Quelle cxx11_tensor_trace.cpp Sprache: C

// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2017 Gagan Goel <gagan.nith@gmail.com>
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.

#include "main.h"

#include <Eigen/CXX11/Tensor>

using Eigen::Tensor;
using Eigen::array;

template <int DataLayout>
static void test_0D_trace() {
  Tensor<float, 0, DataLayout> tensor;
  tensor.setRandom();
  array<ptrdiff_t, 0> dims;
  Tensor<float, 0, DataLayout> result = tensor.trace(dims);
  VERIFY_IS_EQUAL(result(), tensor());
}

template <int DataLayout>
static void test_all_dimensions_trace() {
  Tensor<float, 3, DataLayout> tensor1(5, 5, 5);
  tensor1.setRandom();
  Tensor<float, 0, DataLayout> result1 = tensor1.trace();
  VERIFY_IS_EQUAL(result1.rank(), 0);
  float sum = 0.0f;
  for (int i = 0; i < 5; ++i) {
    sum += tensor1(i, i, i);
  }
  VERIFY_IS_EQUAL(result1(), sum);

  Tensor<float, 5, DataLayout> tensor2(7, 7, 7, 7, 7);
  tensor2.setRandom();
  array<ptrdiff_t, 5> dims = { { 2, 1, 0, 3, 4 } };
  Tensor<float, 0, DataLayout> result2 = tensor2.trace(dims);
  VERIFY_IS_EQUAL(result2.rank(), 0);
  sum = 0.0f;
  for (int i = 0; i < 7; ++i) {
    sum += tensor2(i, i, i, i, i);
  }
  VERIFY_IS_EQUAL(result2(), sum);
}

template <int DataLayout>
static void test_simple_trace() {
  Tensor<float, 3, DataLayout> tensor1(3, 5, 3);
  tensor1.setRandom();
  array<ptrdiff_t, 2> dims1 = { { 0, 2 } };
  Tensor<float, 1, DataLayout> result1 = tensor1.trace(dims1);
  VERIFY_IS_EQUAL(result1.rank(), 1);
  VERIFY_IS_EQUAL(result1.dimension(0), 5);
  float sum = 0.0f;
  for (int i = 0; i < 5; ++i) {
    sum = 0.0f;
    for (int j = 0; j < 3; ++j) {
      sum += tensor1(j, i, j);
    }
    VERIFY_IS_EQUAL(result1(i), sum);
  }

  Tensor<float, 4, DataLayout> tensor2(5, 5, 7, 7);
  tensor2.setRandom();
  array<ptrdiff_t, 2> dims2 = { { 2, 3 } };
  Tensor<float, 2, DataLayout> result2 = tensor2.trace(dims2);
  VERIFY_IS_EQUAL(result2.rank(), 2);
  VERIFY_IS_EQUAL(result2.dimension(0), 5);
  VERIFY_IS_EQUAL(result2.dimension(1), 5);
  for (int i = 0; i < 5; ++i) {
    for (int j = 0; j < 5; ++j) {
      sum = 0.0f;
      for (int k = 0; k < 7; ++k) {
        sum += tensor2(i, j, k, k);
      }
      VERIFY_IS_EQUAL(result2(i, j), sum);
    }
  }

  array<ptrdiff_t, 2> dims3 = { { 1, 0 } };
  Tensor<float, 2, DataLayout> result3 = tensor2.trace(dims3);
  VERIFY_IS_EQUAL(result3.rank(), 2);
  VERIFY_IS_EQUAL(result3.dimension(0), 7);
  VERIFY_IS_EQUAL(result3.dimension(1), 7);
  for (int i = 0; i < 7; ++i) {
    for (int j = 0; j < 7; ++j) {
      sum = 0.0f;
      for (int k = 0; k < 5; ++k) {
        sum += tensor2(k, k, i, j);
      }
      VERIFY_IS_EQUAL(result3(i, j), sum);
    }
  }

  Tensor<float, 5, DataLayout> tensor3(3, 7, 3, 7, 3);
  tensor3.setRandom();
  array<ptrdiff_t, 3> dims4 = { { 0, 2, 4 } };
  Tensor<float, 2, DataLayout> result4 = tensor3.trace(dims4);
  VERIFY_IS_EQUAL(result4.rank(), 2);
  VERIFY_IS_EQUAL(result4.dimension(0), 7);
  VERIFY_IS_EQUAL(result4.dimension(1), 7);
  for (int i = 0; i < 7; ++i) {
    for (int j = 0; j < 7; ++j) {
      sum = 0.0f;
      for (int k = 0; k < 3; ++k) {
        sum += tensor3(k, i, k, j, k);
      }
      VERIFY_IS_EQUAL(result4(i, j), sum);
    }
  }

  Tensor<float, 5, DataLayout> tensor4(3, 7, 4, 7, 5);
  tensor4.setRandom();
  array<ptrdiff_t, 2> dims5 = { { 1, 3 } };
  Tensor<float, 3, DataLayout> result5 = tensor4.trace(dims5);
  VERIFY_IS_EQUAL(result5.rank(), 3);
  VERIFY_IS_EQUAL(result5.dimension(0), 3);
  VERIFY_IS_EQUAL(result5.dimension(1), 4);
  VERIFY_IS_EQUAL(result5.dimension(2), 5);
  for (int i = 0; i < 3; ++i) {
    for (int j = 0; j < 4; ++j) {
      for (int k = 0; k < 5; ++k) {
        sum = 0.0f;
        for (int l = 0; l < 7; ++l) {
          sum += tensor4(i, l, j, l, k);
        }
        VERIFY_IS_EQUAL(result5(i, j, k), sum);
      }
    }
  }
}

template<int DataLayout>
static void test_trace_in_expr() {
  Tensor<float, 4, DataLayout> tensor(2, 3, 5, 3);
  tensor.setRandom();
  array<ptrdiff_t, 2> dims = { { 1, 3 } };
  Tensor<float, 2, DataLayout> result(2, 5);
  result = result.constant(1.0f) - tensor.trace(dims);
  VERIFY_IS_EQUAL(result.rank(), 2);
  VERIFY_IS_EQUAL(result.dimension(0), 2);
  VERIFY_IS_EQUAL(result.dimension(1), 5);
  float sum = 0.0f;
  for (int i = 0; i < 2; ++i) {
    for (int j = 0; j < 5; ++j) {
      sum = 0.0f;
      for (int k = 0; k < 3; ++k) {
        sum += tensor(i, k, j, k);
      }
      VERIFY_IS_EQUAL(result(i, j), 1.0f - sum);
    }
  }
}

EIGEN_DECLARE_TEST(cxx11_tensor_trace) {
  CALL_SUBTEST(test_0D_trace<ColMajor>());
  CALL_SUBTEST(test_0D_trace<RowMajor>());
  CALL_SUBTEST(test_all_dimensions_trace<ColMajor>());
  CALL_SUBTEST(test_all_dimensions_trace<RowMajor>());
  CALL_SUBTEST(test_simple_trace<ColMajor>());
  CALL_SUBTEST(test_simple_trace<RowMajor>());
  CALL_SUBTEST(test_trace_in_expr<ColMajor>());
  CALL_SUBTEST(test_trace_in_expr<RowMajor>());
}

quality49%

¤ Dauer der Verarbeitung: 0.13 Sekunden (vorverarbeitet) ¤

Wurzel

Suchen

Beweissystem der NASA

Beweissystem Isabelle

NIST Cobol Testsuite

Cephes Mathematical Library

Wiener Entwicklungsmethode

Haftungshinweis

Die Informationen auf dieser Webseite wurden nach bestem Wissen sorgfältig zusammengestellt. Es wird jedoch weder Vollständigkeit, noch Richtigkeit, noch Qualität der bereit gestellten Informationen zugesichert.

Bemerkung:

Die farbliche Syntaxdarstellung ist noch experimentell.