代码搜索:construct
找到约 6,584 项符合「construct」的源代码
代码结果 6,584
www.eeworm.com/read/370045/2787756
txt arraydemo.txt
public class ArrayDemo {
public static void main(String[] argv) {
int ages[]; // declare a reference
ages = new int[10]; // construct it
int ages2[] = new int[10]; // short form
// an eve
www.eeworm.com/read/366702/2871612
c t128.c
// { dg-do assemble }
// GROUPS niklas uncaught default-construct
struct A { A (int); };
struct B : A {}; // { dg-error "" } without ctor // ERROR - candidates
void f () { B (0); }// { dg-error "" }
www.eeworm.com/read/366702/2873256
f90 forall_1.f90
! Program to test FORALL construct
program forall_1
call actual_variable ()
call negative_stride ()
call forall_index ()
contains
subroutine actual_variable ()
integer:: x = -1
www.eeworm.com/read/366702/2873288
f90 forall.f90
! Program to test the FORALL construct
program testforall
implicit none
integer, dimension (3, 3) :: a
integer, dimension (3) :: b
integer i
a = reshape ((/1, 2, 3, 4, 5, 6, 7, 8, 9/),
www.eeworm.com/read/366702/2883496
c barrier-2.c
/* { dg-do compile } */
void f1(void)
{
#pragma omp barrier a /* { dg-error "expected end of line" } */
}
/* OpenMP 2.5, section 2.7.3:
Note that because the barrier construct does not have a
www.eeworm.com/read/365015/2899810
txt featureselectexhaustive01.txt
Construct 15 KNN models, each with up to 4 inputs selected from 4 candidates...
modelIndex 1/15: sepal length --> Recognition rate = 58.666667%
modelIndex 2/15: sepal width --> Recognition rate =
www.eeworm.com/read/365015/2899812
txt irises01.txt
Construct 15 KNN models, each with up to 4 inputs selected from 4 candidates...
modelIndex 1/15: 1 --> Recognition rate = 58.666667%
modelIndex 2/15: 2 --> Recognition rate = 48.000000%
modelInde
www.eeworm.com/read/365015/2899813
txt featureselectexhaustive03.txt
Construct 15 KNN models, each with up to 4 inputs selected from 4 candidates...
modelIndex 1/15: sepal length --> Recognition rate = 58.666667%
modelIndex 2/15: sepal width --> Recognition rate =
www.eeworm.com/read/365015/2899820
txt random6es01.txt
Construct 63 KNN models, each with up to 6 inputs selected from 6 candidates...
modelIndex 1/63: 1 --> Recognition rate = 49.500000%
modelIndex 2/63: 2 --> Recognition rate = 49.000000%
modelInde