/* NiuTrans.Tensor - an open-source tensor library * Copyright (C) 2017, Natural Language Processing Lab, Northestern University. * All rights reserved. * * Licensed 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. */ /* * $Created by: Lin Ye (email: linye2015@outlook.com) 2018-06-13 */ #include "TSplit.h" namespace nts { // namespace nt(NiuTrans.Tensor) /* case 1: transform a tensor by splitting it, e.g., (N, M) -> (N/3, M, 3) In this case, (4, 3) -> (2, 2, 3), whereToSplit=0, splitNum=2. */ bool TestSplit1() { /* a source tensor of size (4, 3) */ int sOrder = 2; int * sDimSize = new int[sOrder]; sDimSize[0] = 4; sDimSize[1] = 3; int sUnitNum = 1; for (int i = 0; i < sOrder; i++) sUnitNum *= sDimSize[i]; /* a target tensor of size (2, 2, 3) */ int tOrder = 3; int * tDimSize = new int[tOrder]; tDimSize[0] = 2; tDimSize[1] = 2; tDimSize[2] = 3; int tUnitNum = 1; for (int i = 0; i < tOrder; i++) tUnitNum *= tDimSize[i]; DTYPE sData[4][3] = { {0.0F, 1.0F, 2.0F}, {3.0F, 4.0F, 5.0F}, {0.1F, 1.1F, 2.1F}, {3.1F, 4.1F, 5.1F} }; DTYPE answer[2][2][3] = { { {0.0F, 1.0F, 2.0F}, {3.0F, 4.0F, 5.0F} }, { {0.1F, 1.1F, 2.1F}, {3.1F, 4.1F, 5.1F} } }; /* CPU test */ bool cpuTest = true; /* create tensors */ XTensor * s = NewTensor(sOrder, sDimSize); XTensor * t = NewTensor(tOrder, tDimSize); XTensor tUser; /* initialize variables */ s->SetData(sData, sUnitNum); t->SetZeroAll(); /* call split function */ _Split(s, t, 0, 2); tUser = Split(*s, 0, 2); /* check results */ cpuTest = t->CheckData(answer, tUnitNum) && tUser.CheckData(answer, tUnitNum); #ifdef USE_CUDA /* GPU test */ bool gpuTest = true; /* create tensor */ XTensor * sGPU = NewTensor(sOrder, sDimSize, X_FLOAT, 1.0F, 0); XTensor * tGPU = NewTensor(tOrder, tDimSize, X_FLOAT, 1.0F, 0); XTensor tUserGPU; /* Initialize variables */ sGPU->SetData(sData, sUnitNum); tGPU->SetZeroAll(); /* call sum function */ _Split(sGPU, tGPU, 0, 2); tUserGPU = Split(*sGPU, 0, 2); /* check results */ gpuTest = tGPU->CheckData(answer, tUnitNum) && tUserGPU.CheckData(answer, tUnitNum); /* destroy variables */ delete s; delete t; delete sGPU; delete tGPU; delete[] sDimSize; delete[] tDimSize; return cpuTest && gpuTest; #else /* destroy variables */ delete s; delete t; delete[] sDimSize; delete[] tDimSize; return cpuTest; #endif // USE_CUDA } /* case 2: transform a tensor by splitting it, e.g., (N, M) -> (N/3, M, 3) In this case, (3, 4) -> (2, 3, 2), whereToSplit=1, splitNum=2. */ bool TestSplit2() { /* a source tensor of size (3, 4) */ int sOrder = 2; int * sDimSize = new int[sOrder]; sDimSize[0] = 3; sDimSize[1] = 4; int sUnitNum = 1; for (int i = 0; i < sOrder; i++) sUnitNum *= sDimSize[i]; /* a target tensor of size (2, 3, 2) */ int tOrder = 3; int * tDimSize = new int[tOrder]; tDimSize[0] = 2; tDimSize[1] = 3; tDimSize[2] = 2; int tUnitNum = 1; for (int i = 0; i < tOrder; i++) tUnitNum *= tDimSize[i]; DTYPE sData[3][4] = { {0.0F, 1.0F, 2.0F, 3.0F}, {4.0F, 5.0F, 0.1F, 1.1F}, {2.1F, 3.1F, 4.1F, 5.1F} }; DTYPE answer[2][3][2] = { { {0.0F, 1.0F}, {4.0F, 5.0F}, {2.1F, 3.1F} }, { {2.0F, 3.0F}, {0.1F, 1.1F}, {4.1F, 5.1F} } }; /* CPU test */ bool cpuTest = true; /* create tensors */ XTensor * s = NewTensor(sOrder, sDimSize); XTensor * t = NewTensor(tOrder, tDimSize); XTensor tUser; /* initialize variables */ s->SetData(sData, sUnitNum); t->SetZeroAll();; /* call split function */ _Split(s, t, 1, 2); tUser = Split(*s, 1, 2); /* check results */ cpuTest = t->CheckData(answer, tUnitNum) && tUser.CheckData(answer, tUnitNum); #ifdef USE_CUDA /* GPU test */ bool gpuTest = true; /* create tensor */ XTensor * sGPU = NewTensor(sOrder, sDimSize, X_FLOAT, 1.0F, 0); XTensor * tGPU = NewTensor(tOrder, tDimSize, X_FLOAT, 1.0F, 0); XTensor tUserGPU; /* Initialize variables */ sGPU->SetData(sData, sUnitNum); tGPU->SetZeroAll(); /* call sum function */ _Split(sGPU, tGPU, 1, 2); tUserGPU = Split(*sGPU, 1, 2); /* check results */ gpuTest = tGPU->CheckData(answer, tUnitNum) && tUserGPU.CheckData(answer, tUnitNum); /* destroy variables */ delete s; delete t; delete sGPU; delete tGPU; delete[] sDimSize; delete[] tDimSize; return cpuTest && gpuTest; #else /* destroy variables */ delete s; delete t; delete[] sDimSize; delete[] tDimSize; return cpuTest; #endif // USE_CUDA } /* case 3: split a big tensor into small tensors In this case, (3, 4) -> 2 * (3, 2) , whereToSplit=1, splitNum=2. */ bool TestSplit3() { /* create list */ XList * tList = new XList(); XList tUserList; /* a source tensor of size (3, 4) */ int sOrder = 2; int * sDimSize = new int[sOrder]; sDimSize[0] = 3; sDimSize[1] = 4; int sUnitNum = 1; for (int i = 0; i < sOrder; i++) sUnitNum *= sDimSize[i]; /* a target tensor of size (3, 2) */ int tOrder1 = 2; int * tDimSize1 = new int[tOrder1]; tDimSize1[0] = 3; tDimSize1[1] = 2; int tUnitNum1 = 1; for (int i = 0; i < tOrder1; i++) tUnitNum1 *= tDimSize1[i]; /* a target tensor of size (3 * 2) */ int tOrder2 = 2; int * tDimSize2 = new int[tOrder2]; tDimSize2[0] = 3; tDimSize2[1] = 2; int tUnitNum2 = 1; for (int i = 0; i < tOrder2; i++) tUnitNum2 *= tDimSize2[i]; DTYPE sData[3][4] = { {0.0F, 1.0F, 2.0F, 3.0F}, {4.0F, 5.0F, 0.1F, 1.1F}, {2.1F, 3.1F, 4.1F, 5.1F} }; DTYPE answer1[3][2] = { {0.0F, 1.0F}, {4.0F, 5.0F}, {2.1F, 3.1F} }; DTYPE answer2[3][2] = { {2.0F, 3.0F}, {0.1F, 1.1F}, {4.1F, 5.1F} }; /* CPU test */ bool cpuTest = true; /* create tensors */ XTensor * s = NewTensor(sOrder, sDimSize); XTensor * t1 = NewTensor(tOrder1, tDimSize1); XTensor * t2 = NewTensor(tOrder2, tDimSize2); /* initialize variables */ s->SetData(sData, sUnitNum); t1->SetZeroAll(); t2->SetZeroAll(); /* add tensors to list */ tList->Add(t1); tList->Add(t2); /* call split function */ _Split(s, tList, 1, 2); Split(*s, tUserList, 1, 2); /* check results */ cpuTest = t1->CheckData(answer1, tUnitNum1) && ((XTensor *)tUserList.Get(0))->CheckData(answer1, tUnitNum1) && t2->CheckData(answer2, tUnitNum2) && ((XTensor *)tUserList.Get(1))->CheckData(answer2, tUnitNum2); #ifdef USE_CUDA /* GPU test */ bool gpuTest = true; /* clear list */ tList->Clear(); tUserList.Clear(); /* create tensor */ XTensor * sGPU = NewTensor(sOrder, sDimSize, X_FLOAT, 1.0F, 0); XTensor * tGPU1 = NewTensor(tOrder1, tDimSize1, X_FLOAT, 1.0F, 0); XTensor * tGPU2 = NewTensor(tOrder2, tDimSize2, X_FLOAT, 1.0F, 0); /* Initialize variables */ sGPU->SetData(sData, sUnitNum); tGPU1->SetZeroAll(); tGPU2->SetZeroAll(); /* add tensors to list */ tList->Add(tGPU1); tList->Add(tGPU2); /* call Split function */ _Split(sGPU, tList, 1, 2); Split(*sGPU, tUserList, 1, 2); /* check results */ gpuTest = tGPU1->CheckData(answer1, tUnitNum1) && ((XTensor *)tUserList.Get(0))->CheckData(answer1, tUnitNum1) && tGPU2->CheckData(answer2, tUnitNum2) && ((XTensor *)tUserList.Get(1))->CheckData(answer2, tUnitNum2); /* destroy variables */ delete s; delete t1; delete t2; delete sGPU; delete tGPU1; delete tGPU2; delete[] sDimSize; delete[] tDimSize1; delete[] tDimSize2; delete tList; return cpuTest && gpuTest; #else /* destroy variables */ delete s; delete t1; delete t2; delete[] sDimSize; delete[] tDimSize1; delete[] tDimSize2; return cpuTest; #endif // USE_CUDA } /* other cases */ /* TODO!! */ /* test for Split Function */ bool TestSplit() { XPRINT(0, stdout, "[TEST SPLIT] split a big tensor into small tensors \n"); bool returnFlag = true, caseFlag = true; /* case 1 test */ caseFlag = TestSplit1(); if (!caseFlag) { returnFlag = false; XPRINT(0, stdout, ">> case 1 failed!\n"); } else XPRINT(0, stdout, ">> case 1 passed!\n"); /* case 2 test */ caseFlag = TestSplit2(); if (!caseFlag) { returnFlag = false; XPRINT(0, stdout, ">> case 2 failed!\n"); } else XPRINT(0, stdout, ">> case 2 passed!\n"); /* case 3 test */ caseFlag = TestSplit3(); if (!caseFlag) { returnFlag = false; XPRINT(0, stdout, ">> case 3 failed!\n"); } else XPRINT(0, stdout, ">> case 3 passed!\n"); /* other cases test */ /* TODO!! */ if (returnFlag) { XPRINT(0, stdout, ">> All Passed!\n"); } else XPRINT(0, stdout, ">> Failed!\n"); XPRINT(0, stdout, "\n"); return returnFlag; } } // namespace nts(NiuTrans.Tensor)