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Declarative Machine Learning
/*
* 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
*
* Unless required by applicable law or agreed to in writing,
* software distributed under the License is distributed on an
* "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
* KIND, either express or implied. See the License for the
* specific language governing permissions and limitations
* under the License.
*/
package org.apache.sysml.lops;
import org.apache.sysml.hops.Hop.OpOp3;
import org.apache.sysml.lops.LopProperties.ExecLocation;
import org.apache.sysml.lops.LopProperties.ExecType;
import org.apache.sysml.lops.compile.JobType;
import org.apache.sysml.parser.Expression.DataType;
import org.apache.sysml.parser.Expression.ValueType;
/**
* Lop to perform Sum of a matrix with another matrix multiplied by Scalar.
*/
public class PlusMult extends Lop
{
private void init(Lop input1, Lop input2, Lop input3, ExecType et) {
addInput(input1);
addInput(input2);
addInput(input3);
input1.addOutput(this);
input2.addOutput(this);
input3.addOutput(this);
boolean breaksAlignment = false;
boolean aligner = false;
boolean definesMRJob = false;
if ( et == ExecType.CP || et == ExecType.SPARK ){
lps.addCompatibility(JobType.INVALID);
lps.setProperties( inputs, et, ExecLocation.ControlProgram, breaksAlignment, aligner, definesMRJob );
}
else if( et == ExecType.MR ) {
lps.addCompatibility(JobType.GMR);
lps.addCompatibility(JobType.DATAGEN);
lps.addCompatibility(JobType.REBLOCK);
lps.setProperties( inputs, et, ExecLocation.Reduce, breaksAlignment, aligner, definesMRJob );
}
}
public PlusMult(Lop input1, Lop input2, Lop input3, OpOp3 op, DataType dt, ValueType vt, ExecType et) {
super(Lop.Type.PlusMult, dt, vt);
if(op == OpOp3.MINUS_MULT)
type=Lop.Type.MinusMult;
init(input1, input2, input3, et);
}
@Override
public String toString() {
return "Operation = PlusMult";
}
public String getOpString() {
return (type==Lop.Type.PlusMult) ? "+*" : "-*";
}
/**
* Function to generate CP/Spark axpy.
*
* input1: matrix1
* input2: Scalar
* input3: matrix2
*/
@Override
public String getInstructions(String input1, String input2, String input3, String output) {
StringBuilder sb = new StringBuilder();
sb.append( getExecType() );
sb.append( OPERAND_DELIMITOR );
sb.append(getOpString());
sb.append( OPERAND_DELIMITOR );
// Matrix1
sb.append( getInputs().get(0).prepInputOperand(input1) );
sb.append( OPERAND_DELIMITOR );
// Scalar
sb.append( getInputs().get(1).prepScalarInputOperand(input2) );
sb.append( OPERAND_DELIMITOR );
// Matrix2
sb.append( getInputs().get(2).prepInputOperand(input3));
sb.append( OPERAND_DELIMITOR );
sb.append( prepOutputOperand(output));
return sb.toString();
}
@Override
public String getInstructions(int input1, int input2, int input3, int output)
throws LopsException
{
StringBuilder sb = new StringBuilder();
sb.append( getExecType() );
sb.append( OPERAND_DELIMITOR );
sb.append(getOpString());
sb.append( OPERAND_DELIMITOR );
// Matrix1
sb.append( getInputs().get(0).prepInputOperand(input1) );
sb.append( OPERAND_DELIMITOR );
// Scalar
sb.append( getInputs().get(1).prepScalarLabel() );
sb.append( OPERAND_DELIMITOR );
// Matrix2
sb.append( getInputs().get(2).prepInputOperand(input3));
sb.append( OPERAND_DELIMITOR );
sb.append( prepOutputOperand(output));
return sb.toString();
}
}