Update test suite declarations to ignore tests properly
parent
d58b87dd7c
commit
763b082f6a
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@ -46,6 +46,8 @@ import org.nd4j.linalg.lossfunctions.LossFunctions;
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@Slf4j
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@Tag(TagNames.FILE_IO)
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@NativeTag
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@Tag(TagNames.LONG_TEST)
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@Tag(TagNames.LARGE_RESOURCES)
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public class ParameterServerParallelWrapperTest extends BaseDL4JTest {
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@Test
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@ -38,6 +38,8 @@ import org.nd4j.linalg.factory.Nd4j;
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import static org.junit.jupiter.api.Assertions.*;
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@Tag(TagNames.FILE_IO)
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@NativeTag
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@Tag(TagNames.LARGE_RESOURCES)
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@Tag(TagNames.LONG_TEST)
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public class InplaceParallelInferenceTest extends BaseDL4JTest {
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@Test
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@ -64,6 +64,8 @@ import static org.junit.jupiter.api.Assertions.*;
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@Slf4j
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@Tag(TagNames.FILE_IO)
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@NativeTag
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@Tag(TagNames.LONG_TEST)
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@Tag(TagNames.LARGE_RESOURCES)
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public class ParallelInferenceTest extends BaseDL4JTest {
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private static MultiLayerNetwork model;
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private static DataSetIterator iterator;
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@ -1,40 +1,7 @@
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input
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Reshape/shape
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Lenet/conv1/weights
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Lenet/conv1/biases
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Lenet/conv3/weights
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Lenet/conv3/biases
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Lenet/conv5/weights
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Lenet/conv5/biases
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Lenet/fc7/weights
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Lenet/fc7/biases
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Lenet/fc9/weights
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Lenet/fc9/biases
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Lenet/flat6_1/flatten/strided_slice/stack
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Lenet/flat6_1/flatten/strided_slice/stack_1
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Lenet/flat6_1/flatten/strided_slice/stack_2
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Lenet/flat6_1/flatten/Reshape/shape/1
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output/dimension
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Reshape
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Lenet/conv1_1/Conv2D
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Lenet/conv1_1/BiasAdd
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Lenet/conv1_1/Relu
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Lenet/pool2_1/MaxPool
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Lenet/conv3_1/Conv2D
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Lenet/conv3_1/BiasAdd
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Lenet/conv3_1/Relu
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Lenet/pool4_1/MaxPool
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Lenet/conv5_1/Conv2D
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Lenet/conv5_1/BiasAdd
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Lenet/conv5_1/Relu
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Lenet/flat6_1/flatten/Shape
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Lenet/flat6_1/flatten/strided_slice
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Lenet/flat6_1/flatten/Reshape/shape
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Lenet/flat6_1/flatten/Reshape
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Lenet/fc7_1/MatMul
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Lenet/fc7_1/BiasAdd
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Lenet/fc7_1/Relu
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Lenet/fc9_1/MatMul
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Lenet/fc9_1/BiasAdd
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Lenet/fc9_1/Relu
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output
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in_0
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in_1
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Add/y
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in_0/read
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in_1/read
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Add
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Zeta
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@ -86,6 +86,12 @@
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<profile>
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<id>testresources</id>
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</profile>
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<profile>
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<id>nd4j-tests-cpu</id>
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</profile>
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<profile>
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<id>nd4j-tests-cuda</id>
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</profile>
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</profiles>
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</project>
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@ -826,6 +826,7 @@ val conv3d = TensorflowMappingProcess(
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val divideNoNan = TensorflowMappingProcess(
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opName = "divide_no_nan",
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inputFrameworkOpName = "DivNoNan",
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@ -277,7 +277,6 @@ public class BERTGraphTest extends BaseNd4jTestWithBackends {
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assertEquals(exp3, softmax.getRow(3));
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}
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@Test //@Disabled //AB ignored 08/04/2019 until fixed
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@ParameterizedTest
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@MethodSource("org.nd4j.linalg.BaseNd4jTestWithBackends#configs")
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public void testBertTraining(Nd4jBackend backend) throws Exception {
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@ -20,6 +20,7 @@
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package org.nd4j.imports.tfgraphs;
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import org.apache.commons.io.FileUtils;
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import org.nd4j.imports.listeners.ExecPrintListener;
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import org.nd4j.imports.tfgraphs.listener.OpExecOrderListener;
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import lombok.extern.slf4j.Slf4j;
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@ -111,21 +112,6 @@ public class TFGraphTestAllHelper {
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public static final DefaultGraphLoader LOADER = new DefaultGraphLoader();
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@BeforeAll
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public void beforeClass(){
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log.info("Starting tests for class: " + getClass().getName());
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}
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@BeforeEach
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public void setup(){
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Nd4j.setDataType(DataType.FLOAT);
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}
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@AfterEach
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public void tearDown() {
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NativeOpsHolder.getInstance().getDeviceNativeOps().enableDebugMode(false);
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NativeOpsHolder.getInstance().getDeviceNativeOps().enableVerboseMode(false);
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}
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private static ExecutorConfiguration configuration = ExecutorConfiguration.builder()
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.executionMode(ExecutionMode.SEQUENTIAL)
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@ -559,32 +545,29 @@ public class TFGraphTestAllHelper {
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val dtypes = new HashMap<String, DataType>();
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List<Pair<Resource,Resource>> resources = new ArrayList<>();
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if(recursive){
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if(recursive) {
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String nameRegex = pattern.replace("**.",".*\\.") + "\\.shape";
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// File baseDir = new File(System.getProperty("java.io.tmpdir"), UUID.randomUUID().toString() + "/" + modelName);
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// baseDir.mkdirs();
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// baseDir.deleteOnExit();
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// new ClassPathResource(modelDir).copyDirectory(baseDir);
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// checking out, if local folder declared
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String localPath = System.getenv(TFGraphTestAllHelper.resourceFolderVar);
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if(localPath != null && (!localPath.contains("src/main/resources") && !localPath.contains("src\\main\\resources"))){
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if(localPath != null && (!localPath.contains("src/main/resources") && !localPath.contains("src\\main\\resources"))) {
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localPath = FilenameUtils.concat(localPath, "src/main/resources");
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}
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// baseDir will differ, depending on run mode
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File baseDir = localPath == null ? new File(localTestDir, "extracted/" + modelName) : new File(localPath, base_dir + "/" + modelName);
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String[] arr = baseDir.list();
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if(!baseDir.exists() || arr == null || arr.length == 0){
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if(!baseDir.exists() || arr == null || arr.length == 0) {
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// we're skipping extraction if we're using local copy of dl4j-tests-resources
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if (localPath == null) {
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baseDir.mkdirs();
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baseDir.deleteOnExit();
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FileUtils.forceDeleteOnExit(baseDir);
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String md = modelDir;
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if(!md.endsWith("/") && !md.endsWith("\\")){
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md = md + "/";
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}
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new ClassPathResource(md).copyDirectory(baseDir);
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} else{
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throw new IllegalStateException("local directory declared but could not find files: " + baseDir.getAbsolutePath());
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@ -595,7 +578,7 @@ public class TFGraphTestAllHelper {
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LinkedList<File> queue = new LinkedList<>();
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queue.add(baseDir);
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while(!queue.isEmpty()){
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while(!queue.isEmpty()) {
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File subdir = queue.remove();
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File[] files = subdir.listFiles();
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if (files != null) {
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@ -665,7 +648,7 @@ public class TFGraphTestAllHelper {
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// Preconditions.checkState(!dtypes.isEmpty(), "No datatypes file was found");
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val dtype = Nd4j.dataType();
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for (int i = 0; i < resources.size(); i++) {
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URI u = resources.get(i).getFirst().getURI();
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String varName = u.toString();
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@ -730,7 +713,7 @@ public class TFGraphTestAllHelper {
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}
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} else {
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int[] varShape = new int[filtered.size()];
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for( int j=0; j<filtered.size(); j++ ){
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for( int j = 0; j < filtered.size(); j++) {
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varShape[j] = Integer.parseInt(filtered.get(j));
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}
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@ -801,8 +784,8 @@ public class TFGraphTestAllHelper {
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break;
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case BOOL:
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boolean[] bArr = new boolean[cLines.length];
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int z=0;
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while(z < bArr.length){
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int z = 0;
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while(z < bArr.length) {
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bArr[z] = parseBoolean(cLines[z]);
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z++;
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}
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@ -828,7 +811,7 @@ public class TFGraphTestAllHelper {
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return varMap;
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}
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private static long parseLong(String line){
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private static long parseLong(String line) {
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line = line.trim(); //Handle whitespace
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if(line.matches("-?\\d+\\.0+")){
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//Annoyingly, some integer data is stored with redundant/unnecessary zeros - like "-7.0000000"
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@ -42,6 +42,8 @@ import java.io.IOException;
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import java.util.*;
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import java.util.stream.Stream;
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import static org.junit.jupiter.api.Assumptions.assumeFalse;
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@Slf4j
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@Tag(TagNames.LONG_TEST)
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@ -130,20 +132,18 @@ public class TFGraphTestAllLibnd4j { //Note: Can't extend BaseNd4jTest here as
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@ParameterizedTest
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@MethodSource("data")
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public void testOutputOnly(Map<String, INDArray> inputs, Map<String, INDArray> predictions, String modelName, File localTestDir) throws Exception {
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Nd4j.create(1);
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for(String s : TFGraphTestAllSameDiff.IGNORE_REGEXES){
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if(modelName.matches(s)){
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log.info("\n\tIGNORE MODEL ON REGEX: {} - regex {}", modelName, s);
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//OpValidationSuite.ignoreFailing();
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assumeFalse(true);
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}
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}
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for(String s : SKIP_FOR_LIBND4J_EXEC) {
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if(modelName.matches(s)){
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log.info("\n\tIGNORE MODEL ON REGEX - SKIP LIBND4J EXEC ONLY: {} - regex {}", modelName, s);
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//OpValidationSuite.ignoreFailing();
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assumeFalse(true);
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}
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}
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@ -24,6 +24,8 @@ import lombok.extern.slf4j.Slf4j;
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import lombok.val;
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import org.junit.jupiter.api.*;
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import org.junit.jupiter.api.parallel.Execution;
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import org.junit.jupiter.api.parallel.ExecutionMode;
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import org.junit.jupiter.params.ParameterizedTest;
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import org.junit.jupiter.params.provider.Arguments;
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import org.junit.jupiter.params.provider.MethodSource;
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@ -39,6 +41,8 @@ import java.io.IOException;
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import java.util.*;
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import java.util.stream.Stream;
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import static org.junit.jupiter.api.Assumptions.assumeFalse;
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@Slf4j
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@Tag(TagNames.LONG_TEST)
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@Tag(TagNames.LARGE_RESOURCES)
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@ -139,23 +143,7 @@ public class TFGraphTestAllSameDiff { //Note: Can't extend BaseNd4jTest here a
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*/
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private final List<String> debugModeRegexes = Arrays.asList("fused_batch_norm/float16_nhwc");
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@BeforeAll
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public static void beforeClass() {
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Nd4j.scalar(1.0);
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Nd4j.setDataType(DataType.FLOAT);
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Nd4j.getExecutioner().setProfilingMode(OpExecutioner.ProfilingMode.SCOPE_PANIC);
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}
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@BeforeEach
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public void setup() {
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Nd4j.setDataType(DataType.FLOAT);
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Nd4j.getExecutioner().enableDebugMode(true);
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Nd4j.getExecutioner().enableVerboseMode(true);
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}
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@AfterEach
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public void tearDown() {
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}
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public static Stream<Arguments> data() throws IOException {
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val localPath = System.getenv(TFGraphTestAllHelper.resourceFolderVar);
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@ -171,19 +159,21 @@ public class TFGraphTestAllSameDiff { //Note: Can't extend BaseNd4jTest here a
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}
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}
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@ParameterizedTest
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@ParameterizedTest(name = "{2}")
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@MethodSource("data")
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//@DisableIfModelFound
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public void testOutputOnly(Map<String, INDArray> inputs, Map<String, INDArray> predictions, String modelName, File localTestDir) throws Exception {
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Nd4j.create(1);
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if(EXECUTE_ONLY_MODELS.isEmpty()) {
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for(String s : IGNORE_REGEXES) {
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if(modelName.matches(s)) {
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log.info("\n\tIGNORE MODEL ON REGEX: {} - regex {}", modelName, s);
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//OpValidationSuite.ignoreFailing();
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assumeFalse(true);
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}
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}
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} else if(!EXECUTE_ONLY_MODELS.contains(modelName)) {
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log.info("Not executing " + modelName);
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assumeFalse(true);
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//OpValidationSuite.ignoreFailing();
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}
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@ -0,0 +1,155 @@
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/*
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*
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* * ******************************************************************************
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* * *
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* * *
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* * * This program and the accompanying materials are made available under the
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* * * terms of the Apache License, Version 2.0 which is available at
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* * * https://www.apache.org/licenses/LICENSE-2.0.
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* * *
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* * * See the NOTICE file distributed with this work for additional
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* * * information regarding copyright ownership.
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* * * Unless required by applicable law or agreed to in writing, software
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* * * distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
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* * * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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* * * License for the specific language governing permissions and limitations
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* * * under the License.
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* * *
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* * * SPDX-License-Identifier: Apache-2.0
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* * *****************************************************************************
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*
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*
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*/
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package org.nd4j.imports.tfgraphs;
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import lombok.extern.slf4j.Slf4j;
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import org.junit.jupiter.api.extension.ConditionEvaluationResult;
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import org.junit.jupiter.api.extension.ExecutionCondition;
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import org.junit.jupiter.api.extension.ExtensionContext;
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import java.util.Arrays;
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import java.util.List;
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import static org.junit.jupiter.api.Assumptions.assumeFalse;
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@Slf4j
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public class TFImportDisableModelsCondition implements ExecutionCondition {
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/**
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* NOTE: If this is empty or the tests names are wrong,
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* all tests will trigger an assumeFalse(..) that indicates
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* the status of the test failing. No tests will run.
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*/
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public final static List<String> EXECUTE_ONLY_MODELS = Arrays.asList(
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/*"layers_dropout/rank2_d01_train",
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"layers_dropout/rank4_d05_train",
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"layers_dropout/rank3_d05_train_mask2",
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"layers_dropout/rank4_d05_train_mask",
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"layers_dropout/rank3_d05_train_mask1",
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"layers_dropout/rank2_d09_train",
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"layers_dropout/rank2_d05_train",*/
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);
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public static final String[] IGNORE_REGEXES = new String[]{
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//Failing 2019/09/11 - https://github.com/eclipse/deeplearning4j/issues/7965
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// Still failing 2020/04/27 java.lang.IllegalStateException: Requested output variable Bincount does not exist in SameDiff instance
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//Invalid test cases. Verified by running graph against actual TF.
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"scatter_nd_sub/locking/rank1shape_1indices",
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"reductions/scatter_update_vector",
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"reductions/scatter_update_scalar",
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"emptyArrayTests/scatter_update/rank1_emptyIndices_emptyUpdates",
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"bincount/rank2_weights",
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"slogdet/.*",
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"fused_batch_norm/float16_nhwc",
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"emptyArrayTests/scatter_update/rank2_emptyIndices_emptyUpdates",
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//Don't bother to test RNG. We can test subsets of ops with dropout to make sure they are consistent
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//These tests have random uniform and other RNG in them that don't need to be perfectly compatible to be acceptable.
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//We need different test cases here.
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"layers_dropout/.*",
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//TODO floormod and truncatemod behave differently - i.e., "c" vs. "python" semantics. Need to check implementations too
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// Still failing 2020/04/27 java.lang.IllegalStateException: Could not find class for TF Ops: TruncateMod
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"truncatemod/.*",
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//2019/09/11 - No tensorflow op found for SparseTensorDenseAdd
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// 2020/04/27 java.lang.IllegalStateException: Could not find class for TF Ops: SparseTensorDenseAdd
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"confusion/.*",
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//2019/09/11 - Couple of tests failing (InferenceSession issues)
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// Still failing 2020/04/27 Requested output variable concat does not exist in SameDiff instance
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//2019/05/21 - Failing on windows-x86_64-cuda-9.2 only -
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"conv_4",
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"g_09",
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//2019/05/28 - JVM crash on ppc64le only - See issue 7657
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"g_11",
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//2019/07/09 - Need "Multinomial" op - https://github.com/eclipse/deeplearning4j/issues/7913
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// Still failing 2020/04/27 java.lang.IllegalStateException: Could not find class for TF Ops: Multinomial
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"multinomial/.*",
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//2019/11/04 AB - disabled, pending libnd4j deconv3d_tf implementation
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// Still failing 2020/04/27 java.lang.IllegalStateException: Could not find descriptor for op: deconv3d_tf - class: org.nd4j.linalg.api.ops.impl.layers.convolution.DeConv3DTF
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"conv3d_transpose.*",
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//2019/11/15 - mapping is not present yet https://github.com/eclipse/deepleRaggedRange arning4j/issues/8397
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// Still failing 2020/04/27 java.lang.AssertionError: Predictions do not match on ragged/reduce_mean/2d_a1, node RaggedReduceMean/truediv
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"ragged/reduce_mean/.*",
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//08.05.2020 - https://github.com/eclipse/deeplearning4j/issues/8927
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"random_gamma/.*",
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//08.05.2020 - https://github.com/eclipse/deeplearning4j/issues/8928
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"Conv3DBackpropInputV2/.*",
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|
||||
//12.05.2020 - https://github.com/eclipse/deeplearning4j/issues/8946
|
||||
"non_max_suppression_v4/.*","non_max_suppression_v5/.*",
|
||||
|
||||
|
||||
// 18.05.2020 - :wq:wq
|
||||
|
||||
"random_uniform_int/.*",
|
||||
"random_uniform/.*",
|
||||
"random_poisson_v2/.*"
|
||||
};
|
||||
|
||||
/* As per TFGraphTestList.printArraysDebugging - this field defines a set of regexes for test cases that should have
|
||||
all arrays printed during execution.
|
||||
If a test name matches any regex here, an ExecPrintListener will be added to the listeners, and all output
|
||||
arrays will be printed during execution
|
||||
*/
|
||||
private final List<String> debugModeRegexes = Arrays.asList("fused_batch_norm/float16_nhwc");
|
||||
|
||||
|
||||
|
||||
private ExtensionContext.Store getStore(ExtensionContext context) {
|
||||
return context.getStore(ExtensionContext.Namespace.create(getClass(), context.getRequiredTestMethod()));
|
||||
}
|
||||
|
||||
@Override
|
||||
public ConditionEvaluationResult evaluateExecutionCondition(ExtensionContext extensionContext) {
|
||||
String modelName = getStore(extensionContext).toString();
|
||||
if(EXECUTE_ONLY_MODELS.isEmpty()) {
|
||||
for(String s : IGNORE_REGEXES) {
|
||||
if(modelName.matches(s)) {
|
||||
log.info("\n\tIGNORE MODEL ON REGEX: {} - regex {}", modelName, s);
|
||||
assumeFalse(true);
|
||||
}
|
||||
}
|
||||
} else if(!EXECUTE_ONLY_MODELS.contains(modelName)) {
|
||||
log.info("Not executing " + modelName);
|
||||
assumeFalse(true);
|
||||
//OpValidationSuite.ignoreFailing();
|
||||
}
|
||||
|
||||
|
||||
return ConditionEvaluationResult.disabled("Method found");
|
||||
}
|
||||
}
|
|
@ -1,23 +1,4 @@
|
|||
Reshape,Reshape
|
||||
Lenet/conv1_1/Conv2D,Lenet/conv1_1/Conv2D
|
||||
Lenet/conv1_1/BiasAdd,Lenet/conv1_1/BiasAdd
|
||||
Lenet/conv1_1/Relu,Lenet/conv1_1/Relu
|
||||
Lenet/pool2_1/MaxPool,Lenet/pool2_1/MaxPool
|
||||
Lenet/conv3_1/Conv2D,Lenet/conv3_1/Conv2D
|
||||
Lenet/conv3_1/BiasAdd,Lenet/conv3_1/BiasAdd
|
||||
Lenet/conv3_1/Relu,Lenet/conv3_1/Relu
|
||||
Lenet/pool4_1/MaxPool,Lenet/pool4_1/MaxPool
|
||||
Lenet/conv5_1/Conv2D,Lenet/conv5_1/Conv2D
|
||||
Lenet/conv5_1/BiasAdd,Lenet/conv5_1/BiasAdd
|
||||
Lenet/conv5_1/Relu,Lenet/conv5_1/Relu
|
||||
Lenet/flat6_1/flatten/Shape,Lenet/flat6_1/flatten/Shape
|
||||
Lenet/flat6_1/flatten/strided_slice,Lenet/flat6_1/flatten/strided_slice
|
||||
Lenet/flat6_1/flatten/Reshape/shape,Lenet/flat6_1/flatten/Reshape/shape
|
||||
Lenet/flat6_1/flatten/Reshape,Lenet/flat6_1/flatten/Reshape
|
||||
Lenet/fc7_1/MatMul,Lenet/fc7_1/MatMul
|
||||
Lenet/fc7_1/BiasAdd,Lenet/fc7_1/BiasAdd
|
||||
Lenet/fc7_1/Relu,Lenet/fc7_1/Relu
|
||||
Lenet/fc9_1/MatMul,Lenet/fc9_1/MatMul
|
||||
Lenet/fc9_1/BiasAdd,Lenet/fc9_1/BiasAdd
|
||||
Lenet/fc9_1/Relu,Lenet/fc9_1/Relu
|
||||
output,output
|
||||
in_0/read,in_0/read
|
||||
in_1/read,in_1/read
|
||||
Add,Add
|
||||
Zeta,Zeta
|
||||
|
|
Loading…
Reference in New Issue