprecated

Inherited from Serializable

Inherited from Product

Inherited from Equals

Inherited from GenericModule[Graph, Graph]

Inherited from AnyRef

Inherited from Any

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