case class BatchNormalization[T](name: String, axis: Int = -1, momentum: Float = 0.9f, epsilon: Float = 1e-3f, center: Boolean = true, scale: Boolean = true, betaInitializer: tf.VariableInitializer = tf.ZerosInitializer, gammaInitializer: tf.VariableInitializer = tf.OnesInitializer, movingMeanInitializer: tf.VariableInitializer = tf.ZerosInitializer, movingVarianceInitializer: tf.VariableInitializer = tf.OnesInitializer, betaRegularizer: tf.VariableRegularizer = null, gammaRegularizer: tf.VariableRegularizer = null, renorm: Boolean = false, renormMomentum: Float = 0.9f, fused: Boolean = true)(implicit evidence$1: TF[T], evidence$2: IsDecimal[T]) extends Layer[ops.Output[T], ops.Output[T]] with Product with Serializable

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  1. BatchNormalization
  2. Serializable
  3. Serializable
  4. Product
  5. Equals
  6. Layer
  7. AnyRef
  8. Any
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Instance Constructors

  1. new BatchNormalization(name: String, axis: Int = -1, momentum: Float = 0.9f, epsilon: Float = 1e-3f, center: Boolean = true, scale: Boolean = true, betaInitializer: tf.VariableInitializer = tf.ZerosInitializer, gammaInitializer: tf.VariableInitializer = tf.OnesInitializer, movingMeanInitializer: tf.VariableInitializer = tf.ZerosInitializer, movingVarianceInitializer: tf.VariableInitializer = tf.OnesInitializer, betaRegularizer: tf.VariableRegularizer = null, gammaRegularizer: tf.VariableRegularizer = null, renorm: Boolean = false, renormMomentum: Float = 0.9f, fused: Boolean = true)(implicit arg0: TF[T], arg1: IsDecimal[T])

Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int
    Definition Classes
    AnyRef → Any
  3. def +(other: Layer[ops.Output[T], ops.Output[T]]): Concatenate[ops.Output[T], ops.Output[T]]
    Definition Classes
    Layer
  4. def ++(others: Seq[Layer[ops.Output[T], ops.Output[T]]]): Concatenate[ops.Output[T], ops.Output[T]]
    Definition Classes
    Layer
  5. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  6. def >>[S](other: Layer[ops.Output[T], S]): Compose[ops.Output[T], ops.Output[T], S]
    Definition Classes
    Layer
  7. def apply(input: ops.Output[T])(implicit mode: Mode): ops.Output[T]
    Definition Classes
    Layer
  8. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  9. def assignMovingAverage(variable: Variable[Float], value: ops.Output[Float], momentum: ops.Output[Float]): ops.Output[Float]
    Attributes
    protected
  10. val axis: Int
  11. val betaInitializer: tf.VariableInitializer
  12. val betaRegularizer: tf.VariableRegularizer
  13. val center: Boolean
  14. def clone(): AnyRef
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @native() @throws( ... )
  15. def compose[S](other: Layer[ops.Output[T], S]): Compose[ops.Output[T], ops.Output[T], S]
    Definition Classes
    Layer
  16. def concatenate(others: Layer[ops.Output[T], ops.Output[T]]*): Concatenate[ops.Output[T], ops.Output[T]]
    Definition Classes
    Layer
  17. final def currentStep: ops.Output[Long]
    Definition Classes
    Layer
  18. val epsilon: Float
  19. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  20. def finalize(): Unit
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  21. def forward(input: ops.Output[T])(implicit mode: Mode): ops.Output[T]
    Definition Classes
    Layer
  22. def forwardWithoutContext(input: ops.Output[T])(implicit mode: Mode): ops.Output[T]
    Definition Classes
    BatchNormalization → Layer
  23. val fused: Boolean
  24. val gammaInitializer: tf.VariableInitializer
  25. val gammaRegularizer: tf.VariableRegularizer
  26. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  27. final def getParameter[P](name: String, shape: core.Shape, initializer: Initializer = null, regularizer: Regularizer = null, trainable: Boolean = true, reuse: Reuse = ReuseOrCreateNew, collections: Set[Key[ops.variables.Variable[Any]]] = Set.empty, cachingDevice: (OpSpecification) ⇒ String = null)(implicit arg0: core.types.TF[P]): ops.Output[P]
    Definition Classes
    Layer
  28. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  29. val layerType: String
    Definition Classes
    BatchNormalization → Layer
  30. def map[MR](mapFn: (ops.Output[T]) ⇒ MR): Layer[ops.Output[T], MR]
    Definition Classes
    Layer
  31. val momentum: Float
  32. val movingMeanInitializer: tf.VariableInitializer
  33. val movingVarianceInitializer: tf.VariableInitializer
  34. val name: String
    Definition Classes
    BatchNormalization → Layer
  35. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  36. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  37. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  38. val renorm: Boolean
  39. val renormMomentum: Float
  40. val scale: Boolean
  41. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  42. def toString(): String
    Definition Classes
    Layer → AnyRef → Any
  43. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  44. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  45. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @throws( ... )

Inherited from Serializable

Inherited from Serializable

Inherited from Product

Inherited from Equals

Inherited from Layer[ops.Output[T], ops.Output[T]]

Inherited from AnyRef

Inherited from Any

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