/* * 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/NEON/functions/NEMatMul.h" #include "tests/NEON/Accessor.h" #include "tests/framework/Asserts.h" #include "tests/framework/Macros.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 { TEST_SUITE(NEON) TEST_SUITE(MatMul) constexpr AbsoluteTolerance tolerance_fp32(0.001f); /**< Tolerance value for comparing reference's output against implementation's output for FP32 data types */ const AbsoluteTolerance tolerance_fp16(half(0.1f)); // clang-format off // *INDENT-OFF* // Validation Tests DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip( framework::dataset::make("InputAInfo", { TensorInfo(TensorShape(9U, 6U), 1, DataType::F32), // Mismatching datatype TensorInfo(TensorShape(9U, 6U), 1, DataType::S32), // Unsupported datatypes TensorInfo(TensorShape(9U, 6U, 2U), 1, DataType::F32), // Broadcasting in batch dimension not supported TensorInfo(TensorShape(9U, 6U), 1, DataType::F32), // Invalid shape for multiplication TensorInfo(TensorShape(9U, 6U), 1, DataType::F32), TensorInfo(TensorShape(9U, 6U , 12U) , 1 , DataType::F32), TensorInfo(TensorShape(9U, 6U , 12U) , 1 , DataType::F32), // Tensors are not dynamic }), framework::dataset::make("InputBInfo",{ TensorInfo(TensorShape(5U, 9U), 1, DataType::QASYMM8), TensorInfo(TensorShape(5U, 9U), 1, DataType::S32), TensorInfo(TensorShape(5U, 9U, 1U), 1, DataType::F32), TensorInfo(TensorShape(5U, 12U), 1, DataType::F32), TensorInfo(TensorShape(5U, 9U), 1, DataType::F32), TensorInfo(TensorShape(5U, 9U, 12U), 1, DataType::F32), TensorInfo(TensorShape(5U, 9U, 12U), 1, DataType::F32), })), framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(5U, 6U), 1, DataType::F32), TensorInfo(TensorShape(5U, 6U), 1, DataType::S32), TensorInfo(TensorShape(5U, 6U, 2U), 1, DataType::F32), TensorInfo(TensorShape(5U, 6U), 1, DataType::F32), TensorInfo(TensorShape(5U, 6U), 1, DataType::F32), TensorInfo(TensorShape(5U, 6U, 12U) , 1, DataType::F32), TensorInfo(TensorShape(5U, 6U, 12U) , 1, DataType::F32), })), framework::dataset::make( "TensorIsConst", {false, false, false, false, false , false, true} )), framework::dataset::make("Expected", { false, false, false, false, true, true, false })), a_info, b_info, output_info, are_tensors_const, expected) { TensorInfo a{a_info}; TensorInfo b{b_info}; a.set_are_values_constant(are_tensors_const); b.set_are_values_constant(are_tensors_const); Status status = NEMatMul::validate(&a, &b, &output_info, MatMulInfo(), CpuMatMulSettings()); ARM_COMPUTE_EXPECT(bool(status) == expected, framework::LogLevel::ERRORS); } // *INDENT-ON* // clang-format on // Generic Template template using NEMatMulFixture = MatMulValidationWithActivationFixture; // Fast math Template template using NEMatMulFastMathFixture = MatMulGenericValidationFixture; template using NEMatMulDynamicTensorsFixture = MatMulValidationWithDynamicTensorsFixture; TEST_SUITE(Float) TEST_SUITE(FP32) FIXTURE_DATA_TEST_CASE(RunSmall, NEMatMulFixture, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallMatMulDataset(), framework::dataset::make("TransposeA", { false, true })), framework::dataset::make("TransposeB", { false, true })), framework::dataset::make("DataType", DataType::F32)), framework::dataset::make("ActivationInfo", { ActivationLayerInfo(), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) }))) { // Validate output validate(Accessor(_target), _reference, tolerance_fp32); } FIXTURE_DATA_TEST_CASE(RunLarge, NEMatMulFixture, 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)), framework::dataset::make("ActivationInfo", { ActivationLayerInfo(), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) }))) { // Validate output validate(Accessor(_target), _reference, tolerance_fp32); } FIXTURE_DATA_TEST_CASE(RunHighDimensions, NEMatMulFixture, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(datasets::HighDimensionalMatMulDataset(), framework::dataset::make("TransposeA", { false, true })), framework::dataset::make("TransposeB", { false, true })), framework::dataset::make("DataType", DataType::F32)), framework::dataset::make("ActivationInfo", { ActivationLayerInfo(), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) }))) { // Validate output validate(Accessor(_target), _reference, tolerance_fp32); } FIXTURE_DATA_TEST_CASE(RunStressDynamicTensors, NEMatMulDynamicTensorsFixture, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(combine(datasets::SmallMatMulDataset(), framework::dataset::make("TransposeA", { false, true })), framework::dataset::make("TransposeB", { false, true })), framework::dataset::make("DataType", DataType::F32)), framework::dataset::make("ActivationInfo", { ActivationLayerInfo(), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) })), framework::dataset::make("NumberOfRuns", 5))) { // Validate output validate(Accessor(_target), _reference, tolerance_fp32); } TEST_SUITE_END() // FP32 #ifdef ARM_COMPUTE_ENABLE_BF16 /* Note : MatMul BF16 is enabled by specifying FP32 datatype and enabling the fast math setting */ constexpr AbsoluteTolerance tolerance_bf16(0.001f); TEST_SUITE(BF16) FIXTURE_DATA_TEST_CASE(RunSmall, NEMatMulFastMathFixture, framework::DatasetMode::PRECOMMIT, 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::F32)), framework::dataset::make("ActivationInfo", { ActivationLayerInfo() })), framework::dataset::make("RunTimes", { 0 })), framework::dataset::make("Settings", { CpuMatMulSettings().fast_math(true) }))) { // Validate output validate(Accessor(_target), _reference, tolerance_bf16); } TEST_SUITE_END() // BF16 #endif /* ARM_COMPUTE_ENABLE_BF16 */ #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC TEST_SUITE(FP16) FIXTURE_DATA_TEST_CASE(RunSmall, NEMatMulFixture, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallMatMulDataset(), framework::dataset::make("TransposeA", { false, true })), framework::dataset::make("TransposeB", { false, true })), framework::dataset::make("DataType", DataType::F16)), framework::dataset::make("ActivationInfo", { ActivationLayerInfo(), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) }))) { // Validate output validate(Accessor(_target), _reference, tolerance_fp16); } FIXTURE_DATA_TEST_CASE(RunLarge, NEMatMulFixture, 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)), framework::dataset::make("ActivationInfo", { ActivationLayerInfo(), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) }))) { // Validate output validate(Accessor(_target), _reference, tolerance_fp16); } FIXTURE_DATA_TEST_CASE(RunStressDynamicTensors, NEMatMulDynamicTensorsFixture, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(combine(datasets::SmallMatMulDataset(), framework::dataset::make("TransposeA", { false, true })), framework::dataset::make("TransposeB", { false, true })), framework::dataset::make("DataType", DataType::F16)), framework::dataset::make("ActivationInfo", { ActivationLayerInfo(), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) })), framework::dataset::make("NumberOfRuns", 5))) { // Validate output validate(Accessor(_target), _reference, tolerance_fp16); } TEST_SUITE_END() // FP16 #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ TEST_SUITE_END() // Float TEST_SUITE_END() // MatMul TEST_SUITE_END() // NEON } // namespace validation } // namespace test } // namespace arm_compute