diff options
Diffstat (limited to 'tests/validation/CL/MatMulLowpNativeKernel.cpp')
-rw-r--r-- | tests/validation/CL/MatMulLowpNativeKernel.cpp | 92 |
1 files changed, 57 insertions, 35 deletions
diff --git a/tests/validation/CL/MatMulLowpNativeKernel.cpp b/tests/validation/CL/MatMulLowpNativeKernel.cpp index fd7a4cb156..90eee4fb82 100644 --- a/tests/validation/CL/MatMulLowpNativeKernel.cpp +++ b/tests/validation/CL/MatMulLowpNativeKernel.cpp @@ -49,6 +49,9 @@ constexpr AbsoluteTolerance<float> tolerance_quant(1); /**< Tolerance value for template <typename T> using CLMatMulLowpNativeKernelFixture = MatMulKernelValidationFixture<T, ClMatMulLowpNativeKernel>; +template <typename T> +using CLMatMulLowpKernelWithBiasFixture = MatMulKernelWithBiasValidation<T, ClMatMulLowpNativeKernel>; + /** M0 values to test --precommit*/ const auto m0_values_precommit = framework::dataset::make("M0", { 1, 3 }); @@ -103,7 +106,7 @@ TEST_CASE(SupportedKernelConfigurations, framework::DatasetMode::ALL) for(auto &pair : supported_block_sizes) { TensorInfo output_info; - Status status = ClMatMulLowpNativeKernel::validate(&lhs_info, &rhs_info, &output_info, pair.first); + Status status = ClMatMulLowpNativeKernel::validate(&lhs_info, &rhs_info, nullptr, &output_info, pair.first); ARM_COMPUTE_EXPECT(bool(status) == pair.second, framework::LogLevel::ERRORS); } @@ -112,22 +115,24 @@ TEST_CASE(SupportedKernelConfigurations, 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 }, // invalid broadcast of bias + { TensorShape(5U, 1U), TensorShape(3U, 5U), TensorShape(3U, 3U), false }, // 2d bias is invalid }; for(auto &tuple : shape_configurations) { - const bool expected = std::get<2>(tuple); + const bool expected = std::get<3>(tuple); for(bool adj_lhs : { @@ -141,6 +146,7 @@ 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) { @@ -154,11 +160,12 @@ TEST_CASE(ValidateInputShapes, framework::DatasetMode::ALL) const TensorInfo lhs_info = TensorInfo(lhs_shape, 1, DataType::QASYMM8_SIGNED); const TensorInfo rhs_info = TensorInfo(rhs_shape, 1, DataType::QASYMM8_SIGNED); + const TensorInfo bia_info = TensorInfo(bia_shape, 1, DataType::S32); TensorInfo output_info; MatMulKernelInfo matmul_kernel_info{ adj_lhs, adj_rhs, 1, 1, 1, false /* export_rhs_to_cl_image */ }; - Status status = ClMatMulLowpNativeKernel::validate(&lhs_info, &rhs_info, &output_info, matmul_kernel_info); + Status status = ClMatMulLowpNativeKernel::validate(&lhs_info, &rhs_info, &bia_info, &output_info, matmul_kernel_info); ARM_COMPUTE_EXPECT(bool(status) == expected, framework::LogLevel::ERRORS); } } @@ -167,41 +174,44 @@ TEST_CASE(ValidateInputShapes, framework::DatasetMode::ALL) TEST_CASE(ValidateDataTypes, framework::DatasetMode::ALL) { - using DataTypeConfigurationTuple = std::tuple<DataType, DataType, DataType, bool>; + using DataTypeConfigurationTuple = std::tuple<DataType, DataType, DataType, DataType, bool>; const std::vector<DataTypeConfigurationTuple> data_type_configurations = { - { DataType::F32, DataType::F32, DataType::F32, false }, // no floating point types - { DataType::F16, DataType::F16, DataType::F16, false }, // no floating point types - { DataType::F64, DataType::F64, DataType::F64, false }, // no double precision - { DataType::QASYMM8, DataType::QASYMM8, DataType::QASYMM8, true }, - { DataType::QASYMM8_SIGNED, DataType::QASYMM8_SIGNED, DataType::QASYMM8_SIGNED, true }, - { DataType::QSYMM8_PER_CHANNEL, DataType::QSYMM8_PER_CHANNEL, DataType::QSYMM8_PER_CHANNEL, false }, // only qasymm8/qasymm8_signed is supported - { DataType::QASYMM16, DataType::QASYMM16, DataType::QASYMM16, false }, // only qasymm8/qasymm8_signed is supported - { DataType::QSYMM16, DataType::QSYMM16, DataType::QSYMM16, false }, // only qasymm8/qasymm8_signed is supported - { DataType::QSYMM8, DataType::QSYMM8, DataType::QSYMM8, false }, // only qasymm8/qasymm8_signed is supported - { DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::QASYMM8, false }, // no mixed data types - { DataType::S64, DataType::S64, DataType::S64, false }, // no integral types - { DataType::S32, DataType::S32, DataType::S32, false }, // no integral types - { DataType::S16, DataType::S16, DataType::S16, false }, // no integral types - { DataType::S8, DataType::S8, DataType::S8, false }, // no integral types - { DataType::U64, DataType::U64, DataType::U64, false }, // no integral types - { DataType::U32, DataType::U32, DataType::U32, false }, // no integral types - { DataType::U16, DataType::U16, DataType::U16, false }, // no integral types - { DataType::U8, DataType::U8, DataType::U8, false }, // no integral types + { DataType::F32, DataType::F32, DataType::F32, DataType::F32, false }, // no floating point types + { DataType::F16, DataType::F16, DataType::F16, DataType::F16, false }, // no floating point types + { DataType::F64, DataType::F64, DataType::F64, DataType::F64, false }, // no double precision + { DataType::QASYMM8, DataType::QASYMM8, DataType::S32, DataType::QASYMM8, true }, + { DataType::QASYMM8_SIGNED, DataType::QASYMM8_SIGNED, DataType::S32, DataType::QASYMM8_SIGNED, true }, + { DataType::QSYMM8_PER_CHANNEL, DataType::QSYMM8_PER_CHANNEL, DataType::S32, DataType::QSYMM8_PER_CHANNEL, false }, // only qasymm8/qasymm8_signed is supported + { DataType::QASYMM16, DataType::QASYMM16, DataType::S32, DataType::QASYMM16, false }, // only qasymm8/qasymm8_signed is supported + { DataType::QSYMM16, DataType::QSYMM16, DataType::S32, DataType::QSYMM16, false }, // only qasymm8/qasymm8_signed is supported + { DataType::QSYMM8, DataType::QSYMM8, DataType::S32, DataType::QSYMM8, false }, // only qasymm8/qasymm8_signed is supported + { DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::S32, DataType::QASYMM8, false }, // no mixed data types + { DataType::S64, DataType::S64, DataType::S64, DataType::S64, false }, // no integral types + { DataType::S32, DataType::S32, DataType::S32, DataType::S32, false }, // no integral types + { DataType::S16, DataType::S16, DataType::S16, DataType::S16, false }, // no integral types + { DataType::S8, DataType::S8, DataType::S8, DataType::S8, false }, // no integral types + { DataType::U64, DataType::U64, DataType::U64, DataType::U64, false }, // no integral types + { DataType::U32, DataType::U32, DataType::U32, DataType::U32, false }, // no integral types + { DataType::U16, DataType::U16, DataType::U16, DataType::U16, false }, // no integral types + { DataType::U8, DataType::U8, DataType::U8, DataType::U8, false }, // no integral types + { DataType::QASYMM8, DataType::QASYMM8, DataType::F32, DataType::QASYMM8, false } // Only S32 bias is supported }; // It's enough to test a single shape and block size configuration while checking data types - const TensorShape shape = TensorShape(10U, 10U); + const TensorShape shape = TensorShape(10U, 10U); + const TensorShape bia_shape = TensorShape(10U); const MatMulKernelInfo matmul_kernel_info{ false, false, 1, 1, 1, false }; for(auto &tuple : data_type_configurations) { - const bool expected = std::get<3>(tuple); + const bool expected = std::get<4>(tuple); const TensorInfo lhs_info(shape, 1, std::get<0>(tuple)); const TensorInfo rhs_info(shape, 1, std::get<1>(tuple)); - TensorInfo output_info(shape, 1, std::get<2>(tuple)); + const TensorInfo bia_info(bia_shape, 1, std::get<2>(tuple)); + TensorInfo output_info(shape, 1, std::get<3>(tuple)); - Status status = ClMatMulLowpNativeKernel::validate(&lhs_info, &rhs_info, &output_info, matmul_kernel_info); + Status status = ClMatMulLowpNativeKernel::validate(&lhs_info, &rhs_info, &bia_info, &output_info, matmul_kernel_info); ARM_COMPUTE_EXPECT(bool(status) == expected, framework::LogLevel::ERRORS); } } @@ -234,6 +244,18 @@ FIXTURE_DATA_TEST_CASE(RunSmall, CLMatMulLowpNativeKernelFixture<int8_t>, framew // Validate output validate(CLAccessor(_target), _reference, tolerance_quant); } +FIXTURE_DATA_TEST_CASE(RunWithBias, CLMatMulLowpKernelWithBiasFixture<int8_t>, framework::DatasetMode::ALL, combine(combine(combine(combine(combine(combine(combine(datasets::SmallMatMulDataset(), + framework::dataset::make("TransposeA", { true, false })), + framework::dataset::make("TransposeB", { true, false })), + m0_values_precommit), + n0_values_precommit), + k0_values_precommit), + framework::dataset::make("ExportRhsToCLImage", { false })), + framework::dataset::make("DataType", DataType::QASYMM8_SIGNED))) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_quant); +} FIXTURE_DATA_TEST_CASE(RunLargeNoTranspose, CLMatMulLowpNativeKernelFixture<int8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(combine(combine(combine(datasets::LargeMatMulDataset(), framework::dataset::make("TransposeA", { false })), |