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Add tests for evalShardedByInnerDim contraction + fix bugs

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This commit is contained in:
Eugene Zhulenev
2018-09-28 11:24:08 -07:00
parent e95696acb3
commit 524c81f3fa
4 changed files with 135 additions and 31 deletions
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107
unsupported/test/cxx11_tensor_thread_pool.cpp
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@@ -306,6 +306,86 @@ static void test_multithread_contraction_with_output_kernel() {
}
}
// We are triggering 'evalShardedByInnerDim' optimization.
template <int DataLayout>
static void test_sharded_by_inner_dim_contraction()
{
typedef Tensor<float, 1>::DimensionPair DimPair;
const int num_threads = internal::random<int>(4, 16);
ThreadPool threads(num_threads);
Eigen::ThreadPoolDevice device(&threads, num_threads);
Tensor<float, 2, DataLayout> t_left(2, 10000);
Tensor<float, 2, DataLayout> t_right(10000, 10);
Tensor<float, 2, DataLayout> t_result(2, 10);
t_left.setRandom();
t_right.setRandom();
// Put trash in t_result 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(), 2, 10000);
MapXf m_right(t_right.data(), 10000, 10);
Eigen::Matrix<float, Dynamic, Dynamic, DataLayout> m_result(2, 10);
// this contraction should be equivalent to a single matrix multiplication
Eigen::array<DimPair, 1> dims({{DimPair(1, 0)}});
// compute results by separate methods
t_result.device(device) = t_left.contract(t_right, dims);
m_result = m_left * m_right;
for (Index i = 0; i < t_result.dimensions().TotalSize(); i++) {
VERIFY_IS_APPROX(t_result.data()[i], m_result.data()[i]);
}
}
// We are triggering 'evalShardedByInnerDim' optimization with output kernel.
template <int DataLayout>
static void test_sharded_by_inner_dim_contraction_with_output_kernel()
{
typedef Tensor<float, 1>::DimensionPair DimPair;
const int num_threads = internal::random<int>(4, 16);
ThreadPool threads(num_threads);
Eigen::ThreadPoolDevice device(&threads, num_threads);
Tensor<float, 2, DataLayout> t_left(2, 10000);
Tensor<float, 2, DataLayout> t_right(10000, 10);
Tensor<float, 2, DataLayout> t_result(2, 10);
t_left.setRandom();
t_right.setRandom();
// Put trash in t_result 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(), 2, 10000);
MapXf m_right(t_right.data(), 10000, 10);
Eigen::Matrix<float, Dynamic, Dynamic, DataLayout> m_result(2, 10);
// this contraction should be equivalent to a single matrix multiplication
Eigen::array<DimPair, 1> dims({{DimPair(1, 0)}});
// compute results by separate methods
t_result.device(device) = t_left.contract(t_right, dims, SqrtOutputKernel());
m_result = m_left * m_right;
for (Index i = 0; i < t_result.dimensions().TotalSize(); i++) {
VERIFY_IS_APPROX(t_result.data()[i], std::sqrt(m_result.data()[i]));
}
}
template<int DataLayout>
void test_full_contraction() {
int contract_size1 = internal::random<int>(1, 500);
@@ -446,21 +526,26 @@ EIGEN_DECLARE_TEST(cxx11_tensor_thread_pool)
CALL_SUBTEST_3(test_multithread_contraction_with_output_kernel<ColMajor>());
CALL_SUBTEST_3(test_multithread_contraction_with_output_kernel<RowMajor>());
CALL_SUBTEST_4(test_sharded_by_inner_dim_contraction<ColMajor>());
CALL_SUBTEST_4(test_sharded_by_inner_dim_contraction<RowMajor>());
CALL_SUBTEST_4(test_sharded_by_inner_dim_contraction_with_output_kernel<ColMajor>());
CALL_SUBTEST_4(test_sharded_by_inner_dim_contraction_with_output_kernel<RowMajor>());
// Exercise various cases that have been problematic in the past.
CALL_SUBTEST_4(test_contraction_corner_cases<ColMajor>());
CALL_SUBTEST_4(test_contraction_corner_cases<RowMajor>());
CALL_SUBTEST_5(test_contraction_corner_cases<ColMajor>());
CALL_SUBTEST_5(test_contraction_corner_cases<RowMajor>());
CALL_SUBTEST_4(test_full_contraction<ColMajor>());
CALL_SUBTEST_4(test_full_contraction<RowMajor>());
CALL_SUBTEST_6(test_full_contraction<ColMajor>());
CALL_SUBTEST_6(test_full_contraction<RowMajor>());
CALL_SUBTEST_5(test_multithreaded_reductions<ColMajor>());
CALL_SUBTEST_5(test_multithreaded_reductions<RowMajor>());
CALL_SUBTEST_7(test_multithreaded_reductions<ColMajor>());
CALL_SUBTEST_7(test_multithreaded_reductions<RowMajor>());
CALL_SUBTEST_6(test_memcpy());
CALL_SUBTEST_6(test_multithread_random());
CALL_SUBTEST_7(test_memcpy());
CALL_SUBTEST_7(test_multithread_random());
TestAllocator test_allocator;
CALL_SUBTEST_6(test_multithread_shuffle<ColMajor>(NULL));
CALL_SUBTEST_6(test_multithread_shuffle<RowMajor>(&test_allocator));
CALL_SUBTEST_6(test_threadpool_allocate(&test_allocator));
CALL_SUBTEST_7(test_multithread_shuffle<ColMajor>(NULL));
CALL_SUBTEST_7(test_multithread_shuffle<RowMajor>(&test_allocator));
CALL_SUBTEST_7(test_threadpool_allocate(&test_allocator));
}