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+/*
+ * 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
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