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Fix Eigen::array constructors.

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libeigen/eigen!2235
This commit is contained in:
Antonio Sánchez
2026-03-03 22:15:47 +00:00
parent 661cdb227f
commit d36a7db7b5
4 changed files with 22 additions and 22 deletions
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4
unsupported/test/cxx11_tensor_contraction.cpp
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@@ -139,7 +139,7 @@ static void test_multidims() {
Tensor<float, 1, DataLayout> mat6(2);
mat6.setZero();
Eigen::array<DimPair, 2> dims2({{DimPair(0, 1), DimPair(1, 0)}});
Eigen::array<DimPair, 2> dims2{{DimPair(0, 1), DimPair(1, 0)}};
typedef TensorEvaluator<decltype(mat4.contract(mat5, dims2)), DefaultDevice> Evaluator2;
Evaluator2 eval2(mat4.contract(mat5, dims2), DefaultDevice());
eval2.evalTo(mat6.data());
@@ -515,7 +515,7 @@ static void test_large_contraction_with_output_kernel() {
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)}});
Eigen::array<DimPair, 2> dims{{DimPair(2, 0), DimPair(3, 1)}};
// compute results by separate methods
t_result = t_left.contract(t_right, dims, SqrtOutputKernel());

2
unsupported/test/cxx11_tensor_of_bfloat16_gpu.cu
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@@ -278,7 +278,7 @@ void test_gpu_contractions() {
gpu_float2.device(gpu_device) = gpu_float2.random() - gpu_float2.constant(0.5f);
typedef Tensor<float, 2>::DimensionPair DimPair;
Eigen::array<DimPair, 1> dims(DimPair(1, 0));
Eigen::array<DimPair, 1> dims{DimPair(1, 0)};
gpu_res_float.device(gpu_device) = gpu_float1.contract(gpu_float2, dims).cast<Eigen::bfloat16>();
gpu_res_bfloat16.device(gpu_device) =
gpu_float1.cast<Eigen::bfloat16>().contract(gpu_float2.cast<Eigen::bfloat16>(), dims);

18
unsupported/test/cxx11_tensor_thread_pool.cpp
View File

@@ -193,7 +193,7 @@ void test_multithread_contraction() {
// this contraction should be equivalent to a single matrix multiplication
typedef Tensor<float, 1>::DimensionPair DimPair;
Eigen::array<DimPair, 2> dims({{DimPair(2, 0), DimPair(3, 1)}});
Eigen::array<DimPair, 2> dims{{DimPair(2, 0), DimPair(3, 1)}};
typedef Map<Matrix<float, Dynamic, Dynamic, DataLayout>> MapXf;
MapXf m_left(t_left.data(), 1500, 1147);
@@ -324,7 +324,7 @@ void test_multithread_contraction_agrees_with_singlethread() {
right += right.constant(1.5f);
typedef Tensor<float, 1>::DimensionPair DimPair;
Eigen::array<DimPair, 1> dims({{DimPair(1, 2)}});
Eigen::array<DimPair, 1> dims{{DimPair(1, 2)}};
Eigen::ThreadPool tp(internal::random<int>(2, 11));
Eigen::ThreadPoolDevice thread_pool_device(&tp, internal::random<int>(2, 11));
@@ -386,7 +386,7 @@ static void test_multithread_contraction_with_output_kernel() {
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)}});
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());
@@ -416,7 +416,7 @@ void test_async_multithread_contraction_agrees_with_singlethread() {
right += right.constant(1.5f);
typedef Tensor<float, 1>::DimensionPair DimPair;
Eigen::array<DimPair, 1> dims({{DimPair(1, 2)}});
Eigen::array<DimPair, 1> dims{{DimPair(1, 2)}};
Eigen::ThreadPool tp(internal::random<int>(2, 11));
Eigen::ThreadPoolDevice thread_pool_device(&tp, internal::random<int>(8, 32));
@@ -468,7 +468,7 @@ static void test_sharded_by_inner_dim_contraction() {
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)}});
Eigen::array<DimPair, 1> dims{{DimPair(1, 0)}};
// compute results by separate methods
t_result.device(device) = t_left.contract(t_right, dims);
@@ -507,7 +507,7 @@ static void test_sharded_by_inner_dim_contraction_with_output_kernel() {
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)}});
Eigen::array<DimPair, 1> dims{{DimPair(1, 0)}};
// compute results by separate methods
t_result.device(device) = t_left.contract(t_right, dims, SqrtOutputKernel());
@@ -546,7 +546,7 @@ static void test_async_sharded_by_inner_dim_contraction() {
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)}});
Eigen::array<DimPair, 1> dims{{DimPair(1, 0)}};
// compute results by separate methods
Eigen::Barrier barrier(1);
@@ -588,7 +588,7 @@ static void test_async_sharded_by_inner_dim_contraction_with_output_kernel() {
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)}});
Eigen::array<DimPair, 1> dims{{DimPair(1, 0)}};
// compute results by separate methods
Eigen::Barrier barrier(1);
@@ -616,7 +616,7 @@ void test_full_contraction() {
right += right.constant(1.5f);
typedef Tensor<float, 2>::DimensionPair DimPair;
Eigen::array<DimPair, 2> dims({{DimPair(0, 0), DimPair(1, 1)}});
Eigen::array<DimPair, 2> dims{{DimPair(0, 0), DimPair(1, 1)}};
Eigen::ThreadPool tp(internal::random<int>(2, 11));
Eigen::ThreadPoolDevice thread_pool_device(&tp, internal::random<int>(2, 11));