Class/Object

org.platanios.tensorflow.api.ops.training.optimizers

GradientDescent

Related Docs: object GradientDescent | package optimizers

Permalink

case class GradientDescent(learningRate: Double, decay: Decay = NoDecay, momentum: Double = 0.0, useNesterov: Boolean = false, useLocking: Boolean = false, learningRateSummaryTag: String = null, name: String = "GradientDescent") extends Optimizer with Product with Serializable

Linear Supertypes
Serializable, Serializable, Product, Equals, Optimizer, AnyRef, Any
Ordering
  1. Alphabetic
  2. By Inheritance
Inherited
  1. GradientDescent
  2. Serializable
  3. Serializable
  4. Product
  5. Equals
  6. Optimizer
  7. AnyRef
  8. Any
  1. Hide All
  2. Show All
Visibility
  1. Public
  2. All

Instance Constructors

  1. new GradientDescent(learningRate: Double, decay: Decay = NoDecay, momentum: Double = 0.0, useNesterov: Boolean = false, useLocking: Boolean = false, learningRateSummaryTag: String = null, name: String = "GradientDescent")

    Permalink

Value Members

  1. final def !=(arg0: Any): Boolean

    Permalink
    Definition Classes
    AnyRef → Any

  2. final def ##(): Int

    Permalink
    Definition Classes
    AnyRef → Any

  3. final def ==(arg0: Any): Boolean

    Permalink
    Definition Classes
    AnyRef → Any

  4. def applyDense(gradient: Output, variable: variables.Variable, iteration: Option[variables.Variable]): Op

    Permalink
    Definition Classes
    GradientDescent → Optimizer

  5. def applyGradients(gradientsAndVariables: Seq[(OutputLike, variables.Variable)], iteration: Option[variables.Variable] = None, name: String = this.name): Op

    Permalink
    Definition Classes
    Optimizer

  6. def applySparse(gradient: OutputIndexedSlices, variable: variables.Variable, iteration: Option[variables.Variable]): Op

    Permalink
    Definition Classes
    GradientDescent → Optimizer

  7. def applySparseDuplicateIndices(gradient: OutputIndexedSlices, variable: variables.Variable, iteration: Option[variables.Variable]): Op

    Permalink
    Definition Classes
    GradientDescent → Optimizer

  8. final def asInstanceOf[T0]: T0

    Permalink
    Definition Classes
    Any

  9. def clone(): AnyRef

    Permalink
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  10. def computeGradients(loss: Output, lossGradients: Seq[OutputLike] = null, variables: Set[variables.Variable] = null, gradientsGatingMethod: GatingMethod = Gradients.OpGating, gradientsAggregationMethod: AggregationMethod = Gradients.AddAggregationMethod, colocateGradientsWithOps: Boolean = false): Seq[(OutputLike, variables.Variable)]

    Permalink
    Definition Classes
    Optimizer

  11. def createSlots(variables: Seq[variables.Variable]): Unit

    Permalink
    Attributes
    protected
    Definition Classes
    GradientDescent → Optimizer

  12. val decay: Decay

    Permalink

  13. final def eq(arg0: AnyRef): Boolean

    Permalink
    Definition Classes
    AnyRef

  14. def finalize(): Unit

    Permalink
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )

  15. def finish(updateOps: Set[Op], nameScope: String): Op

    Permalink
    Attributes
    protected
    Definition Classes
    Optimizer

  16. final def getClass(): Class[_]

    Permalink
    Definition Classes
    AnyRef → Any

  17. def getSlot(name: String, variable: variables.Variable): variables.Variable

    Permalink
    Attributes
    protected
    Definition Classes
    Optimizer

  18. def getSlot(name: String, variable: variables.Variable, initializer: Initializer, shape: core.Shape, dataType: types.DataType, variableScope: String): variables.Variable

    Permalink
    Attributes
    protected
    Definition Classes
    Optimizer

  19. final def isInstanceOf[T0]: Boolean

    Permalink
    Definition Classes
    Any

  20. val learningRate: Double

    Permalink

  21. val learningRateSummaryTag: String

    Permalink

  22. def minimize(loss: Output, lossGradients: Seq[OutputLike] = null, variables: Set[variables.Variable] = null, gradientsGatingMethod: GatingMethod = Gradients.OpGating, gradientsAggregationMethod: AggregationMethod = Gradients.AddAggregationMethod, colocateGradientsWithOps: Boolean = false, iteration: Option[variables.Variable] = None, name: String = "Minimize"): Op

    Permalink
    Definition Classes
    Optimizer

  23. val momentum: Double

    Permalink

  24. val name: String

    Permalink
    Definition Classes
    GradientDescent → Optimizer

  25. final def ne(arg0: AnyRef): Boolean

    Permalink
    Definition Classes
    AnyRef

  26. final def notify(): Unit

    Permalink
    Definition Classes
    AnyRef

  27. final def notifyAll(): Unit

    Permalink
    Definition Classes
    AnyRef

  28. def prepare(iteration: Option[variables.Variable]): Unit

    Permalink
    Definition Classes
    GradientDescent → Optimizer

  29. def slotNames: Set[String]

    Permalink
    Attributes
    protected
    Definition Classes
    Optimizer

  30. val slots: Map[String, Map[variables.Variable, variables.Variable]]

    Permalink
    Attributes
    protected
    Definition Classes
    Optimizer

  31. val supportedDataTypes: Set[types.DataType]

    Permalink
    Attributes
    protected
    Definition Classes
    Optimizer

  32. final def synchronized[T0](arg0: ⇒ T0): T0

    Permalink
    Definition Classes
    AnyRef

  33. val useLocking: Boolean

    Permalink
    Definition Classes
    GradientDescent → Optimizer

  34. val useNesterov: Boolean

    Permalink

  35. final def wait(): Unit

    Permalink
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  36. final def wait(arg0: Long, arg1: Int): Unit

    Permalink
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  37. final def wait(arg0: Long): Unit

    Permalink
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  38. def zerosSlot(name: String, variable: variables.Variable, variableScope: String): variables.Variable

    Permalink
    Attributes
    protected
    Definition Classes
    Optimizer

Inherited from Serializable

Inherited from Serializable

Inherited from Product

Inherited from Equals

Inherited from Optimizer

Inherited from AnyRef

Inherited from Any

Ungrouped