diff options
Diffstat (limited to 'tests/validation/CL/MatMulKernel.cpp')
| -rw-r--r-- | tests/validation/CL/MatMulKernel.cpp | 49 |
1 files changed, 35 insertions, 14 deletions
diff --git a/tests/validation/CL/MatMulKernel.cpp b/tests/validation/CL/MatMulKernel.cpp index ff872aaa0a..b47f8bc924 100644 --- a/tests/validation/CL/MatMulKernel.cpp +++ b/tests/validation/CL/MatMulKernel.cpp @@ -75,6 +75,9 @@ const auto k0_values_nightly_lhs_t_rhs_nt = framework::dataset::make("K0", { 1, template <typename T> using CLMatMulKernelFixture = MatMulKernelValidationFixture<T, ClMatMulNativeKernel>; +template <typename T> +using CLMatMulKernelBiasFixture = MatMulKernelWithBiasValidation<T, ClMatMulNativeKernel>; + TEST_SUITE(CL) TEST_SUITE(MatMulKernel) TEST_SUITE(Validate) @@ -162,7 +165,7 @@ TEST_CASE(SupportedBlockSizes, framework::DatasetMode::ALL) for(auto &pair : supported_block_sizes) { TensorInfo output_info; - Status status = ClMatMulNativeKernel::validate(&lhs_info, &rhs_info, &output_info, pair.first); + Status status = ClMatMulNativeKernel::validate(&lhs_info, &rhs_info, nullptr, &output_info, pair.first); if(!pair.first.export_rhs_to_cl_image || export_to_cl_image_supported) { @@ -222,7 +225,7 @@ TEST_CASE(ExportToCLImage, framework::DatasetMode::ALL) }; TensorInfo output_info; - Status status = ClMatMulNativeKernel::validate(&lhs_info, &rhs_info, &output_info, matmul_kernel_info); + Status status = ClMatMulNativeKernel::validate(&lhs_info, &rhs_info, nullptr, &output_info, matmul_kernel_info); const bool expected = std::get<4>(tuple); ARM_COMPUTE_EXPECT(bool(status) == expected, framework::LogLevel::ERRORS); @@ -233,22 +236,25 @@ TEST_CASE(ExportToCLImage, framework::DatasetMode::ALL) TEST_CASE(ValidateInputShapes, framework::DatasetMode::ALL) { // Configurations are assumed to be Nt/Nt, but will be transposed inside the test to test other configurations - using ShapeConfigurationTuple = std::tuple<TensorShape, TensorShape, bool>; + using ShapeConfigurationTuple = std::tuple<TensorShape, TensorShape, TensorShape, bool>; const std::vector<ShapeConfigurationTuple> shape_configurations = { - { TensorShape(5U, 1U), TensorShape(3U, 5U), true }, - { TensorShape(10U, 12U), TensorShape(3U, 10U), true }, - { TensorShape(8U, 4U), TensorShape(2U, 8U), true }, - { TensorShape(8U, 4U), TensorShape(2U, 5U), false }, // Mismatch in the K dimension - { TensorShape(5U, 0U), TensorShape(2U, 5U), false }, // Invalid dimension - { TensorShape(5U, 4U, 3U, 4U, 5U, 6U), TensorShape(2U, 5U, 3U, 4U, 5U, 6U), true }, - { TensorShape(5U, 4U, 3U, 4U, 5U, 1U), TensorShape(2U, 5U, 3U, 4U, 5U, 6U), false }, // no batch broadcasting - { TensorShape(5U, 4U, 3U, 4U, 9U, 6U), TensorShape(2U, 5U, 3U, 4U, 5U, 6U), false }, // mismatch in batch dimension + { TensorShape(5U, 1U), TensorShape(3U, 5U), TensorShape(3U), true }, + { TensorShape(10U, 12U), TensorShape(3U, 10U), TensorShape(3U), true }, + { TensorShape(8U, 4U), TensorShape(2U, 8U), TensorShape(2U), true }, + { TensorShape(8U, 4U), TensorShape(2U, 5U), TensorShape(2U), false }, // Mismatch in the K dimension + { TensorShape(5U, 0U), TensorShape(2U, 5U), TensorShape(2U), false }, // Invalid dimension + { TensorShape(5U, 4U, 3U, 4U, 5U, 6U), TensorShape(2U, 5U, 3U, 4U, 5U, 6U), TensorShape(2U), true }, + { TensorShape(5U, 4U, 3U, 4U, 5U, 1U), TensorShape(2U, 5U, 3U, 4U, 5U, 6U), TensorShape(2U), false }, // no batch broadcasting + { TensorShape(5U, 4U, 3U, 4U, 9U, 6U), TensorShape(2U, 5U, 3U, 4U, 5U, 6U), TensorShape(2U), false }, // mismatch in batch dimension + { TensorShape(5U, 1U), TensorShape(3U, 5U), TensorShape(1U), false }, // Unsupported bias broadcasting. + { TensorShape(5U, 1U), TensorShape(3U, 5U), TensorShape(3U, 3U), false }, // 2D bias is unsupported. + { TensorShape(5U, 1U), TensorShape(3U, 5U), TensorShape(6U), false }, // bias first dimension != dst first dimension }; for(auto &tuple : shape_configurations) { - const bool expected = std::get<2>(tuple); + const bool expected = std::get<3>(tuple); for(bool adj_lhs : { @@ -262,6 +268,7 @@ TEST_CASE(ValidateInputShapes, framework::DatasetMode::ALL) { TensorShape lhs_shape = std::get<0>(tuple); TensorShape rhs_shape = std::get<1>(tuple); + TensorShape bia_shape = std::get<2>(tuple); if(adj_lhs) { @@ -275,11 +282,12 @@ TEST_CASE(ValidateInputShapes, framework::DatasetMode::ALL) const TensorInfo lhs_info = TensorInfo(lhs_shape, 1, DataType::F32); const TensorInfo rhs_info = TensorInfo(rhs_shape, 1, DataType::F32); + const TensorInfo bia_info = TensorInfo(bia_shape, 1, DataType::F32); TensorInfo output_info; MatMulKernelInfo matmul_kernel_info{ adj_lhs, adj_rhs, 1, 1, 1, false /* export_rhs_to_cl_image */ }; - Status status = ClMatMulNativeKernel::validate(&lhs_info, &rhs_info, &output_info, matmul_kernel_info); + Status status = ClMatMulNativeKernel::validate(&lhs_info, &rhs_info, &bia_info, &output_info, matmul_kernel_info); ARM_COMPUTE_EXPECT(bool(status) == expected, framework::LogLevel::ERRORS); } } @@ -322,7 +330,7 @@ TEST_CASE(ValidateDataTypes, framework::DatasetMode::ALL) const TensorInfo rhs_info(shape, 1, std::get<1>(tuple)); TensorInfo output_info(shape, 1, std::get<2>(tuple)); - Status status = ClMatMulNativeKernel::validate(&lhs_info, &rhs_info, &output_info, matmul_kernel_info); + Status status = ClMatMulNativeKernel::validate(&lhs_info, &rhs_info, nullptr, &output_info, matmul_kernel_info); ARM_COMPUTE_EXPECT(bool(status) == expected, framework::LogLevel::ERRORS); } } @@ -356,6 +364,19 @@ FIXTURE_DATA_TEST_CASE(RunSmall, CLMatMulKernelFixture<float>, framework::Datase // Validate output validate(CLAccessor(_target), _reference, tolerance_f32, 0.f, abs_tolerance_f32); } +FIXTURE_DATA_TEST_CASE(RunWithBias, CLMatMulKernelBiasFixture<float>, framework::DatasetMode::ALL, combine(combine(combine(combine(combine(combine(combine(datasets::SmallMatMulDataset(), + framework::dataset::make("TransposeA", { false, true })), + framework::dataset::make("TransposeB", { false, true })), + m0_values_precommit), + n0_values_precommit), + k0_values_precommit), + framework::dataset::make("ExportRhsToCLImage", { false })), + framework::dataset::make("DataType", DataType::F32))) + +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_f32, 0.f, abs_tolerance_f32); +} FIXTURE_DATA_TEST_CASE(RunLargeNoTranspose, CLMatMulKernelFixture<float>, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(combine(combine(combine(datasets::LargeMatMulDataset(), framework::dataset::make("TransposeA", { false })), framework::dataset::make("TransposeB", { false })), |