cart-elc

Source code for CART-ELC
git clone git://git.laack.co/cart-elc.git
Log | Files | Refs | README | LICENSE

cxx11_tensor_forced_eval.cpp (2167B)


      1 // This file is part of Eigen, a lightweight C++ template library
      2 // for linear algebra.
      3 //
      4 // Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
      5 //
      6 // This Source Code Form is subject to the terms of the Mozilla
      7 // Public License v. 2.0. If a copy of the MPL was not distributed
      8 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
      9 
     10 #include "main.h"
     11 
     12 #include <Eigen/Core>
     13 #include <Eigen/CXX11/Tensor>
     14 
     15 using Eigen::MatrixXf;
     16 using Eigen::Tensor;
     17 
     18 static void test_simple()
     19 {
     20   MatrixXf m1(3,3);
     21   MatrixXf m2(3,3);
     22   m1.setRandom();
     23   m2.setRandom();
     24 
     25   TensorMap<Tensor<float, 2> > mat1(m1.data(), 3,3);
     26   TensorMap<Tensor<float, 2> > mat2(m2.data(), 3,3);
     27 
     28   Tensor<float, 2> mat3(3,3);
     29   mat3 = mat1;
     30 
     31   typedef Tensor<float, 1>::DimensionPair DimPair;
     32   Eigen::array<DimPair, 1> dims;
     33   dims[0] = DimPair(1, 0);
     34 
     35   mat3 = mat3.contract(mat2, dims).eval();
     36 
     37   VERIFY_IS_APPROX(mat3(0, 0), (m1*m2).eval()(0,0));
     38   VERIFY_IS_APPROX(mat3(0, 1), (m1*m2).eval()(0,1));
     39   VERIFY_IS_APPROX(mat3(0, 2), (m1*m2).eval()(0,2));
     40   VERIFY_IS_APPROX(mat3(1, 0), (m1*m2).eval()(1,0));
     41   VERIFY_IS_APPROX(mat3(1, 1), (m1*m2).eval()(1,1));
     42   VERIFY_IS_APPROX(mat3(1, 2), (m1*m2).eval()(1,2));
     43   VERIFY_IS_APPROX(mat3(2, 0), (m1*m2).eval()(2,0));
     44   VERIFY_IS_APPROX(mat3(2, 1), (m1*m2).eval()(2,1));
     45   VERIFY_IS_APPROX(mat3(2, 2), (m1*m2).eval()(2,2));
     46 }
     47 
     48 
     49 static void test_const()
     50 {
     51   MatrixXf input(3,3);
     52   input.setRandom();
     53   MatrixXf output = input;
     54   output.rowwise() -= input.colwise().maxCoeff();
     55 
     56   Eigen::array<int, 1> depth_dim;
     57   depth_dim[0] = 0;
     58   Tensor<float, 2>::Dimensions dims2d;
     59   dims2d[0] = 1;
     60   dims2d[1] = 3;
     61   Eigen::array<int, 2> bcast;
     62   bcast[0] = 3;
     63   bcast[1] = 1;
     64   const TensorMap<const Tensor<float, 2> > input_tensor(input.data(), 3, 3);
     65   Tensor<float, 2> output_tensor= (input_tensor - input_tensor.maximum(depth_dim).eval().reshape(dims2d).broadcast(bcast));
     66 
     67   for (int i = 0; i < 3; ++i) {
     68     for (int j = 0; j < 3; ++j) {
     69       VERIFY_IS_APPROX(output(i, j), output_tensor(i, j));
     70     }
     71   }
     72 }
     73 
     74 
     75 EIGEN_DECLARE_TEST(cxx11_tensor_forced_eval)
     76 {
     77   CALL_SUBTEST(test_simple());
     78   CALL_SUBTEST(test_const());
     79 }