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author | Eugene Zhulenev <ezhulenev@google.com> | 2018-07-10 13:16:38 -0700 |
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committer | Eugene Zhulenev <ezhulenev@google.com> | 2018-07-10 13:16:38 -0700 |
commit | 01fd4096d395e7b816459f571bf2328c8435cc37 (patch) | |
tree | 02b928b34f77c3e63126c3175b6ea06174818f51 /unsupported/test/cxx11_tensor_thread_pool.cpp | |
parent | 5539587b1f5b5922b2419b0a4468cf2f393def51 (diff) |
Fuse computations into the Tensor contractions using output kernel
Diffstat (limited to 'unsupported/test/cxx11_tensor_thread_pool.cpp')
-rw-r--r-- | unsupported/test/cxx11_tensor_thread_pool.cpp | 56 |
1 files changed, 56 insertions, 0 deletions
diff --git a/unsupported/test/cxx11_tensor_thread_pool.cpp b/unsupported/test/cxx11_tensor_thread_pool.cpp index 2ef665f30..ea9d8afdc 100644 --- a/unsupported/test/cxx11_tensor_thread_pool.cpp +++ b/unsupported/test/cxx11_tensor_thread_pool.cpp @@ -232,6 +232,60 @@ void test_multithread_contraction_agrees_with_singlethread() { } } +// Apply Sqrt to all output elements. +struct SqrtOutputKernel { + template <typename Index, typename Scalar> + EIGEN_ALWAYS_INLINE void operator()( + const OutputKernel::OutputMapper<Index, Scalar>& output_mapper, + const TensorContractionParams&, Index, Index, Index num_rows, + Index num_cols) const { + for (int i = 0; i < num_rows; ++i) { + for (int j = 0; j < num_cols; ++j) { + output_mapper(i, j) = std::sqrt(output_mapper(i, j)); + } + } + } +}; + +template <int DataLayout> +static void test_multithread_contraction_with_output_kernel() { + typedef Tensor<float, 1>::DimensionPair DimPair; + + const int num_threads = internal::random<int>(2, 11); + ThreadPool threads(num_threads); + Eigen::ThreadPoolDevice device(&threads, num_threads); + + Tensor<float, 4, DataLayout> t_left(30, 50, 8, 31); + Tensor<float, 5, DataLayout> t_right(8, 31, 7, 20, 10); + Tensor<float, 5, DataLayout> t_result(30, 50, 7, 20, 10); + + t_left.setRandom(); + t_right.setRandom(); + // Put trash in mat4 to verify contraction clears output memory. + t_result.setRandom(); + + // Add a little offset so that the results won't be close to zero. + t_left += t_left.constant(1.0f); + t_right += t_right.constant(1.0f); + + typedef Map<Eigen::Matrix<float, Dynamic, Dynamic, DataLayout>> MapXf; + MapXf m_left(t_left.data(), 1500, 248); + MapXf m_right(t_right.data(), 248, 1400); + Eigen::Matrix<float, Dynamic, Dynamic, DataLayout> m_result(1500, 1400); + + // this contraction should be equivalent to a single matrix multiplication + Eigen::array<DimPair, 2> dims({{DimPair(2, 0), DimPair(3, 1)}}); + + // compute results by separate methods + t_result.device(device) = t_left.contract(t_right, dims, SqrtOutputKernel()); + + m_result = m_left * m_right; + + for (size_t i = 0; i < t_result.dimensions().TotalSize(); i++) { + VERIFY(&t_result.data()[i] != &m_result.data()[i]); + VERIFY_IS_APPROX(t_result.data()[i], std::sqrt(m_result.data()[i])); + } +} template<int DataLayout> void test_full_contraction() { @@ -355,6 +409,8 @@ void test_cxx11_tensor_thread_pool() CALL_SUBTEST_3(test_multithread_contraction_agrees_with_singlethread<ColMajor>()); CALL_SUBTEST_3(test_multithread_contraction_agrees_with_singlethread<RowMajor>()); + CALL_SUBTEST_3(test_multithread_contraction_with_output_kernel<ColMajor>()); + CALL_SUBTEST_3(test_multithread_contraction_with_output_kernel<RowMajor>()); // Exercise various cases that have been problematic in the past. CALL_SUBTEST_4(test_contraction_corner_cases<ColMajor>()); |