M2 version update

Author: agibsonccc

README.md

@@ -24,12 +24,12 @@ We do not monitor the github issues of this repository very often.
 The **Eclipse Deeplearning4J** (DL4J) ecosystem is a set of projects intended to support all the needs of a JVM based deep learning application. This means starting with the raw data, loading and preprocessing it from wherever and whatever format it is in to building and tuning a wide variety of simple and complex deep learning networks.
 
 The DL4J stack comprises of:
-- **DL4J**: High level API to build MultiLayerNetworks and ComputationGraphs with a variety of layers, including custom ones. Supports importing Keras models from h5, including tf.keras models (as of 1.0.0-M1.1) and also supports distributed training on Apache Spark
+- **DL4J**: High level API to build MultiLayerNetworks and ComputationGraphs with a variety of layers, including custom ones. Supports importing Keras models from h5, including tf.keras models (as of 1.0.0-M2) and also supports distributed training on Apache Spark
 - **ND4J**: General purpose linear algebra library with over 500 mathematical, linear algebra and deep learning operations. ND4J is based on the highly-optimized C++ codebase LibND4J that provides CPU (AVX2/512) and GPU (CUDA) support and acceleration by libraries such as OpenBLAS, OneDNN (MKL-DNN), cuDNN, cuBLAS, etc
 - **SameDiff** : Part of the ND4J library, SameDiff is our automatic differentiation / deep learning framework. SameDiff uses a graph-based (define then run) approach, similar to TensorFlow graph mode. Eager graph (TensorFlow 2.x eager/PyTorch) graph execution is planned. SameDiff supports importing TensorFlow frozen model format .pb (protobuf) models. Import for ONNX, TensorFlow SavedModel and Keras models are planned. Deeplearning4j also has full SameDiff support for easily writing custom layers and loss functions.
 - **DataVec**: ETL for machine learning data in a wide variety of formats and files (HDFS, Spark, Images, Video, Audio, CSV, Excel etc)
 - **Arbiter**: Library for hyperparameter search
-- **LibND4J** : C++ library that underpins everything. For more information on how the JVM acceses native arrays and operations refer to [JavaCPP](https://github.com/bytedeco/javacpp)
+- **LibND4J** : C++ library that underpins everything. For more information on how the JVM accesses native arrays and operations refer to [JavaCPP](https://github.com/bytedeco/javacpp)
 
 All projects in the DL4J ecosystem support Windows, Linux and macOS. Hardware support includes CUDA GPUs (10.0, 10.1, 10.2 except OSX), x86 CPU (x86_64, avx2, avx512), ARM CPU (arm, arm64, armhf) and PowerPC (ppc64le).
 

android-examples/app/build.gradle

@@ -48,7 +48,7 @@ android {
 }
 
 dependencies {
-    def dl4jVersion = '1.0.0-M1.1'
+    def dl4jVersion = '1.0.0-M2'
     def openblasVersion = '0.3.10-1.5.5'
     def opencvVersion = '4.5.1-1.5.5'
     def leptonicaVersion = '1.80.0-1.5.5'

data-pipeline-examples/pom.xml

@@ -27,12 +27,12 @@ information regarding copyright ownership.
 
     <groupId>org.deeplearning4j</groupId>
     <artifactId>data-pipeline-examples</artifactId>
-    <version>1.0.0-M1.1</version>
+    <version>1.0.0-M2</version>
     <name>Building a data pipeline prior to modeling</name>
     <description>Loading raw data and processing it before training</description>
 
     <properties>
-        <dl4j-master.version>1.0.0-M1.1</dl4j-master.version>
+        <dl4j-master.version>1.0.0-M2</dl4j-master.version>
         <!-- Change the nd4j.backend property to nd4j-cuda-X-platform to use CUDA GPUs -->
         <!-- <nd4j.backend>nd4j-cuda-10.2-platform</nd4j.backend> -->
         <nd4j.backend>nd4j-native</nd4j.backend>
@@ -62,6 +62,13 @@ information regarding copyright ownership.
                 <updatePolicy>daily</updatePolicy>  <!-- Optional, update daily -->
             </snapshots>
         </repository>
+        <repository>
+            <id>M2</id>
+            <url>https://s01.oss.sonatype.org/content/repositories/orgdeeplearning4j-1019</url>
+            <releases>
+                <enabled>true</enabled>
+            </releases>
+        </repository>
     </repositories>
 
 

dl4j-distributed-training-examples/pom.xml

@@ -27,12 +27,12 @@ information regarding copyright ownership.
 
     <groupId>org.deeplearning4j</groupId>
     <artifactId>dl4j-distributed-training-examples</artifactId>
-    <version>1.0.0-M1.1</version>
+    <version>1.0.0-M2</version>
     <name>Introduction to Distributed Training with DL4J</name>
     <description>A set of examples introducing distributed training with the DL4J framework</description>
 
     <properties>
-        <dl4j-master.version>1.0.0-M1.1</dl4j-master.version>
+        <dl4j-master.version>1.0.0-M2</dl4j-master.version>
         <!-- Change the nd4j.backend property to nd4j-cuda-X-platform to use CUDA GPUs -->
         <!-- <nd4j.backend>nd4j-cuda-10.2-platform</nd4j.backend> -->
         <nd4j.backend>nd4j-native</nd4j.backend>
@@ -68,6 +68,13 @@ information regarding copyright ownership.
                 <updatePolicy>daily</updatePolicy>  <!-- Optional, update daily -->
             </snapshots>
         </repository>
+        <repository>
+            <id>M2</id>
+            <url>https://s01.oss.sonatype.org/content/repositories/orgdeeplearning4j-1019</url>
+            <releases>
+                <enabled>true</enabled>
+            </releases>
+        </repository>
     </repositories>
 
 

dl4j-distributed-training-examples/scripts/patentExamplePreproc.sh

@@ -36,7 +36,7 @@ MINIBATCH=32                                    #Minibatch size for preprocessed
 
 #Other variables. Don't modify these
 SCRIPTDIR=$(dirname "$0")
-JARFILE=${SCRIPTDIR}/../target/dl4j-spark-1.0.0-M1.1-bin.jar
+JARFILE=${SCRIPTDIR}/../target/dl4j-spark-1.0.0-M2-bin.jar
 AZURE_ACCT=fs.azure.account.key.${AZURE_STORAGE_ACCT}.blob.core.windows.net
 
 

dl4j-distributed-training-examples/scripts/patentExampleTrain.sh

@@ -44,7 +44,7 @@ AERON_BUFFER=33554432
 
 #Other variables. Don't modify these
 SCRIPTDIR=$(dirname "$0")
-JARFILE=${SCRIPTDIR}/../target/dl4j-spark-1.0.0-M1.1-bin.jar
+JARFILE=${SCRIPTDIR}/../target/dl4j-spark-1.0.0-M2-bin.jar
 AZURE_ACCT=fs.azure.account.key.${AZURE_STORAGE_ACCT}.blob.core.windows.net
 
 

dl4j-distributed-training-examples/scripts/tinyImagenetTrain.sh

@@ -36,7 +36,7 @@ EXECUTOR_MEMORY=12G
 MASTER_PORT=7077                                # Port for the spark master. Default is 7077
 MINIBATCH=32                                    # Minibatch size for preprocessed datasets
 SCRIPTDIR=$(dirname "$0")
-JARFILE=${SCRIPTDIR}/../target/dl4j-spark-1.0.0-M1.1-bin.jar
+JARFILE=${SCRIPTDIR}/../target/dl4j-spark-1.0.0-M2-bin.jar
 
 #Memory
 OFFHEAP_MEM_JAVACPP=20G         # Maximum amount of off-heap memory

dl4j-examples/pom.xml

@@ -32,7 +32,7 @@ information regarding copyright ownership.
     <description>A set of examples introducing the DL4J framework</description>
 
     <properties>
-        <dl4j-master.version>1.0.0-M1.1</dl4j-master.version>
+        <dl4j-master.version>1.0.0-M2</dl4j-master.version>
         <!-- Change the nd4j.backend property to nd4j-cuda-X-platform to use CUDA GPUs -->
         <!-- <nd4j.backend>nd4j-cuda-10.2-platform</nd4j.backend> -->
         <nd4j.backend>nd4j-native</nd4j.backend>
@@ -64,6 +64,13 @@ information regarding copyright ownership.
                 <updatePolicy>daily</updatePolicy>  <!-- Optional, update daily -->
             </snapshots>
         </repository>
+        <repository>
+            <id>M2</id>
+            <url>https://s01.oss.sonatype.org/content/repositories/orgdeeplearning4j-1019</url>
+            <releases>
+                <enabled>true</enabled>
+            </releases>
+        </repository>
     </repositories>
 
     <dependencies>

mvn-project-template/pom.xml

@@ -28,11 +28,11 @@ information regarding copyright ownership.
     <!-- Group-ID, artifact ID and version of the project. You can modify these as you want -->
     <groupId>org.deeplearning4j</groupId>
     <artifactId>deeplearning4j-example-sample</artifactId>
-    <version>1.0.0-M1.1</version>
+    <version>1.0.0-M2</version>
 
     <!-- Properties Section. Change ND4J versions here, if required -->
     <properties>
-        <dl4j-master.version>1.0.0-M1.1</dl4j-master.version>
+        <dl4j-master.version>1.0.0-M2</dl4j-master.version>
         <logback.version>1.2.3</logback.version>
         <java.version>1.8</java.version>
         <maven-shade-plugin.version>2.4.3</maven-shade-plugin.version>

nd4j-ndarray-examples/pom.xml

@@ -44,11 +44,18 @@ information regarding copyright ownership.
                 <updatePolicy>daily</updatePolicy>  <!-- Optional, update daily -->
             </snapshots>
         </repository>
+        <repository>
+            <id>M2</id>
+            <url>https://s01.oss.sonatype.org/content/repositories/orgdeeplearning4j-1019</url>
+            <releases>
+                <enabled>true</enabled>
+            </releases>
+        </repository>
     </repositories>
 
 
     <properties>
-        <dl4j-master.version>1.0.0-M1.1</dl4j-master.version>
+        <dl4j-master.version>1.0.0-M2</dl4j-master.version>
         <!-- Change the nd4j.backend property to nd4j-cuda-X-platform to use CUDA GPUs -->
         <!-- <nd4j.backend>nd4j-cuda-10.2-platform</nd4j.backend> -->
         <nd4j.backend>nd4j-native</nd4j.backend>