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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.runtime.instructions.mr;
import java.util.ArrayList;
import org.apache.sysml.lops.AppendM.CacheType;
import org.apache.sysml.runtime.DMLRuntimeException;
import org.apache.sysml.runtime.instructions.InstructionUtils;
import org.apache.sysml.runtime.matrix.data.MatrixIndexes;
import org.apache.sysml.runtime.matrix.data.MatrixValue;
import org.apache.sysml.runtime.matrix.data.OperationsOnMatrixValues;
import org.apache.sysml.runtime.matrix.mapred.CachedValueMap;
import org.apache.sysml.runtime.matrix.mapred.DistributedCacheInput;
import org.apache.sysml.runtime.matrix.mapred.IndexedMatrixValue;
import org.apache.sysml.runtime.matrix.mapred.MRBaseForCommonInstructions;
import org.apache.sysml.runtime.matrix.operators.Operator;
public class AppendMInstruction extends AppendInstruction implements IDistributedCacheConsumer
{
private long _offset = -1;
public AppendMInstruction(Operator op, byte in1, byte in2, long offset, CacheType type, byte out, boolean cbind, String istr)
{
super(op, in1, in2, out, cbind, istr);
_offset = offset;
}
public static AppendMInstruction parseInstruction ( String str )
throws DMLRuntimeException
{
String[] parts = InstructionUtils.getInstructionParts ( str );
InstructionUtils.checkNumFields(parts, 6);
byte in1 = Byte.parseByte(parts[1]);
byte in2 = Byte.parseByte(parts[2]);
long offset = (long)(Double.parseDouble(parts[3]));
byte out = Byte.parseByte(parts[4]);
CacheType type = CacheType.valueOf(parts[5]);
boolean cbind = Boolean.parseBoolean(parts[6]);
return new AppendMInstruction(null, in1, in2, offset, type, out, cbind, str);
}
@Override //IDistributedCacheConsumer
public boolean isDistCacheOnlyIndex( String inst, byte index )
{
return (index==input2 && index!=input1);
}
@Override //IDistributedCacheConsumer
public void addDistCacheIndex( String inst, ArrayList indexes )
{
indexes.add(input2);
}
@Override
public void processInstruction(Class valueClass,
CachedValueMap cachedValues, IndexedMatrixValue tempValue, IndexedMatrixValue zeroInput,
int blockRowFactor, int blockColFactor)
throws DMLRuntimeException
{
ArrayList blkList = cachedValues.get(input1);
if( blkList == null )
return;
//right now this only deals with appending matrix with number of column <= blockColFactor
for(IndexedMatrixValue in1 : blkList)
{
if(in1 == null)
continue;
//check for boundary block
int blen = _cbind ? blockColFactor : blockRowFactor;
long lastBlockColIndex = (long)Math.ceil((double)_offset/blen);
//case 1: pass through of non-boundary blocks
MatrixIndexes ix = in1.getIndexes();
if( (_cbind?ix.getColumnIndex():ix.getRowIndex())!=lastBlockColIndex ) {
cachedValues.add(output, in1);
}
//case 2: pass through full input block and rhs block
else if( _cbind && in1.getValue().getNumColumns() == blen
|| !_cbind && in1.getValue().getNumRows() == blen ) {
//output lhs block
cachedValues.add(output, in1);
//output shallow copy of rhs block
DistributedCacheInput dcInput = MRBaseForCommonInstructions.dcValues.get(input2);
if( _cbind ) {
cachedValues.add(output, new IndexedMatrixValue(
new MatrixIndexes(ix.getRowIndex(), ix.getColumnIndex()+1),
dcInput.getDataBlock((int)ix.getRowIndex(), 1).getValue()));
}
else {
cachedValues.add(output, new IndexedMatrixValue(
new MatrixIndexes(ix.getRowIndex()+1, ix.getColumnIndex()),
dcInput.getDataBlock(1, (int)ix.getColumnIndex()).getValue()));
}
}
//case 3: append operation on boundary block
else
{
DistributedCacheInput dcInput = MRBaseForCommonInstructions.dcValues.get(input2);
//allocate space for the output value
ArrayList outlist=new ArrayList(2);
IndexedMatrixValue first=cachedValues.holdPlace(output, valueClass);
first.getIndexes().setIndexes(ix);
outlist.add(first);
MatrixValue value_in2 = null;
if( _cbind ) {
value_in2 = dcInput.getDataBlock((int)ix.getRowIndex(), 1).getValue();
if(in1.getValue().getNumColumns()+value_in2.getNumColumns()>blen) {
IndexedMatrixValue second=cachedValues.holdPlace(output, valueClass);
second.getIndexes().setIndexes(ix.getRowIndex(), ix.getColumnIndex()+1);
outlist.add(second);
}
}
else { //rbind
value_in2 = dcInput.getDataBlock(1, (int)ix.getRowIndex()).getValue();
if(in1.getValue().getNumRows()+value_in2.getNumRows()>blen) {
IndexedMatrixValue second=cachedValues.holdPlace(output, valueClass);
second.getIndexes().setIndexes(ix.getRowIndex()+1, ix.getColumnIndex());
outlist.add(second);
}
}
OperationsOnMatrixValues.performAppend(in1.getValue(), value_in2, outlist,
blockRowFactor, blockColFactor, _cbind, true, 0);
}
}
}
}