/* NiuTrans.Tensor - an open-source tensor library * Copyright (C) 2017, Natural Language Processing Lab, Northeastern 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) 2018-06-15 */ #include "../core/utilities/CheckData.h" #include "TMatrixMul2D.h" namespace nts { // namespace nts(NiuTrans.Tensor) /* case 1: matrix multiplication (for 2d tensors). In this case, a=(2, 3), b=(3, 2) -> c=(2, 2), transposedA=X_NOTRANS, transposedB=X_NOTRANS. */ bool TestMatrixMul2D1() { /* a source tensor of size (2, 3) */ int sOrder1 = 2; int * sDimSize1 = new int[sOrder1]; sDimSize1[0] = 2; sDimSize1[1] = 3; int sUnitNum1 = 1; for (int i = 0; i < sOrder1; i++) sUnitNum1 *= sDimSize1[i]; /* a source tensor of size (3, 2) */ int sOrder2 = 2; int * sDimSize2 = new int[sOrder2]; sDimSize2[0] = 3; sDimSize2[1] = 2; int sUnitNum2 = 1; for (int i = 0; i < sOrder2; i++) sUnitNum2 *= sDimSize2[i]; /* a target tensor of size (2, 2) */ int tOrder = 2; int * tDimSize = new int[tOrder]; tDimSize[0] = 2; tDimSize[1] = 2; int tUnitNum = 1; for (int i = 0; i < tOrder; i++) tUnitNum *= tDimSize[i]; DTYPE sData1[2][3] = { {1.0F, 2.0F, 3.0F}, {-4.0F, 5.0F, 6.0F} }; DTYPE sData2[3][2] = { {0.0F, -1.0F}, {1.0F, 2.0F}, {2.0F, 1.0F} }; DTYPE answer[2][2] = { {8.0F, 6.0F}, {17.0F, 20.0F} }; /* CPU test */ bool cpuTest = true; /* create tensors */ XTensor * s1 = NewTensorV2(sOrder1, sDimSize1); XTensor * s2 = NewTensorV2(sOrder2, sDimSize2); XTensor * t = NewTensorV2(tOrder, tDimSize); /* initialize variables */ s1->SetData(sData1, sUnitNum1); s2->SetData(sData2, sUnitNum2); t->SetZeroAll(); /* call MatrixMul2D function */ _MatrixMul2D(s1, X_NOTRANS, s2, X_NOTRANS, t); /* check results */ cpuTest = _CheckData(t, answer, tUnitNum, 1e-4F); #ifdef USE_CUDA /* GPU test */ bool gpuTest = true; /* create tensor */ XTensor * sGPU1 = NewTensorV2(sOrder1, sDimSize1, X_FLOAT, 1.0F, 0); XTensor * sGPU2 = NewTensorV2(sOrder2, sDimSize2, X_FLOAT, 1.0F, 0); XTensor * tGPU = NewTensorV2(tOrder, tDimSize, X_FLOAT, 1.0F, 0); /* Initialize variables */ sGPU1->SetData(sData1, sUnitNum1); sGPU2->SetData(sData2, sUnitNum2); tGPU->SetZeroAll(); /* call MatrixMul2D function */ _MatrixMul2D(sGPU1, X_NOTRANS, sGPU2, X_NOTRANS, tGPU); /* check results */ gpuTest = _CheckData(tGPU, answer, tUnitNum, 1e-4F); /* destroy variables */ delete s1; delete s2; delete t; delete sGPU1; delete sGPU2; delete tGPU; delete[] sDimSize1; delete[] sDimSize2; delete[] tDimSize; return cpuTest && gpuTest; #else /* destroy variables */ delete s1; delete s2; delete t; delete[] sDimSize1; delete[] sDimSize2; delete[] tDimSize; return cpuTest; #endif // USE_CUDA } /* case 2: matrix multiplication (for 2d tensors). In this case, a=(3, 2), b=(3, 2) -> c=(2, 2), transposedA=X_TRANS, transposedB=X_NOTRANS. */ bool TestMatrixMul2D2() { /* a source tensor of size (3, 2) */ int sOrder1 = 2; int * sDimSize1 = new int[sOrder1]; sDimSize1[0] = 3; sDimSize1[1] = 2; int sUnitNum1 = 1; for (int i = 0; i < sOrder1; i++) sUnitNum1 *= sDimSize1[i]; /* a source tensor of size (3, 2) */ int sOrder2 = 2; int * sDimSize2 = new int[sOrder2]; sDimSize2[0] = 3; sDimSize2[1] = 2; int sUnitNum2 = 1; for (int i = 0; i < sOrder2; i++) sUnitNum2 *= sDimSize2[i]; /* a target tensor of size (2, 2) */ int tOrder = 2; int * tDimSize = new int[tOrder]; tDimSize[0] = 2; tDimSize[1] = 2; int tUnitNum = 1; for (int i = 0; i < tOrder; i++) tUnitNum *= tDimSize[i]; DTYPE sData1[3][2] = { {1.0F, -4.0F}, {2.0F, 5.0F}, {3.0F, 6.0F} }; DTYPE sData2[3][2] = { {0.0F, -1.0F}, {1.0F, 2.0F}, {2.0F, 1.0F} }; DTYPE answer[2][2] = { {8.0F, 6.0F}, {17.0F, 20.0F} }; /* CPU test */ bool cpuTest = true; /* create tensors */ XTensor * s1 = NewTensorV2(sOrder1, sDimSize1); XTensor * s2 = NewTensorV2(sOrder2, sDimSize2); XTensor * t = NewTensorV2(tOrder, tDimSize); /* initialize variables */ s1->SetData(sData1, sUnitNum1); s2->SetData(sData2, sUnitNum2); t->SetZeroAll(); /* call MatrixMul2D function */ _MatrixMul2D(s1, X_TRANS, s2, X_NOTRANS, t); /* check results */ cpuTest = _CheckData(t, answer, tUnitNum, 1e-4F); #ifdef USE_CUDA /* GPU test */ bool gpuTest = true; /* create tensor */ XTensor * sGPU1 = NewTensorV2(sOrder1, sDimSize1, X_FLOAT, 1.0F, 0); XTensor * sGPU2 = NewTensorV2(sOrder2, sDimSize2, X_FLOAT, 1.0F, 0); XTensor * tGPU = NewTensorV2(tOrder, tDimSize, X_FLOAT, 1.0F, 0); /* Initialize variables */ sGPU1->SetData(sData1, sUnitNum1); sGPU2->SetData(sData2, sUnitNum2); tGPU->SetZeroAll(); /* call MatrixMul2D function */ _MatrixMul2D(sGPU1, X_TRANS, sGPU2, X_NOTRANS, tGPU); /* check results */ gpuTest = _CheckData(tGPU, answer, tUnitNum, 1e-4F); /* destroy variables */ delete s1; delete s2; delete t; delete sGPU1; delete sGPU2; delete tGPU; delete[] sDimSize1; delete[] sDimSize2; delete[] tDimSize; return cpuTest && gpuTest; #else /* destroy variables */ delete s1; delete s2; delete t; delete[] sDimSize1; delete[] sDimSize2; delete[] tDimSize; return cpuTest; #endif // USE_CUDA } /* other cases */ /* TODO!! */ /* test for MatrixMul2D Function */ bool TestMatrixMul2D() { XPRINT(0, stdout, "[TEST MATRIXMUL2D] matrix multiplication (for 2d tensors) \n"); bool returnFlag = true, caseFlag = true; /* case 1 test */ caseFlag = TestMatrixMul2D1(); if (!caseFlag) { returnFlag = false; XPRINT(0, stdout, ">> case 1 failed!\n"); } else XPRINT(0, stdout, ">> case 1 passed!\n"); /* case 2 test */ caseFlag = TestMatrixMul2D2(); if (!caseFlag) { returnFlag = false; XPRINT(0, stdout, ">> case 2 failed!\n"); } else XPRINT(0, stdout, ">> case 2 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)