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Add a test that GPU complex product reductions match CPU reductions.
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@ -108,8 +108,46 @@ static void test_cuda_sum_reductions() {
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}
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static void test_cuda_product_reductions() {
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Eigen::CudaStreamDevice stream;
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Eigen::GpuDevice gpu_device(&stream);
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const int num_rows = internal::random<int>(1024, 5*1024);
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const int num_cols = internal::random<int>(1024, 5*1024);
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Tensor<std::complex<float>, 2> in(num_rows, num_cols);
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in.setRandom();
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Tensor<std::complex<float>, 0> full_redux;
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full_redux = in.prod();
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std::size_t in_bytes = in.size() * sizeof(std::complex<float>);
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std::size_t out_bytes = full_redux.size() * sizeof(std::complex<float>);
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std::complex<float>* gpu_in_ptr = static_cast<std::complex<float>*>(gpu_device.allocate(in_bytes));
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std::complex<float>* gpu_out_ptr = static_cast<std::complex<float>*>(gpu_device.allocate(out_bytes));
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gpu_device.memcpyHostToDevice(gpu_in_ptr, in.data(), in_bytes);
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TensorMap<Tensor<std::complex<float>, 2> > in_gpu(gpu_in_ptr, num_rows, num_cols);
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TensorMap<Tensor<std::complex<float>, 0> > out_gpu(gpu_out_ptr);
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out_gpu.device(gpu_device) = in_gpu.prod();
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Tensor<std::complex<float>, 0> full_redux_gpu;
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gpu_device.memcpyDeviceToHost(full_redux_gpu.data(), gpu_out_ptr, out_bytes);
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gpu_device.synchronize();
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// Check that the CPU and GPU reductions return the same result.
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VERIFY_IS_APPROX(full_redux(), full_redux_gpu());
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gpu_device.deallocate(gpu_in_ptr);
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gpu_device.deallocate(gpu_out_ptr);
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}
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void test_cxx11_tensor_complex()
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void test_cxx11_tensor_complex()
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{
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{
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CALL_SUBTEST(test_cuda_nullary());
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CALL_SUBTEST(test_cuda_nullary());
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CALL_SUBTEST(test_cuda_sum_reductions());
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CALL_SUBTEST(test_cuda_sum_reductions());
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CALL_SUBTEST(test_cuda_product_reductions());
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}
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}
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