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Disable test for 32-bit systems (e.g. ARM, i386)

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Both i386 and 32-bit ARM do not define __uint128_t. On most systems, if
__uint128_t is defined, then so is the macro __SIZEOF_INT128__.

https://stackoverflow.com/questions/18531782/how-to-know-if-uint128-t-is-defined1
This commit is contained in:
Antonio Sánchez 2020-05-28 17:40:15 +00:00 committed by Rasmus Munk Larsen
parent 8e1df5b082
commit 8719b9c5bc
5 changed files with 12 additions and 10 deletions
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2
unsupported/test/cxx11_tensor_complex_cwise_ops_gpu.cu
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@ -77,6 +77,8 @@ void test_cuda_complex_cwise_ops() {
gpu_out.device(gpu_device) = -gpu_in1; gpu_out.device(gpu_device) = -gpu_in1;
expected = -a; expected = -a;
break; break;
case NbOps:
break;
} }
assert(cudaMemcpyAsync(actual.data(), d_out, complex_bytes, cudaMemcpyDeviceToHost, assert(cudaMemcpyAsync(actual.data(), d_out, complex_bytes, cudaMemcpyDeviceToHost,
gpu_device.stream()) == cudaSuccess); gpu_device.stream()) == cudaSuccess);

8
unsupported/test/cxx11_tensor_fft.cpp
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@ -228,10 +228,10 @@ template <typename RealScalar>
static void test_fft_non_power_of_2_round_trip(int exponent) { static void test_fft_non_power_of_2_round_trip(int exponent) {
int n = (1 << exponent) + 1; int n = (1 << exponent) + 1;
Eigen::DSizes<std::int64_t, 1> dimensions; Eigen::DSizes<ptrdiff_t, 1> dimensions;
dimensions[0] = n; dimensions[0] = n;
const DSizes<std::int64_t, 1> arr = dimensions; const DSizes<ptrdiff_t, 1> arr = dimensions;
Tensor<RealScalar, 1, ColMajor, std::int64_t> input; Tensor<RealScalar, 1, ColMajor, ptrdiff_t> input;
input.resize(arr); input.resize(arr);
input.setRandom(); input.setRandom();
@ -242,7 +242,7 @@ static void test_fft_non_power_of_2_round_trip(int exponent) {
Tensor<std::complex<RealScalar>, 1, ColMajor> forward = Tensor<std::complex<RealScalar>, 1, ColMajor> forward =
input.template fft<BothParts, FFT_FORWARD>(fft); input.template fft<BothParts, FFT_FORWARD>(fft);
Tensor<RealScalar, 1, ColMajor, std::int64_t> output = Tensor<RealScalar, 1, ColMajor, ptrdiff_t> output =
forward.template fft<RealPart, FFT_REVERSE>(fft); forward.template fft<RealPart, FFT_REVERSE>(fft);
for (int i = 0; i < n; ++i) { for (int i = 0; i < n; ++i) {

2
unsupported/test/cxx11_tensor_morphing.cpp
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@ -51,7 +51,7 @@ static void test_static_reshape() {
// New dimensions: [2, 3, 7] // New dimensions: [2, 3, 7]
Eigen::IndexList<type2index<2>, type2index<3>, type2index<7>> dim; Eigen::IndexList<type2index<2>, type2index<3>, type2index<7>> dim;
Tensor<float, 3> reshaped = tensor.reshape(static_cast<Eigen::DSizes<long,3>>(dim)); Tensor<float, 3> reshaped = tensor.reshape(static_cast<Eigen::DSizes<ptrdiff_t,3>>(dim));
for (int i = 0; i < 2; ++i) { for (int i = 0; i < 2; ++i) {

2
unsupported/test/cxx11_tensor_of_float16_gpu.cu
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@ -346,7 +346,7 @@ void test_gpu_reductions(int size1, int size2, int redux) {
gpu_float1.device(gpu_device) = gpu_float1.random() * 2.0f; gpu_float1.device(gpu_device) = gpu_float1.random() * 2.0f;
gpu_float2.device(gpu_device) = gpu_float2.random() * 2.0f; gpu_float2.device(gpu_device) = gpu_float2.random() * 2.0f;
Eigen::array<int, 1> redux_dim = {{redux}}; Eigen::array<int, 1> redux_dim = {redux};
gpu_res_float.device(gpu_device) = gpu_float1.sum(redux_dim).cast<Eigen::half>(); gpu_res_float.device(gpu_device) = gpu_float1.sum(redux_dim).cast<Eigen::half>();
gpu_res_half.device(gpu_device) = gpu_float1.cast<Eigen::half>().sum(redux_dim); gpu_res_half.device(gpu_device) = gpu_float1.cast<Eigen::half>().sum(redux_dim);

2
unsupported/test/cxx11_tensor_uint128.cpp
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@ -12,7 +12,7 @@
#include <Eigen/CXX11/Tensor> #include <Eigen/CXX11/Tensor>
#if EIGEN_COMP_MSVC #if EIGEN_COMP_MSVC || !defined(__SIZEOF_INT128__)
#define EIGEN_NO_INT128 #define EIGEN_NO_INT128
#else #else
typedef __uint128_t uint128_t; typedef __uint128_t uint128_t;