implicit class NNOps[T] extends AnyRef
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Instance Constructors
- new NNOps(output: ops.Output[T])
Value Members
- final def !=(arg0: Any): Boolean
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- final def ##: Int
- Definition Classes
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- final def ==(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
- def addBias(bias: ops.Output[T], cNNDataFormat: CNNDataFormat = CNNDataFormat.default)(implicit ev: core.types.IsNumeric[T]): ops.Output[T]
- final def asInstanceOf[T0]: T0
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- def clone(): AnyRef
- Attributes
- protected[lang]
- Definition Classes
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- Annotations
- @throws(classOf[java.lang.CloneNotSupportedException]) @native() @HotSpotIntrinsicCandidate()
- def conv2D(filter: ops.Output[T], stride1: Long, stride2: Long, padding: ConvPaddingMode, dataFormat: CNNDataFormat = CNNDataFormat.default, dilations: (Int, Int, Int, Int) = (1, 1, 1, 1), useCuDNNOnGPU: Boolean = true, name: String = "Conv2D")(implicit ev: core.types.IsDecimal[T]): ops.Output[T]
- def crelu(implicit ev: core.types.IsReal[T]): ops.Output[T]
- def dropout[I](keepProbability: Float, scaleOutput: Boolean = true, noiseShape: ops.Output[I] = null, seed: Option[Int] = None)(implicit arg0: IntDefault[I], arg1: core.types.IsIntOrLong[I], arg2: core.types.TF[I], ev: core.types.IsHalfOrFloatOrDouble[T]): ops.Output[T]
- def dynamicDropout[I](keepProbability: ops.Output[T], scaleOutput: Boolean = true, noiseShape: ops.Output[I] = null, seed: Option[Int] = None)(implicit arg0: IntDefault[I], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I], ev: core.types.IsHalfOrFloatOrDouble[T]): ops.Output[T]
- def elu(implicit ev: core.types.IsReal[T]): ops.Output[T]
- final def eq(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
- def equals(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef → Any
- implicit val evTTF: core.types.TF[T]
- Attributes
- protected
- final def getClass(): Class[_ <: AnyRef]
- Definition Classes
- AnyRef → Any
- Annotations
- @native() @HotSpotIntrinsicCandidate()
- def hashCode(): Int
- Definition Classes
- AnyRef → Any
- Annotations
- @native() @HotSpotIntrinsicCandidate()
- def inTopK[I](targets: ops.Output[I], k: ops.Output[I])(implicit arg0: core.types.TF[I], arg1: core.types.IsIntOrLong[I], ev: =:=[T, Float]): ops.Output[Boolean]
- final def isInstanceOf[T0]: Boolean
- Definition Classes
- Any
- def l2Normalize[I](axes: ops.Output[I], epsilon: Float = 1e-12f)(implicit arg0: core.types.TF[I], arg1: core.types.IsIntOrLong[I], ev: core.types.IsNotQuantized[T]): ops.Output[T]
- def linear(weights: ops.Output[T], bias: ops.Output[T])(implicit ev: core.types.IsNotQuantized[T]): ops.Output[T]
- def localResponseNormalization(depthRadius: Int = 5, bias: Float = 1.0f, alpha: Float = 1.0f, beta: Float = 0.5f, name: String = "LocalResponseNormalization")(implicit ev: core.types.IsTruncatedHalfOrHalfOrFloat[T]): ops.Output[T]
- def logSoftmax(axis: Int = -1)(implicit ev: core.types.IsDecimal[T]): ops.Output[T]
- def lrn(depthRadius: Int = 5, bias: Float = 1.0f, alpha: Float = 1.0f, beta: Float = 0.5f, name: String = "LRN")(implicit ev: core.types.IsTruncatedHalfOrHalfOrFloat[T]): ops.Output[T]
- def maxPool(windowSize: ops.Output[Int], strides: ops.Output[Int], padding: ConvPaddingMode, dataFormat: CNNDataFormat = CNNDataFormat.default, name: String = "MaxPool")(implicit ev: core.types.IsNumeric[T]): ops.Output[T]
- final def ne(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
- final def notify(): Unit
- Definition Classes
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- Annotations
- @native() @HotSpotIntrinsicCandidate()
- final def notifyAll(): Unit
- Definition Classes
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- Annotations
- @native() @HotSpotIntrinsicCandidate()
- val output: ops.Output[T]
- def relu(alpha: Float = 0.0f)(implicit ev: core.types.IsReal[T]): ops.Output[T]
- def relu6(implicit ev: core.types.IsReal[T]): ops.Output[T]
- def selu(implicit ev: core.types.IsReal[T]): ops.Output[T]
- def softmax(axis: Int = -1)(implicit ev: core.types.IsDecimal[T]): ops.Output[T]
- def softplus(implicit ev: core.types.IsDecimal[T]): ops.Output[T]
- def softsign(implicit ev: core.types.IsDecimal[T]): ops.Output[T]
- final def synchronized[T0](arg0: => T0): T0
- Definition Classes
- AnyRef
- def toString(): String
- Definition Classes
- AnyRef → Any
- def topK(k: ops.Output[Int], sorted: Boolean = true)(implicit ev: core.types.IsReal[T]): (ops.Output[T], ops.Output[Int])
- final def wait(arg0: Long, arg1: Int): Unit
- Definition Classes
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- Annotations
- @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])