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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Instance Constructors
- 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
- final def !=(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
- final def ##: Int
- Definition Classes
- AnyRef → Any
- def +(other: Layer[ops.Output[T], ops.Output[T]]): Concatenate[ops.Output[T], ops.Output[T]]
- Definition Classes
- Layer
- def ++(others: Seq[Layer[ops.Output[T], ops.Output[T]]]): Concatenate[ops.Output[T], ops.Output[T]]
- Definition Classes
- Layer
- final def ==(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
- def >>[S](other: Layer[ops.Output[T], S]): Compose[ops.Output[T], ops.Output[T], S]
- Definition Classes
- Layer
- def apply(input: ops.Output[T])(implicit mode: Mode): ops.Output[T]
- Definition Classes
- Layer
- final def asInstanceOf[T0]: T0
- Definition Classes
- Any
- def assignMovingAverage(variable: Variable[Float], value: ops.Output[Float], momentum: ops.Output[Float]): ops.Output[Float]
- Attributes
- protected
- val axis: Int
- val betaInitializer: tf.VariableInitializer
- val betaRegularizer: tf.VariableRegularizer
- val center: Boolean
- def clone(): AnyRef
- Attributes
- protected[lang]
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.CloneNotSupportedException]) @native() @HotSpotIntrinsicCandidate()
- def compose[S](other: Layer[ops.Output[T], S]): Compose[ops.Output[T], ops.Output[T], S]
- Definition Classes
- Layer
- def concatenate(others: Layer[ops.Output[T], ops.Output[T]]*): Concatenate[ops.Output[T], ops.Output[T]]
- Definition Classes
- Layer
- final def currentStep: ops.Output[Long]
- Definition Classes
- Layer
- val epsilon: Float
- final def eq(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
- def forward(input: ops.Output[T])(implicit mode: Mode): ops.Output[T]
- Definition Classes
- Layer
- def forwardWithoutContext(input: ops.Output[T])(implicit mode: Mode): ops.Output[T]
- Definition Classes
- BatchNormalization → Layer
- val fused: Boolean
- val gammaInitializer: tf.VariableInitializer
- val gammaRegularizer: tf.VariableRegularizer
- final def getClass(): Class[_ <: AnyRef]
- Definition Classes
- AnyRef → Any
- Annotations
- @native() @HotSpotIntrinsicCandidate()
- 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
- final def isInstanceOf[T0]: Boolean
- Definition Classes
- Any
- val layerType: String
- Definition Classes
- BatchNormalization → Layer
- def map[MR](mapFn: (ops.Output[T]) => MR): Layer[ops.Output[T], MR]
- Definition Classes
- Layer
- val momentum: Float
- val movingMeanInitializer: tf.VariableInitializer
- val movingVarianceInitializer: tf.VariableInitializer
- val name: String
- Definition Classes
- BatchNormalization → Layer
- final def ne(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
- final def notify(): Unit
- Definition Classes
- AnyRef
- Annotations
- @native() @HotSpotIntrinsicCandidate()
- final def notifyAll(): Unit
- Definition Classes
- AnyRef
- Annotations
- @native() @HotSpotIntrinsicCandidate()
- def productElementNames: Iterator[String]
- Definition Classes
- Product
- val renorm: Boolean
- val renormMomentum: Float
- val scale: Boolean
- final def synchronized[T0](arg0: => T0): T0
- Definition Classes
- AnyRef
- def toString(): String
- Definition Classes
- Layer → AnyRef → Any
- final def wait(arg0: Long, arg1: Int): Unit
- Definition Classes
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- @throws(classOf[java.lang.InterruptedException])
- final def wait(arg0: Long): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException]) @native()
- final def wait(): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException])