Merge branch 'passthroughargs-docs' of https://github.com/svotaw/Syna…

…pseML into passthroughargs-docs

.github/ISSUE_TEMPLATE/bug_report_template.yaml

@@ -27,7 +27,7 @@ body:
         Describe the system where you encountered the bug.
       value: |
         - **Language version** (e.g. python 3.8, scala 2.12):
-        - **Spark Version** (e.g. 3.2.2):
+        - **Spark Version** (e.g. 3.2.3):
         - **Spark Platform** (e.g. Synapse, Databricks):
     validations:
       required: true

README.md

@@ -14,7 +14,7 @@ SynapseML requires Scala 2.12, Spark 3.2+, and Python 3.6+.
 | Version | [![Version](https://img.shields.io/badge/version-0.10.2-blue)](https://github.com/Microsoft/SynapseML/releases) [![Release Notes](https://img.shields.io/badge/release-notes-blue)](https://github.com/Microsoft/SynapseML/releases) [![Snapshot Version](https://mmlspark.blob.core.windows.net/icons/badges/master_version3.svg)](#sbt)                                                                                                                                      |
 | Docs    | [![Scala Docs](https://img.shields.io/static/v1?label=api%20docs&message=scala&color=blue&logo=scala)](https://mmlspark.blob.core.windows.net/docs/0.10.2/scala/index.html#package) [![PySpark Docs](https://img.shields.io/static/v1?label=api%20docs&message=python&color=blue&logo=python)](https://mmlspark.blob.core.windows.net/docs/0.10.2/pyspark/index.html) [![Academic Paper](https://img.shields.io/badge/academic-paper-7fdcf7)](https://arxiv.org/abs/1810.08744) |
 | Support | [![Gitter](https://badges.gitter.im/Microsoft/MMLSpark.svg)](https://gitter.im/Microsoft/MMLSpark?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge) [![Mail](https://img.shields.io/badge/mail-synapseml--support-brightgreen)](mailto:[email protected])                                                                                                                                                                                                |
-| Binder  | [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/microsoft/SynapseML/93d7ccf?labpath=notebooks%2Ffeatures) |
+| Binder  | [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/microsoft/SynapseML/v0.10.2?labpath=notebooks%2Ffeatures) |
 
 <summary><strong><em>Table of Contents</em></strong></summary>
 

build.sbt

@@ -8,7 +8,7 @@ import scala.xml.transform.{RewriteRule, RuleTransformer}
 import scala.xml.{Node => XmlNode, NodeSeq => XmlNodeSeq, _}
 
 val condaEnvName = "synapseml"
-val sparkVersion = "3.2.2"
+val sparkVersion = "3.2.3"
 name := "synapseml"
 ThisBuild / organization := "com.microsoft.azure"
 ThisBuild / scalaVersion := "2.12.15"
@@ -402,7 +402,6 @@ lazy val deepLearning = (project in file("deep-learning"))
   .settings(settings ++ Seq(
     libraryDependencies ++= Seq(
       "com.microsoft.azure" % "onnx-protobuf_2.12" % "0.9.1" classifier "assembly",
-      "com.microsoft.cntk" % "cntk" % "2.4",
       "com.microsoft.onnxruntime" % "onnxruntime_gpu" % "1.8.1"
     ),
     name := "synapseml-deep-learning"

core/src/main/scala/com/microsoft/azure/synapse/ml/image/UnrollImage.scala

@@ -21,6 +21,7 @@ import org.apache.spark.sql.{DataFrame, Dataset, Row}
 import java.awt.Color
 import java.awt.color.ColorSpace
 import java.awt.image.BufferedImage
+import java.awt.{Image => JImage}
 import scala.math.round
 
 object UnrollImage extends DefaultParamsReadable[UnrollImage] {
@@ -132,14 +133,31 @@ object UnrollImage extends DefaultParamsReadable[UnrollImage] {
     val biOpt = ImageUtils.safeRead(bytes)
     biOpt.map { bi =>
       (height, width) match {
-        case (Some(h), Some(w)) => unrollBI(ResizeUtils.resizeBufferedImage(w, h, nChannels)(bi))
+        case (Some(h), Some(w)) => unrollBI(resizeBufferedImage(w, h, nChannels)(bi))
         case (None, None) => unrollBI(bi)
         case _ =>
           throw new IllegalArgumentException("Height and width must either both be specified or unspecified")
       }
     }
   }
 
+  private[ml] def resizeBufferedImage(width: Int,
+                                      height: Int,
+                                      channels: Option[Int])(image: BufferedImage): BufferedImage = {
+    val imgType = channels.map(ImageUtils.channelsToType).getOrElse(image.getType)
+
+    if (image.getWidth == width && image.getHeight == height && image.getType == imgType) {
+      image
+    } else {
+      val resizedImage = image.getScaledInstance(width, height, JImage.SCALE_DEFAULT)
+      val bufferedImage = new BufferedImage(width, height, imgType)
+      val g = bufferedImage.createGraphics()
+      g.drawImage(resizedImage, 0, 0, null) //scalastyle:ignore null
+      g.dispose()
+      bufferedImage
+    }
+  }
+
 }
 
 /** Converts the representation of an m X n pixel image to an m * n vector of Doubles
@@ -148,7 +166,6 @@ object UnrollImage extends DefaultParamsReadable[UnrollImage] {
   *
   * @param uid The id of the module
   */
-@deprecated("Please use 'OnnxModel'.", since="0.10.2")
 class UnrollImage(val uid: String) extends Transformer
   with HasInputCol with HasOutputCol with Wrappable with DefaultParamsWritable with BasicLogging {
   logClass()

core/src/main/scala/com/microsoft/azure/synapse/ml/logging/BasicLogging.scala

@@ -52,10 +52,6 @@ trait BasicLogging extends Logging {
     logVerb("transform", f)
   }
 
-  def logPredict[T](f: => T): T = {
-    logVerb("predict", f)
-  }
-
   def logVerb[T](verb: String, f: => T): T = {
     logBase(verb)
     try {

core/src/test/scala/com/microsoft/azure/synapse/ml/codegen/RTestGen.scala

@@ -101,7 +101,7 @@ object RTestGen {
          |  "spark.sql.shuffle.partitions=10",
          |  "spark.sql.crossJoin.enabled=true")
          |
-         |sc <- spark_connect(master = "local", version = "3.2.2", config = conf)
+         |sc <- spark_connect(master = "local", version = "3.2.3", config = conf)
          |
          |""".stripMargin, StandardOpenOption.CREATE)
 

core/src/test/scala/com/microsoft/azure/synapse/ml/core/test/fuzzing/Fuzzing.scala

@@ -191,8 +191,7 @@ trait DotnetTestFuzzing[S <: PipelineStage] extends TestBase with DataFrameEqual
       .split(".".toCharArray).map(capitalize).mkString(".")
     val externalLoaderImports = conf.name match {
       case "synapseml-deep-learning" =>
-        s"""using Synapse.ML.Cntk;
-           |using Synapse.ML.Onnx;
+        s"""using Synapse.ML.Onnx;
            |using Synapse.ML.Stages;
            |""".stripMargin
       case _ => ""