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Added a way to detect errors generated by the opencl device from the host
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@ -12,13 +12,16 @@
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// Public License v. 2.0. If a copy of the MPL was not distributed
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// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
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#include <iostream>
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#if defined(EIGEN_USE_SYCL) && !defined(EIGEN_CXX11_TENSOR_TENSOR_DEVICE_SYCL_H)
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#define EIGEN_CXX11_TENSOR_TENSOR_DEVICE_SYCL_H
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namespace Eigen {
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struct SyclDevice {
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/// class members:
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bool exception_caught_ = false;
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/// sycl queue
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mutable cl::sycl::queue m_queue;
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@ -34,6 +37,7 @@ struct SyclDevice {
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for (const auto& e : l) {
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try {
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if (e) {
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exception_caught_ = true;
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std::rethrow_exception(e);
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}
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} catch (const cl::sycl::exception& e) {
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@ -231,6 +235,12 @@ struct SyclDevice {
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EIGEN_STRONG_INLINE void synchronize() const {
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m_queue.wait_and_throw();
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}
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// This function checks if the runtime recorded an error for the
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// underlying stream device.
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EIGEN_STRONG_INLINE bool ok() const {
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return !exception_caught_;
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}
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};
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} // end namespace Eigen
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@ -42,17 +42,13 @@ void test_device_memory(const Eigen::SyclDevice &sycl_device) {
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void test_device_exceptions(const Eigen::SyclDevice &sycl_device) {
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bool threw_exception = false;
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VERIFY(sycl_device.ok());
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array<int, 1> tensorDims = {{100}};
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int* gpu_data = static_cast<int*>(sycl_device.allocate(100*sizeof(int)));
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TensorMap<Tensor<int, 1>> in(gpu_data, tensorDims);
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TensorMap<Tensor<int, 1>> out(gpu_data, tensorDims);
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try {
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out.device(sycl_device) = in / in.constant(0);
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} catch(...) {
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threw_exception = true;
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}
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VERIFY(threw_exception);
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out.device(sycl_device) = in / in.constant(0);
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VERIFY(!sycl_device.ok());
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sycl_device.deallocate(gpu_data);
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}
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@ -62,5 +58,5 @@ void test_cxx11_tensor_device_sycl() {
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Eigen::SyclDevice sycl_device(s);
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CALL_SUBTEST(test_device_memory(sycl_device));
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// This deadlocks
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// CALL_SUBTEST(test_device_exceptions(sycl_device));
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//CALL_SUBTEST(test_device_exceptions(sycl_device));
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}
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