Examples with Connection org.apache.sysml.api.jmlc.Connection used on opensource projects

Example 41 with Connection

use of org.apache.sysml.api.jmlc.Connection in project incubator-systemml by apache.

the class JMLCInputOutputTest method testScalarOutputString.

@Test
public void testScalarOutputString() throws DMLException {
    Connection conn = new Connection();
    String str = "outString = 'hello';\nwrite(outString, './tmp/outString');";
    PreparedScript script = conn.prepareScript(str, new String[] {}, new String[] { "outString" }, false);
    String result = script.executeScript().getString("outString");
    Assert.assertEquals("hello", result);
    conn.close();
}

Example 42 with Connection

use of org.apache.sysml.api.jmlc.Connection in project incubator-systemml by apache.

the class JMLCInputOutputTest method testScalarInputStringExplicitValueType.

@Test
public void testScalarInputStringExplicitValueType() throws IOException, DMLException {
    Connection conn = new Connection();
    String str = conn.readScript(baseDirectory + File.separator + "scalar-input-string.dml");
    PreparedScript script = conn.prepareScript(str, new String[] { "inScalar1", "inScalar2" }, new String[] {}, false);
    String inScalar1 = "hello";
    String inScalar2 = "goodbye";
    script.setScalar("inScalar1", inScalar1);
    script.setScalar("inScalar2", inScalar2);
    setExpectedStdOut("result:hellogoodbye");
    script.executeScript();
    conn.close();
}

Example 43 with Connection

use of org.apache.sysml.api.jmlc.Connection in project incubator-systemml by apache.

the class JMLCInputStreamReadTest method runJMLCInputStreamReadTest.

private void runJMLCInputStreamReadTest(DataType dt, boolean sparse, String format, boolean metaData) throws IOException {
    TestConfiguration config = getTestConfiguration(TEST_NAME);
    loadTestConfiguration(config);
    // generate inputs
    OutputInfo oinfo = format.equals("csv") ? OutputInfo.CSVOutputInfo : OutputInfo.TextCellOutputInfo;
    double[][] data = TestUtils.round(getRandomMatrix(rows, cols, 0.51, 7.49, sparse ? sparsity2 : sparsity1, 7));
    Connection conn = new Connection();
    try {
        if (dt == DataType.MATRIX) {
            // write input matrix
            MatrixBlock mb = DataConverter.convertToMatrixBlock(data);
            MatrixWriter writer = MatrixWriterFactory.createMatrixWriter(oinfo);
            writer.writeMatrixToHDFS(mb, output("X"), rows, cols, -1, -1, -1);
            // read matrix from input stream
            FileInputStream fis = new FileInputStream(output("X"));
            double[][] data2 = conn.convertToDoubleMatrix(fis, rows, cols, format);
            fis.close();
            // compare matrix result
            TestUtils.compareMatrices(data, data2, rows, cols, 0);
        } else if (dt == DataType.FRAME) {
            // write input frame
            String[][] fdata = FrameTransformTest.createFrameData(data, "V");
            // test quoted tokens w/ inner quotes
            fdata[3][1] = "\"ab\"\"cdef\"";
            if (format.equals("csv"))
                // test delimiter and space tokens
                fdata[7][2] = "\"a,bc def\"";
            FrameBlock fb = DataConverter.convertToFrameBlock(fdata);
            if (metaData) {
                fb.setColumnNames(IntStream.range(0, cols).mapToObj(i -> "CC" + i).collect(Collectors.toList()).toArray(new String[0]));
            }
            FrameWriter writer = FrameWriterFactory.createFrameWriter(oinfo);
            writer.writeFrameToHDFS(fb, output("X"), rows, cols);
            // read frame from input stream
            FileInputStream fis = new FileInputStream(output("X"));
            String[][] fdata2 = conn.convertToStringFrame(fis, rows, cols, format);
            fis.close();
            // compare frame result
            TestUtils.compareFrames(fdata, fdata2, rows, cols);
        } else {
            throw new IOException("Unsupported data type: " + dt.name());
        }
    } catch (Exception ex) {
        throw new RuntimeException(ex);
    } finally {
        MapReduceTool.deleteFileIfExistOnHDFS(output("X"));
        IOUtilFunctions.closeSilently(conn);
    }
}

Example 44 with Connection

use of org.apache.sysml.api.jmlc.Connection in project incubator-systemml by apache.

the class MulticlassSVMScoreTest method execDMLScriptviaJMLC.

private static ArrayList<double[][]> execDMLScriptviaJMLC(ArrayList<double[][]> X, boolean flags) throws IOException {
    Timing time = new Timing(true);
    ArrayList<double[][]> ret = new ArrayList<double[][]>();
    // establish connection to SystemML
    Connection conn = !flags ? new Connection() : new Connection(ConfigType.PARALLEL_CP_MATRIX_OPERATIONS, ConfigType.PARALLEL_LOCAL_OR_REMOTE_PARFOR, ConfigType.ALLOW_DYN_RECOMPILATION);
    try {
        // For now, JMLC pipeline only allows dml
        boolean parsePyDML = false;
        // read and precompile script
        String script = conn.readScript(SCRIPT_DIR + TEST_DIR + TEST_NAME + ".dml");
        PreparedScript pstmt = conn.prepareScript(script, new String[] { "X", "W" }, new String[] { "predicted_y" }, parsePyDML);
        // read model
        String modelData = conn.readScript(SCRIPT_DIR + TEST_DIR + MODEL_FILE);
        double[][] W = conn.convertToDoubleMatrix(modelData, rows, cols);
        // execute script multiple times
        for (int i = 0; i < nRuns; i++) {
            // bind input parameters
            pstmt.setMatrix("W", W);
            pstmt.setMatrix("X", X.get(i));
            // execute script
            ResultVariables rs = pstmt.executeScript();
            // get output parameter
            double[][] Y = rs.getMatrix("predicted_y");
            // keep result for comparison
            ret.add(Y);
        }
    } catch (Exception ex) {
        ex.printStackTrace();
        throw new IOException(ex);
    } finally {
        if (conn != null)
            conn.close();
    }
    System.out.println("JMLC scoring w/ " + nRuns + " runs in " + time.stop() + "ms.");
    return ret;
}

Example 45 with Connection

use of org.apache.sysml.api.jmlc.Connection in project incubator-systemml by apache.

the class ReuseModelVariablesTest method execDMLScriptviaJMLC.

private static ArrayList<double[][]> execDMLScriptviaJMLC(String testname, ArrayList<double[][]> X, boolean modelReuse) throws IOException {
    Timing time = new Timing(true);
    ArrayList<double[][]> ret = new ArrayList<double[][]>();
    // establish connection to SystemML
    Connection conn = new Connection();
    try {
        // For now, JMLC pipeline only allows dml
        boolean parsePyDML = false;
        // read and precompile script
        String script = conn.readScript(SCRIPT_DIR + TEST_DIR + testname + ".dml");
        PreparedScript pstmt = conn.prepareScript(script, new String[] { "X", "W" }, new String[] { "predicted_y" }, parsePyDML);
        // read model
        String modelData = conn.readScript(SCRIPT_DIR + TEST_DIR + MODEL_FILE);
        double[][] W = conn.convertToDoubleMatrix(modelData, rows, cols);
        if (modelReuse)
            pstmt.setMatrix("W", W, true);
        // execute script multiple times
        for (int i = 0; i < nRuns; i++) {
            // bind input parameters
            if (!modelReuse)
                pstmt.setMatrix("W", W);
            pstmt.setMatrix("X", X.get(i));
            // execute script
            ResultVariables rs = pstmt.executeScript();
            // get output parameter
            double[][] Y = rs.getMatrix("predicted_y");
            // keep result for comparison
            ret.add(Y);
        }
    } catch (Exception ex) {
        ex.printStackTrace();
        throw new IOException(ex);
    } finally {
        IOUtilFunctions.closeSilently(conn);
    }
    System.out.println("JMLC scoring w/ " + nRuns + " runs in " + time.stop() + "ms.");
    return ret;
}