typedef cub::BlockReduce<DataMaxSum, BLOCK_DIM> BlockReduce; __shared__ typename BlockReduce::TempStorage temp_storage; __shared__ DataMaxSum dms_total; DataMaxSum dms_block = BlockReduce(temp_storage).Reduce(dms_partial, reduce_dms_op); if (threadIdx.x == 0) { // must set threadIdx...
(dms_partial, dms_input); // reduce the data to one block } } typedef cub::BlockReduce<DataMaxSum, BLOCK_DIM> BlockReduce; __shared__ typename BlockReduce::TempStorage temp_storage; __shared__ DataMaxSum dms_total; DataMaxSum dms_block = BlockReduce(temp_storage).Reduce(dms_partial, ...
using Eigen::Matrix, Eigen::Dynamic; typedef Matrix<std::complex<double>, Eigen::Dynamic, Eigen::Dynamic> myMatrix; class MyClass { int N; double a; double b; public: Eigen::VectorXd v_data; Eigen::VectorXd v_gamma; MyClass(){} MyClass( double a_in, double b_in, int N_in) {...
using Eigen::Matrix, Eigen::Dynamic; typedef Matrix<std::complex<double>, Eigen::Dynamic, Eigen::Dynamic> myMatrix; class MyClass { int N; double a; double b; public: Eigen::VectorXd v_data; Eigen::VectorXd v_gamma; MyClass(){} MyClass( double a_in, double b_in, int N_in) {...
typedef typename py::array_t<double, py::array::c_style | py::array::forcecast> py_cdarray_t; // py_cd_array_t _test() std::unique_ptr<py_cdarray_t> _test() { double * memory = new double[3]; memory[0] = 11; memory[1] = 12; memory[2] = 13; ...
typedef op_impl<id, ot, Base, L_type, R_type> op; cl.def(op::name(), &op::execute_cast, is_operator(), extra...); } }; #define PYBIND11_BINARY_OPERATOR(id, rid, op, expr) \ template <typename B, typename L, typename R> struct op_impl<op_##id, op_l, B, L, R> ...
For example replacing 7 // all occurrences of "Eigen::MatrixXd" with "MatD", with the following definition: 8 // 9 // typedef Eigen::Matrix<double, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor> MatD; 10 11 Eigen::MatrixXd inv(const Eigen::MatrixXd &xs) 12 { 13 return xs....
在构造每个张量时,我将读取表示维数std::vector<double> values (r times)张量的数据向量。/Tensor> typedefEigen::Tensor< double , 4 >Tensor4d;typedefEigen::Tensor& 浏览3提问于2017-02-26得票数 6 1回答 无法返回派生类(无法转换) 我有以下派生类,它是Eigen::Tensor的子类class TensorD : publicEigen...
#include<pybind11/pybind11.h>#include<pybind11/eigen.h>#include<Eigen/LU>// N.B. this would equally work with Eigen-types that are not predefined. For example replacing// all occurrences of "Eigen::MatrixXd" with "MatD", with the following definition:/// typedef Eigen::Matrix<double, ...
typedef std::chrono::duration<uint_fast32_t, std::ratio<86400>> days; // signed 25 bits required by the standard. using days = std::chrono::duration<int_least32_t, std::ratio<86400>>; bool load(handle src, bool) { using namespace std::chrono; // Lazy initialise the PyDateTime ...