| /* |
| * 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.sysds.runtime.instructions.spark; |
| |
| import org.apache.spark.api.java.JavaPairRDD; |
| import org.apache.spark.api.java.function.PairFlatMapFunction; |
| import org.apache.sysds.common.Types; |
| import org.apache.sysds.common.Types.ValueType; |
| import org.apache.sysds.runtime.DMLRuntimeException; |
| import org.apache.sysds.runtime.controlprogram.context.ExecutionContext; |
| import org.apache.sysds.runtime.controlprogram.context.SparkExecutionContext; |
| import org.apache.sysds.runtime.data.IndexedTensorBlock; |
| import org.apache.sysds.runtime.data.TensorBlock; |
| import org.apache.sysds.runtime.data.TensorIndexes; |
| import org.apache.sysds.runtime.instructions.InstructionUtils; |
| import org.apache.sysds.runtime.instructions.cp.CPOperand; |
| import org.apache.sysds.runtime.instructions.spark.data.IndexedMatrixValue; |
| import org.apache.sysds.runtime.instructions.spark.functions.FilterNonEmptyBlocksFunction; |
| import org.apache.sysds.runtime.instructions.spark.utils.RDDAggregateUtils; |
| import org.apache.sysds.runtime.instructions.spark.utils.SparkUtils; |
| import org.apache.sysds.runtime.matrix.data.LibMatrixReorg; |
| import org.apache.sysds.runtime.matrix.data.MatrixBlock; |
| import org.apache.sysds.runtime.matrix.data.MatrixIndexes; |
| import org.apache.sysds.runtime.matrix.operators.Operator; |
| import org.apache.sysds.runtime.meta.DataCharacteristics; |
| import scala.Tuple2; |
| |
| import java.util.Iterator; |
| import java.util.List; |
| |
| public class MatrixReshapeSPInstruction extends UnarySPInstruction |
| { |
| private final CPOperand _opRows; |
| private final CPOperand _opCols; |
| private final CPOperand _opByRow; |
| private final boolean _outputEmptyBlocks; |
| |
| private MatrixReshapeSPInstruction(Operator op, CPOperand in1, CPOperand in2, CPOperand in3, CPOperand in4, |
| CPOperand out, boolean outputEmptyBlocks, String opcode, String istr) { |
| super(SPType.MatrixReshape, op, in1, out, opcode, istr); |
| _opRows = in2; |
| _opCols = in3; |
| _opByRow = in4; |
| _outputEmptyBlocks = outputEmptyBlocks; |
| } |
| |
| public static MatrixReshapeSPInstruction parseInstruction ( String str ) { |
| String[] parts = InstructionUtils.getInstructionPartsWithValueType(str); |
| InstructionUtils.checkNumFields( parts, 7 ); |
| |
| String opcode = parts[0]; |
| CPOperand in1 = new CPOperand(parts[1]); |
| CPOperand rows = new CPOperand(parts[2]); |
| CPOperand cols = new CPOperand(parts[3]); |
| //TODO handle dims for tensors parts[4] |
| CPOperand byRow = new CPOperand(parts[5]); |
| CPOperand out = new CPOperand(parts[6]); |
| boolean outputEmptyBlocks = Boolean.parseBoolean(parts[7]); |
| |
| if(!opcode.equalsIgnoreCase("rshape")) |
| throw new DMLRuntimeException("Unknown opcode while parsing an MatrixReshapeInstruction: " + str); |
| else |
| return new MatrixReshapeSPInstruction(new Operator(true), in1, rows, cols, byRow, out, outputEmptyBlocks, opcode, str); |
| } |
| |
| @Override |
| public void processInstruction(ExecutionContext ec) { |
| SparkExecutionContext sec = (SparkExecutionContext)ec; |
| |
| //get parameters |
| long rows = ec.getScalarInput(_opRows).getLongValue(); //save cast |
| long cols = ec.getScalarInput(_opCols).getLongValue(); //save cast |
| boolean byRow = ec.getScalarInput(_opByRow.getName(), ValueType.BOOLEAN, _opByRow.isLiteral()).getBooleanValue(); |
| |
| DataCharacteristics mcIn = sec.getDataCharacteristics(input1.getName()); |
| DataCharacteristics mcOut = sec.getDataCharacteristics(output.getName()); |
| if (input1.getDataType() == Types.DataType.MATRIX) { |
| JavaPairRDD<MatrixIndexes, MatrixBlock> in1 = sec |
| .getBinaryMatrixBlockRDDHandleForVariable(input1.getName(), -1, _outputEmptyBlocks); |
| |
| //update output characteristics and sanity check |
| mcOut.set(rows, cols, mcIn.getBlocksize(), mcIn.getNonZeros()); |
| if (!mcIn.nnzKnown()) |
| mcOut.setNonZerosBound(mcIn.getNonZerosBound()); |
| if (mcIn.getRows() * mcIn.getCols() != mcOut.getRows() * mcOut.getCols()) { |
| throw new DMLRuntimeException("Incompatible matrix characteristics for reshape: " |
| + mcIn.getRows() + "x" + mcIn.getCols() + " vs " + mcOut.getRows() + "x" + mcOut.getCols()); |
| } |
| |
| if (!_outputEmptyBlocks) |
| in1 = in1.filter(new FilterNonEmptyBlocksFunction()); |
| |
| //execute reshape instruction |
| JavaPairRDD<MatrixIndexes, MatrixBlock> out = |
| in1.flatMapToPair(new RDDReshapeFunction(mcIn, mcOut, byRow, _outputEmptyBlocks)); |
| out = RDDAggregateUtils.mergeByKey(out); |
| |
| //put output RDD handle into symbol table |
| sec.setRDDHandleForVariable(output.getName(), out); |
| sec.addLineageRDD(output.getName(), input1.getName()); |
| } else { |
| // TODO Tensor reshape |
| JavaPairRDD<TensorIndexes, TensorBlock> in1 = sec.getBinaryTensorBlockRDDHandleForVariable(input1.getName(), |
| -1, _outputEmptyBlocks); |
| JavaPairRDD<TensorIndexes, TensorBlock> out = in1.flatMapToPair( |
| new RDDTensorReshapeFunction(mcIn, mcOut, byRow, _outputEmptyBlocks)); |
| // TODO merge by key |
| //out = RDDAggregateUtils.mergeByKey(out); |
| sec.setRDDHandleForVariable(output.getName(), out); |
| sec.addLineageRDD(output.getName(), input1.getName()); |
| } |
| } |
| |
| private static class RDDReshapeFunction implements PairFlatMapFunction<Tuple2<MatrixIndexes, MatrixBlock>, MatrixIndexes, MatrixBlock> |
| { |
| private static final long serialVersionUID = 2819309412002224478L; |
| |
| private final DataCharacteristics _mcIn; |
| private final DataCharacteristics _mcOut; |
| private final boolean _byrow; |
| private final boolean _outputEmptyBlocks; |
| |
| public RDDReshapeFunction(DataCharacteristics mcIn, DataCharacteristics mcOut, boolean byrow, boolean outputEmptyBlocks) { |
| _mcIn = mcIn; |
| _mcOut = mcOut; |
| _byrow = byrow; |
| _outputEmptyBlocks = outputEmptyBlocks; |
| } |
| |
| @Override |
| public Iterator<Tuple2<MatrixIndexes, MatrixBlock>> call( Tuple2<MatrixIndexes, MatrixBlock> arg0 ) |
| throws Exception |
| { |
| //input conversion (for libmatrixreorg compatibility) |
| IndexedMatrixValue in = SparkUtils.toIndexedMatrixBlock(arg0); |
| |
| //execute actual reshape operation |
| List<IndexedMatrixValue> out = LibMatrixReorg |
| .reshape(in, _mcIn, _mcOut, _byrow, _outputEmptyBlocks); |
| |
| //output conversion (for compatibility w/ rdd schema) |
| return SparkUtils.fromIndexedMatrixBlock(out).iterator(); |
| } |
| } |
| |
| @SuppressWarnings("unused") |
| private static class RDDTensorReshapeFunction implements PairFlatMapFunction<Tuple2<TensorIndexes, TensorBlock>, |
| TensorIndexes, TensorBlock> { |
| private static final long serialVersionUID = 8030648988828223639L; |
| |
| private final DataCharacteristics _mcIn; |
| private final DataCharacteristics _mcOut; |
| private final boolean _byrow; |
| private final boolean _outputEmptyBlocks; |
| |
| public RDDTensorReshapeFunction(DataCharacteristics mcIn, DataCharacteristics mcOut, boolean byrow, boolean outputEmptyBlocks) { |
| _mcIn = mcIn; |
| _mcOut = mcOut; |
| _byrow = byrow; |
| _outputEmptyBlocks = outputEmptyBlocks; |
| } |
| |
| @Override |
| public Iterator<Tuple2<TensorIndexes, TensorBlock>> call(Tuple2<TensorIndexes, TensorBlock> arg0) |
| throws Exception { |
| //input conversion (for libmatrixreorg compatibility) |
| IndexedTensorBlock in = SparkUtils.toIndexedTensorBlock(arg0); |
| |
| //execute actual reshape operation |
| //LibTensorReorg.reshape() |
| // List<IndexedTensorBlock> out = LibTensorReorg |
| // .reshape(in, _mcIn, _mcOut, _byrow, _outputEmptyBlocks); |
| // // TODO create iterator |
| return null; |
| } |
| } |
| } |