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Added more tests for half floats

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This commit is contained in:
Benoit Steiner 2016-05-11 21:27:15 -07:00
parent b6a517c47d
commit 595e890391
1 changed files with 42 additions and 16 deletions
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58
unsupported/test/cxx11_tensor_of_float16_cuda.cu
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@ -294,6 +294,18 @@ void test_cuda_reductions() {
gpu_device.memcpyDeviceToHost(full_prec.data(), d_res_float, size*sizeof(Eigen::half)); gpu_device.memcpyDeviceToHost(full_prec.data(), d_res_float, size*sizeof(Eigen::half));
gpu_device.synchronize(); gpu_device.synchronize();
for (int i = 0; i < size; ++i) {
std::cout << "Checking redux " << i << std::endl;
VERIFY_IS_APPROX(full_prec(i), half_prec(i));
}
gpu_res_float.device(gpu_device) = gpu_float1.maximum(redux_dim).cast<Eigen::half>();
gpu_res_half.device(gpu_device) = gpu_float1.cast<Eigen::half>().maximum(redux_dim);
gpu_device.memcpyDeviceToHost(half_prec.data(), d_res_half, size*sizeof(Eigen::half));
gpu_device.memcpyDeviceToHost(full_prec.data(), d_res_float, size*sizeof(Eigen::half));
gpu_device.synchronize();
for (int i = 0; i < size; ++i) { for (int i = 0; i < size; ++i) {
std::cout << "Checking redux " << i << std::endl; std::cout << "Checking redux " << i << std::endl;
VERIFY_IS_APPROX(full_prec(i), half_prec(i)); VERIFY_IS_APPROX(full_prec(i), half_prec(i));
@ -341,6 +353,14 @@ void test_cuda_full_reductions() {
VERIFY_IS_APPROX(full_prec(), half_prec()); VERIFY_IS_APPROX(full_prec(), half_prec());
gpu_res_float.device(gpu_device) = gpu_float1.maximum().cast<Eigen::half>();
gpu_res_half.device(gpu_device) = gpu_float1.cast<Eigen::half>().maximum();
gpu_device.memcpyDeviceToHost(half_prec.data(), d_res_half, sizeof(Eigen::half));
gpu_device.memcpyDeviceToHost(full_prec.data(), d_res_float, sizeof(Eigen::half));
gpu_device.synchronize();
VERIFY_IS_APPROX(full_prec(), half_prec());
gpu_device.deallocate(d_float1); gpu_device.deallocate(d_float1);
gpu_device.deallocate(d_float2); gpu_device.deallocate(d_float2);
gpu_device.deallocate(d_res_half); gpu_device.deallocate(d_res_half);
@ -355,42 +375,49 @@ void test_cuda_forced_evals() {
int num_elem = 101; int num_elem = 101;
float* d_float = (float*)gpu_device.allocate(num_elem * sizeof(float)); float* d_float = (float*)gpu_device.allocate(num_elem * sizeof(float));
float* d_res_half = (float*)gpu_device.allocate(num_elem * sizeof(float)); float* d_res_half1 = (float*)gpu_device.allocate(num_elem * sizeof(float));
float* d_res_half2 = (float*)gpu_device.allocate(num_elem * sizeof(float));
float* d_res_float = (float*)gpu_device.allocate(num_elem * sizeof(float)); float* d_res_float = (float*)gpu_device.allocate(num_elem * sizeof(float));
Eigen::TensorMap<Eigen::Tensor<float, 1>, Eigen::Aligned> gpu_float( Eigen::TensorMap<Eigen::Tensor<float, 1>, Eigen::Aligned> gpu_float(
d_float, num_elem); d_float, num_elem);
Eigen::TensorMap<Eigen::Tensor<float, 1>, Eigen::Aligned> gpu_res_half( Eigen::TensorMap<Eigen::Tensor<float, 1>, Eigen::Aligned> gpu_res_half1(
d_res_half, num_elem); d_res_half1, num_elem);
Eigen::TensorMap<Eigen::Tensor<float, 1>, Eigen::Unaligned> gpu_res_half2(
d_res_half2, num_elem);
Eigen::TensorMap<Eigen::Tensor<float, 1>, Eigen::Aligned> gpu_res_float( Eigen::TensorMap<Eigen::Tensor<float, 1>, Eigen::Aligned> gpu_res_float(
d_res_float, num_elem); d_res_float, num_elem);
gpu_float.device(gpu_device) = gpu_float.random() - gpu_float.constant(0.5f); Eigen::array<int, 1> no_bcast;
gpu_res_float.device(gpu_device) = gpu_float.abs(); no_bcast[0] = 1;
gpu_res_half.device(gpu_device) = gpu_float.cast<Eigen::half>().abs().eval().cast<float>();
Tensor<float, 1> half_prec(num_elem); gpu_float.device(gpu_device) = gpu_float.random() - gpu_float.constant(0.5f);
gpu_res_float.device(gpu_device) = gpu_float.log();
gpu_res_half1.device(gpu_device) = gpu_float.cast<Eigen::half>().abs().eval().cast<float>();
gpu_res_half2.device(gpu_device) = gpu_float.cast<Eigen::half>().abs().broadcast(no_bcast).eval().cast<float>();
Tensor<float, 1> half_prec1(num_elem);
Tensor<float, 1> half_prec2(num_elem);
Tensor<float, 1> full_prec(num_elem); Tensor<float, 1> full_prec(num_elem);
gpu_device.memcpyDeviceToHost(half_prec.data(), d_res_half, num_elem*sizeof(float)); gpu_device.memcpyDeviceToHost(half_prec1.data(), d_res_half1, num_elem*sizeof(float));
gpu_device.memcpyDeviceToHost(half_prec2.data(), d_res_half1, num_elem*sizeof(float));
gpu_device.memcpyDeviceToHost(full_prec.data(), d_res_float, num_elem*sizeof(float)); gpu_device.memcpyDeviceToHost(full_prec.data(), d_res_float, num_elem*sizeof(float));
gpu_device.synchronize(); gpu_device.synchronize();
for (int i = 0; i < num_elem; ++i) { for (int i = 0; i < num_elem; ++i) {
std::cout << "Checking unary " << i << std::endl; std::cout << "Checking forced eval " << i << std::endl;
VERIFY_IS_APPROX(full_prec(i), half_prec(i)); VERIFY_IS_APPROX(full_prec(i), half_prec1(i));
VERIFY_IS_APPROX(full_prec(i), half_prec2(i));
} }
gpu_device.deallocate(d_float); gpu_device.deallocate(d_float);
gpu_device.deallocate(d_res_half); gpu_device.deallocate(d_res_half1);
gpu_device.deallocate(d_res_half2);
gpu_device.deallocate(d_res_float); gpu_device.deallocate(d_res_float);
} }
#endif #endif
void test_cxx11_tensor_of_float16_cuda() void test_cxx11_tensor_of_float16_cuda()
{ {
#ifdef EIGEN_HAS_CUDA_FP16 #ifdef EIGEN_HAS_CUDA_FP16
@ -402,7 +429,6 @@ void test_cxx11_tensor_of_float16_cuda()
CALL_SUBTEST_3(test_cuda_reductions()); CALL_SUBTEST_3(test_cuda_reductions());
CALL_SUBTEST_3(test_cuda_full_reductions()); CALL_SUBTEST_3(test_cuda_full_reductions());
CALL_SUBTEST_4(test_cuda_forced_evals()); CALL_SUBTEST_4(test_cuda_forced_evals());
#else #else
std::cout << "Half floats are not supported by this version of cuda: skipping the test" << std::endl; std::cout << "Half floats are not supported by this version of cuda: skipping the test" << std::endl;
#endif #endif