tests/validation/CL/MatMul.cpp

/*
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#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