Armadillo静态链接

Question

我曾尝试静态地将armadillo库链接到VisualStudio2017 for C++，应用以下步骤，但没有效果。为x64设置了平台

1. C/C++ ->通用->附加包含目录-> $(SolutionDir)依赖\包括
2. 在源文件中写入#include "armadillo" (也包括< armadillo >)。
3. 链接器->输入->附加依赖项-> blas_win64_MT.lib；lapack_win64_MT.lib
4. 链接器->通用->附加库目录-> $(SolutionDir)Dependencies\lib_win64

注意：

armadillo_bits包含是步骤1中包含、armadillo、和文件夹的文件夹的名称。 blas_win64_MT.lib lib_win64是步骤4中具有和lapack_win64_MT.lib的文件夹的名称。

。

当我试图编译时，会遇到以下错误：

c:........\dependencies\include\armadillo_bits\arma_rng.hpp(444)：error C2760:语法错误:意外令牌“标识符”，“预期”； c:........\dependencies\include\armadillo_bits\arma_rng.hpp(524)：注意:参见对正在编译的类模板实例化'arma::arma_rng::randn<std::complex<_Other>>‘的引用

。

arma_rng.hpp的代码，直接来源于armadillo库代码。

template<typename T>
struct arma_rng::randn < std::complex<T> > 
  {
  inline
  operator std::complex<T> () const
    {
    T a, b; //************line 444***************

    arma_rng::randn<T>::dual_val(a, b);

    return std::complex<T>(a, b);
    }


  inline
  static
  void
  fill(std::complex<T>* mem, const uword N)
    {
    ...

  }; //************line 524***************

。

这是一个直接来自armadillo示例的代码，用于测试我是否正确地链接了armadillo，目前还没有实现任何头文件：

#include <iostream>
#include <armadillo>

using namespace std;
using namespace arma;

// Armadillo documentation is available at:
// http://arma.sourceforge.net/docs.html

int
main(int argc, char** argv)
  {
  cout << "Armadillo version: " << arma_version::as_string() << endl;

  mat A(2,3);  // directly specify the matrix size (elements are uninitialised)

  cout << "A.n_rows: " << A.n_rows << endl;  // .n_rows and .n_cols are read only
  cout << "A.n_cols: " << A.n_cols << endl;

  A(1,2) = 456.0;  // directly access an element (indexing starts at 0)
  A.print("A:");

  A = 5.0;         // scalars are treated as a 1x1 matrix
  A.print("A:");

  A.set_size(4,5); // change the size (data is not preserved)

  A.fill(5.0);     // set all elements to a particular value
  A.print("A:");

  // endr indicates "end of row"
  A << 0.165300 << 0.454037 << 0.995795 << 0.124098 << 0.047084 << endr
    << 0.688782 << 0.036549 << 0.552848 << 0.937664 << 0.866401 << endr
    << 0.348740 << 0.479388 << 0.506228 << 0.145673 << 0.491547 << endr
    << 0.148678 << 0.682258 << 0.571154 << 0.874724 << 0.444632 << endr
    << 0.245726 << 0.595218 << 0.409327 << 0.367827 << 0.385736 << endr;

  A.print("A:");

  // determinant
  cout << "det(A): " << det(A) << endl;

  // inverse
  cout << "inv(A): " << endl << inv(A) << endl;

  // save matrix as a text file
  A.save("A.txt", raw_ascii);

  // load from file
  mat B;
  B.load("A.txt");

  // submatrices
  cout << "B( span(0,2), span(3,4) ):" << endl << B( span(0,2), span(3,4) ) << endl;

  cout << "B( 0,3, size(3,2) ):" << endl << B( 0,3, size(3,2) ) << endl;

  cout << "B.row(0): " << endl << B.row(0) << endl;

  cout << "B.col(1): " << endl << B.col(1) << endl;

  // transpose
  cout << "B.t(): " << endl << B.t() << endl;

  // maximum from each column (traverse along rows)
  cout << "max(B): " << endl << max(B) << endl;

  // maximum from each row (traverse along columns)
  cout << "max(B,1): " << endl << max(B,1) << endl;

  // maximum value in B
  cout << "max(max(B)) = " << max(max(B)) << endl;

  // sum of each column (traverse along rows)
  cout << "sum(B): " << endl << sum(B) << endl;

  // sum of each row (traverse along columns)
  cout << "sum(B,1) =" << endl << sum(B,1) << endl;

  // sum of all elements
  cout << "accu(B): " << accu(B) << endl;

  // trace = sum along diagonal
  cout << "trace(B): " << trace(B) << endl;

  // generate the identity matrix
  mat C = eye<mat>(4,4);

  // random matrix with values uniformly distributed in the [0,1] interval
  mat D = randu<mat>(4,4);
  D.print("D:");

  // row vectors are treated like a matrix with one row
  rowvec r;
  r << 0.59119 << 0.77321 << 0.60275 << 0.35887 << 0.51683;
  r.print("r:");

  // column vectors are treated like a matrix with one column
  vec q;
  q << 0.14333 << 0.59478 << 0.14481 << 0.58558 << 0.60809;
  q.print("q:");

  // convert matrix to vector; data in matrices is stored column-by-column
  vec v = vectorise(A);
  v.print("v:");

  // dot or inner product
  cout << "as_scalar(r*q): " << as_scalar(r*q) << endl;

  // outer product
  cout << "q*r: " << endl << q*r << endl;

  // multiply-and-accumulate operation (no temporary matrices are created)
  cout << "accu(A % B) = " << accu(A % B) << endl;

  // example of a compound operation
  B += 2.0 * A.t();
  B.print("B:");

  // imat specifies an integer matrix
  imat AA;
  imat BB;

  AA << 1 << 2 << 3 << endr << 4 << 5 << 6 << endr << 7 << 8 << 9;
  BB << 3 << 2 << 1 << endr << 6 << 5 << 4 << endr << 9 << 8 << 7;

  // comparison of matrices (element-wise); output of a relational operator is a umat
  umat ZZ = (AA >= BB);
  ZZ.print("ZZ:");

  // cubes ("3D matrices")
  cube Q( B.n_rows, B.n_cols, 2 );

  Q.slice(0) = B;
  Q.slice(1) = 2.0 * B;

  Q.print("Q:");

  // 2D field of matrices; 3D fields are also supported
  field<mat> F(4,3); 

  for(uword col=0; col < F.n_cols; ++col)
  for(uword row=0; row < F.n_rows; ++row)
    {
    F(row,col) = randu<mat>(2,3);  // each element in field<mat> is a matrix
    }

  F.print("F:");

  return 0;
  }

。

Answer 1

请将VS2017平台工具集更改为v140而不是v141。然后编译，它必须工作。

Answer 2

对于面临同样问题的其他人，使用VC++ 2015.3 v140 toolset可以将OpenBLAS和armadillo编译为静态库。

以下是Visual 2017 (VS2017)所需的步骤：

• 如果需要，请安装v140工具集：
  • 修改VS2017安装(即详细信息这里)
  • 检查桌面开发框
  • 在右侧，在汇总下单击桌面开发和C++
  • 在列表的底部，检查VC++ 2015.3 v140桌面工具集(x86，x64)

​

• 接下来，您需要告诉编译器使用v140而不是v141，因此：
  • 右键单击VS2017中的项目名称
  • 转到Configuration Properties→General→Platform Toolset
  • 选择Visual 2015 (v140)

​

现在，您应该能够对代码进行#include <armadillo>和编译。

备注：

• 您仍然需要确保设置正确的包含路径(即，如果您通过Nuget Package Manager安装了，那么按照上面指出的步骤就可以了)

希望这能有所帮助。

Answer 3

它似乎是由Visual 2017引起的一个BUG，它与一致性模式相关，最近默认启用了Visual Studio.They尝试修复它(details 这里)。

在VS2017中工作的解决方案(V141，而不是安装V140)是禁用一致性模式.You可以这样做：

• 项目属性-> C/C++ -> language ->一致性模式-> 禁用