package layers
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- abstract class Activation[T] extends Layer[ops.Output[T], ops.Output[T]]
- 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
- 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
- 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
- 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
- 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
- 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
- case class Compose[T, R, S](name: String, layer1: Layer[T, R], layer2: Layer[R, S]) extends Layer[T, S] with Product with Serializable
- case class Concatenate[T, R](name: String, layers: Seq[Layer[T, R]]) extends Layer[T, Seq[R]] with Product with Serializable
- 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
- 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
- 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
- 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
- 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
- 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
- case class Identity[T](name: String) extends Layer[T, T] with Product with Serializable
- 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
- class Input[T] extends AnyRef
- 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
- 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
- abstract class Layer[T, R] extends AnyRef
- 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
- 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
- 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
- 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
- abstract class Loss[T, L] extends Layer[T, ops.Output[L]]
- case class Map[T, R, MR](name: String, layer: Layer[T, R], mapFn: (R) => MR) extends Layer[T, MR] with Product with Serializable
- 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
- 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
- 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
- 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
- trait ParameterGetter extends AnyRef
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- 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
- abstract class Summary[T] extends Layer[ops.Output[T], ops.Output[T]]
- 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