Packages

class YellowFin extends GradientDescent

Linear Supertypes
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Inherited
  1. YellowFin
  2. GradientDescent
  3. Optimizer
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  5. Any
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Visibility
  1. Public
  2. Protected

Instance Constructors

  1. new YellowFin(learningRate: Float = 1.0f, decay: Schedule[Float] = FixedSchedule[Float](), momentum: Float = 0.0f, beta: Float = 0.999f, curvatureWindowWidth: Int = 20, zeroDebias: Boolean = true, sparsityDebias: Boolean = true, useNesterov: Boolean = false, useLocking: Boolean = false, learningRateSummaryTag: String = null, name: String = "YellowFin")
    Attributes
    protected

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. def applyDense[T, I](gradient: Output[T], variable: variables.Variable[T], iteration: Option[variables.Variable[I]])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], arg2: core.types.TF[I], arg3: core.types.IsIntOrLong[I]): UntypedOp
    Definition Classes
    YellowFinGradientDescentOptimizer
  5. def applyGradients[T, I](gradientsAndVariables: Seq[(OutputLike[T], variables.Variable[Any])], iteration: Option[variables.Variable[I]] = None, name: String = this.name)(implicit arg0: core.types.TF[T], arg1: LongDefault[I], arg2: core.types.TF[I], arg3: core.types.IsIntOrLong[I]): UntypedOp
    Definition Classes
    YellowFinOptimizer
  6. def applySparse[T, I](gradient: OutputIndexedSlices[T], variable: variables.Variable[T], iteration: Option[variables.Variable[I]])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], arg2: core.types.TF[I], arg3: core.types.IsIntOrLong[I]): UntypedOp
    Definition Classes
    YellowFinGradientDescentOptimizer
  7. def applySparseDuplicateIndices[T, I](gradient: OutputIndexedSlices[T], variable: variables.Variable[T], iteration: Option[variables.Variable[I]])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], arg2: core.types.TF[I], arg3: core.types.IsIntOrLong[I]): UntypedOp
    Definition Classes
    GradientDescentOptimizer
  8. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  9. val beta: Float
  10. var betaTensor: Output[Float]
    Attributes
    protected
  11. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.CloneNotSupportedException]) @native() @HotSpotIntrinsicCandidate()
  12. def computeGradients[T](loss: Output[T], lossGradients: Seq[OutputLike[T]] = null, variables: Set[variables.Variable[Any]] = null, gradientsGatingMethod: GatingMethod = Gradients.OpGating, gradientsAggregationMethod: AggregationMethod = Gradients.AddAggregationMethod, colocateGradientsWithOps: Boolean = false)(implicit arg0: core.types.TF[T], arg1: core.types.IsFloatOrDouble[T]): Seq[(OutputLike[T], variables.Variable[Any])]
    Definition Classes
    Optimizer
    Annotations
    @throws(scala.this.throws.<init>$default$1[IllegalArgumentException])
  13. def createSlots(variables: Seq[variables.Variable[Any]]): Unit
    Definition Classes
    YellowFinGradientDescentOptimizer
  14. def curvatureRange(gradNormSquaredSum: Output[Float], sparsityAvg: Option[Output[Float]]): (Output[Float], Output[Float])
    Attributes
    protected
  15. var curvatureWindow: variables.Variable[Float]
    Attributes
    protected
  16. val curvatureWindowWidth: Int
  17. val decay: Schedule[Float]
    Definition Classes
    YellowFinGradientDescent
  18. def distanceToOptimum(gradNormSquaredSum: Output[Float], gradNormSquaredAvg: Output[Float], sparsityAvg: Option[Output[Float]]): Output[Float]
    Attributes
    protected
  19. var doTune: Output[Boolean]
    Attributes
    protected
  20. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  21. def equals(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef → Any
  22. def finish(updateOps: Set[UntypedOp], nameScope: String): UntypedOp
    Definition Classes
    Optimizer
  23. final def getClass(): Class[_ <: AnyRef]
    Definition Classes
    AnyRef → Any
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  24. def getLearningRate[V, I](variable: variables.Variable[V], iteration: Option[variables.Variable[I]])(implicit arg0: core.types.TF[V], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): Output[V]
    Attributes
    protected
    Definition Classes
    YellowFinGradientDescent
  25. def getMomentum[V](variable: variables.Variable[V])(implicit arg0: core.types.TF[V]): Output[V]
    Attributes
    protected
    Definition Classes
    YellowFinGradientDescent
  26. final def getNonSlotVariable[T](name: String, graph: core.Graph = null): variables.Variable[T]
    Attributes
    protected
    Definition Classes
    Optimizer
  27. final def getNonSlotVariables: Iterable[variables.Variable[Any]]
    Attributes
    protected
    Definition Classes
    Optimizer
  28. final def getOrCreateNonSlotVariable[T](name: String, initialValue: tensors.Tensor[T], colocationOps: Set[UntypedOp] = Set.empty, ignoreExisting: Boolean = false)(implicit arg0: core.types.TF[T]): variables.Variable[T]
    Attributes
    protected
    Definition Classes
    Optimizer
  29. final def getSlot[T, R](name: String, variable: variables.Variable[T])(implicit arg0: core.types.TF[R]): variables.Variable[R]
    Attributes
    protected
    Definition Classes
    Optimizer
  30. final def getSlot[T, R](name: String, variable: variables.Variable[T], dataType: core.types.DataType[R], initializer: Initializer, shape: core.Shape, variableScope: String)(implicit arg0: core.types.TF[R]): variables.Variable[R]
    Attributes
    protected
    Definition Classes
    Optimizer
  31. def gradientsSparsity(gradients: Seq[Output[Float]]): Option[Output[Float]]
    Attributes
    protected
  32. def gradientsVariance(gradients: Seq[OutputLike[Float]], gradNormSquaredAvg: Output[Float], sparsityAvg: Option[Output[Float]]): Output[Float]
    Attributes
    protected
  33. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  34. val ignoreDuplicateSparseIndices: Boolean
    Definition Classes
    GradientDescentOptimizer
  35. var incrementStepOp: UntypedOp
    Attributes
    protected
  36. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  37. val learningRate: Float
    Definition Classes
    YellowFinGradientDescent
  38. var learningRateFactorVariable: variables.Variable[Float]
    Attributes
    protected
  39. val learningRateSummaryTag: String
    Definition Classes
    YellowFinGradientDescent
  40. var learningRateTensor: Output[Float]
    Attributes
    protected
    Definition Classes
    GradientDescent
  41. var learningRateVariable: variables.Variable[Float]
    Attributes
    protected
  42. def minimize[T, I](loss: Output[T], lossGradients: Seq[OutputLike[T]] = null, variables: Set[variables.Variable[Any]] = null, gradientsGatingMethod: GatingMethod = Gradients.OpGating, gradientsAggregationMethod: AggregationMethod = Gradients.AddAggregationMethod, colocateGradientsWithOps: Boolean = false, iteration: Option[variables.Variable[I]] = None, name: String = "Minimize")(implicit arg0: core.types.TF[T], arg1: core.types.IsFloatOrDouble[T], arg2: LongDefault[I], arg3: core.types.TF[I], arg4: core.types.IsIntOrLong[I]): UntypedOp
    Definition Classes
    Optimizer
    Annotations
    @throws(scala.this.throws.<init>$default$1[IllegalArgumentException])
  43. val momentum: Float
    Definition Classes
    YellowFinGradientDescent
  44. var momentumTensor: Output[Float]
    Attributes
    protected
    Definition Classes
    GradientDescent
  45. var momentumVariable: variables.Variable[Float]
    Attributes
    protected
  46. var movingAverage: ExponentialMovingAverage
    Attributes
    protected
  47. val name: String
    Definition Classes
    YellowFinGradientDescentOptimizer
  48. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  49. final val nonSlotVariables: Map[(String, Option[core.Graph]), variables.Variable[Any]]
    Attributes
    protected
    Definition Classes
    Optimizer
  50. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  51. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  52. def prepare[I](iteration: Option[variables.Variable[I]])(implicit arg0: core.types.TF[I], arg1: core.types.IsIntOrLong[I]): Unit
    Definition Classes
    YellowFinGradientDescentOptimizer
  53. final def slotNames: Set[String]
    Attributes
    protected
    Definition Classes
    Optimizer
  54. final val slots: Map[String, Map[variables.Variable[Any], variables.Variable[Any]]]
    Attributes
    protected
    Definition Classes
    Optimizer
  55. val sparsityDebias: Boolean
  56. final def state: Seq[variables.Variable[Any]]
    Definition Classes
    Optimizer
  57. var step: variables.Variable[Int]
    Attributes
    protected
  58. final def synchronized[T0](arg0: => T0): T0
    Definition Classes
    AnyRef
  59. def toString(): String
    Definition Classes
    AnyRef → Any
  60. val useLocking: Boolean
    Definition Classes
    YellowFinGradientDescentOptimizer
  61. val useNesterov: Boolean
    Definition Classes
    YellowFinGradientDescent
  62. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException])
  63. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException]) @native()
  64. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException])
  65. def yellowFinUpdate[T](gradientsAndVariables: Seq[(OutputLike[T], variables.Variable[Any])])(implicit arg0: core.types.TF[T]): UntypedOp
    Attributes
    protected
  66. val zeroDebias: Boolean
  67. final def zerosSlot[T](name: String, variable: variables.Variable[T], variableScope: String)(implicit arg0: core.types.TF[T]): variables.Variable[T]
    Attributes
    protected
    Definition Classes
    Optimizer

Deprecated Value Members

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

    (Since version ) see corresponding Javadoc for more information.

Inherited from GradientDescent

Inherited from Optimizer

Inherited from AnyRef

Inherited from Any

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