/* * 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 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 tolerance_f16(half(0.01)); /**< Tolerance value for comparing reference's output against implementation's output for fp16 data type */ constexpr AbsoluteTolerance tolerance_quant(1); /**< Tolerance value for comparing reference's output against implementation's output for quantized data types */ } // namespace template using CLMatMulFixture = MatMulValidationFixture; template using CLQuantizedMatMulFixture = QuantizedMatMulValidationFixture; template using CLMatMulActivationFixture = MatMulValidationWithActivationFixture; template using CLMatMulActivationAlphaBetaFixture = MatMulValidationWithActivationAlphaBetaFixture; template using CLQuantizedMatMulActivationFixture = QuantizedMatMulValidationWithActivationFixture; /* 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, 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, 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, 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, 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, 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, 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, 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, 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, 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