Added missing HelperUtilsTest.java
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285c6755d1
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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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package org.deeplearning4j.nn.layers;
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import org.deeplearning4j.BaseDL4JTest;
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import org.deeplearning4j.datasets.iterator.impl.MnistDataSetIterator;
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import org.deeplearning4j.nn.api.OptimizationAlgorithm;
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import org.deeplearning4j.nn.conf.ComputationGraphConfiguration;
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import org.deeplearning4j.nn.conf.MultiLayerConfiguration;
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import org.deeplearning4j.nn.conf.NeuralNetConfiguration;
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import org.deeplearning4j.nn.conf.inputs.InputType;
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import org.deeplearning4j.nn.conf.layers.ActivationLayer;
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import org.deeplearning4j.nn.conf.layers.OutputLayer;
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import org.deeplearning4j.nn.conf.layers.*;
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import org.deeplearning4j.nn.graph.ComputationGraph;
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import org.deeplearning4j.nn.layers.convolution.ConvolutionHelper;
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import org.deeplearning4j.nn.layers.convolution.subsampling.SubsamplingHelper;
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import org.deeplearning4j.nn.layers.mkldnn.*;
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import org.deeplearning4j.nn.layers.normalization.BatchNormalizationHelper;
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import org.deeplearning4j.nn.layers.normalization.LocalResponseNormalizationHelper;
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import org.deeplearning4j.nn.layers.recurrent.LSTMHelper;
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import org.deeplearning4j.nn.multilayer.MultiLayerNetwork;
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import org.deeplearning4j.nn.weights.WeightInit;
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import org.junit.jupiter.api.DisplayName;
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import org.junit.jupiter.api.Tag;
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import org.junit.jupiter.api.Test;
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import org.nd4j.common.tests.tags.NativeTag;
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import org.nd4j.common.tests.tags.TagNames;
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import org.nd4j.linalg.activations.Activation;
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import org.nd4j.linalg.activations.impl.ActivationELU;
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import org.nd4j.linalg.activations.impl.ActivationRationalTanh;
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import org.nd4j.linalg.activations.impl.ActivationSoftmax;
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import org.nd4j.linalg.api.buffer.DataType;
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import org.nd4j.linalg.api.ndarray.INDArray;
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import org.nd4j.linalg.dataset.DataSet;
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import org.nd4j.linalg.dataset.api.iterator.DataSetIterator;
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import org.nd4j.linalg.factory.Nd4j;
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import org.nd4j.linalg.lossfunctions.LossFunctions;
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import java.util.List;
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import static org.junit.jupiter.api.Assertions.*;
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/**
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*/
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@DisplayName("Activation Layer Test")
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@NativeTag
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@Tag(TagNames.CUSTOM_FUNCTIONALITY)
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@Tag(TagNames.DL4J_OLD_API)
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public class HelperUtilsTest extends BaseDL4JTest {
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@Override
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public DataType getDataType() {
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return DataType.FLOAT;
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}
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@Test
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@DisplayName("Test instance creation of various helpers")
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public void testOneDnnHelperCreation() {
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assertNotNull(HelperUtils.createHelper("",
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MKLDNNLSTMHelper.class.getName(), LSTMHelper.class,"layername",getDataType()));
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assertNotNull(HelperUtils.createHelper("", MKLDNNBatchNormHelper.class.getName(),
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BatchNormalizationHelper.class,"layername",getDataType()));
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assertNotNull(HelperUtils.createHelper("", MKLDNNLocalResponseNormalizationHelper.class.getName(),
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LocalResponseNormalizationHelper.class,"layername",getDataType()));
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assertNotNull(HelperUtils.createHelper("", MKLDNNSubsamplingHelper.class.getName(),
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SubsamplingHelper.class,"layername",getDataType()));
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assertNotNull(HelperUtils.createHelper("", MKLDNNConvHelper.class.getName(),
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ConvolutionHelper.class,"layername",getDataType()));
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}
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}
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