Java* API Reference for Intel® Data Analytics Acceleration Library 2019 Update 5

ReLUDenseBatch.java

/* file: ReLUDenseBatch.java */
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/*
// Content:
// Java example of ReLU algorithm
*/
package com.intel.daal.examples.math;
import com.intel.daal.algorithms.math.relu.*;
import com.intel.daal.data_management.data.NumericTable;
import com.intel.daal.data_management.data_source.DataSource;
import com.intel.daal.data_management.data_source.FileDataSource;
import com.intel.daal.examples.utils.Service;
import com.intel.daal.services.DaalContext;
class ReLUDenseBatch {
private static final String dataset = "../data/batch/covcormoments_dense.csv";
private static DaalContext context = new DaalContext();
public static void main(String[] args) throws java.io.FileNotFoundException, java.io.IOException {
/* Retrieve the input data */
FileDataSource dataSource = new FileDataSource(context, dataset,
DataSource.DictionaryCreationFlag.DoDictionaryFromContext,
DataSource.NumericTableAllocationFlag.DoAllocateNumericTable);
dataSource.loadDataBlock();
NumericTable input = dataSource.getNumericTable();
/* Create an algorithm */
Batch reluAlgorithm = new Batch(context, Float.class, Method.defaultDense);
/* Set an input object for the algorithm */
reluAlgorithm.input.set(InputId.data, input);
/* Compute ReLU function */
Result result = reluAlgorithm.compute();
/* Print the results of the algorithm */
Service.printNumericTable("ReLU result (first 5 rows):", result.get(ResultId.value), 5);
context.dispose();
}
}

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