| /* |
| * 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 |