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Declarative Machine Learning

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/*
 * Licensed to the Apache Software Foundation (ASF) under one
 * or more contributor license agreements.  See the NOTICE file
 * distributed with this work for additional information
 * regarding copyright ownership.  The ASF licenses this file
 * to you under the Apache License, Version 2.0 (the
 * "License"); you may not use this file except in compliance
 * with the License.  You may obtain a copy of the License at
 * 
 *   http://www.apache.org/licenses/LICENSE-2.0
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package org.apache.sysml.runtime.instructions.cp;

import org.apache.sysml.parser.Expression.DataType;
import org.apache.sysml.runtime.DMLRuntimeException;
import org.apache.sysml.runtime.DMLUnsupportedOperationException;
import org.apache.sysml.runtime.controlprogram.context.ExecutionContext;
import org.apache.sysml.runtime.matrix.data.MatrixBlock;
import org.apache.sysml.runtime.matrix.operators.Operator;
import org.apache.sysml.runtime.matrix.operators.ScalarOperator;


public class MatrixScalarBuiltinCPInstruction extends BuiltinBinaryCPInstruction
{
	
	public MatrixScalarBuiltinCPInstruction(Operator op,
											CPOperand in1,
											CPOperand in2,
											CPOperand out,
											String opcode,
											String instr){
		super(op, in1, in2, out, 2, opcode, instr);
	}
	
	@Override 
	public void processInstruction(ExecutionContext ec) 
		throws DMLRuntimeException, DMLUnsupportedOperationException 
	{	
		CPOperand mat = ( input1.getDataType() == DataType.MATRIX ) ? input1 : input2;
		CPOperand scalar = ( input1.getDataType() == DataType.MATRIX ) ? input2 : input1;
		
		MatrixBlock inBlock = ec.getMatrixInput(mat.getName());
		ScalarObject constant = (ScalarObject) ec.getScalarInput(scalar.getName(), scalar.getValueType(), scalar.isLiteral());
		
		ScalarOperator sc_op = (ScalarOperator)	_optr;
		sc_op.setConstant(constant.getDoubleValue());
		
		MatrixBlock retBlock = (MatrixBlock) inBlock.scalarOperations(sc_op, new MatrixBlock());

		ec.releaseMatrixInput(mat.getName());
		
		// Ensure right dense/sparse output representation (guarded by released input memory)
		if( checkGuardedRepresentationChange(inBlock, retBlock) ) {
 			retBlock.examSparsity();
 		}
		
		ec.setMatrixOutput(output.getName(), retBlock);
	}
}