Pre-Release 1.4.2 (Beta 3)

 - Refined `GenericNeuralStack` class and hierarchy

Author: mandar2812

build.sbt

@@ -12,7 +12,7 @@ packageDescription := "DynaML is a scala library/repl for implementing and worki
   "which can be extended easily to implement advanced models for small and large scale applications.\n\n"+
   "But the library can also be used as an educational/research tool for data analysis."
 
-val mainVersion = "v1.4.2-beta.2"
+val mainVersion = "v1.4.2-beta.3"
 
 val dataDirectory = settingKey[File]("The directory holding the data files for running example scripts")
 

dynaml-core/src/main/scala-2.11/io/github/mandar2812/dynaml/models/neuralnets/GenericNeuralStack.scala

@@ -12,7 +12,7 @@ import scala.collection.GenTraversableLike
   * */
 class GenericNeuralStack[
 P, I, Layer <: NeuralLayer[P, I, I],
-T[Layer] <: Traversable[Layer] with GenTraversableLike[Layer, T[Layer]]
+T[L] <: Traversable[L] with GenTraversableLike[L, T[L]]
 ](elements: T[Layer]) extends NeuralGraph[T[Layer], I, I] {
 
   self =>
@@ -55,7 +55,7 @@ T[Layer] <: Traversable[Layer] with GenTraversableLike[Layer, T[Layer]]
     * */
   def ++[
   L <: NeuralLayer[P, I, I],
-  G[L] <: Traversable[L] with GenTraversableLike[L, G[L]]](
+  G[L1] <: Traversable[L1] with GenTraversableLike[L1, G[L1]]](
     otherStack: GenericNeuralStack[P, I, L, G])
   : GenericNeuralStack[P, I, NeuralLayer[P, I, I], T] = new GenericNeuralStack[P, I, NeuralLayer[P, I, I], T](
     (self.g.map((l: Layer) => l.asInstanceOf[NeuralLayer[P, I, I]]) ++

dynaml-core/src/main/scala-2.11/io/github/mandar2812/dynaml/models/neuralnets/LazyNeuralStack.scala

@@ -25,7 +25,7 @@ class LazyNeuralStack[P, I](elements: Stream[NeuralLayer[P, I, I]]) extends
     **/
   override def ++[
   L <: NeuralLayer[P, I, I],
-  G[L] <: Traversable[L] with GenTraversableLike[L, G[L]]](
+  G[L1] <: Traversable[L1] with GenTraversableLike[L1, G[L1]]](
     otherStack: GenericNeuralStack[P, I, L, G]) =
     new LazyNeuralStack[P, I](self.g ++ otherStack._layers.asInstanceOf[Stream[NeuralLayer[P, I, I]]])
 

dynaml-core/src/main/scala-2.11/io/github/mandar2812/dynaml/models/neuralnets/NeuralStack.scala

@@ -17,29 +17,6 @@ class NeuralStack[P, I](elements: Seq[NeuralLayer[P, I, I]])
 
   val layerParameters: Seq[P] = g.map(_.parameters)
 
-  override def _layers = g
-
-  /**
-    * Do a forward pass through the network outputting all the intermediate.
-    * layer activations.
-    * */
-  override def forwardPropagate(x: I): Seq[I] = g.scanLeft(x)((h, layer) => layer.forward(h))
-
-  /**
-    * Do a forward pass through the network outputting only the output layer activations.
-    * */
-  override val forwardPass: (I) => I = (x: I) => g.foldLeft(x)((h, layer) => layer.forward(h))
-
-  /**
-    * Batch version of [[forwardPropagate()]]
-    * */
-  override def forwardPropagateBatch[T <: Traversable[I]](d: T): Seq[T] = g.scanLeft(d)((h, layer) => layer.forward(h))
-
-  /**
-    * Batch version of [[forwardPass()]]
-    * */
-  override def forwardPassBatch[T <: Traversable[I]](d: T): T = g.foldLeft(d)((h, layer) => layer.forward(h))
-
   /**
     * Slice the stack according to a range.
     * */
@@ -52,7 +29,7 @@ class NeuralStack[P, I](elements: Seq[NeuralLayer[P, I, I]])
     **/
   override def ++[
   L <: NeuralLayer[P, I, I],
-  G[L] <: Traversable[L] with GenTraversableLike[L, G[L]]](
+  G[L1] <: Traversable[L1] with GenTraversableLike[L1, G[L1]]](
     otherStack: GenericNeuralStack[P, I, L, G]) =
     new NeuralStack(self.g ++ otherStack._layers.asInstanceOf[Seq[NeuralLayer[P, I, I]]])