Snapshot update (#8194)

* fix double consumption of rng on cpu Signed-off-by: raver119 <raver119@gmail.com> * Shyrma docs (#222) * - documenting and profiling matrix_set_diag cuda kernel Signed-off-by: Yurii <yurii@skymind.io> * - correct formula of pnorm pooling in cuda 2d/3d kernels - remove helper matrix_diag which duplicates work of helper matrix_set_diag Signed-off-by: Yurii <yurii@skymind.io> * cublasHandle sharing + lock Signed-off-by: raver119 <raver119@gmail.com> * cublasHandle sharing + lock Signed-off-by: raver119 <raver119@gmail.com> * Documentation from serialization/deserialization in NLP (#221) * refactoring Signed-off-by: Alexander Stoyakin <alexander.stoyakin@gmail.com> * Javadocs Signed-off-by: Alexander Stoyakin <alexander.stoyakin@gmail.com> * Javadoc fixed Signed-off-by: Alexander Stoyakin <alexander.stoyakin@gmail.com> * Cleanup Signed-off-by: Alexander Stoyakin <alexander.stoyakin@gmail.com> * dedicated lock for getCudaCublasHandle Signed-off-by: raver119 <raver119@gmail.com> * Small fixes (#223) Signed-off-by: AlexDBlack <blacka101@gmail.com> * ELU DL4J fixes (#224) Signed-off-by: AlexDBlack <blacka101@gmail.com> * javadoc (#225) Signed-off-by: Robert Altena <Rob@Ra-ai.com> * Small test compilation fix (#226) Signed-off-by: AlexDBlack <blacka101@gmail.com> * #8182 remove spark version suffix (#227) Signed-off-by: AlexDBlack <blacka101@gmail.com> * [WIP] Thread safety (#229) * sync after cublas*gemm Signed-off-by: raver119 <raver119@gmail.com> * mutex for CublasHelper Signed-off-by: raver119 <raver119@gmail.com> * don't store cublasHandle in LaunchContext, it's per-device anyway Signed-off-by: raver119 <raver119@gmail.com> * some printout Signed-off-by: raver119 <raver119@gmail.com> * check for field instead Signed-off-by: raver119 <raver119@gmail.com> * pew-pew Signed-off-by: raver119 <raver119@gmail.com> * don't release ContextBuffers until device changed Signed-off-by: raver119 <raver119@gmail.com> * small tweak Signed-off-by: raver119 <raver119@gmail.com> * some logging in sgemm Signed-off-by: raver119 <raver119@gmail.com> * stream sync Signed-off-by: raver119 <raver119@gmail.com> * some more logging Signed-off-by: raver119 <raver119@gmail.com> * some more error checks Signed-off-by: raver119 <raver119@gmail.com> * one fancy test Signed-off-by: raver119 <raver119@gmail.com> * one fancy test Signed-off-by: raver119 <raver119@gmail.com> * minor AffinityManager fix Signed-off-by: raver119 <raver119@gmail.com> * cudaEvent error logging improvement Signed-off-by: raver119 <raver119@gmail.com> * ConstantHelper thread safety Signed-off-by: raver119 <raver119@gmail.com> * - minor corrections in ConstantTadHelper Signed-off-by: Yurii <yurii@skymind.io> * ConstantShapeHelper thread safety Signed-off-by: raver119 <raver119@gmail.com> * ConstantTadHelper.cu updated Signed-off-by: raver119 <raver119@gmail.com> * logging off Signed-off-by: raver119 <raver119@gmail.com> * logging off Signed-off-by: raver119 <raver119@gmail.com>
deeplearning4j · Sep 3, 2019 · 7abc574 · 7abc574
1 parent 9d03bb9
commit 7abc574
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Showing 58 changed files with 833 additions and 837 deletions.
diff --git a/datavec/datavec-spark-inference-parent/datavec-spark-inference-client/pom.xml b/datavec/datavec-spark-inference-parent/datavec-spark-inference-client/pom.xml
@@ -38,7 +38,7 @@
         <dependency>
             <groupId>org.datavec</groupId>
             <artifactId>datavec-spark-inference-server_2.11</artifactId>
-            <version>1.0.0_spark_2-SNAPSHOT</version>
+            <version>1.0.0-SNAPSHOT</version>
             <scope>test</scope>
         </dependency>
         <dependency>

diff --git a/datavec/datavec-spark-inference-parent/datavec-spark-inference-server/pom.xml b/datavec/datavec-spark-inference-parent/datavec-spark-inference-server/pom.xml
@@ -25,7 +25,7 @@
 
     <artifactId>datavec-spark-inference-server_2.11</artifactId>
     <packaging>jar</packaging>
-    <version>1.0.0_spark_2-SNAPSHOT</version>
+    <version>1.0.0-SNAPSHOT</version>
     <name>datavec-spark-inference-server</name>
 
     <properties>

diff --git a/datavec/datavec-spark/pom.xml b/datavec/datavec-spark/pom.xml
@@ -24,7 +24,7 @@
     </parent>
 
     <modelVersion>4.0.0</modelVersion>
-    <version>1.0.0_spark_2-SNAPSHOT</version>
+    <version>1.0.0-SNAPSHOT</version>
     <artifactId>datavec-spark_2.11</artifactId>
 
     <properties>

diff --git a/deeplearning4j/deeplearning4j-core/src/test/java/org/deeplearning4j/RandomTests.java b/deeplearning4j/deeplearning4j-core/src/test/java/org/deeplearning4j/RandomTests.java
@@ -0,0 +1,63 @@
+package org.deeplearning4j;
+
+import org.deeplearning4j.datasets.iterator.EarlyTerminationDataSetIterator;
+import org.deeplearning4j.datasets.iterator.impl.MnistDataSetIterator;
+import org.deeplearning4j.nn.api.OptimizationAlgorithm;
+import org.deeplearning4j.nn.conf.MultiLayerConfiguration;
+import org.deeplearning4j.nn.conf.NeuralNetConfiguration;
+import org.deeplearning4j.nn.multilayer.MultiLayerNetwork;
+import org.junit.Ignore;
+import org.junit.Test;
+import org.nd4j.linalg.activations.Activation;
+import org.nd4j.linalg.dataset.api.iterator.DataSetIterator;
+import org.nd4j.linalg.factory.Nd4j;
+import org.nd4j.linalg.learning.config.RmsProp;
+import org.nd4j.linalg.lossfunctions.LossFunctions;
+
+import java.util.concurrent.CountDownLatch;
+
+@Ignore
+public class RandomTests {
+
+    @Test
+    public void testReproduce() throws Exception {
+
+        final MultiLayerConfiguration conf = new NeuralNetConfiguration.Builder().updater(new RmsProp())
+                .optimizationAlgo(OptimizationAlgorithm.STOCHASTIC_GRADIENT_DESCENT).list()
+                .layer(0, new org.deeplearning4j.nn.conf.layers.DenseLayer.Builder().nIn(28 * 28).nOut(10)
+                        .activation(Activation.TANH).build())
+                .layer(1, new org.deeplearning4j.nn.conf.layers.OutputLayer.Builder(
+                        LossFunctions.LossFunction.MCXENT).nIn(10).nOut(10)
+                        .activation(Activation.SOFTMAX).build())
+                .build();
+
+        for (int e = 0; e < 3; e++) {
+
+            int nThreads = 10;
+            final CountDownLatch l = new CountDownLatch(nThreads);
+            for (int i = 0; i < nThreads; i++) {
+                final int j = i;
+                Thread t = new Thread(new Runnable() {
+                    @Override
+                    public void run() {
+                        try {
+                            MultiLayerNetwork net = new MultiLayerNetwork(conf.clone());
+                            net.init();
+                            DataSetIterator iter = new EarlyTerminationDataSetIterator(new MnistDataSetIterator(10, false, 12345), 100);
+                            net.fit(iter);
+                        } catch (Throwable t) {
+                            System.out.println("Thread failed: " + j);
+                            t.printStackTrace();
+                        } finally {
+                            l.countDown();
+                        }
+                    }
+                });
+                t.start();
+            }
+
+            l.await();
+            System.out.println("DONE " + e + "\n");
+        }
+    }
+}
diff --git a/...learning4j-nlp-uima/src/test/java/org/deeplearning4j/models/WordVectorSerializerTest.java b/...learning4j-nlp-uima/src/test/java/org/deeplearning4j/models/WordVectorSerializerTest.java
@@ -833,14 +833,14 @@ public void testMalformedLabels1() throws Exception {
     public void testB64_1() throws Exception {
         String wordA = "night";
         String wordB = "night day";
-        String encA = WordVectorSerializer.encodeB64(wordA);
-        String encB = WordVectorSerializer.encodeB64(wordB);
+        String encA = WordVectorSerializer.ReadHelper.encodeB64(wordA);
+        String encB = WordVectorSerializer.ReadHelper.encodeB64(wordB);
 
-        assertEquals(wordA, WordVectorSerializer.decodeB64(encA));
-        assertEquals(wordB, WordVectorSerializer.decodeB64(encB));
+        assertEquals(wordA, WordVectorSerializer.ReadHelper.decodeB64(encA));
+        assertEquals(wordB, WordVectorSerializer.ReadHelper.decodeB64(encB));
 
-        assertEquals(wordA, WordVectorSerializer.decodeB64(wordA));
-        assertEquals(wordB, WordVectorSerializer.decodeB64(wordB));
+        assertEquals(wordA, WordVectorSerializer.ReadHelper.decodeB64(wordA));
+        assertEquals(wordB, WordVectorSerializer.ReadHelper.decodeB64(wordB));
 
     }