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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.runtime.DMLRuntimeException;
import org.apache.sysml.runtime.instructions.InstructionUtils;
import org.apache.sysml.runtime.matrix.data.MatrixBlock;
import org.apache.sysml.runtime.matrix.data.MatrixIndexes;
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.Operator;
public class AppendGInstruction extends AppendInstruction
{
private long _offset = -1; //cols of input1
private long _offset2 = -1; //cols of input2
private long _len = -1;
public AppendGInstruction(Operator op, byte in1, byte in2, long offset, long offset2, byte out, boolean cbind, String istr)
{
super(op, in1, in2, out, cbind, istr);
_offset = offset;
_offset2 = offset2;
_len = _offset + _offset2;
}
public static AppendGInstruction 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]));
long len = (long)(Double.parseDouble(parts[4]));
byte out = Byte.parseByte(parts[5]);
boolean cbind = Boolean.parseBoolean(parts[6]);
return new AppendGInstruction(null, in1, in2, offset, len, out, cbind, str);
}
@Override
public void processInstruction(Class valueClass,
CachedValueMap cachedValues, IndexedMatrixValue tempValue, IndexedMatrixValue zeroInput, int brlen, int bclen)
throws DMLRuntimeException
{
//setup basic meta data
int blen = _cbind ? bclen : brlen;
//Step 1: handle first input (forward blocks, change dim of last block)
ArrayList blkList1 = cachedValues.get(input1);
if( blkList1 != null )
for( IndexedMatrixValue in1 : blkList1 )
{
if( in1 == null )
continue;
if( _offset%blen == 0 ) { //special case: forward only
cachedValues.add(output, in1);
}
else //general case: change dims and forward
{
MatrixIndexes tmpix = in1.getIndexes();
MatrixBlock tmpval = (MatrixBlock) in1.getValue(); //always block
if( _cbind && _offset/blen+1 == tmpix.getColumnIndex() //border block
|| !_cbind && _offset/blen+1 == tmpix.getRowIndex())
{
IndexedMatrixValue data = cachedValues.holdPlace(output, valueClass);
MatrixBlock tmpvalNew = (MatrixBlock)data.getValue(); //always block
int lrlen = _cbind ? tmpval.getNumRows() : Math.min(blen, (int)(_len-(tmpix.getRowIndex()-1)*blen));
int lclen = _cbind ? Math.min(blen, (int)(_len-(tmpix.getColumnIndex()-1)*blen)) : tmpval.getNumColumns();
tmpvalNew.reset(lrlen, lclen);
tmpvalNew.copy(0, tmpval.getNumRows()-1, 0, tmpval.getNumColumns()-1, tmpval, true);
data.getIndexes().setIndexes(tmpix);
}
else //inner block
{
cachedValues.add(output, in1);
}
}
}
//Step 2: handle second input (split/forward blocks with new index)
ArrayList blkList2 = cachedValues.get(input2);
if( blkList2 != null )
for( IndexedMatrixValue in2 : blkList2 )
{
if( in2 == null )
continue;
MatrixIndexes tmpix = in2.getIndexes();
MatrixBlock tmpval = (MatrixBlock) in2.getValue(); //always block
if( _offset%bclen == 0 ) //special case no split
{
IndexedMatrixValue data = cachedValues.holdPlace(output, valueClass);
MatrixIndexes ix1 = data.getIndexes();
long rix = _cbind ? tmpix.getRowIndex() : _offset/blen + tmpix.getRowIndex();
long cix = _cbind ? _offset/blen + tmpix.getColumnIndex() : tmpix.getColumnIndex();
ix1.setIndexes(rix, cix);
data.set(ix1, in2.getValue());
}
else //general case: split and forward
{
IndexedMatrixValue data1 = cachedValues.holdPlace(output, valueClass);
MatrixIndexes ix1 = data1.getIndexes();
MatrixBlock tmpvalNew = (MatrixBlock)data1.getValue(); //always block
if( _cbind )
{
//first half
int cix1 = (int)(_offset/blen + tmpix.getColumnIndex());
int cols1 = Math.min(blen, (int)(_len-(long)(cix1-1)*blen));
ix1.setIndexes( tmpix.getRowIndex(), cix1);
tmpvalNew.reset( tmpval.getNumRows(), cols1 );
tmpvalNew.copy(0, tmpval.getNumRows()-1, (int)((_offset+1)%blen)-1, cols1-1,
tmpval.sliceOperations(0, tmpval.getNumRows()-1, 0,
(int)(cols1-((_offset)%blen)-1), new MatrixBlock()), true);
data1.getIndexes().setIndexes(ix1);
if( cols1-((_offset)%blen)