class RBM[T] extends TrainableModel[ops.Output[T], ops.Output[T], ops.Output[T], ops.Output[T], Float, ops.Output[T]]
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- RBM
- TrainableModel
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Instance Constructors
- new RBM(input: Input[ops.Output[T]], numHidden: Int, meanField: Boolean = true, numSamples: Int = 100, meanFieldCD: Boolean = false, cdSteps: Int = 1, optimizer: Optimizer, colocateGradientsWithOps: Boolean = false, name: String = "RBM")(implicit arg0: core.types.TF[T], arg1: core.types.IsIntOrLongOrHalfOrFloatOrDouble[T])
Value Members
- final def !=(arg0: Any): Boolean
- Definition Classes
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- final def ##: Int
- Definition Classes
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- final def ==(arg0: Any): Boolean
- Definition Classes
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- final def asInstanceOf[T0]: T0
- Definition Classes
- Any
- def buildEvalOps(metrics: Seq[Metric[ops.Output[T], ops.Output[Float]]]): EvalOps[ops.Output[T], ops.Output[T]]
- Definition Classes
- RBM → TrainableModel
- def buildInferOps(): InferOps[ops.Output[T], ops.Output[T]]
- Definition Classes
- RBM → InferenceModel
- def buildTrainOps(): TrainOps[ops.Output[T], ops.Output[T], Float]
- Definition Classes
- RBM → TrainableModel
- val cdSteps: Int
- def clone(): AnyRef
- Attributes
- protected[lang]
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.CloneNotSupportedException]) @native() @HotSpotIntrinsicCandidate()
- val colocateGradientsWithOps: Boolean
- def contrastiveDivergence(initialV: ops.Output[T], vb: ops.variables.Variable[T], hb: ops.variables.Variable[T], w: ops.variables.Variable[T]): ops.Output[T]
- Attributes
- protected
- final def eq(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
- def equals(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef → Any
- val evalOpsCache: Map[core.Graph, EvalOps[ops.Output[T], ops.Output[T]]]
- Attributes
- protected
- final def getClass(): Class[_ <: AnyRef]
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- @native() @HotSpotIntrinsicCandidate()
- def hashCode(): Int
- Definition Classes
- AnyRef → Any
- Annotations
- @native() @HotSpotIntrinsicCandidate()
- val inferOpsCache: Map[core.Graph, InferOps[ops.Output[T], ops.Output[T]]]
- Attributes
- protected
- val input: Input[ops.Output[T]]
- final def isInstanceOf[T0]: Boolean
- Definition Classes
- Any
- val meanField: Boolean
- val meanFieldCD: Boolean
- val name: String
- final def ne(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
- val nextInputCache: Map[core.Graph, ops.Output[T]]
- Attributes
- protected
- final def notify(): Unit
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- @native() @HotSpotIntrinsicCandidate()
- final def notifyAll(): Unit
- Definition Classes
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- @native() @HotSpotIntrinsicCandidate()
- val numHidden: Int
- val numInputs: Int
- val numSamples: Int
- val optimizer: Optimizer
- final def synchronized[T0](arg0: => T0): T0
- Definition Classes
- AnyRef
- def toString(): String
- Definition Classes
- AnyRef → Any
- val trainOpsCache: Map[core.Graph, TrainOps[ops.Output[T], ops.Output[T], Float]]
- Attributes
- protected
- def variables(): (ops.variables.Variable[T], ops.variables.Variable[T], ops.variables.Variable[T])
- Attributes
- protected
- val variablesCache: Map[core.Graph, (ops.variables.Variable[T], ops.variables.Variable[T], ops.variables.Variable[T])]
- Attributes
- protected
- 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
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- Annotations
- @throws(classOf[java.lang.InterruptedException]) @native()
- final def wait(): Unit
- Definition Classes
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- Annotations
- @throws(classOf[java.lang.InterruptedException])