package layers

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Package Members

  1. package rnn

Type Members

  1. abstract class Activation[T] extends Layer[ops.Output[T], ops.Output[T]]
  2. case class AddBias[T](name: String, initializer: Initializer = RandomNormalInitializer())(implicit evidence$8: core.types.TF[T], evidence$9: core.types.IsNumeric[T]) extends Layer[ops.Output[T], ops.Output[T]] with Product with Serializable
  3. case class AddN[T](name: String)(implicit evidence$2: core.types.TF[T], evidence$3: core.types.IsNumeric[T]) extends Layer[Seq[ops.Output[T]], ops.Output[T]] with Product with Serializable
  4. case class AudioSummary(name: String, tag: String, samplingRate: tensors.Tensor[Float], maxOutputs: Int = 3, family: String = null, collections: Set[Key[ops.Output[Any]]] = Set(Graph.Keys.SUMMARIES)) extends Summary[Float] with Product with Serializable
  5. 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
  6. case class CReLU[T](name: String)(implicit evidence$10: core.types.TF[T], evidence$11: core.types.IsReal[T]) extends Activation[T] with Product with Serializable
  7. case class Cast[From, To](name: String)(implicit evidence$1: core.types.TF[To]) extends Layer[ops.Output[From], ops.Output[To]] with Product with Serializable
  8. case class Compose[T, R, S](name: String, layer1: Layer[T, R], layer2: Layer[R, S]) extends Layer[T, S] with Product with Serializable
  9. case class Concatenate[T, R](name: String, layers: Seq[Layer[T, R]]) extends Layer[T, Seq[R]] with Product with Serializable
  10. case class Conv2D[T](name: String, filterShape: Shape, stride1: Long, stride2: Long, padding: ConvPaddingMode, dataFormat: CNNDataFormat = CNNDataFormat.default, dilations: (Int, Int, Int, Int) = (1, 1, 1, 1), useCuDNNOnGPU: Boolean = true, weightsInitializer: tf.VariableInitializer = tf.RandomNormalInitializer())(implicit evidence$12: TF[T], evidence$13: IsDecimal[T]) extends Layer[ops.Output[T], ops.Output[T]] with Product with Serializable
  11. case class Dropout[T](name: String, keepProbability: Float, scaleOutput: Boolean = true, noiseShape: Shape = null, seed: Option[Int] = None)(implicit evidence$10: TF[T], evidence$11: IsHalfOrFloatOrDouble[T]) extends Layer[ops.Output[T], ops.Output[T]] with Product with Serializable
  12. case class ELU[T](name: String)(implicit evidence$12: core.types.TF[T], evidence$13: core.types.IsReal[T]) extends Activation[T] with Product with Serializable
  13. case class Embedding[T](name: String, vocabularySize: Int, embeddingSize: Int, partitionStrategy: ops.Embedding.PartitionStrategy = ops.Embedding.ModStrategy, transformFn: (ops.Output[T]) => ops.Output[T] = null, maxNorm: tensors.Tensor[T] = null)(implicit evidence$1: core.types.TF[T], evidence$2: core.types.IsNotQuantized[T]) extends Layer[ops.Output[Int], ops.Output[T]] with Product with Serializable
  14. case class Flatten[T](name: String)(implicit evidence$3: core.types.TF[T]) extends Layer[ops.Output[T], ops.Output[T]] with Product with Serializable
  15. case class HistogramSummary[T](name: String, tag: String, family: String = null, collections: Set[Key[ops.Output[Any]]] = Set(Graph.Keys.SUMMARIES))(implicit evidence$5: core.types.TF[T], evidence$6: core.types.IsReal[T]) extends Summary[T] with Product with Serializable
  16. case class Identity[T](name: String) extends Layer[T, T] with Product with Serializable
  17. case class ImageSummary[T](name: String, tag: String, badColor: tensors.Tensor[core.types.UByte] = Tensor[UByte]( Tensor.fill[UByte](Shape())(UByte(255.toByte)), Tensor.fill[UByte](Shape())(UByte(0.toByte)), Tensor.fill[UByte](Shape())(UByte(0.toByte)), Tensor.fill[UByte](Shape())(UByte(255.toByte))), maxOutputs: Int = 3, family: String = null, collections: Set[Key[ops.Output[Any]]] = Set(Graph.Keys.SUMMARIES))(implicit evidence$7: core.types.TF[T], evidence$8: core.types.IsReal[T]) extends Summary[T] with Product with Serializable
  18. class Input[T] extends AnyRef
  19. case class L2Loss[Predictions, L](name: String)(implicit evidence$2: core.types.TF[Predictions], evidence$3: core.types.IsDecimal[Predictions], evidence$4: core.types.IsNotQuantized[Predictions], evidence$5: core.types.TF[L], evidence$6: core.types.IsFloatOrDouble[L]) extends Loss[(ops.Output[Predictions], ops.Output[Predictions]), L] with Product with Serializable
  20. case class LRN[T](name: String, depthRadius: Int = 5, bias: Float = 1.0f, alpha: Float = 1.0f, beta: Float = 0.5f)(implicit evidence$8: TF[T], evidence$9: IsTruncatedHalfOrHalfOrFloat[T]) extends Layer[ops.Output[T], ops.Output[T]] with Product with Serializable
  21. abstract class Layer[T, R] extends AnyRef
  22. case class Linear[T](name: String, units: Int, useBias: Boolean = true, weightsInitializer: Initializer = RandomNormalInitializer(), biasInitializer: Initializer = RandomNormalInitializer())(implicit evidence$10: core.types.TF[T], evidence$11: core.types.IsNotQuantized[T]) extends Layer[ops.Output[T], ops.Output[T]] with Product with Serializable
  23. case class LogPoissonLoss[Predictions, L](name: String, computeFullLoss: Boolean = false)(implicit evidence$21: core.types.TF[Predictions], evidence$22: core.types.IsDecimal[Predictions], evidence$23: core.types.TF[L], evidence$24: core.types.IsFloatOrDouble[L]) extends Loss[(ops.Output[Predictions], ops.Output[Predictions]), L] with Product with Serializable
  24. case class LogSigmoid[T](name: String)(implicit evidence$4: core.types.TF[T], evidence$5: core.types.IsDecimal[T]) extends Activation[T] with Product with Serializable
  25. case class LogSoftmax[T](name: String)(implicit evidence$6: TF[T], evidence$7: IsDecimal[T]) extends Layer[ops.Output[T], ops.Output[T]] with Product with Serializable
  26. abstract class Loss[T, L] extends Layer[T, ops.Output[L]]
  27. case class Map[T, R, MR](name: String, layer: Layer[T, R], mapFn: (R) => MR) extends Layer[T, MR] with Product with Serializable
  28. case class MapSeq[T, R, S, CC[A] <: Iterable[A]](name: String, layer: Layer[CC[T], CC[R]], mapLayer: Layer[R, S])(implicit ccFactory: Factory[S, CC[S]]) extends Layer[CC[T], CC[S]] with Product with Serializable
  29. case class MaxPool[T](name: String, windowSize: Seq[Int], stride1: Int, stride2: Int, padding: ConvPaddingMode, dataFormat: CNNDataFormat = CNNDataFormat.default)(implicit evidence$14: TF[T], evidence$15: IsNumeric[T]) extends Layer[ops.Output[T], ops.Output[T]] with Product with Serializable
  30. case class Mean[T](name: String, axes: Seq[Int] = null, keepDims: Boolean = false)(implicit evidence$6: core.types.TF[T], evidence$7: core.types.IsNotQuantized[T]) extends Layer[ops.Output[T], ops.Output[T]] with Product with Serializable
  31. case class OneHot[T, I](name: String, numberOfLabels: Int)(implicit evidence$6: core.types.TF[T], evidence$7: core.types.TF[I], evidence$8: core.types.IsIntOrLongOrUByte[I]) extends Layer[ops.Output[I], ops.Output[T]] with Product with Serializable
  32. trait ParameterGetter extends AnyRef
  33. case class ReLU[T](name: String, alpha: Float = 0.0f)(implicit evidence$6: core.types.TF[T], evidence$7: core.types.IsReal[T]) extends Activation[T] with Product with Serializable
  34. case class ReLU6[T](name: String)(implicit evidence$8: core.types.TF[T], evidence$9: core.types.IsReal[T]) extends Activation[T] with Product with Serializable
  35. case class Reshape[T](name: String, shape: core.Shape)(implicit evidence$4: core.types.TF[T]) extends Layer[ops.Output[T], ops.Output[T]] with Product with Serializable
  36. case class SELU[T](name: String)(implicit evidence$14: core.types.TF[T], evidence$15: core.types.IsReal[T]) extends Activation[T] with Product with Serializable
  37. case class ScalarSummary[T](name: String, tag: String, family: String = null, collections: Set[Key[ops.Output[Any]]] = Set(Graph.Keys.SUMMARIES))(implicit evidence$3: core.types.TF[T], evidence$4: core.types.IsReal[T]) extends Summary[T] with Product with Serializable
  38. case class SequenceLoss[Predictions, Labels, L](name: String, loss: (ops.Output[Predictions], ops.Output[Labels]) => ops.Output[Predictions], averageAcrossTimeSteps: Boolean = true, averageAcrossBatch: Boolean = true, weights: tensors.Tensor[Predictions] = null)(implicit evidence$25: core.types.TF[Predictions], evidence$26: core.types.IsDecimal[Predictions], evidence$27: core.types.TF[Labels], evidence$28: core.types.TF[L], evidence$29: core.types.IsFloatOrDouble[L]) extends Loss[(ops.Output[Predictions], ops.Output[Labels]), L] with Product with Serializable
  39. case class Sigmoid[T](name: String)(implicit evidence$2: core.types.TF[T], evidence$3: core.types.IsNotQuantized[T]) extends Activation[T] with Product with Serializable
  40. case class SigmoidCrossEntropy[Predictions, L](name: String)(implicit evidence$17: core.types.TF[Predictions], evidence$18: core.types.IsDecimal[Predictions], evidence$19: core.types.TF[L], evidence$20: core.types.IsFloatOrDouble[L]) extends Loss[(ops.Output[Predictions], ops.Output[Predictions]), L] with Product with Serializable
  41. case class Softmax[T](name: String)(implicit evidence$4: TF[T], evidence$5: IsDecimal[T]) extends Layer[ops.Output[T], ops.Output[T]] with Product with Serializable
  42. case class SoftmaxCrossEntropy[Predictions, L](name: String)(implicit evidence$7: core.types.TF[Predictions], evidence$8: core.types.IsDecimal[Predictions], evidence$9: core.types.TF[L], evidence$10: core.types.IsFloatOrDouble[L]) extends Loss[(ops.Output[Predictions], ops.Output[Predictions]), L] with Product with Serializable
  43. case class Softplus[T](name: String)(implicit evidence$16: core.types.TF[T], evidence$17: core.types.IsDecimal[T]) extends Activation[T] with Product with Serializable
  44. case class Softsign[T](name: String)(implicit evidence$18: core.types.TF[T], evidence$19: core.types.IsDecimal[T]) extends Activation[T] with Product with Serializable
  45. case class SparseSoftmaxCrossEntropy[Predictions, Labels, L](name: String)(implicit evidence$11: core.types.TF[Predictions], evidence$12: core.types.IsDecimal[Predictions], evidence$13: core.types.TF[Labels], evidence$14: core.types.IsIntOrLong[Labels], evidence$15: core.types.TF[L], evidence$16: core.types.IsFloatOrDouble[L]) extends Loss[(ops.Output[Predictions], ops.Output[Labels]), L] with Product with Serializable
  46. case class Squeeze[T](name: String, axes: Seq[Int] = null)(implicit evidence$1: core.types.TF[T]) extends Layer[ops.Output[T], ops.Output[T]] with Product with Serializable
  47. case class Stack[T](name: String, axis: Int = 0)(implicit evidence$2: core.types.TF[T]) extends Layer[Seq[ops.Output[T]], ops.Output[T]] with Product with Serializable
  48. case class Sum[T](name: String, axes: Seq[Int] = null, keepDims: Boolean = false)(implicit evidence$4: core.types.TF[T], evidence$5: core.types.IsNumeric[T]) extends Layer[ops.Output[T], ops.Output[T]] with Product with Serializable
  49. abstract class Summary[T] extends Layer[ops.Output[T], ops.Output[T]]
  50. case class Transpose[T](name: String, permutation: Seq[Int])(implicit evidence$5: core.types.TF[T]) extends Layer[ops.Output[T], ops.Output[T]] with Product with Serializable

Value Members

  1. object Activation
  2. object Basic
  3. object Embedding extends Serializable
  4. object Input
  5. object Layer
  6. object Loss
  7. object Math
  8. object NN
  9. object Summary

Inherited from AnyRef

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