| /* |
| * 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.util; |
| |
| import java.nio.ByteBuffer; |
| import java.nio.ByteOrder; |
| |
| import org.apache.sysds.common.Types; |
| import org.apache.sysds.runtime.DMLRuntimeException; |
| import org.apache.sysds.runtime.matrix.data.MatrixBlock; |
| |
| /** |
| * Utils for converting python data to java. |
| */ |
| public class Py4jConverterUtils { |
| public static MatrixBlock convertPy4JArrayToMB(byte[] data, int rlen, int clen) { |
| return convertPy4JArrayToMB(data, rlen, clen, false, Types.ValueType.FP64); |
| } |
| |
| public static MatrixBlock convertPy4JArrayToMB(byte[] data, int rlen, int clen, Types.ValueType valueType) { |
| return convertPy4JArrayToMB(data, rlen, clen, false, valueType); |
| } |
| |
| public static MatrixBlock convertSciPyCOOToMB(byte[] data, byte[] row, byte[] col, int rlen, int clen, int nnz) { |
| MatrixBlock mb = new MatrixBlock(rlen, clen, true); |
| mb.allocateSparseRowsBlock(false); |
| ByteBuffer buf1 = ByteBuffer.wrap(data); |
| buf1.order(ByteOrder.nativeOrder()); |
| ByteBuffer buf2 = ByteBuffer.wrap(row); |
| buf2.order(ByteOrder.nativeOrder()); |
| ByteBuffer buf3 = ByteBuffer.wrap(col); |
| buf3.order(ByteOrder.nativeOrder()); |
| for(int i = 0; i < nnz; i++) { |
| double val = buf1.getDouble(); |
| int rowIndex = buf2.getInt(); |
| int colIndex = buf3.getInt(); |
| mb.setValue(rowIndex, colIndex, val); |
| } |
| mb.recomputeNonZeros(); |
| mb.examSparsity(); |
| return mb; |
| } |
| |
| public static MatrixBlock allocateDenseOrSparse(int rlen, int clen, boolean isSparse) { |
| MatrixBlock ret = new MatrixBlock(rlen, clen, isSparse); |
| ret.allocateBlock(); |
| return ret; |
| } |
| |
| public static MatrixBlock allocateDenseOrSparse(long rlen, long clen, boolean isSparse) { |
| if(rlen > Integer.MAX_VALUE || clen > Integer.MAX_VALUE) { |
| throw new DMLRuntimeException( |
| "Dimensions of matrix are too large to be passed via NumPy/SciPy:" + rlen + " X " + clen); |
| } |
| return allocateDenseOrSparse((int) rlen, (int) clen, isSparse); |
| } |
| |
| public static MatrixBlock convertPy4JArrayToMB(byte[] data, int rlen, int clen, boolean isSparse, |
| Types.ValueType valueType) { |
| MatrixBlock mb = new MatrixBlock(rlen, clen, isSparse, -1); |
| if(isSparse) { |
| throw new DMLRuntimeException("Convertion to sparse format not supported"); |
| } |
| else { |
| long limit = (long) rlen * clen; |
| if(limit > Integer.MAX_VALUE) |
| throw new DMLRuntimeException( |
| "Dense NumPy array of size " + limit + " cannot be converted to MatrixBlock"); |
| double[] denseBlock = new double[(int) limit]; |
| ByteBuffer buf = ByteBuffer.wrap(data); |
| buf.order(ByteOrder.nativeOrder()); |
| switch(valueType) { |
| case INT32: |
| for(int i = 0; i < rlen * clen; i++) |
| denseBlock[i] = buf.getInt(); |
| break; |
| case FP32: |
| for(int i = 0; i < rlen * clen; i++) |
| denseBlock[i] = buf.getFloat(); |
| break; |
| case FP64: |
| for(int i = 0; i < rlen * clen; i++) |
| denseBlock[i] = buf.getDouble(); |
| break; |
| default: |
| throw new DMLRuntimeException("Unsupported value type: " + valueType.name()); |
| } |
| mb.init(denseBlock, rlen, clen); |
| } |
| mb.recomputeNonZeros(); |
| mb.examSparsity(); |
| return mb; |
| } |
| |
| public static byte[] convertMBtoPy4JDenseArr(MatrixBlock mb) { |
| byte[] ret = null; |
| if(mb.isInSparseFormat()) { |
| mb.sparseToDense(); |
| } |
| |
| long limit = mb.getNumRows() * mb.getNumColumns(); |
| int times = Double.SIZE / Byte.SIZE; |
| if(limit > Integer.MAX_VALUE / times) |
| throw new DMLRuntimeException("MatrixBlock of size " + limit + " cannot be converted to dense numpy array"); |
| ret = new byte[(int) (limit * times)]; |
| |
| double[] denseBlock = mb.getDenseBlockValues(); |
| if(mb.isEmptyBlock()) { |
| for(int i = 0; i < limit; i++) { |
| ByteBuffer.wrap(ret, i * times, times).order(ByteOrder.nativeOrder()).putDouble(0); |
| } |
| } |
| else if(denseBlock == null) { |
| throw new DMLRuntimeException("Error while dealing with empty blocks."); |
| } |
| else { |
| for(int i = 0; i < denseBlock.length; i++) { |
| ByteBuffer.wrap(ret, i * times, times).order(ByteOrder.nativeOrder()).putDouble(denseBlock[i]); |
| } |
| } |
| |
| return ret; |
| } |
| } |