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Diffstat (limited to 'tests/validation/NEON/MatMul.cpp')
| -rw-r--r-- | tests/validation/NEON/MatMul.cpp | 467 |
1 files changed, 467 insertions, 0 deletions
diff --git a/tests/validation/NEON/MatMul.cpp b/tests/validation/NEON/MatMul.cpp new file mode 100644 index 0000000000..f22bd9e86a --- /dev/null +++ b/tests/validation/NEON/MatMul.cpp @@ -0,0 +1,467 @@ +/* + * Copyright (c) 2023-2024 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/datasets/LargeMatMulDataset.h" +#include "tests/datasets/SmallMatMulDataset.h" +#include "tests/framework/Asserts.h" +#include "tests/framework/datasets/Datasets.h" +#include "tests/framework/Macros.h" +#include "tests/NEON/Accessor.h" +#include "tests/validation/fixtures/MatMulFixture.h" +#include "tests/validation/Validation.h" + +namespace arm_compute +{ +namespace test +{ +namespace validation +{ +using framework::dataset::make; + +TEST_SUITE(NEON) +TEST_SUITE(MatMul) + +constexpr AbsoluteTolerance<float> tolerance_fp32( + 0.001f); /**< Tolerance value for comparing reference's output against implementation's output for FP32 data types */ +const AbsoluteTolerance<half> tolerance_fp16(half(0.1f)); +#ifdef __aarch64__ +constexpr AbsoluteTolerance<int32_t> tolerance_qasymm8(1); +constexpr AbsoluteTolerance<int32_t> tolerance_qasymm8_signed(1); +#endif // __aarch64__ + +// clang-format off +// *INDENT-OFF* +// Validation Tests +DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, + zip( + 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 + TensorInfo(TensorShape(9U, 6U), 1, DataType::QASYMM8), + TensorInfo(TensorShape(9U, 6U), 1, DataType::QASYMM8_SIGNED), + TensorInfo(TensorShape(9U, 6U), 1, DataType::QASYMM8_SIGNED), // Mismatching data type + }), + 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), + TensorInfo(TensorShape(5U, 9U), 1, DataType::QASYMM8), + TensorInfo(TensorShape(5U, 9U), 1, DataType::QASYMM8_SIGNED), + TensorInfo(TensorShape(5U, 9U), 1, DataType::QASYMM8_SIGNED), + }), + 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), + TensorInfo(TensorShape(5U, 6U), 1, DataType::QASYMM8), + TensorInfo(TensorShape(5U, 6U), 1, DataType::QASYMM8_SIGNED), + TensorInfo(TensorShape(5U, 6U), 1, DataType::QASYMM8), + }), + make("TensorIsConst", {false, false, false, false, false , false, true, false, false, false}), + make("Expected", { false, false, false, false, true, true, 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 <typename T> +using NEMatMulFixture = MatMulValidationWithActivationFixture<Tensor, Accessor, NEMatMul, CpuMatMulSettings, T>; + +// Fast math Template +template <typename T> +using NEMatMulFastMathFixture = MatMulGenericValidationFixture<Tensor, Accessor, NEMatMul, CpuMatMulSettings, T>; + +template <typename T> +using NEMatMulFixedFormatFixture = MatMulFixedFormatFixture<Tensor, Accessor, NEMatMul, CpuMatMulSettings, T>; + +template <typename T> +using NEMatMulDynamicTensorsFixture = + MatMulValidationWithDynamicTensorsFixture<Tensor, Accessor, NEMatMul, CpuMatMulSettings, T>; + +template <typename T> +using NEQuantizedMatMulFixture = QuantizedMatMulValidationFixture<Tensor, Accessor, NEMatMul, CpuMatMulSettings, T>; + +TEST_SUITE(Float) +TEST_SUITE(FP32) +FIXTURE_DATA_TEST_CASE(RunSmall, + NEMatMulFixture<float>, + framework::DatasetMode::PRECOMMIT, + combine(datasets::SmallMatMulDataset(), + make("TransposeA", {false, true}), + make("TransposeB", {false, true}), + make("DataType", DataType::F32), + make("ActivationInfo", +{ + ActivationLayerInfo(), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) +}))) +{ + // Validate output + validate(Accessor(_target), _reference, tolerance_fp32); +} +FIXTURE_DATA_TEST_CASE(RunLarge, + NEMatMulFixture<float>, + framework::DatasetMode::NIGHTLY, + combine(datasets::LargeMatMulDataset(), + make("TransposeA", {false, true}), + make("TransposeB", {false, true}), + make("DataType", DataType::F32), + make("ActivationInfo", +{ + ActivationLayerInfo(), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) +}))) +{ + // Validate output + validate(Accessor(_target), _reference, tolerance_fp32); +} +FIXTURE_DATA_TEST_CASE(RunHighDimensions, + NEMatMulFixture<float>, + framework::DatasetMode::NIGHTLY, + combine(datasets::HighDimensionalMatMulDataset(), + make("TransposeA", {false, true}), + make("TransposeB", {false, true}), + make("DataType", DataType::F32), + make("ActivationInfo", +{ + ActivationLayerInfo(), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) +}))) +{ + // Validate output + validate(Accessor(_target), _reference, tolerance_fp32); +} + +FIXTURE_DATA_TEST_CASE(RunStressDynamicTensors, + NEMatMulDynamicTensorsFixture<float>, + framework::DatasetMode::PRECOMMIT, + combine(datasets::SmallMatMulDataset(), + make("TransposeA", {false, true}), + make("TransposeB", {false, true}), + make("DataType", DataType::F32), + make("ActivationInfo", +{ + ActivationLayerInfo(), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) +}), +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<float> tolerance_bf16(0.02f); +TEST_SUITE(BF16) +FIXTURE_DATA_TEST_CASE(RunSmall, + NEMatMulFastMathFixture<float>, + framework::DatasetMode::PRECOMMIT, + combine(datasets::SmallMatMulDataset(), + make("TransposeA", {false, true}), + make("TransposeB", {false, true}), + make("DataType", DataType::F32), + make("ActivationInfo", {ActivationLayerInfo()}), + make("RunTimes", {0}), + make("Settings", {CpuMatMulSettings().fast_math(true)}), + make("LhsQInfo", {QuantizationInfo()}), + make("RhsQInfo", {QuantizationInfo()}), + make("OutQInfo", {QuantizationInfo()}))) +{ + // Validate output + validate(Accessor(_target), _reference, tolerance_bf16); +} + +#ifdef ARM_COMPUTE_ENABLE_FIXED_FORMAT_KERNELS +FIXTURE_DATA_TEST_CASE(RunTinyFixedFormat, + NEMatMulFixedFormatFixture<bfloat16>, + framework::DatasetMode::PRECOMMIT, + combine(datasets::TinyMatMulDataset(), + make("TransposeA", {false}), + make("TransposeB", {false}), + make("DataType", DataType::BFLOAT16), + make("ActivationInfo", {ActivationLayerInfo()}), + make("RunTimes", {0}), + make("Settings", {CpuMatMulSettings().fast_math(true).fixed_format(true)}), + make("LhsQInfo", {QuantizationInfo()}), + make("RhsQInfo", {QuantizationInfo()}), + make("OutQInfo", {QuantizationInfo()}))) +{ + if (CPUInfo::get().has_bf16()) + { + // Validate output + validate(Accessor(_target), _reference, tolerance_bf16); + } +} +#endif /* ARM_COMPUTE_ENABLE_FIXED_FORMAT_KERNELS */ + +FIXTURE_DATA_TEST_CASE(RunLarge, + NEMatMulFastMathFixture<float>, + framework::DatasetMode::NIGHTLY, + combine(datasets::LargeMatMulDataset(), + make("TransposeA", {false, true}), + make("TransposeB", {false, true}), + make("DataType", DataType::F32), + make("ActivationInfo", {ActivationLayerInfo()}), + make("RunTimes", {0}), + make("Settings", {CpuMatMulSettings().fast_math(true)}), + make("LhsQInfo", {QuantizationInfo()}), + make("RhsQInfo", {QuantizationInfo()}), + make("OutQInfo", {QuantizationInfo()}))) +{ + // Validate output + validate(Accessor(_target), _reference, tolerance_bf16, 0.01 /* tolerance_num */); +} +TEST_SUITE_END() // BF16 +#endif /* ARM_COMPUTE_ENABLE_BF16 */ + +#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC +TEST_SUITE(FP16) +FIXTURE_DATA_TEST_CASE(RunSmall, + NEMatMulFixture<half>, + framework::DatasetMode::PRECOMMIT, + combine(datasets::SmallMatMulDataset(), + make("TransposeA", {false, true}), + make("TransposeB", {false, true}), + make("DataType", DataType::F16), + make("ActivationInfo", +{ + ActivationLayerInfo(), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) +}))) +{ + // Validate output + validate(Accessor(_target), _reference, tolerance_fp16); +} +FIXTURE_DATA_TEST_CASE(RunLarge, + NEMatMulFixture<half>, + framework::DatasetMode::NIGHTLY, + combine(datasets::LargeMatMulDataset(), + make("TransposeA", {false, true}), + make("TransposeB", {false, true}), + make("DataType", DataType::F16), + make("ActivationInfo", +{ + ActivationLayerInfo(), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) +}))) +{ + // Validate output + validate(Accessor(_target), _reference, tolerance_fp16); +} +FIXTURE_DATA_TEST_CASE(RunStressDynamicTensors, + NEMatMulDynamicTensorsFixture<half>, + framework::DatasetMode::PRECOMMIT, + combine(datasets::SmallMatMulDataset(), + make("TransposeA", {false, true}), + make("TransposeB", {false, true}), + make("DataType", DataType::F16), + make("ActivationInfo", +{ + ActivationLayerInfo(), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) +}), +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 + +#ifdef __aarch64__ // All the GeMM CPU assembly kernels for integer datatypes require aarch64 +TEST_SUITE(Quantized) + +TEST_SUITE(QASYMM8) + +FIXTURE_DATA_TEST_CASE(RunSmall, + NEQuantizedMatMulFixture<uint8_t>, + framework::DatasetMode::PRECOMMIT, + combine(datasets::SmallMatMulDataset(), + make("TransposeA", {false, true}), + make("TransposeB", {false, true}), + make("DataType", DataType::QASYMM8), + make("ActivationInfo", +{ + ActivationLayerInfo(), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) +}), +make("NumberOfExtraRuns", {0, 1}), +make("LhsQInfo", {QuantizationInfo(1.f / 50, 1)}), +make("RhsQInfo", {QuantizationInfo(1.f / 30, -1)}), +make("OutQInfo", {QuantizationInfo(1.f, 2)}))) +{ + // Validate output + validate(Accessor(_target), _reference, tolerance_qasymm8); +} + +FIXTURE_DATA_TEST_CASE(RunSmallExtraActivation, + NEQuantizedMatMulFixture<uint8_t>, + framework::DatasetMode::NIGHTLY, + combine(datasets::SmallerMatMulDataset(), + make("TransposeA", {false, true}), + make("TransposeB", {false, true}), + make("DataType", DataType::QASYMM8), + make("ActivationInfo", +{ + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU) +}), +make("NumberOfExtraRuns", {0, 1}), +make("LhsQInfo", {QuantizationInfo(1.f / 50, 1)}), +make("RhsQInfo", {QuantizationInfo(1.f / 30, -1)}), +make("OutQInfo", {QuantizationInfo(1.f, 2)}))) +{ + // Validate output + validate(Accessor(_target), _reference, tolerance_qasymm8); +} + +FIXTURE_DATA_TEST_CASE(RunLarge, + NEQuantizedMatMulFixture<uint8_t>, + framework::DatasetMode::NIGHTLY, + combine(datasets::LargeMatMulDataset(), + make("TransposeA", {false, true}), + make("TransposeB", {false, true}), + make("DataType", DataType::QASYMM8), + make("ActivationInfo", +{ + ActivationLayerInfo(), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) +}), +make("NumberOfExtraRuns", {0, 1}), +make("LhsQInfo", {QuantizationInfo(1.f / 100, 1)}), +make("RhsQInfo", {QuantizationInfo(1.f / 200, -1)}), +make("OutQInfo", {QuantizationInfo(1.f, 2)}))) +{ + // Validate output + validate(Accessor(_target), _reference, tolerance_qasymm8); +} + +TEST_SUITE_END() // QASYMM8 + +TEST_SUITE(QASYMM8_SIGNED) + +FIXTURE_DATA_TEST_CASE(RunSmall, + NEQuantizedMatMulFixture<int8_t>, + framework::DatasetMode::PRECOMMIT, + combine(datasets::SmallMatMulDataset(), + make("TransposeA", {false, true}), + make("TransposeB", {false, true}), + make("DataType", DataType::QASYMM8_SIGNED), + make("ActivationInfo", +{ + ActivationLayerInfo(), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) +}), +make("NumberOfExtraRuns", {0, 1}), +make("LhsQInfo", {QuantizationInfo(1.f / 40, -2)}), +make("RhsQInfo", {QuantizationInfo(1.f / 50, 1)}), +make("OutQInfo", {QuantizationInfo(1.f, 1)}))) +{ + // Validate output + validate(Accessor(_target), _reference, tolerance_qasymm8_signed); +} + +FIXTURE_DATA_TEST_CASE(RunSmallExtraActivation, + NEQuantizedMatMulFixture<int8_t>, + framework::DatasetMode::NIGHTLY, + combine(datasets::SmallerMatMulDataset(), + make("TransposeA", {false, true}), + make("TransposeB", {false, true}), + make("DataType", DataType::QASYMM8_SIGNED), + make("ActivationInfo", +{ + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU) +}), +make("NumberOfExtraRuns", {0, 1}), +make("LhsQInfo", {QuantizationInfo(1.f / 40, -2)}), +make("RhsQInfo", {QuantizationInfo(1.f / 50, 1)}), +make("OutQInfo", {QuantizationInfo(1.f, 1)}))) +{ + // Validate output + validate(Accessor(_target), _reference, tolerance_qasymm8_signed); +} + +FIXTURE_DATA_TEST_CASE(RunLarge, + NEQuantizedMatMulFixture<int8_t>, + framework::DatasetMode::NIGHTLY, + combine(datasets::LargeMatMulDataset(), + make("TransposeA", {false, true}), + make("TransposeB", {false, true}), + make("DataType", DataType::QASYMM8_SIGNED), + make("ActivationInfo", +{ + ActivationLayerInfo(), + ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU) +}), +make("NumberOfExtraRuns", {0, 1}), +make("LhsQInfo", {QuantizationInfo(1.f / 150, -2)}), +make("RhsQInfo", {QuantizationInfo(1.f / 250, 1)}), +make("OutQInfo", {QuantizationInfo(1.f, 1)}))) +{ + // Validate output + validate(Accessor(_target), _reference, tolerance_qasymm8_signed); +} + +TEST_SUITE_END() // QASYMM8_SIGNED + +TEST_SUITE_END() // Quantized +#endif // __aarch64__ + +TEST_SUITE_END() // MatMul +TEST_SUITE_END() // NEON +} // namespace validation +} // namespace test +} // namespace arm_compute |