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Declarative Machine Learning
/*
* Licensed to the Apache Software Foundation (ASF) under one
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* 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
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* KIND, either express or implied. See the License for the
* specific language governing permissions and limitations
* under the License.
*/
package org.apache.sysml.runtime.instructions.mr;
import org.apache.sysml.lops.PartialAggregate.CorrectionLocationType;
import org.apache.sysml.runtime.DMLRuntimeException;
import org.apache.sysml.runtime.functionobjects.CM;
import org.apache.sysml.runtime.functionobjects.KahanPlus;
import org.apache.sysml.runtime.instructions.InstructionUtils;
import org.apache.sysml.runtime.matrix.data.MatrixValue;
import org.apache.sysml.runtime.matrix.mapred.CachedValueMap;
import org.apache.sysml.runtime.matrix.mapred.IndexedMatrixValue;
import org.apache.sysml.runtime.matrix.operators.AggregateOperator;
import org.apache.sysml.runtime.matrix.operators.CMOperator;
import org.apache.sysml.runtime.matrix.operators.Operator;
import org.apache.sysml.runtime.matrix.operators.CMOperator.AggregateOperationTypes;
public class GroupedAggregateInstruction extends UnaryMRInstructionBase
{
private boolean _weights = false;
private int _ngroups = -1;
private long _bclen = -1;
public GroupedAggregateInstruction(Operator op, byte in, byte out, boolean weights, int ngroups, String istr) {
super(op, in, out);
mrtype = MRINSTRUCTION_TYPE.GroupedAggregate;
instString = istr;
_weights = weights;
_ngroups = ngroups;
}
public boolean hasWeights() {
return _weights;
}
public int getNGroups() {
return _ngroups;
}
public void setBclen(long bclen){
_bclen = bclen;
}
public long getBclen(){
return _bclen;
}
@Override
public void processInstruction(Class valueClass,
CachedValueMap cachedValues, IndexedMatrixValue tempValue,
IndexedMatrixValue zeroInput,
int blockRowFactor, int blockColFactor)
throws DMLRuntimeException {
throw new DMLRuntimeException("GroupedAggregateInstruction.processInstruction() should not be called!");
}
public static GroupedAggregateInstruction parseInstruction ( String str ) throws DMLRuntimeException {
String[] parts = InstructionUtils.getInstructionParts ( str );
if(parts.length<3)
throw new DMLRuntimeException("the number of fields of instruction "+str+" is less than 2!");
byte in, out;
String opcode = parts[0];
in = Byte.parseByte(parts[1]);
out = Byte.parseByte(parts[parts.length - 3]);
boolean weights = Boolean.parseBoolean(parts[parts.length-2]);
int ngroups = Integer.parseInt(parts[parts.length-1]);
if ( !opcode.equalsIgnoreCase("groupedagg") ) {
throw new DMLRuntimeException("Invalid opcode in GroupedAggregateInstruction: " + opcode);
}
Operator optr = parseGroupedAggOperator(parts[2], parts[3]);
return new GroupedAggregateInstruction(optr, in, out, weights, ngroups, str);
}
public static Operator parseGroupedAggOperator(String fn, String other) throws DMLRuntimeException {
AggregateOperationTypes op = AggregateOperationTypes.INVALID;
if ( fn.equalsIgnoreCase("centralmoment") )
// in case of CM, we also need to pass "order"
op = CMOperator.getAggOpType(fn, other);
else
op = CMOperator.getAggOpType(fn, null);
switch(op) {
case SUM:
return new AggregateOperator(0, KahanPlus.getKahanPlusFnObject(), true, CorrectionLocationType.LASTCOLUMN);
case COUNT:
case MEAN:
case VARIANCE:
case CM2:
case CM3:
case CM4:
return new CMOperator(CM.getCMFnObject(op), op);
case INVALID:
default:
throw new DMLRuntimeException("Invalid Aggregate Operation in GroupedAggregateInstruction: " + op);
}
}
}