// Copyright 2019 Oath Inc. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
package ai.vespa.rankingexpression.importer.tensorflow;

import ai.vespa.rankingexpression.importer.ImportedModel;
import ai.vespa.rankingexpression.importer.configmodelview.ImportedMlFunction;
import org.junit.Assert;
import org.junit.Test;

import static org.junit.Assert.assertNotNull;

/**
 * @author bratseth
 */
public class Issue9662TestCase {

    @Test
    public void testImporting() {
        TestableTensorFlowModel model = new TestableTensorFlowModel("test", "src/test/models/tensorflow/9662");
        ImportedModel.Signature signature = model.get().signature("serving_default");
        Assert.assertEquals("Should have no skipped outputs",
                            0, model.get().signature("serving_default").skippedOutputs().size());

        ImportedMlFunction output = signature.outputFunction("output", "output");
        assertNotNull(output);
        model.assertEqualResultSum("input_embedding_user_guid", "dense_out/MatMul", 0.0001);
    }

}

// Copyright 2019 Oath Inc. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
package ai.vespa.rankingexpression.importer.tensorflow;

import ai.vespa.rankingexpression.importer.ImportedModel;
import ai.vespa.rankingexpression.importer.configmodelview.ImportedMlFunction;
import org.junit.Assert;
import org.junit.Test;

import static org.junit.Assert.assertNotNull;

/**
 * @author bratseth
 */
public class Issue9662TestCase {

    @Test
    public void testImporting() {
        TestableTensorFlowModel model = new TestableTensorFlowModel("test", "src/test/models/tensorflow/9662");
        ImportedModel.Signature signature = model.get().signature("serving_default");
        Assert.assertEquals("Should have no skipped outputs",
                            0, model.get().signature("serving_default").skippedOutputs().size());

        ImportedMlFunction output = signature.outputFunction("output", "output");
        assertNotNull(output);
        model.assertEqualResultSum("input_embedding_user_guid", "dense_out/Sigmoid", 0.00001);
    }

}

Test correct output function