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

Replace memset with fill to work for non-trivial scalars.

Browse Source 
For custom scalars, zero is not necessarily represented by
a zeroed-out memory block (e.g. gnu MPFR). We therefore
cannot rely on `memset` if we want to fill a matrix or tensor
with zeroes. Instead, we should rely on `fill`, which for trivial
types does end up getting converted to a `memset` under-the-hood
(at least with gcc/clang).

Requires adding a `fill(begin, end, v)` to `TensorDevice`.

Replaced all potentially bad instances of memset with fill.

Fixes #2245.
This commit is contained in:
Antonio Sanchez
2021-05-11 09:52:00 -07:00
committed by Rasmus Munk Larsen
parent e9c9a3130b
commit 1e6c6c1576
18 changed files with 229 additions and 61 deletions
Download Patch File Download Diff File Expand all files Collapse all files

19
unsupported/test/cxx11_tensor_device_sycl.cpp
View File

@@ -18,26 +18,36 @@
#define EIGEN_USE_SYCL
#include "main.h"
#include "OffByOneScalar.h"
#include <unsupported/Eigen/CXX11/Tensor>
#include <stdint.h>
#include <iostream>
template <typename DataType, int DataLayout, typename IndexType>
void test_device_memory(const Eigen::SyclDevice &sycl_device) {
std::cout << "Running on : "
<< sycl_device.sycl_queue().get_device(). template get_info<cl::sycl::info::device::name>()
<<std::endl;
IndexType sizeDim1 = 100;
array<IndexType, 1> tensorRange = {{sizeDim1}};
Tensor<DataType, 1, DataLayout,IndexType> in(tensorRange);
Tensor<DataType, 1, DataLayout,IndexType> in1(tensorRange);
memset(in1.data(), 1, in1.size() * sizeof(DataType));
DataType* gpu_in_data = static_cast<DataType*>(sycl_device.allocate(in.size()*sizeof(DataType)));
// memset
memset(in1.data(), 1, in1.size() * sizeof(DataType));
sycl_device.memset(gpu_in_data, 1, in.size()*sizeof(DataType));
sycl_device.memcpyDeviceToHost(in.data(), gpu_in_data, in.size()*sizeof(DataType));
for (IndexType i=0; i<in.size(); i++) {
VERIFY_IS_EQUAL(in(i), in1(i));
}
// fill
DataType value = DataType(7);
std::fill_n(in1.data(), in1.size(), value);
sycl_device.fill(gpu_in_data, gpu_in_data + in.size(), value);
sycl_device.memcpyDeviceToHost(in.data(), gpu_in_data, in.size()*sizeof(DataType));
for (IndexType i=0; i<in.size(); i++) {
VERIFY_IS_EQUAL(in(i), in1(i));
}
sycl_device.deallocate(gpu_in_data);
}
@@ -73,5 +83,6 @@ template<typename DataType> void sycl_device_test_per_device(const cl::sycl::dev
EIGEN_DECLARE_TEST(cxx11_tensor_device_sycl) {
for (const auto& device :Eigen::get_sycl_supported_devices()) {
CALL_SUBTEST(sycl_device_test_per_device<float>(device));
CALL_SUBTEST(sycl_device_test_per_device<OffByOneScalar<int>>(device));
}
}