Java Code Examples for org.nd4j.linalg.api.buffer.util.DataTypeUtil#setDTypeForContext()

The following examples show how to use org.nd4j.linalg.api.buffer.util.DataTypeUtil#setDTypeForContext() . You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may check out the related API usage on the sidebar.

Example 1

Source File: SporadicTests.java From nd4j with Apache License 2.0

6 votes

/**
 * This is special test that checks for memory alignment
 * @throws Exception
 */
@Test
@Ignore
public void testDTypeSpam() throws Exception {
    Random rnd = new Random();
    for(int i = 0; i < 100; i++) {
        DataTypeUtil.setDTypeForContext(DataBuffer.Type.FLOAT);
        float rand[] = new float[rnd.nextInt(10) + 1];
        for (int x = 0; x < rand.length; x++) {
            rand[x] = rnd.nextFloat();
        }
        Nd4j.getConstantHandler().getConstantBuffer(rand);

        int shape[] = new int[rnd.nextInt(3)+2];
        for (int x = 0; x < shape.length; x++) {
            shape[x] = rnd.nextInt(100) + 2;
        }

        DataTypeUtil.setDTypeForContext(DataBuffer.Type.DOUBLE);
        INDArray array = Nd4j.rand(shape);
        BooleanIndexing.applyWhere(array, Conditions.lessThan(rnd.nextDouble()), rnd.nextDouble());
    }
}

Example 2

Source File: TestSerializationFloatToDouble.java From nd4j with Apache License 2.0

5 votes

@Test
public void testSerializationFullArrayNd4jWriteRead() throws Exception {
    int length = 100;

    //WRITE OUT A FLOAT ARRAY
    //Hack before setting datatype - fix already in r119_various branch
    Nd4j.create(1);
    DataTypeUtil.setDTypeForContext(DataBuffer.Type.FLOAT);
    INDArray arr = Nd4j.linspace(1, length, length).reshape('c', 10, 10);
    arr.subi(50.0123456); //assures positive and negative numbers with decimal points

    ByteArrayOutputStream baos = new ByteArrayOutputStream();
    try (DataOutputStream dos = new DataOutputStream(baos)) {
        Nd4j.write(arr, dos);
    }
    byte[] bytes = baos.toByteArray();

    //SET DATA TYPE TO DOUBLE and initialize another array with the same contents
    //Nd4j.create(1);
    DataTypeUtil.setDTypeForContext(DataBuffer.Type.DOUBLE);
    System.out.println("The data opType is " + Nd4j.dataType());
    INDArray arr1 = Nd4j.linspace(1, length, length).reshape('c', 10, 10);
    arr1.subi(50.0123456);

    INDArray arr2;
    try (DataInputStream dis = new DataInputStream(new ByteArrayInputStream(bytes))) {
        arr2 = Nd4j.read(dis);
    }

    //System.out.println(new NDArrayStrings(6).format(arr2.sub(arr1).mul(100).div(arr1)));
    assertTrue(Transforms.abs(arr1.sub(arr2).div(arr1)).maxNumber().doubleValue() < 0.01);
}

Example 3

Source File: NativeOpExecutionerTest.java From nd4j with Apache License 2.0

5 votes

@Test
public void testDebugEdgeCase2(){
    DataTypeUtil.setDTypeForContext(DataBuffer.Type.DOUBLE);
    INDArray l1 = Nd4j.create(new double[]{-0.2585039112684677,-0.005179485353710878,0.4348343401770497,0.020356532375728764,-0.1970793298488186});
    INDArray l2 = Nd4j.create(2,l1.size(1));

    INDArray p1 = Nd4j.create(new double[]{1.3979850406519119,0.6169451410155852,1.128993957530918,0.21000426084450596,0.3171215178932696});
    INDArray p2 = Nd4j.create(2, p1.size(1));

    for( int i=0; i<2; i++ ){
        l2.putRow(i, l1);
        p2.putRow(i, p1);
    }

    INDArray norm2_1 = l1.norm2(1);
    INDArray temp1 = p1.mul(l1);
    INDArray out1 = temp1.diviColumnVector(norm2_1);

    INDArray norm2_2 = l2.norm2(1);
    INDArray temp2 = p2.mul(l2);
    INDArray out2 = temp2.diviColumnVector(norm2_2);

    System.out.println("norm2_1: " + Arrays.toString(norm2_1.data().asDouble()));
    System.out.println("norm2_2: " + Arrays.toString(norm2_2.data().asDouble()));

    System.out.println("temp1: " + Arrays.toString(temp1.data().asDouble()));
    System.out.println("temp2: " + Arrays.toString(temp2.data().asDouble()));

    //Outputs here should be identical:
    System.out.println(Arrays.toString(out1.data().asDouble()));
    System.out.println(Arrays.toString(out2.getRow(0).dup().data().asDouble()));
}

Example 4

Source File: DoublesTests.java From nd4j with Apache License 2.0

5 votes

@Before
public void setUp() throws Exception {
    System.out.println("----------------------");
    DataTypeUtil.setDTypeForContext(DataBuffer.Type.DOUBLE);


    CudaEnvironment.getInstance().getConfiguration().enableDebug(true).setVerbose(true).allowMultiGPU(false);
}

Example 5

Source File: TestSerializationFloatToDouble.java From nd4j with Apache License 2.0

5 votes

@Test
public void testSerializationOnViewsJava() throws Exception {
    int length = 100;
    Nd4j.create(1);
    DataTypeUtil.setDTypeForContext(DataBuffer.Type.FLOAT);
    INDArray arr = Nd4j.linspace(1, length, length).reshape('c', 10, 10);

    INDArray sub = arr.get(NDArrayIndex.interval(5, 10), NDArrayIndex.interval(5, 10));

    ByteArrayOutputStream baos = new ByteArrayOutputStream();
    try (ObjectOutputStream oos = new ObjectOutputStream(baos)) {
        oos.writeObject(sub);
    }
    byte[] bytes = baos.toByteArray();
    DataTypeUtil.setDTypeForContext(DataBuffer.Type.DOUBLE);
    System.out.println("The data opType is " + Nd4j.dataType());
    INDArray arr1 = Nd4j.linspace(1, length, length).reshape('c', 10, 10);
    INDArray sub1 = arr1.get(NDArrayIndex.interval(5, 10), NDArrayIndex.interval(5, 10));

    INDArray arr2;
    try (ObjectInputStream ois = new ObjectInputStream(new ByteArrayInputStream(bytes))) {
        arr2 = (INDArray) ois.readObject();
    }

    //assertEquals(sub,arr2);
    assertTrue(Transforms.abs(sub1.sub(arr2).div(sub1)).maxNumber().doubleValue() < 0.01);
}

Example 6

Source File: LossFunctionGradientChecks.java From nd4j with Apache License 2.0

5 votes

@Before
public void before() throws Exception {
    super.before();

    Nd4j.zeros(1);
    DataTypeUtil.setDTypeForContext(DataBuffer.Type.DOUBLE);

    Nd4j.getRandom().setSeed(123);
}

Example 7

Source File: TestSerializationDoubleToFloat.java From nd4j with Apache License 2.0

5 votes

@Test
public void testSerializationFullArrayJava() throws Exception {
    int length = 100;
    Nd4j.create(1);
    DataTypeUtil.setDTypeForContext(DataBuffer.Type.DOUBLE);
    INDArray arr = Nd4j.linspace(1, length, length).reshape('c', 10, 10);
    arr.subi(50.0123456); //assures positive and negative numbers with decimal points

    ByteArrayOutputStream baos = new ByteArrayOutputStream();
    try (ObjectOutputStream oos = new ObjectOutputStream(baos)) {
        oos.writeObject(arr);
    }
    byte[] bytes = baos.toByteArray();

    //SET DATA TYPE TO FLOAT and initialize another array with the same contents
    //Nd4j.create(1);
    DataTypeUtil.setDTypeForContext(DataBuffer.Type.FLOAT);
    System.out.println("The data opType is " + Nd4j.dataType());
    INDArray arr1 = Nd4j.linspace(1, length, length).reshape('c', 10, 10);
    arr1.subi(50.0123456);

    INDArray arr2;
    try (ObjectInputStream ois = new ObjectInputStream(new ByteArrayInputStream(bytes))) {
        arr2 = (INDArray) ois.readObject();
    }

    assertTrue(Transforms.abs(arr1.sub(arr2).div(arr1)).maxNumber().doubleValue() < 0.01);
}

Example 8

Source File: ShapeTestsC.java From deeplearning4j with Apache License 2.0

5 votes

@Test
public void testColumnSumDouble() {
    DataType initialType = Nd4j.dataType();
    DataTypeUtil.setDTypeForContext(DataType.DOUBLE);
    INDArray twoByThree = Nd4j.linspace(1, 600, 600, DataType.DOUBLE).reshape(150, 4);
    INDArray columnVar = twoByThree.sum(0);
    INDArray assertion = Nd4j.create(new double[] {44850.0f, 45000.0f, 45150.0f, 45300.0f});
    assertEquals(getFailureMessage(), assertion, columnVar);
    DataTypeUtil.setDTypeForContext(initialType);
}

Example 9

Source File: Nd4jTestsComparisonC.java From nd4j with Apache License 2.0

4 votes

@Before
public void before() throws Exception {
    super.before();
    DataTypeUtil.setDTypeForContext(DataBuffer.Type.DOUBLE);
}

Example 10

Source File: AveragingTests.java From nd4j with Apache License 2.0

4 votes

@Before
public void setUp() {
    DataTypeUtil.setDTypeForContext(DataBuffer.Type.DOUBLE);
}

Example 11

Source File: ConvolutionTests.java From nd4j with Apache License 2.0

4 votes

@Test
@Ignore
public void testCompareIm2ColImpl() {

    int[] miniBatches = {1, 3, 5};
    int[] depths = {1, 3, 5};
    int[] inHeights = {5, 21};
    int[] inWidths = {5, 21};
    int[] strideH = {1, 2};
    int[] strideW = {1, 2};
    int[] sizeW = {1, 2, 3};
    int[] sizeH = {1, 2, 3};
    int[] padH = {0, 1, 2};
    int[] padW = {0, 1, 2};
    boolean[] coverall = {false, true};

    DataBuffer.Type[] types = new DataBuffer.Type[] {DataBuffer.Type.FLOAT, DataBuffer.Type.DOUBLE,
                    DataBuffer.Type.FLOAT, DataBuffer.Type.DOUBLE};
    DataBuffer.AllocationMode[] modes =
                    new DataBuffer.AllocationMode[] {DataBuffer.AllocationMode.HEAP, DataBuffer.AllocationMode.HEAP,
                                    DataBuffer.AllocationMode.DIRECT, DataBuffer.AllocationMode.DIRECT};

    String factoryClassName = Nd4j.factory().getClass().toString().toLowerCase();
    if (factoryClassName.contains("jcublas") || factoryClassName.contains("cuda")) {
        //Only test direct for CUDA; test all for CPU
        types = new DataBuffer.Type[] {DataBuffer.Type.FLOAT, DataBuffer.Type.DOUBLE};
        modes = new DataBuffer.AllocationMode[] {DataBuffer.AllocationMode.DIRECT,
                        DataBuffer.AllocationMode.DIRECT};
    }

    DataBuffer.Type initialType = Nd4j.dataType();
    for (int i = 0; i < types.length; i++) {
        DataBuffer.Type type = types[i];
        DataBuffer.AllocationMode mode = modes[i];

        DataTypeUtil.setDTypeForContext(type);
        Nd4j.alloc = mode;

        AllocUtil.setAllocationModeForContext(mode);

        for (int m : miniBatches) {
            for (int d : depths) {
                for (int h : inHeights) {
                    for (int w : inWidths) {
                        for (int sh : strideH) {
                            for (int sw : strideW) {
                                for (int kh : sizeH) {
                                    for (int kw : sizeW) {
                                        for (int ph : padH) {
                                            for (int pw : padW) {
                                                if ((w - kw + 2 * pw) % sw != 0 || (h - kh + 2 * ph) % sh != 0)
                                                    continue; //(w-kp+2*pw)/sw + 1 is not an integer,  i.e., number of outputs doesn't fit

                                                System.out.println("Running " + m + " " + d + " " + h + " " + w);
                                                for (boolean cAll : coverall) {

                                                    INDArray in = Nd4j.rand(new int[] {m, d, h, w});
                                                    //assertEquals(in.data().allocationMode(), mode);
                                                    //assertEquals(in.data().dataType(), opType);

                                                    INDArray outOrig = OldConvolution.im2col(in, kh, kw, sh, sw, ph,
                                                                    pw, -1, cAll); //Old implementation
                                                    INDArray outNew = Convolution.im2col(in, kh, kw, sh, sw, ph, pw,
                                                                    cAll); //Current implementation

                                                    assertArrayEquals(outOrig.data().asFloat(),
                                                                    outNew.data().asFloat(), 0.01f);
                                                    assertEquals(outOrig, outNew);
                                                }
                                            }
                                        }
                                    }
                                }
                            }
                        }
                    }
                }
            }
        }
    }

    DataTypeUtil.setDTypeForContext(initialType);
}

Example 12

Source File: DoubleDataBufferTest.java From nd4j with Apache License 2.0

4 votes

@After
public void after() {
    DataTypeUtil.setDTypeForContext(initialType);
}

Example 13

Source File: Nd4jTestsComparisonC.java From nd4j with Apache License 2.0

4 votes

@After
public void after() throws Exception {
    super.after();
    DataTypeUtil.setDTypeForContext(initialType);
}

Example 14

Source File: Nd4jTestsComparisonC.java From deeplearning4j with Apache License 2.0

4 votes

@After
public void after() throws Exception {
    DataTypeUtil.setDTypeForContext(initialType);
}

Example 15

Source File: ConvolutionTestsC.java From nd4j with Apache License 2.0

4 votes

@Test
@Ignore
public void testCompareIm2ColImpl() {

    int[] miniBatches = {1, 3, 5};
    int[] depths = {1, 3, 5};
    int[] inHeights = {5, 21};
    int[] inWidths = {5, 21};
    int[] strideH = {1, 2};
    int[] strideW = {1, 2};
    int[] sizeW = {1, 2, 3};
    int[] sizeH = {1, 2, 3};
    int[] padH = {0, 1, 2};
    int[] padW = {0, 1, 2};
    boolean[] coverall = {false, true};

    DataBuffer.Type[] types = new DataBuffer.Type[] {DataBuffer.Type.FLOAT, DataBuffer.Type.DOUBLE,
                    DataBuffer.Type.FLOAT, DataBuffer.Type.DOUBLE};
    DataBuffer.AllocationMode[] modes =
                    new DataBuffer.AllocationMode[] {DataBuffer.AllocationMode.HEAP, DataBuffer.AllocationMode.HEAP,
                                    DataBuffer.AllocationMode.DIRECT, DataBuffer.AllocationMode.DIRECT};

    String factoryClassName = Nd4j.factory().getClass().toString().toLowerCase();
    if (factoryClassName.contains("jcublas") || factoryClassName.contains("cuda")) {
        //Only test direct for CUDA; test all for CPU
        types = new DataBuffer.Type[] {DataBuffer.Type.FLOAT, DataBuffer.Type.DOUBLE};
        modes = new DataBuffer.AllocationMode[] {DataBuffer.AllocationMode.DIRECT,
                        DataBuffer.AllocationMode.DIRECT};
    }

    DataBuffer.Type initialType = Nd4j.dataType();
    for (int i = 0; i < types.length; i++) {
        DataBuffer.Type type = types[i];
        DataBuffer.AllocationMode mode = modes[i];

        DataTypeUtil.setDTypeForContext(type);
        Nd4j.alloc = mode;

        AllocUtil.setAllocationModeForContext(mode);

        for (int m : miniBatches) {
            for (int d : depths) {
                for (int h : inHeights) {
                    for (int w : inWidths) {
                        for (int sh : strideH) {
                            for (int sw : strideW) {
                                for (int kh : sizeH) {
                                    for (int kw : sizeW) {
                                        for (int ph : padH) {
                                            for (int pw : padW) {
                                                if ((w - kw + 2 * pw) % sw != 0 || (h - kh + 2 * ph) % sh != 0)
                                                    continue; //(w-kp+2*pw)/sw + 1 is not an integer,  i.e., number of outputs doesn't fit

                                                System.out.println("Running " + m + " " + d + " " + h + " " + w);
                                                for (boolean cAll : coverall) {

                                                    INDArray in = Nd4j.rand(new int[] {m, d, h, w});
                                                    //assertEquals(in.data().allocationMode(), mode);
                                                    //assertEquals(in.data().dataType(), opType);

                                                    INDArray outOrig = OldConvolution.im2col(in, kh, kw, sh, sw, ph,
                                                                    pw, -1, cAll); //Old implementation
                                                    INDArray outNew = Convolution.im2col(in, kh, kw, sh, sw, ph, pw,
                                                                    cAll); //Current implementation

                                                    assertEquals(outOrig, outNew);
                                                }
                                            }
                                        }
                                    }
                                }
                            }
                        }
                    }
                }
            }
        }
    }

    DataTypeUtil.setDTypeForContext(initialType);
}

Example 16

Source File: FloatDataBufferTest.java From nd4j with Apache License 2.0

4 votes

@After
public void after() {
    DataTypeUtil.setDTypeForContext(initialType);
}

Example 17

Source File: RandomTests.java From nd4j with Apache License 2.0

4 votes

@Before
public void setUp() throws Exception {
    initialType = Nd4j.dataType();
    DataTypeUtil.setDTypeForContext(DataBuffer.Type.DOUBLE);
}

Example 18

Source File: Nd4jTestsComparisonC.java From deeplearning4j with Apache License 2.0

4 votes

@Before
public void before() throws Exception {
    DataTypeUtil.setDTypeForContext(DataType.DOUBLE);
}

Example 19

Source File: FloatDataBufferTest.java From nd4j with Apache License 2.0

4 votes

@Before
public void before() {
    DataTypeUtil.setDTypeForContext(DataBuffer.Type.FLOAT);
    System.out.println("DATATYPE HERE: " + Nd4j.dataType());
}

Example 20

Source File: Nd4jTestsComparisonFortran.java From deeplearning4j with Apache License 2.0

4 votes

@After
public void after() throws Exception {
    DataTypeUtil.setDTypeForContext(initialType);
}