/* 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: Xu Chen (email: hello_master1954@163.com) 2018-07-06 */ #include "TSetData.h" #include "../core/getandset/SetData.h" namespace nts { // namespace nts(NiuTrans.Tensor) /* case 1: test SetDataRand function. set the tensor items by a uniform distribution in range [lower, upper]. */ bool TestSetData1() { /* a input tensor of size (2, 4) */ int sOrder = 2; int * sDimSize = new int[sOrder]; sDimSize[0] = 2; sDimSize[1] = 4; int sUnitNum = 1; for (int i = 0; i < sOrder; i++) sUnitNum *= sDimSize[i]; DTYPE answer[2][4] = {0}; /* CPU test */ bool cpuTest = true; /* create tensors */ XTensor * s = NewTensor(sOrder, sDimSize); /* call SetDataRand function */ s->SetDataRand(0.0, 1.0); /* check results */ cpuTest = s->CheckData(answer, sUnitNum, 1.0F); #ifdef USE_CUDA /* GPU test */ bool gpuTest = true; /* create tensors */ XTensor * sGPU = NewTensor(sOrder, sDimSize, X_FLOAT, 1.0F, 0); /* call SetDataRand function */ sGPU->SetDataRand(0.0, 1.0); gpuTest = sGPU->CheckData(answer, sUnitNum, 1.0F); /* destroy variables */ delete s; delete sGPU; delete[] sDimSize; return cpuTest && gpuTest; #else /* destroy variables */ delete s; delete[] sDimSize; return cpuTest; #endif // USE_CUDA } /* case 2: test SetDataIndexed function. modify data items along with a given dimension. */ bool TestSetData2() { /* a input tensor of size (2, 4) */ int sOrder = 2; int * sDimSize = new int[sOrder]; sDimSize[0] = 2; sDimSize[1] = 4; int sUnitNum = 1; for (int i = 0; i < sOrder; i++) sUnitNum *= sDimSize[i]; /* a data tensor of size (4) for GPU test */ int dataOrder = 1; int * dataDimSize = new int[dataOrder]; dataDimSize[0] = 4; int dataUnitNum = 1; for (int i = 0; i < dataOrder; i++) dataUnitNum *= dataDimSize[i]; DTYPE data[4] = {0.0F, 1.0F, 2.0F, 3.0F}; DTYPE answer[2][4] = { {1.0F, 1.0F, 1.0F, 1.0F}, {0.0F, 1.0F, 2.0F, 3.0F} }; /* CPU test */ bool cpuTest = true; /* create tensors */ XTensor * s = NewTensor(sOrder, sDimSize); XTensor * modify = NewTensor(dataOrder, dataDimSize); /* Initialize variables */ _SetDataFixedFloat(s, 1.0F); modify->SetData(data, dataUnitNum); /* call SetDataIndexed function */ _SetDataIndexed(s, modify, 0, 1); /* check results */ cpuTest = s->CheckData(answer, sUnitNum, 1e-5F); #ifdef USE_CUDA /* GPU test */ bool gpuTest = true; /* create tensors */ XTensor * sGPU = NewTensor(sOrder, sDimSize, X_FLOAT, 1.0F, 0); XTensor * modifyGPU = NewTensor(dataOrder, dataDimSize, X_FLOAT, 1.0F, 0); /* Initialize variables */ _SetDataFixedFloat(sGPU, 1.0F); modifyGPU->SetData(data, dataUnitNum); /* call SetDataIndexed function */ _SetDataIndexed(sGPU, modifyGPU, 0, 1); gpuTest = sGPU->CheckData(answer, sUnitNum, 1e-5F); /* destroy variables */ delete s; delete modify; delete sGPU; delete modifyGPU; delete[] sDimSize; delete[] dataDimSize; return cpuTest && gpuTest; #else /* destroy variables */ delete s; delete modify; delete[] sDimSize; delete[] dataDimSize; return cpuTest; #endif // USE_CUDA } /* case 3: test SetDataIndexed function. modify data items along with a given dimension. */ bool TestSetData3() { /* a input tensor of size (2, 4, 3) */ int sOrder = 3; int * sDimSize = new int[sOrder]; sDimSize[0] = 2; sDimSize[1] = 4; sDimSize[2] = 3; int sUnitNum = 1; for (int i = 0; i < sOrder; i++) sUnitNum *= sDimSize[i]; /* a data tensor of size (2, 3) for GPU test */ int dataOrder = 2; int * dataDimSize = new int[dataOrder]; dataDimSize[0] = 2; dataDimSize[1] = 3; int dataUnitNum = 1; for (int i = 0; i < dataOrder; i++) dataUnitNum *= dataDimSize[i]; DTYPE data[2][3] = { {0.0F, 1.0F, 2.0F}, {3.0F, 4.0F, 5.0F} }; DTYPE answer[2][4][3] = { { {1.0F, 1.0F, 1.0F}, {0.0F, 1.0F, 2.0F}, {1.0F, 1.0F, 1.0F}, {1.0F, 1.0F, 1.0F} }, { {1.0F, 1.0F, 1.0F}, {3.0F, 4.0F, 5.0F}, {1.0F, 1.0F, 1.0F}, {1.0F, 1.0F, 1.0F} } }; /* CPU test */ bool cpuTest = true; /* create tensors */ XTensor * s = NewTensor(sOrder, sDimSize); XTensor * modify = NewTensor(dataOrder, dataDimSize); /* Initialize variables */ _SetDataFixedFloat(s, 1.0F); modify->SetData(data, dataUnitNum); /* call SetDataIndexed function */ _SetDataFixedFloat(s, 1.0F); _SetDataIndexed(s, modify, 1, 1); /* check results */ cpuTest = s->CheckData(answer, sUnitNum, 1e-5F); #ifdef USE_CUDA /* GPU test */ bool gpuTest = true; /* create tensors */ XTensor * sGPU = NewTensor(sOrder, sDimSize, X_FLOAT, 1.0F, 0); XTensor * modifyGPU = NewTensor(dataOrder, dataDimSize, X_FLOAT, 1.0F, 0); /* Initialize variables */ _SetDataFixedFloat(sGPU, 1.0F); modifyGPU->SetData(data, dataUnitNum); /* call SetDataIndexed function */ _SetDataIndexed(sGPU, modifyGPU, 1, 1); gpuTest = sGPU->CheckData(answer, sUnitNum, 1e-5F); /* destroy variables */ delete s; delete modify; delete sGPU; delete modifyGPU; delete[] sDimSize; delete[] dataDimSize; return cpuTest && gpuTest; #else /* destroy variables */ delete s; delete modify; delete[] sDimSize; delete[] dataDimSize; return cpuTest; #endif // USE_CUDA } /* case 4: test SetDataDim function. set data items along with a given dimension (and keep the remaining items unchanged) */ bool TestSetData4() { /* a input tensor of size (3, 3) */ int order = 2; int * dimSize = new int[order]; dimSize[0] = 3; dimSize[1] = 3; int unitNum = 1; for (int i = 0; i < order; i++) unitNum *= dimSize[i]; DTYPE sData[3][3] = { {1.0F, 2.0F, 3.0F}, {4.0F, 5.0F, 6.0F}, {7.0F, 8.0F, 9.0F} }; DTYPE answer[3][3] = { {1.0F, 2.0F, 3.0F}, {0.0F, 0.0F, 0.0F}, {7.0F, 8.0F, 9.0F} }; /* CPU test */ bool cpuTest = true; /* create tensors */ XTensor * s = NewTensor(order, dimSize); /* initialize variables */ s->SetData(sData, unitNum); /* call _SetDataDim function */ _SetDataDim(s, 1, 1, 0, 0); /* check results */ cpuTest = s->CheckData(answer, unitNum, 1e-4F); #ifdef USE_CUDA /* GPU test */ bool gpuTest = true; /* create tensors */ XTensor * sGPU = NewTensor(order, dimSize, X_FLOAT, 1.0F, 0); /* initialize variables */ sGPU->SetData(sData, unitNum); /* call _SetDataDim function */ _SetDataDim(sGPU, 1, 1, 0, 0); gpuTest = sGPU->CheckData(answer, unitNum, 1e-4F); /* destroy variables */ delete s; delete sGPU; delete[] dimSize; return cpuTest && gpuTest; #else /* destroy variables */ delete s; delete[] dimSize; return cpuTest; #endif // USE_CUDA } /* case 5: test SetDataDim function. set data items along with a given dimension (and keep the remaining items unchanged) */ bool TestSetData5() { /* a input tensor of size (2, 4, 3) */ int order = 3; int * dimSize = new int[order]; dimSize[0] = 2; dimSize[1] = 4; dimSize[2] = 3; int unitNum = 1; for (int i = 0; i < order; i++) unitNum *= dimSize[i]; DTYPE data[2][4][3] = { { {1.0F, 1.0F, 1.0F}, {0.0F, 1.0F, 2.0F}, {1.0F, 1.0F, 1.0F}, {1.0F, 1.0F, 1.0F} }, { {1.0F, 1.0F, 1.0F}, {3.0F, 4.0F, 5.0F}, {1.0F, 1.0F, 1.0F}, {1.0F, 1.0F, 1.0F} } }; DTYPE answer[2][4][3] = { { {1.0F, 1.0F, 1.0F}, {0.0F, 1.0F, 2.0F}, {5.0F, 5.0F, 5.0F}, {1.0F, 1.0F, 1.0F} }, { {1.0F, 1.0F, 1.0F}, {3.0F, 4.0F, 5.0F}, {5.0F, 5.0F, 5.0F}, {1.0F, 1.0F, 1.0F} } }; /* CPU test */ bool cpuTest = true; /* create tensors */ XTensor * s = NewTensor(order, dimSize); /* initialize variables */ s->SetData(data, unitNum); /* call _SetDataDim function */ _SetDataDim(s, 2, 1, 1, 5.0F); /* check results */ cpuTest = s->CheckData(answer, unitNum, 1e-4F); #ifdef USE_CUDA /* GPU test */ bool gpuTest = true; /* create tensors */ XTensor * sGPU = NewTensor(order, dimSize, X_FLOAT, 1.0F, 0); /* initialize variables */ sGPU->SetData(data, unitNum); /* call _SetDataDim function */ _SetDataDim(sGPU, 2, 1, 1, 5.0F); gpuTest = sGPU->CheckData(answer, unitNum, 1e-4F); /* destroy variables */ delete s; delete sGPU; delete[] dimSize; return cpuTest && gpuTest; #else /* destroy variables */ delete s; delete[] dimSize; return cpuTest; #endif // USE_CUDA } /* other cases */ /* TODO!! */ /* test for SetData Function */ bool TestSetData() { XPRINT(0, stdout, "[TEST SetData] set the data of tensor \n"); bool returnFlag = true, caseFlag = true; /* case 1 test */ caseFlag = TestSetData1(); if (!caseFlag) { returnFlag = false; XPRINT(0, stdout, ">> case 1 failed!\n"); } else XPRINT(0, stdout, ">> case 1 passed!\n"); /* case 2 test */ caseFlag = TestSetData2(); if (!caseFlag) { returnFlag = false; XPRINT(0, stdout, ">> case 2 failed!\n"); } else XPRINT(0, stdout, ">> case 2 passed!\n"); /* case 3 test */ caseFlag = TestSetData3(); if (!caseFlag) { returnFlag = false; XPRINT(0, stdout, ">> case 3 failed!\n"); } else XPRINT(0, stdout, ">> case 3 passed!\n"); /* case 4 test */ caseFlag = TestSetData4(); if (!caseFlag) { returnFlag = false; XPRINT(0, stdout, ">> case 4 failed!\n"); } else XPRINT(0, stdout, ">> case 4 passed!\n"); /* case 5 test */ caseFlag = TestSetData5(); if (!caseFlag) { returnFlag = false; XPRINT(0, stdout, ">> case 5 failed!\n"); } else XPRINT(0, stdout, ">> case 5 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)