devtools/eigen
1
0
Fork 0
mirror of https://gitlab.com/libeigen/eigen.git synced 2026-04-10 11:34:33 +08:00
Code Issues Packages Projects Releases Wiki Activity

Clang-format tests, examples, libraries, benchmarks, etc.

Browse Source
This commit is contained in:
Antonio Sánchez
2023-12-05 21:22:55 +00:00
committed by Rasmus Munk Larsen
parent 3252ecc7a4
commit 46e9cdb7fe
876 changed files with 33453 additions and 37795 deletions
Download Patch File Download Diff File Expand all files Collapse all files

36
unsupported/test/cxx11_tensor_complex_gpu.cu
View File

@@ -37,12 +37,9 @@ void test_cuda_nullary() {
Eigen::GpuStreamDevice stream;
Eigen::GpuDevice gpu_device(&stream);
Eigen::TensorMap<Eigen::Tensor<std::complex<float>, 1, 0, int>, Eigen::Aligned> gpu_in1(
d_in1, 2);
Eigen::TensorMap<Eigen::Tensor<std::complex<float>, 1, 0, int>, Eigen::Aligned> gpu_in2(
d_in2, 2);
Eigen::TensorMap<Eigen::Tensor<float, 1, 0, int>, Eigen::Aligned> gpu_out2(
d_out2, 2);
Eigen::TensorMap<Eigen::Tensor<std::complex<float>, 1, 0, int>, Eigen::Aligned> gpu_in1(d_in1, 2);
Eigen::TensorMap<Eigen::Tensor<std::complex<float>, 1, 0, int>, Eigen::Aligned> gpu_in2(d_in2, 2);
Eigen::TensorMap<Eigen::Tensor<float, 1, 0, int>, Eigen::Aligned> gpu_out2(d_out2, 2);
gpu_in1.device(gpu_device) = gpu_in1.constant(std::complex<float>(3.14f, 2.7f));
gpu_out2.device(gpu_device) = gpu_in2.abs();
@@ -50,10 +47,9 @@ void test_cuda_nullary() {
Tensor<std::complex<float>, 1, 0, int> new1(2);
Tensor<float, 1, 0, int> new2(2);
assert(cudaMemcpyAsync(new1.data(), d_in1, complex_bytes, cudaMemcpyDeviceToHost,
gpu_device.stream()) == cudaSuccess);
assert(cudaMemcpyAsync(new2.data(), d_out2, float_bytes, cudaMemcpyDeviceToHost,
gpu_device.stream()) == cudaSuccess);
assert(cudaMemcpyAsync(new1.data(), d_in1, complex_bytes, cudaMemcpyDeviceToHost, gpu_device.stream()) ==
cudaSuccess);
assert(cudaMemcpyAsync(new2.data(), d_out2, float_bytes, cudaMemcpyDeviceToHost, gpu_device.stream()) == cudaSuccess);
assert(cudaStreamSynchronize(gpu_device.stream()) == cudaSuccess);
@@ -67,14 +63,12 @@ void test_cuda_nullary() {
cudaFree(d_out2);
}
static void test_cuda_sum_reductions() {
Eigen::GpuStreamDevice stream;
Eigen::GpuDevice gpu_device(&stream);
const int num_rows = internal::random<int>(1024, 5*1024);
const int num_cols = internal::random<int>(1024, 5*1024);
const int num_rows = internal::random<int>(1024, 5 * 1024);
const int num_cols = internal::random<int>(1024, 5 * 1024);
Tensor<std::complex<float>, 2> in(num_rows, num_cols);
in.setRandom();
@@ -105,12 +99,11 @@ static void test_cuda_sum_reductions() {
}
static void test_cuda_mean_reductions() {
Eigen::GpuStreamDevice stream;
Eigen::GpuDevice gpu_device(&stream);
const int num_rows = internal::random<int>(1024, 5*1024);
const int num_cols = internal::random<int>(1024, 5*1024);
const int num_rows = internal::random<int>(1024, 5 * 1024);
const int num_cols = internal::random<int>(1024, 5 * 1024);
Tensor<std::complex<float>, 2> in(num_rows, num_cols);
in.setRandom();
@@ -141,12 +134,11 @@ static void test_cuda_mean_reductions() {
}
static void test_cuda_product_reductions() {
Eigen::GpuStreamDevice stream;
Eigen::GpuDevice gpu_device(&stream);
const int num_rows = internal::random<int>(1024, 5*1024);
const int num_cols = internal::random<int>(1024, 5*1024);
const int num_rows = internal::random<int>(1024, 5 * 1024);
const int num_cols = internal::random<int>(1024, 5 * 1024);
Tensor<std::complex<float>, 2> in(num_rows, num_cols);
in.setRandom();
@@ -176,9 +168,7 @@ static void test_cuda_product_reductions() {
gpu_device.deallocate(gpu_out_ptr);
}
EIGEN_DECLARE_TEST(test_cxx11_tensor_complex)
{
EIGEN_DECLARE_TEST(test_cxx11_tensor_complex) {
CALL_SUBTEST(test_cuda_nullary());
CALL_SUBTEST(test_cuda_sum_reductions());
CALL_SUBTEST(test_cuda_mean_reductions());