| /* |
| * 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 |
| { |
| 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<uint8_t> tolerance_qasymm8(0); |
| constexpr AbsoluteTolerance<uint8_t> tolerance_qasymm8_signed(0); |
| #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 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(0.001f); |
| 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); |
| } |
| 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 |