Java Code Examples for org.nd4j.autodiff.samediff.SameDiff#summary()

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Example 1
Source File: LayerOpValidation.java    From deeplearning4j with Apache License 2.0 5 votes vote down vote up 
@Test
    public void testXwPlusB() {
        Nd4j.getRandom().setSeed(12345);

        SameDiff sameDiff = SameDiff.create();
        INDArray input = Nd4j.rand(new long[]{2, 3});
        INDArray weights = Nd4j.rand(new long[]{3, 4});
        INDArray b = Nd4j.rand(new long[]{4});

        SDVariable sdInput = sameDiff.var("input", input);
        SDVariable sdWeights = sameDiff.var("weights", weights);
        SDVariable sdBias = sameDiff.var("bias", b);

        SDVariable res = sameDiff.nn().linear(sdInput, sdWeights, sdBias);
        SDVariable loss = sameDiff.standardDeviation(res, true);

        INDArray exp = input.mmul(weights).addiRowVector(b);

        TestCase tc = new TestCase(sameDiff)
                .gradientCheck(true)
                .expectedOutput(res.name(), exp);

//        System.out.println(sameDiff.summary());
//        System.out.println("============================");
        sameDiff.summary();
        sameDiff.createGradFunction();
//        System.out.println(sameDiff.getFunction("grad").summary());
        sameDiff.getFunction("grad").summary();


        String err = OpValidation.validate(tc);
        assertNull(err);
    }
Example 2
Source File: TensorFlowImportTest.java    From deeplearning4j with Apache License 2.0 4 votes vote down vote up 
@Test
    public void testIntermediateReduction() throws Exception {
        Nd4j.create(1);
        SameDiff tg = TFGraphMapper.importGraph(new ClassPathResource("tf_graphs/reduce_dim.pb.txt").getInputStream());
        SDVariable sumResultVar = tg.getVariable("Sum");

      /*  val func = tg.getFunctionForVertexId(sumResultVar.getVertexId());
        assertEquals(0,func.getDimensions()[0]);
        assertEquals(3,tg.variables().size());
        assertNotNull(sumResultVar);
        assertNotNull(tg.getFunctionForVertexId(sumResultVar.getVertexId()));
        System.out.println(tg.variables());

        assertNotNull(func.getDimensions());
        assertEquals(0,func.getDimensions()[0]);*/

        ByteBuffer fb = tg.asFlatBuffers(true);
        assertNotNull(fb);

        FlatGraph graph = FlatGraph.getRootAsFlatGraph(fb);
        assertEquals(1, graph.nodesLength());
        assertEquals(2, graph.variablesLength());

        assertEquals("Sum", graph.nodes(0).name());

        FlatNode nodeSum = graph.nodes(0);
        assertEquals(2, nodeSum.inputPairedLength());


        // we expect these inputs to be 1:0 and 2:0 respectively
        // where 1 (or 2) is a graph node id
        // and :0 is graph node output index, which is 0 because that's predefined variables
        val in0 = nodeSum.inputPaired(0);
        val in1 = nodeSum.inputPaired(1);

        assertEquals(1, in0.first());
        assertEquals(0, in0.second());

        assertEquals(2, in1.first());
        assertEquals(0, in1.second());

//        System.out.println(tg.summary());
        tg.summary();

        int dimensionsLength = nodeSum.dimensionsLength();
        assertEquals(1, dimensionsLength);
        int d = nodeSum.dimensions(0);
        assertEquals(1, d);


        //log.info("nodeSum inputs length: {}; inputPaired length: {}",nodeSum.inputLength(), nodeSum.inputPairedLength());

        tg.asFlatFile(new File("../../../libnd4j/tests_cpu/resources/reduce_dim.fb"));

        /*val executioner = new NativeGraphExecutioner();

        val exp = Nd4j.create(3, 1).assign(3);

        val results = executioner.executeGraph(tg, configuration);

        assertNotNull(results);
        assertEquals(1, results.length);
        assertEquals(exp, results[0]);
        */
    }