Save KerasModel to pure keras or tf protobuf (intel-analytics#1606)

* checkpoint * add unit test * revert neuralCF * revert neuralCF * some update * some update * some change
Le-Zheng · Sep 30, 2019 · c764f29 · c764f29
1 parent 9841390
commit c764f29
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Showing 11 changed files with 69 additions and 5 deletions.
diff --git a/layers/Dense.scala b/layers/Dense.scala
@@ -60,7 +60,7 @@ class Dense[T: ClassTag](
   extends BigDLDense[T](outputDim, init, activation, wRegularizer, bRegularizer, bias,
     inputShape) with Net {
 
-  override private[zoo] def toKeras2(dir: String): String = {
+  override private[zoo] def toKeras2(): String = {
     val params = Net.inputShapeToString(inputShape) ++
       Net.activationToString(activation) ++
       Net.param(getName()) ++

diff --git a/layers/Dropout.scala b/layers/Dropout.scala
@@ -38,7 +38,7 @@ class Dropout[T: ClassTag](
   (implicit ev: TensorNumeric[T])
   extends com.intel.analytics.bigdl.nn.keras.Dropout[T](p, inputShape) with Net {
 
-  override private[zoo] def toKeras2(dir: String): String = {
+  override private[zoo] def toKeras2(): String = {
     val params = Net.inputShapeToString(inputShape) ++
       Net.param(getName()) ++
       Net.param(p, "rate")

diff --git a/layers/Embedding.scala b/layers/Embedding.scala
@@ -100,6 +100,15 @@ class Embedding[T: ClassTag](
     model.add(layer)
     model.asInstanceOf[AbstractModule[Tensor[T], Tensor[T], T]]
   }
+
+  override private[zoo] def toKeras2(): String = {
+    val params = Net.inputShapeToString(inputShape) ++
+      Net.param(getName()) ++
+      Net.param(inputDim, "input_dim") ++
+      Net.param(outputDim, "output_dim") ++
+      Net.param(maskZero, "mask_zero")
+    Net.kerasDef(this, params)
+  }
 }
 
 object Embedding {

diff --git a/layers/Flatten.scala b/layers/Flatten.scala
@@ -47,6 +47,12 @@ class Flatten[T: ClassTag](
         Array(input.slice(1, input.length).product), batchMode = Some(true))
     layer.asInstanceOf[AbstractModule[Tensor[T], Tensor[T], T]]
   }
+
+  override private[zoo] def toKeras2(): String = {
+    val params = Net.inputShapeToString(inputShape) ++
+      Net.param(getName())
+    Net.kerasDef(this, params)
+  }
 }
 
 object Flatten {

diff --git a/layers/Input.scala b/layers/Input.scala
@@ -44,6 +44,12 @@ class Input[T: ClassTag](val inputShape: Shape)(implicit ev: TensorNumeric[T])
   override def allowRebuilt(): Boolean = true
 
   override def skipDuplicateCheck(): Boolean = skipDuplicate
+
+  override private[zoo] def toKeras2(): String = {
+    val params = Net.inputShapeToString(inputShape, "shape") ++
+      Net.param(getName())
+    Net.kerasDef(this, params)
+  }
 }
 
 /**

diff --git a/layers/LSTM.scala b/layers/LSTM.scala
@@ -79,7 +79,7 @@ class LSTM[T: ClassTag](
       bRegularizer = bRegularizer)
   }
 
-  override private[zoo] def toKeras2(dir: String): String = {
+  override private[zoo] def toKeras2(): String = {
     val params = Net.inputShapeToString(inputShape) ++
       Net.activationToString(activation) ++
       Net.activationToString(innerActivation, "recurrent_activation") ++

diff --git a/layers/Merge.scala b/layers/Merge.scala
@@ -53,6 +53,26 @@ class Merge[T: ClassTag](
   extends KerasLayer[Tensor[T], Tensor[T], T](Merge.calcBatchInputShape(inputShape, layers))
   with Net {
 
+  override private[zoo] def toKeras2(): String = {
+    var params = Net.inputShapeToString(inputShape) ++
+      Net.param(getName())
+    val kerasLayerName = mode match {
+      case "sum" => "Add"
+      case "mul" => "Multiply"
+      case "max" => "Maximum"
+      case "ave" => "Average"
+      case "sub" => "Subtract"
+      case "min" => "Minimum"
+      case "concat" =>
+        params ++= Net.param(concatAxis, "axis")
+        "Concatenate"
+      case "dot" => "Dot"
+      case _ =>
+        throw new IllegalArgumentException(s"Merge ${mode} is not supported in Keras2")
+    }
+    Net.kerasDef(kerasLayerName, params)
+  }
+
   private val mergeMode = mode.toLowerCase()
   private var axis = concatAxis
 

diff --git a/layers/Permute.scala b/layers/Permute.scala
@@ -41,7 +41,7 @@ class Permute[T: ClassTag](
   extends BigDLPermute[T](
     dims, inputShape) with Net {
 
-  override private[zoo] def toKeras2(dir: String): String = {
+  override private[zoo] def toKeras2(): String = {
     val params = Net.inputShapeToString(inputShape) ++
       Net.param(getName()) ++
       Net.arrayToString(dims, "dims")

diff --git a/layers/Reshape.scala b/layers/Reshape.scala
@@ -99,7 +99,7 @@ class Reshape[T: ClassTag](
     layer.asInstanceOf[AbstractModule[Tensor[T], Tensor[T], T]]
   }
 
-  override private[zoo] def toKeras2(dir: String): String = {
+  override private[zoo] def toKeras2(): String = {
     val params = Net.inputShapeToString(inputShape) ++
       Net.param(getName()) ++
       Net.arrayToString(targetShape, "target_shape")

diff --git a/layers/Select.scala b/layers/Select.scala
@@ -78,6 +78,13 @@ class Select[T: ClassTag](
     val layer = com.intel.analytics.bigdl.nn.Select(positiveDim + 1, positiveIndex + 1)
     layer.asInstanceOf[AbstractModule[Tensor[T], Tensor[T], T]]
   }
+
+  override private[zoo] def toKeras2(): String = {
+    val params = Net.inputShapeToString(inputShape) ++
+      Net.param(getName()) ++
+      Net.param(dim, "dim")
+    Net.kerasDef(this, params)
+  }
 }
 
 object Select {

diff --git a/scala/dllib/src/main/scala/com/intel/analytics/bigdl/dllib/keras/models/Topology.scala b/scala/dllib/src/main/scala/com/intel/analytics/bigdl/dllib/keras/models/Topology.scala
@@ -609,6 +609,10 @@ class Model[T: ClassTag] private (private val _inputs : Seq[ModuleNode[T]],
 
   KerasLayerRef(this).setOutShape(Shape(_outputs.map{_.element.getOutputShape()}.toList))
 
+  private[zoo] def getInputs(): Seq[ModuleNode[T]] = _inputs
+
+  private[zoo] def getOutputs(): Seq[ModuleNode[T]] = _outputs
+
   override def isKerasStyle(): Boolean = true
 
   override def computeOutputShape(inputShape: Shape): Shape = {
@@ -664,6 +668,18 @@ class Model[T: ClassTag] private (private val _inputs : Seq[ModuleNode[T]],
 
   override def toKeras(): Model[T] = this
 
+  override private[zoo] def getKerasWeights(): Array[Tensor[Float]] = {
+    val weights = new ArrayBuffer[Tensor[Float]]()
+    modules(0).asInstanceOf[StaticGraph[T]].modules.foreach(m => {
+      val params = m.asInstanceOf[Net].getKerasWeights()
+      if (params != null) {
+        params.foreach(weights += _)
+      }
+    })
+    weights.toArray
+  }
+
+
   override def summary(
       lineLength: Int = 120,
       positions: Array[Double] = Array(.33, .55, .67, 1)): Unit = {