diff options
Diffstat (limited to 'tests/validation/CL/MatMul.cpp')
-rw-r--r-- | tests/validation/CL/MatMul.cpp | 232 |
1 files changed, 232 insertions, 0 deletions
diff --git a/tests/validation/CL/MatMul.cpp b/tests/validation/CL/MatMul.cpp new file mode 100644 index 0000000000..844597f3e9 --- /dev/null +++ b/tests/validation/CL/MatMul.cpp @@ -0,0 +1,232 @@ +/* + * Copyright (c) 2023 Arm Limited. + * + * SPDX-License-Identifier: MIT + * + * Permission is hereby granted, free of charge, to any person obtaining a copy + * of this software and associated documentation files (the "Software"), to + * deal in the Software without restriction, including without limitation the + * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or + * sell copies of the Software, and to permit persons to whom the Software is + * furnished to do so, subject to the following conditions: + * + * The above copyright notice and this permission notice shall be included in all + * copies or substantial portions of the Software. + * + * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR + * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, + * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE + * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER + * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, + * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE + * SOFTWARE. + */ +#include "arm_compute/core/Types.h" +#include "arm_compute/runtime/CL/CLTensor.h" +#include "arm_compute/runtime/CL/functions/CLMatMul.h" + +#include "tests/CL/CLAccessor.h" +#include "tests/datasets/ActivationFunctionsDataset.h" +#include "tests/framework/DatasetModes.h" +#include "tests/framework/Macros.h" +#include "tests/framework/TestCase.h" +#include "tests/framework/datasets/Datasets.h" +#include "tests/validation/Validation.h" + +#include "tests/datasets/LargeMatMulDataset.h" +#include "tests/datasets/SmallMatMulDataset.h" +#include "tests/validation/fixtures/MatMulFixture.h" + +namespace arm_compute +{ +namespace test +{ +namespace validation +{ +namespace +{ +RelativeTolerance<float> tolerance_f32(0.001f); /**< Tolerance value for comparing reference's output against implementation's output for fp32 data type */ +constexpr float abs_tolerance_f32( + 0.0001f); /**< Absolute tolerance value for comparing reference's output against implementation's output for fp32 data type in case using relative tolerance fails because of small values */ +constexpr float abs_tolerance_f16( + 0.001f); /**< Absolute tolerance value for comparing reference's output against implementation's output for fp16 data type in case using relative tolerance fails because of small values */ +RelativeTolerance<half_float::half> tolerance_f16(half(0.01)); /**< Tolerance value for comparing reference's output against implementation's output for fp16 data type */ +constexpr AbsoluteTolerance<uint8_t> tolerance_quant(1); /**< Tolerance value for comparing reference's output against implementation's output for quantized data types */ +} // namespace + +template <typename T> +using CLMatMulFixture = MatMulValidationFixture<CLTensor, CLAccessor, CLMatMul, GpuMatMulSettings, T>; + +template <typename T> +using CLQuantizedMatMulFixture = QuantizedMatMulValidationFixture<CLTensor, CLAccessor, CLMatMul, GpuMatMulSettings, T>; + +template <typename T> +using CLMatMulActivationFixture = MatMulValidationWithActivationFixture<CLTensor, CLAccessor, CLMatMul, GpuMatMulSettings, T>; + +template <typename T> +using CLMatMulActivationAlphaBetaFixture = MatMulValidationWithActivationAlphaBetaFixture<CLTensor, CLAccessor, CLMatMul, GpuMatMulSettings, T>; + +template <typename T> +using CLQuantizedMatMulActivationFixture = QuantizedMatMulValidationWithActivationFixture<CLTensor, CLAccessor, CLMatMul, GpuMatMulSettings, T>; + +/* The main act functions matmul (float) is expected to support */ +const auto ActivationFunctionsDataset = framework::dataset::make("ActivationInfo", +{ + ActivationLayerInfo(), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 0.5f), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 0.75f, 0.25f), +}); + +/* (Float datatype only) Larger activation functions dataset, used during some nightly tests. */ +const auto AllActivationsDataset = combine(datasets::ActivationFunctions(), framework::dataset::make("AlphaBeta", { 0.5f, 1.f })); + +// Alpha beta values should be integer values +// This is for testing purposes with quantized datatypes and is not a limitation of the kernel. +// To properly remove this restriction, dst_qinfo should be auto-initialised with consideration for alpha beta values +// The main act functions quantized matmul kernels are expected to support +const auto ActivationFunctionsQuantizedDataset = concat(concat(concat( + framework::dataset::make("ActivationInfo", ActivationLayerInfo()), + framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))), + framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 1.f))), + framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 2.f, 1.f))); + +TEST_SUITE(CL) +TEST_SUITE(MatMul) + +TEST_SUITE(Float) +TEST_SUITE(FP32) + +FIXTURE_DATA_TEST_CASE(RunSmall, CLMatMulActivationFixture<float>, framework::DatasetMode::ALL, combine(combine(combine(combine(datasets::SmallMatMulDataset(), + framework::dataset::make("TransposeA", { false, true })), + framework::dataset::make("TransposeB", { false, true })), + framework::dataset::make("DataType", DataType::F32)), + ActivationFunctionsDataset)) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_f32, 0.f, abs_tolerance_f32); +} + +FIXTURE_DATA_TEST_CASE(RunLarge, CLMatMulActivationFixture<float>, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(datasets::LargeMatMulDataset(), + framework::dataset::make("TransposeA", { false, true })), + framework::dataset::make("TransposeB", { false, true })), + framework::dataset::make("DataType", DataType::F32)), + ActivationFunctionsDataset)) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_f32, 0.f, abs_tolerance_f32); +} + +FIXTURE_DATA_TEST_CASE(RunAllActivations, CLMatMulActivationAlphaBetaFixture<float>, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(datasets::SmallerMatMulDataset(), + framework::dataset::make("TransposeA", { false })), + framework::dataset::make("TransposeB", { true })), + framework::dataset::make("DataType", DataType::F32)), + AllActivationsDataset)) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_f32, 0.f, abs_tolerance_f32); +} + +TEST_SUITE_END() // FP32 + +TEST_SUITE(FP16) + +FIXTURE_DATA_TEST_CASE(RunSmall, CLMatMulActivationFixture<half>, framework::DatasetMode::ALL, combine(combine(combine(combine(datasets::SmallMatMulDataset(), + framework::dataset::make("TransposeA", { false, true })), + framework::dataset::make("TransposeB", { false, true })), + framework::dataset::make("DataType", DataType::F16)), + ActivationFunctionsDataset)) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_f16, 0.f, abs_tolerance_f16); +} + +FIXTURE_DATA_TEST_CASE(RunLarge, CLMatMulActivationFixture<half>, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(datasets::LargeMatMulDataset(), + framework::dataset::make("TransposeA", { false, true })), + framework::dataset::make("TransposeB", { false, true })), + framework::dataset::make("DataType", DataType::F16)), + ActivationFunctionsDataset)) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_f16, 0.f, abs_tolerance_f16); +} + +TEST_SUITE_END() // FP16 +TEST_SUITE_END() // Float + +TEST_SUITE(Quantized) +TEST_SUITE(QASYMM8) + +FIXTURE_DATA_TEST_CASE(RunSmall, CLQuantizedMatMulFixture<uint8_t>, framework::DatasetMode::ALL, combine(combine(combine(combine(combine(combine(combine(combine( + datasets::SmallMatMulDataset(), + framework::dataset::make("TransposeA", { false, true })), + framework::dataset::make("TransposeB", { false, true })), + framework::dataset::make("DataType", DataType::QASYMM8)), + ActivationFunctionsQuantizedDataset), + framework::dataset::make("NumberOfExtraRuns", { 0, 1 })), + framework::dataset::make("LhsQInfo", { QuantizationInfo(1.f / 50, 1) })), + framework::dataset::make("RhsQInfo", { QuantizationInfo(1.f / 30, -1) })), + framework::dataset::make("DstQInfo", { QuantizationInfo(1.f, 2) }))) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_quant); +} + +FIXTURE_DATA_TEST_CASE(RunLarge, CLQuantizedMatMulFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(combine(combine(combine(combine( + datasets::LargeMatMulDataset(), + framework::dataset::make("TransposeA", { false, true })), + framework::dataset::make("TransposeB", { false, true })), + framework::dataset::make("DataType", DataType::QASYMM8)), + ActivationFunctionsQuantizedDataset), + framework::dataset::make("NumberOfExtraRuns", { 0, 1 })), + framework::dataset::make("LhsQInfo", { QuantizationInfo(1.f / 100, 1) })), + framework::dataset::make("RhsQInfo", { QuantizationInfo(1.f / 200, -1) })), + framework::dataset::make("DstQInfo", { QuantizationInfo(1.f, 2) }))) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_quant); +} + +TEST_SUITE_END() // QASYMM8 + +TEST_SUITE(QASYMM8_SIGNED) + +FIXTURE_DATA_TEST_CASE(RunSmall, CLQuantizedMatMulFixture<int8_t>, framework::DatasetMode::ALL, combine(combine(combine(combine(combine(combine(combine(combine( + datasets::SmallMatMulDataset(), + framework::dataset::make("TransposeA", { false, true })), + framework::dataset::make("TransposeB", { false, true })), + framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)), + ActivationFunctionsQuantizedDataset), + framework::dataset::make("NumberOfExtraRuns", { 0, 1 })), + framework::dataset::make("LhsQInfo", { QuantizationInfo(1.f / 50, 1) })), + framework::dataset::make("RhsQInfo", { QuantizationInfo(1.f / 30, -1) })), + framework::dataset::make("DstQInfo", { QuantizationInfo(1.f, 2) }))) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_quant); +} + +FIXTURE_DATA_TEST_CASE(RunLarge, CLQuantizedMatMulFixture<int8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(combine(combine(combine(combine( + datasets::LargeMatMulDataset(), + framework::dataset::make("TransposeA", { false, true })), + framework::dataset::make("TransposeB", { false, true })), + framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)), + ActivationFunctionsQuantizedDataset), + framework::dataset::make("NumberOfExtraRuns", { 0, 1 })), + framework::dataset::make("LhsQInfo", { QuantizationInfo(1.f / 100, 1) })), + framework::dataset::make("RhsQInfo", { QuantizationInfo(1.f / 200, -1) })), + framework::dataset::make("DstQInfo", { QuantizationInfo(1.f, 50) }))) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_quant); +} + +TEST_SUITE_END() // QASYMM8_SIGNED + +TEST_SUITE_END() // Quantized + +TEST_SUITE_END() // MatMul +TEST_SUITE_END() // CL +} // namespace validation +} // namespace test +} // namespace arm_compute |