/**
Reads the input config file created by sysstart_apparc_setup.bat and returns the
test case number (Defined in sysstart_apparc_run.bat)
@return TInt - the test case number
*/
TInt CSysStartApparcTestCase::ReadConfigFileL()
{
RFs fs;
User::LeaveIfError(fs.Connect());
CleanupClosePushL(fs);
RFileReadStream reader;
User::LeaveIfError(reader.Open(fs, KApparcConfigFile, EFileRead));
CleanupClosePushL(reader);
TChar delimChar('=');
TBuf8<255> aDes;
reader.ReadL(aDes, delimChar);
//Read in a two character representation of a number and convert to an integer
TChar result1(reader.ReadInt8L());
TChar result0(reader.ReadInt8L());
TInt aTestCase = result1.GetNumericValue()*10 + result0.GetNumericValue();
// clean-up
CleanupStack::PopAndDestroy(2, &fs);
return aTestCase;
}
static void test_type2index_list()
{
Tensor<float, 5> tensor(2,3,5,7,11);
tensor.setRandom();
tensor += tensor.constant(10.0f);
typedef Eigen::IndexList<Eigen::type2index<0>> Dims0;
typedef Eigen::IndexList<Eigen::type2index<0>, Eigen::type2index<1>> Dims1;
typedef Eigen::IndexList<Eigen::type2index<0>, Eigen::type2index<1>, Eigen::type2index<2>> Dims2;
typedef Eigen::IndexList<Eigen::type2index<0>, Eigen::type2index<1>, Eigen::type2index<2>, Eigen::type2index<3>> Dims3;
typedef Eigen::IndexList<Eigen::type2index<0>, Eigen::type2index<1>, Eigen::type2index<2>, Eigen::type2index<3>, Eigen::type2index<4>> Dims4;
#if 0
EIGEN_STATIC_ASSERT((internal::indices_statically_known_to_increase<Dims0>()() == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
EIGEN_STATIC_ASSERT((internal::indices_statically_known_to_increase<Dims1>()() == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
EIGEN_STATIC_ASSERT((internal::indices_statically_known_to_increase<Dims2>()() == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
EIGEN_STATIC_ASSERT((internal::indices_statically_known_to_increase<Dims3>()() == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
EIGEN_STATIC_ASSERT((internal::indices_statically_known_to_increase<Dims4>()() == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
#endif
EIGEN_STATIC_ASSERT((internal::are_inner_most_dims<Dims0, 1, ColMajor>::value == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
EIGEN_STATIC_ASSERT((internal::are_inner_most_dims<Dims1, 2, ColMajor>::value == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
EIGEN_STATIC_ASSERT((internal::are_inner_most_dims<Dims2, 3, ColMajor>::value == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
EIGEN_STATIC_ASSERT((internal::are_inner_most_dims<Dims3, 4, ColMajor>::value == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
EIGEN_STATIC_ASSERT((internal::are_inner_most_dims<Dims4, 5, ColMajor>::value == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
EIGEN_STATIC_ASSERT((internal::are_inner_most_dims<Dims0, 1, RowMajor>::value == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
EIGEN_STATIC_ASSERT((internal::are_inner_most_dims<Dims1, 2, RowMajor>::value == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
EIGEN_STATIC_ASSERT((internal::are_inner_most_dims<Dims2, 3, RowMajor>::value == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
EIGEN_STATIC_ASSERT((internal::are_inner_most_dims<Dims3, 4, RowMajor>::value == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
EIGEN_STATIC_ASSERT((internal::are_inner_most_dims<Dims4, 5, RowMajor>::value == true), YOU_MADE_A_PROGRAMMING_MISTAKE);
const Dims0 reduction_axis0;
Tensor<float, 4> result0 = tensor.sum(reduction_axis0);
for (int m = 0; m < 11; ++m) {
for (int l = 0; l < 7; ++l) {
for (int k = 0; k < 5; ++k) {
for (int j = 0; j < 3; ++j) {
float expected = 0.0f;
for (int i = 0; i < 2; ++i) {
expected += tensor(i,j,k,l,m);
}
VERIFY_IS_APPROX(result0(j,k,l,m), expected);
}
}
}
}
const Dims1 reduction_axis1;
Tensor<float, 3> result1 = tensor.sum(reduction_axis1);
for (int m = 0; m < 11; ++m) {
for (int l = 0; l < 7; ++l) {
for (int k = 0; k < 5; ++k) {
float expected = 0.0f;
for (int j = 0; j < 3; ++j) {
for (int i = 0; i < 2; ++i) {
expected += tensor(i,j,k,l,m);
}
}
VERIFY_IS_APPROX(result1(k,l,m), expected);
}
}
}
const Dims2 reduction_axis2;
Tensor<float, 2> result2 = tensor.sum(reduction_axis2);
for (int m = 0; m < 11; ++m) {
for (int l = 0; l < 7; ++l) {
float expected = 0.0f;
for (int k = 0; k < 5; ++k) {
for (int j = 0; j < 3; ++j) {
for (int i = 0; i < 2; ++i) {
expected += tensor(i,j,k,l,m);
}
}
}
VERIFY_IS_APPROX(result2(l,m), expected);
}
}
const Dims3 reduction_axis3;
Tensor<float, 1> result3 = tensor.sum(reduction_axis3);
for (int m = 0; m < 11; ++m) {
float expected = 0.0f;
for (int l = 0; l < 7; ++l) {
for (int k = 0; k < 5; ++k) {
for (int j = 0; j < 3; ++j) {
for (int i = 0; i < 2; ++i) {
expected += tensor(i,j,k,l,m);
}
}
}
}
VERIFY_IS_APPROX(result3(m), expected);
}
const Dims4 reduction_axis4;
Tensor<float, 0> result4 = tensor.sum(reduction_axis4);
float expected = 0.0f;
for (int m = 0; m < 11; ++m) {
for (int l = 0; l < 7; ++l) {
for (int k = 0; k < 5; ++k) {
for (int j = 0; j < 3; ++j) {
for (int i = 0; i < 2; ++i) {
expected += tensor(i,j,k,l,m);
}
}
}
}
}
VERIFY_IS_APPROX(result4(), expected);
}