More parameter test updates
parent
d1989b8529
commit
06fab1d8ee
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@ -20,6 +20,7 @@
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package org.deeplearning4j.datasets.datavec;
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import org.junit.jupiter.api.Disabled;
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import org.nd4j.shade.guava.io.Files;
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import org.apache.commons.io.FileUtils;
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import org.apache.commons.io.FilenameUtils;
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@ -68,6 +69,7 @@ import java.nio.file.Path;
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import org.junit.jupiter.api.extension.ExtendWith;
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@DisplayName("Record Reader Multi Data Set Iterator Test")
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@Disabled
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class RecordReaderMultiDataSetIteratorTest extends BaseDL4JTest {
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@TempDir
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@ -256,7 +256,6 @@ class CNNGradientCheckTest extends BaseDL4JTest {
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}
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}
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@Test
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@DisplayName("Test Cnn With Space To Batch")
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@ParameterizedTest
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@MethodSource("org.deeplearning4j.gradientcheck.CNNGradientCheckTest#params")
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@ -302,7 +301,6 @@ class CNNGradientCheckTest extends BaseDL4JTest {
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}
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}
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@Test
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@DisplayName("Test Cnn With Upsampling")
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@ParameterizedTest
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@MethodSource("org.deeplearning4j.gradientcheck.CNNGradientCheckTest#params")
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@ -338,7 +336,6 @@ class CNNGradientCheckTest extends BaseDL4JTest {
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}
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}
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@Test
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@DisplayName("Test Cnn With Subsampling")
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@ParameterizedTest
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@MethodSource("org.deeplearning4j.gradientcheck.CNNGradientCheckTest#params")
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@ -382,7 +379,6 @@ class CNNGradientCheckTest extends BaseDL4JTest {
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}
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}
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@Test
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@DisplayName("Test Cnn With Subsampling V 2")
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@ParameterizedTest
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@MethodSource("org.deeplearning4j.gradientcheck.CNNGradientCheckTest#params")
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@ -422,7 +418,6 @@ class CNNGradientCheckTest extends BaseDL4JTest {
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}
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}
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@Test
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@DisplayName("Test Cnn Locally Connected 2 D")
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@ParameterizedTest
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@MethodSource("org.deeplearning4j.gradientcheck.CNNGradientCheckTest#params")
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@ -454,7 +449,6 @@ class CNNGradientCheckTest extends BaseDL4JTest {
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}
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}
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@Test
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@DisplayName("Test Cnn Multi Layer")
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@ParameterizedTest
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@MethodSource("org.deeplearning4j.gradientcheck.CNNGradientCheckTest#params")
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@ -496,7 +490,6 @@ class CNNGradientCheckTest extends BaseDL4JTest {
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}
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}
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@Test
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@DisplayName("Test Cnn Same Padding Mode")
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@ParameterizedTest
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@MethodSource("org.deeplearning4j.gradientcheck.CNNGradientCheckTest#params")
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@ -532,7 +525,6 @@ class CNNGradientCheckTest extends BaseDL4JTest {
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}
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}
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@Test
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@DisplayName("Test Cnn Same Padding Mode Strided")
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@ParameterizedTest
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@MethodSource("org.deeplearning4j.gradientcheck.CNNGradientCheckTest#params")
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@ -577,7 +569,6 @@ class CNNGradientCheckTest extends BaseDL4JTest {
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}
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}
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@Test
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@DisplayName("Test Cnn Zero Padding Layer")
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@ParameterizedTest
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@MethodSource("org.deeplearning4j.gradientcheck.CNNGradientCheckTest#params")
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@ -625,7 +616,6 @@ class CNNGradientCheckTest extends BaseDL4JTest {
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}
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}
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@Test
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@DisplayName("Test Deconvolution 2 D")
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@ParameterizedTest
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@MethodSource("org.deeplearning4j.gradientcheck.CNNGradientCheckTest#params")
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@ -672,7 +662,6 @@ class CNNGradientCheckTest extends BaseDL4JTest {
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}
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}
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@Test
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@DisplayName("Test Separable Conv 2 D")
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@ParameterizedTest
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@MethodSource("org.deeplearning4j.gradientcheck.CNNGradientCheckTest#params")
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@ -719,7 +708,6 @@ class CNNGradientCheckTest extends BaseDL4JTest {
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}
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}
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@Test
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@DisplayName("Test Cnn Dilated")
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@ParameterizedTest
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@MethodSource("org.deeplearning4j.gradientcheck.CNNGradientCheckTest#params")
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@ -771,7 +759,6 @@ class CNNGradientCheckTest extends BaseDL4JTest {
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}
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}
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@Test
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@DisplayName("Test Cropping 2 D Layer")
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@ParameterizedTest
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@MethodSource("org.deeplearning4j.gradientcheck.CNNGradientCheckTest#params")
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@ -817,7 +804,6 @@ class CNNGradientCheckTest extends BaseDL4JTest {
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}
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}
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@Test
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@DisplayName("Test Depthwise Conv 2 D")
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@ParameterizedTest
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@MethodSource("org.deeplearning4j.gradientcheck.CNNGradientCheckTest#params")
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@ -92,7 +92,7 @@ public class YoloGradientCheckTests extends BaseDL4JTest {
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}
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@ParameterizedTest
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@MethodSource("org.deeplearning4j.gradientcheckYoloGradientCheckTests.#params")
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@MethodSource("org.deeplearning4j.gradientcheck.YoloGradientCheckTests#params")
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public void testYoloOutputLayer(CNN2DFormat format,Nd4jBackend backend) {
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int depthIn = 2;
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int c = 3;
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@ -192,7 +192,7 @@ public class YoloGradientCheckTests extends BaseDL4JTest {
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@ParameterizedTest
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@MethodSource("org.deeplearning4j.gradientcheckYoloGradientCheckTests#params")
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@MethodSource("org.deeplearning4j.gradientcheck.YoloGradientCheckTests#params")
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public void yoloGradientCheckRealData(CNN2DFormat format,Nd4jBackend backend) throws Exception {
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Nd4j.getRandom().setSeed(12345);
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InputStream is1 = new ClassPathResource("yolo/VOC_TwoImage/JPEGImages/2007_009346.jpg").getInputStream();
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@ -39,13 +39,17 @@ 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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import org.nd4j.enums.RnnDataFormat;
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import org.nd4j.linalg.BaseNd4jTestWithBackends;
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import org.nd4j.linalg.api.ndarray.INDArray;
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import org.nd4j.linalg.factory.Nd4j;
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import org.nd4j.linalg.factory.Nd4jBackend;
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import org.nd4j.linalg.indexing.NDArrayIndex;
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import org.deeplearning4j.nn.workspace.LayerWorkspaceMgr;
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import org.nd4j.linalg.learning.config.AdaGrad;
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import java.util.ArrayList;
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import java.util.Arrays;
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import java.util.List;
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import java.util.stream.Stream;
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import static org.deeplearning4j.nn.api.OptimizationAlgorithm.STOCHASTIC_GRADIENT_DESCENT;
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@ -58,13 +62,19 @@ import static org.nd4j.linalg.lossfunctions.LossFunctions.LossFunction.MSE;
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public class TestLastTimeStepLayer extends BaseDL4JTest {
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public static Stream<Arguments> params(){
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return Arrays.asList(RNNFormat.values()).stream().map(Arguments::of);
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public static Stream<Arguments> params() {
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List<Arguments> args = new ArrayList<>();
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for(Nd4jBackend nd4jBackend : BaseNd4jTestWithBackends.BACKENDS) {
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for(RNNFormat rnnFormat : RNNFormat.values()) {
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args.add(Arguments.of(rnnFormat,nd4jBackend));
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}
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}
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return args.stream();
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}
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@ParameterizedTest
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@MethodSource("#params")
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public void testLastTimeStepVertex(RNNFormat rnnDataFormat) {
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@MethodSource("org.deeplearning4j.nn.layers.recurrent.TestLastTimeStepLayer#params")
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public void testLastTimeStepVertex(RNNFormat rnnDataFormat,Nd4jBackend backend) {
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ComputationGraphConfiguration conf = new NeuralNetConfiguration.Builder().graphBuilder().addInputs("in")
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.addLayer("lastTS", new LastTimeStep(new SimpleRnn.Builder()
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@ -127,8 +137,8 @@ public class TestLastTimeStepLayer extends BaseDL4JTest {
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}
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@ParameterizedTest
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@MethodSource("#params")
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public void testMaskingAndAllMasked(RNNFormat rnnDataFormat) {
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@MethodSource("org.deeplearning4j.nn.layers.recurrent.TestLastTimeStepLayer#params")
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public void testMaskingAndAllMasked(RNNFormat rnnDataFormat,Nd4jBackend backend) {
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ComputationGraphConfiguration.GraphBuilder builder = new NeuralNetConfiguration.Builder()
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.optimizationAlgo(STOCHASTIC_GRADIENT_DESCENT)
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.weightInit(XAVIER_UNIFORM)
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