Object

org.platanios.tensorflow.api.tensors.ops

NN

Related Doc: package ops

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object NN extends NN

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Type Members

  1. case class NNOps(tensor: Tensor) extends Product with Serializable

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Value Members

  1. final def !=(arg0: Any): Boolean

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  2. final def ##(): Int

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  3. final def ==(arg0: Any): Boolean

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  4. def addBias(value: Tensor, bias: Tensor, cNNDataFormat: CNNDataFormat = CNNDataFormat.default)(implicit context: DynamicVariable[Context]): Tensor

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    NN

  5. final def asInstanceOf[T0]: T0

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  6. def clone(): AnyRef

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    protected[java.lang]
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    @throws( ... )

  7. def conv2D(input: Tensor, filter: Tensor, stride1: Long, stride2: Long, padding: PaddingMode, dataFormat: CNNDataFormat = CNNDataFormat.default, useCuDNNOnGPU: Boolean = true)(implicit context: DynamicVariable[Context]): Tensor

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  8. def conv2DBackpropFilter(input: Tensor, filterSizes: Tensor, outputGradient: Tensor, stride1: Long, stride2: Long, padding: PaddingMode, dataFormat: CNNDataFormat = CNNDataFormat.default, useCuDNNOnGPU: Boolean = true)(implicit context: DynamicVariable[Context]): Tensor

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    Definition Classes
    NN

  9. def conv2DBackpropInput(inputSizes: Tensor, filter: Tensor, outputGradient: Tensor, stride1: Long, stride2: Long, padding: PaddingMode, dataFormat: CNNDataFormat = CNNDataFormat.default, useCuDNNOnGPU: Boolean = true)(implicit context: DynamicVariable[Context]): Tensor

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    Definition Classes
    NN

  10. def crelu(input: Tensor): Tensor

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  11. def dropout(input: Tensor, keepProbability: Float, noiseShape: Tensor = null, seed: Option[Int] = None): Tensor

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  12. def elu(input: Tensor)(implicit context: DynamicVariable[Context]): Tensor

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  13. final def eq(arg0: AnyRef): Boolean

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  14. def equals(arg0: Any): Boolean

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  15. def finalize(): Unit

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  16. final def getClass(): Class[_]

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  17. def hashCode(): Int

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  18. def inTopK(predictions: Tensor, targets: Tensor, k: Tensor)(implicit context: DynamicVariable[Context]): Tensor

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  19. final def isInstanceOf[T0]: Boolean

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  20. def l2Loss(input: Tensor)(implicit context: DynamicVariable[Context]): Tensor

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  21. def l2Normalize(x: Tensor, axes: Tensor, epsilon: Float = 1e-12f): Tensor

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  22. def linear(x: Tensor, weights: Tensor, bias: Tensor = null): Tensor

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  23. def logPoissonLoss(logPredictions: Tensor, targets: Tensor, computeFullLoss: Boolean = false): Tensor

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  24. def logSoftmax(logits: Tensor, axis: Int = 1)(implicit context: DynamicVariable[Context]): Tensor

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  25. def maxPool(input: Tensor, windowSize: Seq[Long], stride1: Long, stride2: Long, padding: PaddingMode, dataFormat: CNNDataFormat = CNNDataFormat.default)(implicit context: DynamicVariable[Context]): Tensor

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  26. def maxPoolGrad(originalInput: Tensor, originalOutput: Tensor, outputGradient: Tensor, windowSize: Seq[Long], stride1: Long, stride2: Long, padding: PaddingMode, dataFormat: CNNDataFormat = CNNDataFormat.default)(implicit context: DynamicVariable[Context]): Tensor

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  27. def maxPoolGradGrad(originalInput: Tensor, originalOutput: Tensor, outputGradient: Tensor, windowSize: Seq[Long], stride1: Long, stride2: Long, padding: PaddingMode, dataFormat: CNNDataFormat = CNNDataFormat.default)(implicit context: DynamicVariable[Context]): Tensor

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  28. final def ne(arg0: AnyRef): Boolean

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  29. final def notify(): Unit

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  30. final def notifyAll(): Unit

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  31. def relu(input: Tensor, alpha: Float = 0.0f)(implicit context: DynamicVariable[Context]): Tensor

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  32. def relu6(input: Tensor)(implicit context: DynamicVariable[Context]): Tensor

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  33. def selu(input: Tensor)(implicit context: DynamicVariable[Context]): Tensor

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  34. def sequenceLoss(logits: Tensor, labels: Tensor, weights: Tensor = null, averageAcrossTimeSteps: Boolean = true, averageAcrossBatch: Boolean = true, lossFn: (Tensor, Tensor) ⇒ Tensor = sparseSoftmaxCrossEntropy(_, _)): Tensor

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    @throws( ... )

  35. def sigmoidCrossEntropy(logits: Tensor, labels: Tensor, weights: Tensor = null): Tensor

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  36. def softmax(logits: Tensor, axis: Int = 1)(implicit context: DynamicVariable[Context]): Tensor

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  37. def softmaxCrossEntropy(logits: Tensor, labels: Tensor, axis: Int = 1): Tensor

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  38. def softplus(input: Tensor)(implicit context: DynamicVariable[Context]): Tensor

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  39. def softsign(input: Tensor)(implicit context: DynamicVariable[Context]): Tensor

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  40. def sparseSoftmaxCrossEntropy(logits: Tensor, labels: Tensor, axis: Int = 1): Tensor

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  41. final def synchronized[T0](arg0: ⇒ T0): T0

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  42. def toString(): String

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  43. def topK(input: Tensor, k: Tensor = 1, sorted: Boolean = true)(implicit context: DynamicVariable[Context]): (Tensor, Tensor)

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  44. final def wait(): Unit

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  45. final def wait(arg0: Long, arg1: Int): Unit

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  46. final def wait(arg0: Long): Unit

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