From 9a979ea68f576a2f6fd75e36efa60368a5ad2a8a Mon Sep 17 00:00:00 2001
From: terrytangyuan <terrytangyuan@gmail.com>
Date: Sun, 27 Dec 2015 18:18:27 -0600
Subject: [PATCH 01/11] Random.uniform and normal

---
 .../main/scala/ml/dmlc/mxnet/NDArray.scala    |  6 ++++
 .../src/main/scala/ml/dmlc/mxnet/Random.scala | 29 +++++++++++++++++++
 2 files changed, 35 insertions(+)
 create mode 100644 scala-package/core/src/main/scala/ml/dmlc/mxnet/Random.scala

diff --git a/scala-package/core/src/main/scala/ml/dmlc/mxnet/NDArray.scala b/scala-package/core/src/main/scala/ml/dmlc/mxnet/NDArray.scala
index 53b2145bc29a..aac8077d0d6c 100644
--- a/scala-package/core/src/main/scala/ml/dmlc/mxnet/NDArray.scala
+++ b/scala-package/core/src/main/scala/ml/dmlc/mxnet/NDArray.scala
@@ -268,6 +268,12 @@ object NDArray {
     NDArray._unaryNDArrayFunction("norm", src)
   }
 
+  // TODO
+  def _randomUniform(low: Float, high: Float, out: NDArray) = ???
+
+  def _randomGaussian(mean: Float, stdvar: Float, out: NDArray) = ???
+
+
   /**
    * Create a new NDArray that copies content from source_array.
    * @param sourceArr Source data to create NDArray from.
diff --git a/scala-package/core/src/main/scala/ml/dmlc/mxnet/Random.scala b/scala-package/core/src/main/scala/ml/dmlc/mxnet/Random.scala
new file mode 100644
index 000000000000..407fabdcbffd
--- /dev/null
+++ b/scala-package/core/src/main/scala/ml/dmlc/mxnet/Random.scala
@@ -0,0 +1,29 @@
+package ml.dmlc.mxnet
+
+
+import ml.dmlc.mxnet.NDArray.{_randomUniform}
+/**
+ * Created by yuantang on 12/27/15.
+ */
+class Random {
+
+  def uniform(low: Float, high: Float, shape: Array[Int]=null, ctx: Context=null, out: NDArray=null): NDArray = {
+    if (out != null) {
+      require(shape == null & ctx == null, "shape and ctx is not needed when out is specified.")
+    } else {
+      require(shape != null, "shape is required when out is not specified")
+      var out = NDArray.empty(shape, ctx)
+    }
+    return NDArray._randomUniform(low, high, out)
+  }
+
+  def normal(mean: Float, stdvar: Float, shape: Array[Int]=null, ctx: Context=null, out: NDArray=null): NDArray = {
+    if (out != null) {
+      require(shape == null & ctx == null, "shape and ctx is not needed when out is specified.")
+    } else {
+      require(shape != null, "shape is required when out is not specified")
+      var out = NDArray.empty(shape, ctx)
+    }
+    return NDArray._randomGaussian(mean, stdvar, out)
+  }
+}

From c12eb5e39e77263eb7f436b1cbbf2874ec5b6beb Mon Sep 17 00:00:00 2001
From: terrytangyuan <terrytangyuan@gmail.com>
Date: Sun, 27 Dec 2015 18:26:29 -0600
Subject: [PATCH 02/11] Random.seed and doc-strings

---
 .../src/main/scala/ml/dmlc/mxnet/Random.scala | 54 ++++++++++++++++---
 1 file changed, 47 insertions(+), 7 deletions(-)

diff --git a/scala-package/core/src/main/scala/ml/dmlc/mxnet/Random.scala b/scala-package/core/src/main/scala/ml/dmlc/mxnet/Random.scala
index 407fabdcbffd..9287e9b8bf1b 100644
--- a/scala-package/core/src/main/scala/ml/dmlc/mxnet/Random.scala
+++ b/scala-package/core/src/main/scala/ml/dmlc/mxnet/Random.scala
@@ -1,29 +1,69 @@
 package ml.dmlc.mxnet
 
+import ml.dmlc.mxnet.Base._
+import ml.dmlc.mxnet.NDArray.{_randomUniform, _randomGaussian, empty}
 
-import ml.dmlc.mxnet.NDArray.{_randomUniform}
 /**
- * Created by yuantang on 12/27/15.
+ * Random Number interface of mxnet.
+ * @author Yuan Tang
  */
 class Random {
-
+  /**
+   * Generate uniform distribution in [low, high) with shape.
+   *
+   * @param low The lower bound of distribution.
+   * @param high The upper bound of distribution.
+   * @param shape Output shape of the NDArray generated.
+   * @param ctx Context of output NDArray, will use default context if not specified.
+   * @param out Output place holder
+   * @return The result NDArray with generated result.
+   */
   def uniform(low: Float, high: Float, shape: Array[Int]=null, ctx: Context=null, out: NDArray=null): NDArray = {
     if (out != null) {
       require(shape == null & ctx == null, "shape and ctx is not needed when out is specified.")
     } else {
       require(shape != null, "shape is required when out is not specified")
-      var out = NDArray.empty(shape, ctx)
+      var out = empty(shape, ctx)
     }
-    return NDArray._randomUniform(low, high, out)
+    return _randomUniform(low, high, out)
   }
 
+
+  /**
+   * Generate normal(Gaussian) distribution N(mean, stdvar^^2) with shape.
+   *
+   * @param mean The mean of the normal distribution.
+   * @param stdvar The standard deviation of normal distribution.
+   * @param shape Output shape of the NDArray generated.
+   * @param ctx Context of output NDArray, will use default context if not specified.
+   * @param out Output place holder
+   * @return The result NDArray with generated result.
+   */
   def normal(mean: Float, stdvar: Float, shape: Array[Int]=null, ctx: Context=null, out: NDArray=null): NDArray = {
     if (out != null) {
       require(shape == null & ctx == null, "shape and ctx is not needed when out is specified.")
     } else {
       require(shape != null, "shape is required when out is not specified")
-      var out = NDArray.empty(shape, ctx)
+      var out = empty(shape, ctx)
     }
-    return NDArray._randomGaussian(mean, stdvar, out)
+    return _randomGaussian(mean, stdvar, out)
+  }
+
+
+  /**
+   * Seed the random number generators in mxnet.
+   *
+   * This seed will affect behavior of functions in this module,
+   * as well as results from executors that contains Random number
+   * such as Dropout operators.
+   *
+   * @param seedState The random number seed to set to all devices.
+   * @note The random number generator of mxnet is by default device specific.
+   *       This means if you set the same seed, the random number sequence
+   *       generated from GPU0 can be different from CPU.
+   */
+  def seed(seedState: Int) = {
+    // TODO
+//    checkCall(_LIB.mxRandomSeed(seedState))
   }
 }

From 27b892c50e86ef8b56884778af2fef732385b665 Mon Sep 17 00:00:00 2001
From: terrytangyuan <terrytangyuan@gmail.com>
Date: Sun, 27 Dec 2015 19:35:05 -0600
Subject: [PATCH 03/11] Initializer abstract class

---
 .../scala/ml/dmlc/mxnet/Initializer.scala     | 45 +++++++++++++++++++
 .../main/scala/ml/dmlc/mxnet/NDArray.scala    |  2 +-
 2 files changed, 46 insertions(+), 1 deletion(-)
 create mode 100644 scala-package/core/src/main/scala/ml/dmlc/mxnet/Initializer.scala

diff --git a/scala-package/core/src/main/scala/ml/dmlc/mxnet/Initializer.scala b/scala-package/core/src/main/scala/ml/dmlc/mxnet/Initializer.scala
new file mode 100644
index 000000000000..4b0fb42b3c7a
--- /dev/null
+++ b/scala-package/core/src/main/scala/ml/dmlc/mxnet/Initializer.scala
@@ -0,0 +1,45 @@
+package ml.dmlc.mxnet
+
+import ml.dmlc.mxnet.NDArray.{array, zeros, ones}
+
+/**
+ * Created by yuantang on 12/27/15.
+ */
+abstract class Initializer(name: String, protected var arr: NDArray) {
+
+  def _initBilinear() = {
+    var weight = Array.fill[Float](arr.size)(0.0f)
+    val shape = arr.shape
+    val f = shape(3) / 2.0f
+    val c = (2 * f - 1 - f % 2) / (2.0f * f)
+
+    (0 to (arr.size)).foreach { i =>
+      var x = i % shape(3)
+      var y = (i % shape(3)) % shape(2)
+      weight(i) = (1 - math.abs(x / f - c)) * (1 - math.abs(y / f - c))
+    }
+
+    arr = array(weight)
+
+  }
+
+  def _initZero() = {
+    arr = zeros(arr.size)
+  }
+
+  def _initBias() = {
+    arr = zeros(arr.size)
+  }
+
+  def _initGamma() = {
+    arr = ones(arr.size)
+  }
+
+  def _initBeta() = {
+    arr = zeros(arr.size)
+  }
+
+  def _initWeight()
+
+  def _initDefault()
+}
diff --git a/scala-package/core/src/main/scala/ml/dmlc/mxnet/NDArray.scala b/scala-package/core/src/main/scala/ml/dmlc/mxnet/NDArray.scala
index aac8077d0d6c..0429313b6db1 100644
--- a/scala-package/core/src/main/scala/ml/dmlc/mxnet/NDArray.scala
+++ b/scala-package/core/src/main/scala/ml/dmlc/mxnet/NDArray.scala
@@ -280,7 +280,7 @@ object NDArray {
    * @param ctx The context of the NDArray, default to current default context.
    * @return The created NDArray.
    */
-  def array(sourceArr: Array[Int], ctx: Context=null): NDArray = ???
+  def array(sourceArr: Array[Float], ctx: Context=null): NDArray = ???
 
   /**
    * Load ndarray from binary file.

From 6c2702f4fd8dd0ef36c0181db30b2899da869145 Mon Sep 17 00:00:00 2001
From: terrytangyuan <terrytangyuan@gmail.com>
Date: Sun, 27 Dec 2015 20:05:27 -0600
Subject: [PATCH 04/11] Uniform, Normal, Xavier

---
 .../scala/ml/dmlc/mxnet/Initializer.scala     | 42 ++++++++++++++++++-
 .../src/main/scala/ml/dmlc/mxnet/Random.scala |  2 +-
 2 files changed, 41 insertions(+), 3 deletions(-)

diff --git a/scala-package/core/src/main/scala/ml/dmlc/mxnet/Initializer.scala b/scala-package/core/src/main/scala/ml/dmlc/mxnet/Initializer.scala
index 4b0fb42b3c7a..aeb3551bdcc1 100644
--- a/scala-package/core/src/main/scala/ml/dmlc/mxnet/Initializer.scala
+++ b/scala-package/core/src/main/scala/ml/dmlc/mxnet/Initializer.scala
@@ -5,7 +5,7 @@ import ml.dmlc.mxnet.NDArray.{array, zeros, ones}
 /**
  * Created by yuantang on 12/27/15.
  */
-abstract class Initializer(name: String, protected var arr: NDArray) {
+abstract class Initializer(protected val name: String, protected var arr: NDArray) {
 
   def _initBilinear() = {
     var weight = Array.fill[Float](arr.size)(0.0f)
@@ -41,5 +41,43 @@ abstract class Initializer(name: String, protected var arr: NDArray) {
 
   def _initWeight()
 
-  def _initDefault()
 }
+
+class Uniform(name: String, arr: NDArray, protected val scale: Float=0.07f) extends Initializer(name: String, arr: NDArray) {
+  def _initWeight() = {
+    Random.uniform(-scale, scale, out=arr)
+  }
+}
+
+class Normal(name: String, arr: NDArray, protected val sigma: Float=0.01f) extends Initializer(name: String, arr: NDArray) {
+  def _initWeight() = {
+    Random.normal(0, sigma, out=arr)
+  }
+}
+
+
+class Xavier(name: String, arr: NDArray, protected val rndType: String ="uniform",
+             protected val factorType: String ="avg", protected val magnitude: Int = 3)
+  extends Initializer(name: String, arr: NDArray) {
+
+  def _initWeight() = {
+    val shape = arr.shape
+    val fanIn = shape.slice(1, shape.length).product
+    val fanOut = shape(0)
+    var factor = 1
+
+    factor = factorType match {
+      case "avg" => (fanIn + fanOut) / 2
+      case "in" => fanIn
+      case "out" => fanOut
+      case _ => throw new IllegalArgumentException("Incorrect factor type")
+    }
+    val scale = math.sqrt(magnitude / factor) toFloat
+
+    rndType match {
+      case "uniform" => Random.uniform(-scale, scale, out=arr)
+      case "normal" => Random.normal(0, scale, out=arr)
+      case _ => throw new IllegalArgumentException("Unknown random type")
+    }
+  }
+}
\ No newline at end of file
diff --git a/scala-package/core/src/main/scala/ml/dmlc/mxnet/Random.scala b/scala-package/core/src/main/scala/ml/dmlc/mxnet/Random.scala
index 9287e9b8bf1b..12ca212e09a5 100644
--- a/scala-package/core/src/main/scala/ml/dmlc/mxnet/Random.scala
+++ b/scala-package/core/src/main/scala/ml/dmlc/mxnet/Random.scala
@@ -7,7 +7,7 @@ import ml.dmlc.mxnet.NDArray.{_randomUniform, _randomGaussian, empty}
  * Random Number interface of mxnet.
  * @author Yuan Tang
  */
-class Random {
+object Random {
   /**
    * Generate uniform distribution in [low, high) with shape.
    *

From 95751566ccc3129c2f8852871ee715338cee1f41 Mon Sep 17 00:00:00 2001
From: terrytangyuan <terrytangyuan@gmail.com>
Date: Sun, 27 Dec 2015 20:15:04 -0600
Subject: [PATCH 05/11] Constructor for Initializer and handle exception

---
 .../scala/ml/dmlc/mxnet/Initializer.scala     | 56 ++++++++++++++++++-
 1 file changed, 53 insertions(+), 3 deletions(-)

diff --git a/scala-package/core/src/main/scala/ml/dmlc/mxnet/Initializer.scala b/scala-package/core/src/main/scala/ml/dmlc/mxnet/Initializer.scala
index aeb3551bdcc1..76b2fb0f2c1e 100644
--- a/scala-package/core/src/main/scala/ml/dmlc/mxnet/Initializer.scala
+++ b/scala-package/core/src/main/scala/ml/dmlc/mxnet/Initializer.scala
@@ -2,11 +2,38 @@ package ml.dmlc.mxnet
 
 import ml.dmlc.mxnet.NDArray.{array, zeros, ones}
 
+
 /**
- * Created by yuantang on 12/27/15.
+ *
+ * Base class for Initializer.
+ *
+ * @author Yuan Tang
+ *
+ * @param name name of corrosponding ndarray
+ * @param arr ndarray to be Initialized
  */
 abstract class Initializer(protected val name: String, protected var arr: NDArray) {
 
+  if (name.startsWith("upsampling")) {
+    _initBilinear()
+  } else if (name.endsWith("bias")) {
+    _initBias()
+  } else if (name.endsWith("gamma")) {
+    _initGamma()
+  } else if (name.endsWith("beta")) {
+    _initBeta()
+  } else if (name.endsWith("weight")) {
+    _initWeight()
+  } else if (name.endsWith("moving_mean")) {
+    _initZero()
+  } else if (name.endsWith("moving_var")) {
+    _initZero()
+  } else if (name.endsWith("moving_avg")) {
+    _initZero()
+  } else {
+    throw new IllegalArgumentException(s"Unknown initialization pattern for ${name}.")
+  }
+
   def _initBilinear() = {
     var weight = Array.fill[Float](arr.size)(0.0f)
     val shape = arr.shape
@@ -20,7 +47,6 @@ abstract class Initializer(protected val name: String, protected var arr: NDArra
     }
 
     arr = array(weight)
-
   }
 
   def _initZero() = {
@@ -40,15 +66,30 @@ abstract class Initializer(protected val name: String, protected var arr: NDArra
   }
 
   def _initWeight()
-
 }
 
+
+/**
+ * Initialize the weight with uniform [-scale, scale]
+ *
+ * @param name name of corrosponding ndarray
+ * @param arr ndarray to be Initialized
+ * @param scale The scale of uniform distribution
+ */
 class Uniform(name: String, arr: NDArray, protected val scale: Float=0.07f) extends Initializer(name: String, arr: NDArray) {
   def _initWeight() = {
     Random.uniform(-scale, scale, out=arr)
   }
 }
 
+
+/**
+ * Initialize the weight with normal(0, sigma)
+ *
+ * @param name name of corrosponding ndarray
+ * @param arr ndarray to be Initialized
+ * @param sigma Standard deviation for gaussian distribution.
+ */
 class Normal(name: String, arr: NDArray, protected val sigma: Float=0.01f) extends Initializer(name: String, arr: NDArray) {
   def _initWeight() = {
     Random.normal(0, sigma, out=arr)
@@ -56,6 +97,15 @@ class Normal(name: String, arr: NDArray, protected val sigma: Float=0.01f) exten
 }
 
 
+/**
+ * Initialize the weight with Xavier or similar initialization scheme.
+ *
+ * @param name name of corrosponding ndarray
+ * @param arr ndarray to be Initialized
+ * @param rndType Options are: "gaussian" or "uniform"
+ * @param factorType Options are: "avg", "in", "out"
+ * @param magnitude scale of random number range
+ */
 class Xavier(name: String, arr: NDArray, protected val rndType: String ="uniform",
              protected val factorType: String ="avg", protected val magnitude: Int = 3)
   extends Initializer(name: String, arr: NDArray) {

From 654840df5acf1ece0d03c1228dd7a80008a5cb19 Mon Sep 17 00:00:00 2001
From: terrytangyuan <terrytangyuan@gmail.com>
Date: Sun, 27 Dec 2015 22:54:33 -0600
Subject: [PATCH 06/11] Added missing period and fix typo

---
 .../core/src/main/scala/ml/dmlc/mxnet/Initializer.scala       | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/scala-package/core/src/main/scala/ml/dmlc/mxnet/Initializer.scala b/scala-package/core/src/main/scala/ml/dmlc/mxnet/Initializer.scala
index 76b2fb0f2c1e..416fd1a16d6a 100644
--- a/scala-package/core/src/main/scala/ml/dmlc/mxnet/Initializer.scala
+++ b/scala-package/core/src/main/scala/ml/dmlc/mxnet/Initializer.scala
@@ -42,7 +42,7 @@ abstract class Initializer(protected val name: String, protected var arr: NDArra
 
     (0 to (arr.size)).foreach { i =>
       var x = i % shape(3)
-      var y = (i % shape(3)) % shape(2)
+      var y = (i / shape(3)) % shape(2)
       weight(i) = (1 - math.abs(x / f - c)) * (1 - math.abs(y / f - c))
     }
 
@@ -122,7 +122,7 @@ class Xavier(name: String, arr: NDArray, protected val rndType: String ="uniform
       case "out" => fanOut
       case _ => throw new IllegalArgumentException("Incorrect factor type")
     }
-    val scale = math.sqrt(magnitude / factor) toFloat
+    val scale = math.sqrt(magnitude / factor).toFloat
 
     rndType match {
       case "uniform" => Random.uniform(-scale, scale, out=arr)

From c68542550980b40b1b0457c741e091412e605c46 Mon Sep 17 00:00:00 2001
From: terrytangyuan <terrytangyuan@gmail.com>
Date: Mon, 28 Dec 2015 08:20:49 -0600
Subject: [PATCH 07/11] Avoid scope in ifelse and for, changed var to val

---
 .../src/main/scala/ml/dmlc/mxnet/Initializer.scala |  6 +++---
 .../core/src/main/scala/ml/dmlc/mxnet/Random.scala | 14 ++++++++------
 2 files changed, 11 insertions(+), 9 deletions(-)

diff --git a/scala-package/core/src/main/scala/ml/dmlc/mxnet/Initializer.scala b/scala-package/core/src/main/scala/ml/dmlc/mxnet/Initializer.scala
index 416fd1a16d6a..3c2148a503ca 100644
--- a/scala-package/core/src/main/scala/ml/dmlc/mxnet/Initializer.scala
+++ b/scala-package/core/src/main/scala/ml/dmlc/mxnet/Initializer.scala
@@ -35,14 +35,14 @@ abstract class Initializer(protected val name: String, protected var arr: NDArra
   }
 
   def _initBilinear() = {
-    var weight = Array.fill[Float](arr.size)(0.0f)
+    val weight = Array.fill[Float](arr.size)(0.0f)
     val shape = arr.shape
     val f = shape(3) / 2.0f
     val c = (2 * f - 1 - f % 2) / (2.0f * f)
 
     (0 to (arr.size)).foreach { i =>
-      var x = i % shape(3)
-      var y = (i / shape(3)) % shape(2)
+      val x = i % shape(3)
+      val y = (i / shape(3)) % shape(2)
       weight(i) = (1 - math.abs(x / f - c)) * (1 - math.abs(y / f - c))
     }
 
diff --git a/scala-package/core/src/main/scala/ml/dmlc/mxnet/Random.scala b/scala-package/core/src/main/scala/ml/dmlc/mxnet/Random.scala
index 12ca212e09a5..9bcfe4eb162b 100644
--- a/scala-package/core/src/main/scala/ml/dmlc/mxnet/Random.scala
+++ b/scala-package/core/src/main/scala/ml/dmlc/mxnet/Random.scala
@@ -19,13 +19,14 @@ object Random {
    * @return The result NDArray with generated result.
    */
   def uniform(low: Float, high: Float, shape: Array[Int]=null, ctx: Context=null, out: NDArray=null): NDArray = {
-    if (out != null) {
+    var outCopy = out
+    if (outCopy != null) {
       require(shape == null & ctx == null, "shape and ctx is not needed when out is specified.")
     } else {
       require(shape != null, "shape is required when out is not specified")
-      var out = empty(shape, ctx)
+      outCopy = empty(shape, ctx)
     }
-    return _randomUniform(low, high, out)
+    return _randomUniform(low, high, outCopy)
   }
 
 
@@ -40,13 +41,14 @@ object Random {
    * @return The result NDArray with generated result.
    */
   def normal(mean: Float, stdvar: Float, shape: Array[Int]=null, ctx: Context=null, out: NDArray=null): NDArray = {
-    if (out != null) {
+    var outCopy = out
+    if (outCopy != null) {
       require(shape == null & ctx == null, "shape and ctx is not needed when out is specified.")
     } else {
       require(shape != null, "shape is required when out is not specified")
-      var out = empty(shape, ctx)
+      outCopy = empty(shape, ctx)
     }
-    return _randomGaussian(mean, stdvar, out)
+    return _randomGaussian(mean, stdvar, outCopy)
   }
 
 

From 2a671ba0aa234cc64c0944993fd6b5fb26936dc6 Mon Sep 17 00:00:00 2001
From: terrytangyuan <terrytangyuan@gmail.com>
Date: Mon, 28 Dec 2015 18:26:57 -0600
Subject: [PATCH 08/11] Use apply() for Initializer instead

---
 .../scala/ml/dmlc/mxnet/Initializer.scala     | 45 +++++++++++--------
 1 file changed, 27 insertions(+), 18 deletions(-)

diff --git a/scala-package/core/src/main/scala/ml/dmlc/mxnet/Initializer.scala b/scala-package/core/src/main/scala/ml/dmlc/mxnet/Initializer.scala
index 3c2148a503ca..f60270e615b6 100644
--- a/scala-package/core/src/main/scala/ml/dmlc/mxnet/Initializer.scala
+++ b/scala-package/core/src/main/scala/ml/dmlc/mxnet/Initializer.scala
@@ -14,24 +14,33 @@ import ml.dmlc.mxnet.NDArray.{array, zeros, ones}
  */
 abstract class Initializer(protected val name: String, protected var arr: NDArray) {
 
-  if (name.startsWith("upsampling")) {
-    _initBilinear()
-  } else if (name.endsWith("bias")) {
-    _initBias()
-  } else if (name.endsWith("gamma")) {
-    _initGamma()
-  } else if (name.endsWith("beta")) {
-    _initBeta()
-  } else if (name.endsWith("weight")) {
-    _initWeight()
-  } else if (name.endsWith("moving_mean")) {
-    _initZero()
-  } else if (name.endsWith("moving_var")) {
-    _initZero()
-  } else if (name.endsWith("moving_avg")) {
-    _initZero()
-  } else {
-    throw new IllegalArgumentException(s"Unknown initialization pattern for ${name}.")
+  /**
+   * Initialize an Initializer
+   *
+   * @param name name of corrosponding ndarray
+   * @param arr ndarray to be Initialized
+   */
+  def apply(name: String, arr: NDArray) = {
+
+    if (name.startsWith("upsampling")) {
+      _initBilinear()
+    } else if (name.endsWith("bias")) {
+      _initBias()
+    } else if (name.endsWith("gamma")) {
+      _initGamma()
+    } else if (name.endsWith("beta")) {
+      _initBeta()
+    } else if (name.endsWith("weight")) {
+      _initWeight()
+    } else if (name.endsWith("moving_mean")) {
+      _initZero()
+    } else if (name.endsWith("moving_var")) {
+      _initZero()
+    } else if (name.endsWith("moving_avg")) {
+      _initZero()
+    } else {
+      throw new IllegalArgumentException(s"Unknown initialization pattern for ${name}.")
+    }
   }
 
   def _initBilinear() = {

From 48172b26233f07edb03ac778187493839f7602fa Mon Sep 17 00:00:00 2001
From: terrytangyuan <terrytangyuan@gmail.com>
Date: Mon, 28 Dec 2015 22:53:03 -0600
Subject: [PATCH 09/11] Used arr.set instead of use = to change reference,
 explicit return type for init methods

---
 .../scala/ml/dmlc/mxnet/Initializer.scala     | 26 +++++++++----------
 1 file changed, 13 insertions(+), 13 deletions(-)

diff --git a/scala-package/core/src/main/scala/ml/dmlc/mxnet/Initializer.scala b/scala-package/core/src/main/scala/ml/dmlc/mxnet/Initializer.scala
index f60270e615b6..ea3281cc4066 100644
--- a/scala-package/core/src/main/scala/ml/dmlc/mxnet/Initializer.scala
+++ b/scala-package/core/src/main/scala/ml/dmlc/mxnet/Initializer.scala
@@ -43,7 +43,7 @@ abstract class Initializer(protected val name: String, protected var arr: NDArra
     }
   }
 
-  def _initBilinear() = {
+  def _initBilinear(): Unit = {
     val weight = Array.fill[Float](arr.size)(0.0f)
     val shape = arr.shape
     val f = shape(3) / 2.0f
@@ -55,26 +55,26 @@ abstract class Initializer(protected val name: String, protected var arr: NDArra
       weight(i) = (1 - math.abs(x / f - c)) * (1 - math.abs(y / f - c))
     }
 
-    arr = array(weight)
+    arr.set(array(weight))
   }
 
-  def _initZero() = {
-    arr = zeros(arr.size)
+  def _initZero(): Unit = {
+    arr.set(zeros(arr.size))
   }
 
-  def _initBias() = {
-    arr = zeros(arr.size)
+  def _initBias(): Unit = {
+    arr.set(zeros(arr.size))
   }
 
-  def _initGamma() = {
-    arr = ones(arr.size)
+  def _initGamma(): Unit = {
+    arr.set(ones(arr.size))
   }
 
-  def _initBeta() = {
-    arr = zeros(arr.size)
+  def _initBeta(): Unit = {
+    arr.set(zeros(arr.size))
   }
 
-  def _initWeight()
+  def _initWeight(): Unit
 }
 
 
@@ -86,7 +86,7 @@ abstract class Initializer(protected val name: String, protected var arr: NDArra
  * @param scale The scale of uniform distribution
  */
 class Uniform(name: String, arr: NDArray, protected val scale: Float=0.07f) extends Initializer(name: String, arr: NDArray) {
-  def _initWeight() = {
+  override def _initWeight(): Unit = {
     Random.uniform(-scale, scale, out=arr)
   }
 }
@@ -100,7 +100,7 @@ class Uniform(name: String, arr: NDArray, protected val scale: Float=0.07f) exte
  * @param sigma Standard deviation for gaussian distribution.
  */
 class Normal(name: String, arr: NDArray, protected val sigma: Float=0.01f) extends Initializer(name: String, arr: NDArray) {
-  def _initWeight() = {
+  override def _initWeight(): Unit = {
     Random.normal(0, sigma, out=arr)
   }
 }

From baf12792a935fd50c52d07e3a79f258c3fc1d3de Mon Sep 17 00:00:00 2001
From: terrytangyuan <terrytangyuan@gmail.com>
Date: Mon, 28 Dec 2015 23:05:52 -0600
Subject: [PATCH 10/11] Removed arguments in Initializer and its subclasses,
 add the arguments to init methods instead

---
 .../scala/ml/dmlc/mxnet/Initializer.scala     | 57 ++++++++-----------
 1 file changed, 24 insertions(+), 33 deletions(-)

diff --git a/scala-package/core/src/main/scala/ml/dmlc/mxnet/Initializer.scala b/scala-package/core/src/main/scala/ml/dmlc/mxnet/Initializer.scala
index ea3281cc4066..82473964c368 100644
--- a/scala-package/core/src/main/scala/ml/dmlc/mxnet/Initializer.scala
+++ b/scala-package/core/src/main/scala/ml/dmlc/mxnet/Initializer.scala
@@ -8,11 +8,8 @@ import ml.dmlc.mxnet.NDArray.{array, zeros, ones}
  * Base class for Initializer.
  *
  * @author Yuan Tang
- *
- * @param name name of corrosponding ndarray
- * @param arr ndarray to be Initialized
  */
-abstract class Initializer(protected val name: String, protected var arr: NDArray) {
+abstract class Initializer {
 
   /**
    * Initialize an Initializer
@@ -20,30 +17,30 @@ abstract class Initializer(protected val name: String, protected var arr: NDArra
    * @param name name of corrosponding ndarray
    * @param arr ndarray to be Initialized
    */
-  def apply(name: String, arr: NDArray) = {
+  def apply(name: String, arr: NDArray): Unit = {
 
     if (name.startsWith("upsampling")) {
-      _initBilinear()
+      _initBilinear(name, arr)
     } else if (name.endsWith("bias")) {
-      _initBias()
+      _initBias(name, arr)
     } else if (name.endsWith("gamma")) {
-      _initGamma()
+      _initGamma(name, arr)
     } else if (name.endsWith("beta")) {
-      _initBeta()
+      _initBeta(name, arr)
     } else if (name.endsWith("weight")) {
-      _initWeight()
+      _initWeight(name, arr)
     } else if (name.endsWith("moving_mean")) {
-      _initZero()
+      _initZero(name, arr)
     } else if (name.endsWith("moving_var")) {
-      _initZero()
+      _initZero(name, arr)
     } else if (name.endsWith("moving_avg")) {
-      _initZero()
+      _initZero(name, arr)
     } else {
       throw new IllegalArgumentException(s"Unknown initialization pattern for ${name}.")
     }
   }
 
-  def _initBilinear(): Unit = {
+  def _initBilinear(name: String, arr: NDArray): Unit = {
     val weight = Array.fill[Float](arr.size)(0.0f)
     val shape = arr.shape
     val f = shape(3) / 2.0f
@@ -58,35 +55,33 @@ abstract class Initializer(protected val name: String, protected var arr: NDArra
     arr.set(array(weight))
   }
 
-  def _initZero(): Unit = {
+  def _initZero(name: String, arr: NDArray): Unit = {
     arr.set(zeros(arr.size))
   }
 
-  def _initBias(): Unit = {
+  def _initBias(name: String, arr: NDArray): Unit = {
     arr.set(zeros(arr.size))
   }
 
-  def _initGamma(): Unit = {
+  def _initGamma(name: String, arr: NDArray): Unit = {
     arr.set(ones(arr.size))
   }
 
-  def _initBeta(): Unit = {
+  def _initBeta(name: String, arr: NDArray): Unit = {
     arr.set(zeros(arr.size))
   }
 
-  def _initWeight(): Unit
+  def _initWeight(name: String, arr: NDArray): Unit
 }
 
 
 /**
  * Initialize the weight with uniform [-scale, scale]
  *
- * @param name name of corrosponding ndarray
- * @param arr ndarray to be Initialized
  * @param scale The scale of uniform distribution
  */
-class Uniform(name: String, arr: NDArray, protected val scale: Float=0.07f) extends Initializer(name: String, arr: NDArray) {
-  override def _initWeight(): Unit = {
+class Uniform(protected val scale: Float=0.07f) extends Initializer {
+  override def _initWeight(name: String, arr: NDArray): Unit = {
     Random.uniform(-scale, scale, out=arr)
   }
 }
@@ -95,12 +90,10 @@ class Uniform(name: String, arr: NDArray, protected val scale: Float=0.07f) exte
 /**
  * Initialize the weight with normal(0, sigma)
  *
- * @param name name of corrosponding ndarray
- * @param arr ndarray to be Initialized
  * @param sigma Standard deviation for gaussian distribution.
  */
-class Normal(name: String, arr: NDArray, protected val sigma: Float=0.01f) extends Initializer(name: String, arr: NDArray) {
-  override def _initWeight(): Unit = {
+class Normal(protected val sigma: Float=0.01f) extends Initializer {
+  override def _initWeight(name: String, arr: NDArray): Unit = {
     Random.normal(0, sigma, out=arr)
   }
 }
@@ -109,17 +102,15 @@ class Normal(name: String, arr: NDArray, protected val sigma: Float=0.01f) exten
 /**
  * Initialize the weight with Xavier or similar initialization scheme.
  *
- * @param name name of corrosponding ndarray
- * @param arr ndarray to be Initialized
  * @param rndType Options are: "gaussian" or "uniform"
  * @param factorType Options are: "avg", "in", "out"
  * @param magnitude scale of random number range
  */
-class Xavier(name: String, arr: NDArray, protected val rndType: String ="uniform",
-             protected val factorType: String ="avg", protected val magnitude: Int = 3)
-  extends Initializer(name: String, arr: NDArray) {
+class Xavier(protected val rndType: String ="uniform",
+             protected val factorType: String ="avg",
+             protected val magnitude: Int = 3) extends Initializer {
 
-  def _initWeight() = {
+  override def _initWeight(name: String, arr: NDArray): Unit = {
     val shape = arr.shape
     val fanIn = shape.slice(1, shape.length).product
     val fanOut = shape(0)

From acb82e2e6e60b6e2bd6b8af1f351ea9716f45c27 Mon Sep 17 00:00:00 2001
From: terrytangyuan <terrytangyuan@gmail.com>
Date: Mon, 28 Dec 2015 23:23:18 -0600
Subject: [PATCH 11/11] Changed to set()0f without initializing a new array
 first

---
 .../core/src/main/scala/ml/dmlc/mxnet/Initializer.scala   | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/scala-package/core/src/main/scala/ml/dmlc/mxnet/Initializer.scala b/scala-package/core/src/main/scala/ml/dmlc/mxnet/Initializer.scala
index 82473964c368..5287200065e2 100644
--- a/scala-package/core/src/main/scala/ml/dmlc/mxnet/Initializer.scala
+++ b/scala-package/core/src/main/scala/ml/dmlc/mxnet/Initializer.scala
@@ -56,19 +56,19 @@ abstract class Initializer {
   }
 
   def _initZero(name: String, arr: NDArray): Unit = {
-    arr.set(zeros(arr.size))
+    arr.set(0f)
   }
 
   def _initBias(name: String, arr: NDArray): Unit = {
-    arr.set(zeros(arr.size))
+    arr.set(0f)
   }
 
   def _initGamma(name: String, arr: NDArray): Unit = {
-    arr.set(ones(arr.size))
+    arr.set(1f)
   }
 
   def _initBeta(name: String, arr: NDArray): Unit = {
-    arr.set(zeros(arr.size))
+    arr.set(0f)
   }
 
   def _initWeight(name: String, arr: NDArray): Unit