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Fixes, and ignores for known/logged failing issues (#7943) 

Signed-off-by: AlexDBlack <blacka101@gmail.com>
master
Alex Black 2019-06-25 12:07:28 +10:00 committed by GitHub
parent e2db385682
commit cae4fc9760
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GPG Key ID: 4AEE18F83AFDEB23
10 changed files with 35 additions and 13 deletions
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2
deeplearning4j/deeplearning4j-core/src/test/java/org/deeplearning4j/gradientcheck/GradientCheckTests.java
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@ -31,6 +31,7 @@ import org.deeplearning4j.nn.conf.layers.misc.ElementWiseMultiplicationLayer;
import org.deeplearning4j.nn.graph.ComputationGraph;
import org.deeplearning4j.nn.multilayer.MultiLayerNetwork;
import org.deeplearning4j.nn.weights.WeightInit;
import org.junit.Ignore;
import org.junit.Test;
import org.nd4j.linalg.activations.Activation;
import org.nd4j.linalg.api.buffer.DataType;
@ -699,6 +700,7 @@ public class GradientCheckTests extends BaseDL4JTest {
}
@Test
@Ignore("AB 2019/06/24 - Ignored to get to all passing baseline to prevent regressions via CI - see issue #7912")
public void testGradientMLP2LayerIrisLayerNorm() {
//Parameterized test, testing combinations of:
// (a) activation function

4
deeplearning4j/deeplearning4j-core/src/test/java/org/deeplearning4j/gradientcheck/RnnGradientChecks.java
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@ -29,6 +29,7 @@ import org.deeplearning4j.nn.conf.layers.recurrent.LastTimeStep;
import org.deeplearning4j.nn.conf.layers.recurrent.SimpleRnn;
import org.deeplearning4j.nn.multilayer.MultiLayerNetwork;
import org.deeplearning4j.nn.weights.WeightInit;
import org.junit.Ignore;
import org.junit.Test;
import org.nd4j.linalg.activations.Activation;
import org.nd4j.linalg.api.buffer.DataType;
@ -54,6 +55,7 @@ public class RnnGradientChecks extends BaseDL4JTest {
}
@Test
@Ignore("AB 2019/06/24 - Ignored to get to all passing baseline to prevent regressions via CI - see issue #7912")
public void testBidirectionalWrapper() {
int nIn = 3;
@ -137,6 +139,7 @@ public class RnnGradientChecks extends BaseDL4JTest {
}
@Test
@Ignore("AB 2019/06/24 - Ignored to get to all passing baseline to prevent regressions via CI - see issue #7912")
public void testSimpleRnn() {
int nOut = 5;
@ -216,6 +219,7 @@ public class RnnGradientChecks extends BaseDL4JTest {
}
@Test
@Ignore("AB 2019/06/24 - Ignored to get to all passing baseline to prevent regressions via CI - see issue #7912")
public void testLastTimeStepLayer(){
int nIn = 3;
int nOut = 5;

7
deeplearning4j/deeplearning4j-nlp-parent/deeplearning4j-nlp-uima/src/test/java/org/deeplearning4j/models/WordVectorSerializerTest.java
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@ -229,6 +229,7 @@ public class WordVectorSerializerTest extends BaseDL4JTest {
}
@Test
@Ignore("AB 2019/06/24 - Failing: Ignored to get to all passing baseline to prevent regressions via CI - see issue #7912")
public void testIndexPersistence() throws Exception {
File inputFile = Resources.asFile("big/raw_sentences.txt");
SentenceIterator iter = UimaSentenceIterator.createWithPath(inputFile.getAbsolutePath());
@ -434,6 +435,7 @@ public class WordVectorSerializerTest extends BaseDL4JTest {
@Test
@Ignore("AB 2019/06/24 - Failing: Ignored to get to all passing baseline to prevent regressions via CI - see issue #7912")
public void testOutputStream() throws Exception {
File file = File.createTempFile("tmp_ser", "ssa");
file.deleteOnExit();
@ -476,6 +478,7 @@ public class WordVectorSerializerTest extends BaseDL4JTest {
}
@Test
@Ignore("AB 2019/06/24 - Failing: Ignored to get to all passing baseline to prevent regressions via CI - see issue #7912")
public void testParaVecSerialization1() throws Exception {
VectorsConfiguration configuration = new VectorsConfiguration();
configuration.setIterations(14123);
@ -588,6 +591,7 @@ public class WordVectorSerializerTest extends BaseDL4JTest {
* @throws Exception
*/
@Test
@Ignore("AB 2019/06/24 - Failing: Ignored to get to all passing baseline to prevent regressions via CI - see issue #7912")
public void testStaticLoaderBinary() throws Exception {
logger.info("Executor name: {}", Nd4j.getExecutioner().getClass().getSimpleName());
@ -603,6 +607,7 @@ public class WordVectorSerializerTest extends BaseDL4JTest {
}
@Test
@Ignore("AB 2019/06/24 - Failing: Ignored to get to all passing baseline to prevent regressions via CI - see issue #7912")
public void testStaticLoaderFromStream() throws Exception {
logger.info("Executor name: {}", Nd4j.getExecutioner().getClass().getSimpleName());
@ -623,6 +628,7 @@ public class WordVectorSerializerTest extends BaseDL4JTest {
* @throws Exception
*/
@Test
@Ignore("AB 2019/06/24 - Failing: Ignored to get to all passing baseline to prevent regressions via CI - see issue #7912")
public void testStaticLoaderText() throws Exception {
logger.info("Executor name: {}", Nd4j.getExecutioner().getClass().getSimpleName());
@ -642,6 +648,7 @@ public class WordVectorSerializerTest extends BaseDL4JTest {
* @throws Exception
*/
@Test
@Ignore("AB 2019/06/24 - Failing: Ignored to get to all passing baseline to prevent regressions via CI - see issue #7912")
public void testStaticLoaderArchive() throws Exception {
logger.info("Executor name: {}", Nd4j.getExecutioner().getClass().getSimpleName());

2
deeplearning4j/deeplearning4j-nlp-parent/deeplearning4j-nlp/src/main/java/org/deeplearning4j/models/embeddings/reader/impl/BasicModelUtils.java
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@ -207,7 +207,7 @@ public class BasicModelUtils<T extends SequenceElement> implements ModelUtils<T>
words.putRow(row++, lookupTable.vector(s).mul(-1));
}
INDArray mean = words.isMatrix() ? words.mean(0) : words;
INDArray mean = words.isMatrix() ? words.mean(0).reshape(1, words.size(1)) : words;
Collection<String> tempRes = wordsNearest(mean, top + positive.size() + negative.size());
List<String> realResults = new ArrayList<>();

2
deeplearning4j/deeplearning4j-nlp-parent/deeplearning4j-nlp/src/test/java/org/deeplearning4j/models/fasttext/FastTextTest.java
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@ -103,6 +103,7 @@ public class FastTextTest extends BaseDL4JTest {
}
@Test
@Ignore("AB 2019/06/24 - Failing: Ignored to get to all passing baseline to prevent regressions via CI - see issue #7912")
public void testPredict() throws IOException {
String text = "I like soccer";
@ -118,6 +119,7 @@ public class FastTextTest extends BaseDL4JTest {
}
@Test
@Ignore("AB 2019/06/24 - Failing: Ignored to get to all passing baseline to prevent regressions via CI - see issue #7912")
public void testPredictProbability() throws IOException {
String text = "I like soccer";

11
deeplearning4j/deeplearning4j-nlp-parent/deeplearning4j-nlp/src/test/java/org/deeplearning4j/models/sequencevectors/serialization/WordVectorSerializerTest.java
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@ -295,21 +295,22 @@ public class WordVectorSerializerTest extends BaseDL4JTest {
@Test
public void FastText_Correct_WhenDeserialized() throws IOException {
FastText fastText =
FastText fastText =
FastText.builder().cbow(true).build();
WordVectorSerializer.writeWordVectors(fastText, new File("some.data"));
File dir = testDir.newFolder();
WordVectorSerializer.writeWordVectors(fastText, new File(dir, "some.data"));
FastText deser = null;
FastText deser = null;
try {
ByteArrayOutputStream baos = new ByteArrayOutputStream();
deser = WordVectorSerializer.readWordVectors(new File("some.data"));
deser = WordVectorSerializer.readWordVectors(new File(dir, "some.data"));
} catch (Exception e) {
e.printStackTrace();
fail();
}
assertNotNull(deser);
assertNotNull(deser);
assertEquals(fastText.isCbow(), deser.isCbow());
assertEquals(fastText.isModelLoaded(), deser.isModelLoaded());
assertEquals(fastText.isAnalogies(), deser.isAnalogies());

2
nd4j/nd4j-backends/nd4j-tests/src/test/java/org/nd4j/autodiff/opvalidation/LayerOpValidation.java
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@ -18,6 +18,7 @@ package org.nd4j.autodiff.opvalidation;
import lombok.extern.slf4j.Slf4j;
import lombok.val;
import org.junit.Ignore;
import org.junit.Test;
import org.nd4j.OpValidationSuite;
import org.nd4j.autodiff.samediff.SDVariable;
@ -1201,6 +1202,7 @@ public class LayerOpValidation extends BaseOpValidation {
}
@Test
@Ignore("AB 2019/06/24 - Failing: Ignored to get to all passing baseline to prevent regressions via CI - see issue #7912")
public void testLayerNormMixedOrders(){
Nd4j.getRandom().setSeed(12345);
INDArray input = Nd4j.rand(DataType.DOUBLE, 3, 8).dup('f');

2
nd4j/nd4j-backends/nd4j-tests/src/test/java/org/nd4j/autodiff/opvalidation/ReductionOpValidation.java
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@ -17,6 +17,7 @@
package org.nd4j.autodiff.opvalidation;
import lombok.extern.slf4j.Slf4j;
import org.junit.Ignore;
import org.junit.Rule;
import org.junit.Test;
import org.junit.rules.TemporaryFolder;
@ -767,6 +768,7 @@ public class ReductionOpValidation extends BaseOpValidation {
}
@Test
@Ignore("AB 2019/06/24 - Failing: Ignored to get to all passing baseline to prevent regressions via CI - see issue #7912")
public void testNormalizeMomentsOp() {
INDArray data = Nd4j.linspace(1, 100, 100, DataType.DOUBLE).reshape(10, 10);
INDArray ssSum = data.sum(0);

8
nd4j/nd4j-backends/nd4j-tests/src/test/java/org/nd4j/imports/TFGraphs/TFGraphTestZooModels.java
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@ -65,9 +65,11 @@ public class TFGraphTestZooModels { //Note: Can't extend BaseNd4jTest here as we
//Also: https://github.com/deeplearning4j/deeplearning4j/issues/7112
"ssd_mobilenet_v1_coco_2018_01_28",
//2019/05/15 - Strided slice: "Can't assign new value to the array: this shape [3]; other shape: [3, 3]"
//2019/05/17 - https://github.com/deeplearning4j/deeplearning4j/issues/7751
"faster_rcnn_resnet101_coco_2018_01_28"
//2019/06/24 - size op dtypes / libnd4j size op issue: https://github.com/eclipse/deeplearning4j/issues/7938
"faster_rcnn_resnet101_coco_2018_01_28",
//2019/06/24 - JVM crash on linux-x86_64-cpu-avx2 and -avx512 CI machines only - runs fine elsewhere
"deeplabv3_pascal_train_aug_2018_01_04"
};
public static final String[] IGNORE_REGEXES_LIBND4J_EXEC_ONLY = {

8
nd4j/nd4j-parameter-server-parent/nd4j-parameter-server-node/src/test/java/org/nd4j/parameterserver/distributed/v2/DelayedModelParameterServerTest.java
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@ -110,7 +110,7 @@ public class DelayedModelParameterServerTest {
}
}
@Test
@Test(timeout = 180000L)
public void testUpdatesPropagation_1() throws Exception {
val conf = VoidConfiguration.builder().meshBuildMode(MeshBuildMode.PLAIN).build();
val array = Nd4j.ones(10, 10);
@ -168,7 +168,7 @@ public class DelayedModelParameterServerTest {
}
}
@Test
@Test(timeout = 180000L)
public void testModelAndUpdaterParamsUpdate_1() throws Exception {
val config = VoidConfiguration.builder().meshBuildMode(MeshBuildMode.PLAIN).build();
val connector = new DummyTransport.Connector();
@ -301,7 +301,7 @@ public class DelayedModelParameterServerTest {
assertTrue(gotGradients.get());
}
@Test
@Test(timeout = 180000L)
public void testMeshConsistency_1() throws Exception {
Nd4j.create(1);
final int numMessages = 500;
@ -381,7 +381,7 @@ public class DelayedModelParameterServerTest {
}
@Test
@Test(timeout = 180000L)
public void testMeshConsistency_2() throws Exception {
Nd4j.create(1);
final int numMessages = 100;