test

build.sbt

@@ -8,7 +8,7 @@ import scala.xml.transform.{RewriteRule, RuleTransformer}
 import scala.xml.{Node => XmlNode, NodeSeq => XmlNodeSeq, _}
 
 val condaEnvName = "synapseml"
-val sparkVersion = "3.3.1"
+val sparkVersion = "3.3.2"
 name := "synapseml"
 ThisBuild / organization := "com.microsoft.azure"
 ThisBuild / scalaVersion := "2.12.15"

core/src/main/scala/com/microsoft/azure/synapse/ml/codegen/PyCodegen.scala

@@ -68,7 +68,7 @@ object PyCodegen {
       // There's `Already borrowed` error found in transformers 4.16.2 when using tokenizers
       s"""extras_require={"extras": [
          |    "cmake",
-         |    "horovod==0.28.1",
+         |    "horovod==0.27.0",
          |    "pytorch_lightning>=1.5.0,<1.5.10",
          |    "torch==1.13.1",
          |    "torchvision>=0.14.1",

core/src/test/scala/com/microsoft/azure/synapse/ml/nbtest/DatabricksGPUTests.scala

@@ -11,11 +11,7 @@ import java.io.File
 import scala.collection.mutable.ListBuffer
 
 class DatabricksGPUTests extends DatabricksTestHelper {
-  val horovodInstallationScript: File = FileUtilities.join(
-    BuildInfo.baseDirectory.getParent, "deep-learning",
-    "src", "main", "python", "horovod_installation.sh").getCanonicalFile
-  uploadFileToDBFS(horovodInstallationScript, "/FileStore/horovod-fix-commit/horovod_installation.sh")
-  val clusterId: String = createClusterInPool(GPUClusterName, AdbGpuRuntime, 2, GpuPoolId, GPUInitScripts)
+  val clusterId: String = createClusterInPool(GPUClusterName, AdbGpuRuntime, 2, GpuPoolId, "[]")
   val jobIdsToCancel: ListBuffer[Int] = databricksTestHelper(
     clusterId, GPULibraries, GPUNotebooks)
 

core/src/test/scala/com/microsoft/azure/synapse/ml/nbtest/DatabricksUtilities.scala

@@ -29,11 +29,11 @@ object DatabricksUtilities {
 
   // ADB Info
   val Region = "eastus"
-  val PoolName = "synapseml-build-11.2"
-  val GpuPoolName = "synapseml-build-11.2-gpu"
-  val AdbRuntime = "11.2.x-scala2.12"
-  // https://learn.microsoft.com/en-us/azure/databricks/release-notes/runtime/11.2
-  val AdbGpuRuntime = "11.2.x-gpu-ml-scala2.12"
+  val PoolName = "synapseml-build-12.2"
+  val GpuPoolName = "synapseml-build-12.2-gpu"
+  val AdbRuntime = "12.2.x-scala2.12"
+  // https://learn.microsoft.com/en-us/azure/databricks/release-notes/runtime/
+  val AdbGpuRuntime = "12.2.x-gpu-ml-scala2.12"
   val NumWorkers = 5
   val AutoTerminationMinutes = 15
 
@@ -77,10 +77,10 @@ object DatabricksUtilities {
   val GPULibraries: String = List(
     Map("maven" -> Map("coordinates" -> PackageMavenCoordinate, "repo" -> PackageRepository)),
     Map("pypi" -> Map("package" -> "pytorch-lightning==1.5.0")),
-    Map("pypi" -> Map("package" -> "torchvision==0.12.0")),
-    Map("pypi" -> Map("package" -> "transformers==4.32.1")),
-    Map("pypi" -> Map("package" -> "petastorm==0.12.0")),
-    Map("pypi" -> Map("package" -> "protobuf==3.20.3"))
+    Map("pypi" -> Map("package" -> "torchvision==0.14.1")),
+    Map("pypi" -> Map("package" -> "transformers==4.25.1")),
+    Map("pypi" -> Map("package" -> "petastorm==0.12.1")),
+    Map("pypi" -> Map("package" -> "protobuf==3.19.4"))
   ).toJson.compactPrint
 
   val GPUInitScripts: String = List(

deep-learning/src/main/python/horovod_installation.sh

@@ -7,10 +7,10 @@ set -eu
 
 # Install prerequisite libraries that horovod depends on
 pip install pytorch-lightning==1.5.0
-pip install torchvision==0.12.0
-pip install transformers==4.15.0
+pip install torchvision==0.14.1
+pip install transformers==4.25.1
 pip install petastorm>=0.12.0
-pip install protobuf==3.20.3
+pip install protobuf==3.19.1
 
 # Remove Outdated Signing Key:
 sudo apt-key del 7fa2af80
@@ -35,13 +35,13 @@ libcusparse-dev-11-0=11.1.1.245-1
 
 git clone --recursive https://github.com/horovod/horovod.git
 cd horovod
-# git fetch origin refs/tags/v0.28.1:tags/v0.28.1
-git checkout 1d217b59949986d025f6db93c49943fb6b6cc78f
+# git fetch origin refs/tags/v0.27.0:tags/v0.27.0
+git checkout bfaca90d5cf66780a97d8799d4e1573855b64560
 git checkout -b tmp-branch
 rm -rf build/ dist/
 HOROVOD_GPU_ALLREDUCE=NCCL HOROVOD_CUDA_HOME=/usr/local/cuda-11/ HOROVOD_WITH_PYTORCH=1 HOROVOD_WITHOUT_MXNET=1 \
 /databricks/python3/bin/python setup.py bdist_wheel
 
 readlink -f dist/horovod-*.whl
 
-pip install --no-cache-dir dist/horovod-0.28.1-cp38-cp38-linux_x86_64.whl --force-reinstall --no-deps
+pip install --no-cache-dir dist/horovod-0.27.0-cp38-cp38-linux_x86_64.whl --force-reinstall --no-deps

deep-learning/src/main/python/synapse/ml/dl/DeepTextClassifier.py

@@ -11,12 +11,12 @@
 if _TRANSFORMERS_AVAILABLE:
     import transformers
 
-    _TRANSFORMERS_EQUAL_4_15_0 = transformers.__version__ == "4.15.0"
-    if _TRANSFORMERS_EQUAL_4_15_0:
+    _TRANSFORMERS_EQUAL_4_25_1 = transformers.__version__ == "4.25.1"
+    if _TRANSFORMERS_EQUAL_4_25_1:
         from transformers import AutoTokenizer
     else:
         raise RuntimeError(
-            "transformers should be == 4.15.0, found: {}".format(
+            "transformers should be == 4.25.1, found: {}".format(
                 transformers.__version__
             )
         )

deep-learning/src/main/python/synapse/ml/dl/DeepVisionClassifier.py

@@ -19,10 +19,10 @@
 if _HOROVOD_AVAILABLE:
     import horovod
 
-    _HOROVOD_EQUAL_0_28_1 = horovod.__version__ == "0.28.1"
-    if not _HOROVOD_EQUAL_0_28_1:
+    _HOROVOD_EQUAL_0_27_0 = horovod.__version__ == "0.27.0"
+    if not _HOROVOD_EQUAL_0_27_0:
         raise RuntimeError(
-            "horovod should be of version 0.28.1, found: {}".format(horovod.__version__)
+            "horovod should be of version 0.27.0, found: {}".format(horovod.__version__)
         )
 else:
     raise ModuleNotFoundError("module not found: horovod")

deep-learning/src/main/python/synapse/ml/dl/LitDeepTextModel.py

@@ -13,12 +13,12 @@
 if _TRANSFORMERS_AVAILABLE:
     import transformers
 
-    _TRANSFORMERS_EQUAL_4_15_0 = transformers.__version__ == "4.15.0"
-    if _TRANSFORMERS_EQUAL_4_15_0:
+    _TRANSFORMERS_EQUAL_4_25_1 = transformers.__version__ == "4.25.1"
+    if _TRANSFORMERS_EQUAL_4_25_1:
         from transformers import AutoModelForSequenceClassification
     else:
         raise RuntimeError(
-            "transformers should be == 4.15.0, found: {}".format(
+            "transformers should be == 4.25.1, found: {}".format(
                 transformers.__version__
             )
         )

environment.yml

@@ -11,7 +11,7 @@ dependencies:
   - r-devtools=2.4.2
   - pip:
     - pyarrow>=0.15.0
-    - pyspark==3.3.1
+    - pyspark==3.3.2
     - pandas==1.2.5
     - wheel
     - sphinx==4.2.0
@@ -31,16 +31,16 @@ dependencies:
     - twine
     - jupyter
     - mlflow
-    - numpy==1.23.0
-    - torch==1.11.0
-    - torchvision==0.12.0
-    - horovod==0.25.0
+    - numpy
+    - torch==1.13.1
+    - torchvision==0.14.1
+    - horovod==0.27.0
     - petastorm>=0.11.0
     - pytorch_lightning==1.5.0
     - onnxmltools==1.7.0
     - matplotlib
     - Pillow
-    - transformers==4.15.0
+    - transformers==4.25.1
     - huggingface-hub>=0.8.1
     - langchain==0.0.151
     - openai==0.27.5

pipeline.yaml

@@ -511,7 +511,7 @@ jobs:
           fi
           sbt publishM2
 
-          SPARK_VERSION=3.3.1
+          SPARK_VERSION=3.3.2
           HADOOP_VERSION=3
           wget https://archive.apache.org/dist/spark/spark-${SPARK_VERSION}/spark-${SPARK_VERSION}-bin-hadoop${HADOOP_VERSION}.tgz
           (timeout 20m sbt "project $(PACKAGE)" coverage testR) || (echo "retrying" && timeout 20m sbt "project $(PACKAGE)" coverage testR) || (echo "retrying" && timeout 20m sbt "project $(PACKAGE)" coverage testR)

start

@@ -1,7 +1,7 @@
 #!/bin/bash
 
 export OPENMPI_VERSION="3.1.2"
-export SPARK_VERSION="3.3.1"
+export SPARK_VERSION="3.3.2"
 export HADOOP_VERSION="2.7"
 export SYNAPSEML_VERSION="0.11.2" # Binder compatibility version
 

tools/docker/demo/Dockerfile

@@ -3,7 +3,7 @@ FROM mcr.microsoft.com/oss/mirror/docker.io/library/ubuntu:20.04
 ARG SYNAPSEML_VERSION=0.11.2
 ARG DEBIAN_FRONTEND=noninteractive
 
-ENV SPARK_VERSION=3.3.1
+ENV SPARK_VERSION=3.3.2
 ENV HADOOP_VERSION=3
 ENV SYNAPSEML_VERSION=${SYNAPSEML_VERSION}
 ENV JAVA_HOME /usr/lib/jvm/java-1.11.0-openjdk-amd64

tools/docker/minimal/Dockerfile

@@ -3,7 +3,7 @@ FROM mcr.microsoft.com/oss/mirror/docker.io/library/ubuntu:20.04
 ARG SYNAPSEML_VERSION=0.11.2
 ARG DEBIAN_FRONTEND=noninteractive
 
-ENV SPARK_VERSION=3.3.1
+ENV SPARK_VERSION=3.3.2
 ENV HADOOP_VERSION=3
 ENV SYNAPSEML_VERSION=${SYNAPSEML_VERSION}
 ENV JAVA_HOME /usr/lib/jvm/java-1.11.0-openjdk-amd64

tools/dotnet/dotnetSetup.sh

@@ -21,10 +21,10 @@ echo "##vso[task.setvariable variable=DOTNET_WORKER_DIR]$DOTNET_WORKER_DIR"
 dotnet tool install -g sleet
 
 # Install Apache Spark-3.3
-curl https://archive.apache.org/dist/spark/spark-3.3.1/spark-3.3.1-bin-hadoop3.tgz -o spark-3.3.1-bin-hadoop3.tgz
+curl https://archive.apache.org/dist/spark/spark-3.3.2/spark-3.3.2-bin-hadoop3.tgz -o spark-3.3.2-bin-hadoop3.tgz
 mkdir ~/bin
-tar -xzvf spark-3.3.1-bin-hadoop3.tgz -C ~/bin
-export SPARK_HOME=~/bin/spark-3.3.1-bin-hadoop3/
+tar -xzvf spark-3.3.2-bin-hadoop3.tgz -C ~/bin
+export SPARK_HOME=~/bin/spark-3.3.2-bin-hadoop3/
 export PATH=$SPARK_HOME/bin:$PATH
 echo "##vso[task.setvariable variable=SPARK_HOME]$SPARK_HOME"
 echo "##vso[task.setvariable variable=PATH]$SPARK_HOME/bin:$PATH"

tools/tests/run_r_tests.R

@@ -3,7 +3,7 @@ if (!require("sparklyr")) {
   library("sparklyr")
 }
 
-spark_install_tar(paste(getwd(), "/../../../../../../spark-3.3.1-bin-hadoop3.tgz", sep = ""))
+spark_install_tar(paste(getwd(), "/../../../../../../spark-3.3.2-bin-hadoop3.tgz", sep = ""))
 
 options("testthat.output_file" = "../../../../r-test-results.xml")
 devtools::test(reporter = JunitReporter$new())