From a1b1e41bb261f5613f443fed7071936a360686ed Mon Sep 17 00:00:00 2001 From: Mohammed Suhail Munshi Date: Thu, 23 Mar 2023 22:21:31 +0000 Subject: Implement MatMul Function and Operator with Floating Point support for CPU - Implements MatMul function and operator for floating point datatype FP16/FP32 - Includes support for transposing dynamic tensors prior to matrix multiplication. - Adds tests for 2D/3D/4D+ tensors in MatMul with F32/F16 datatype (with all combinations of transposed/not-transposed tensors) - Updates fixture to allow for testing fused activation in MatMul - Adds tests for matmul with and without fused activation Resolved: [COMPMID-5898] Signed-off-by: Mohammed Suhail Munshi Change-Id: Iefa84b26dd723c9a51e6c3f91023152c6c31ace2 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9411 Reviewed-by: SiCong Li Tested-by: Arm Jenkins Benchmark: Arm Jenkins --- tests/validation/NEON/MatMul.cpp | 205 +++++++++++++++++++++++++++++++++++++++ 1 file changed, 205 insertions(+) create mode 100644 tests/validation/NEON/MatMul.cpp (limited to 'tests/validation/NEON/MatMul.cpp') diff --git a/tests/validation/NEON/MatMul.cpp b/tests/validation/NEON/MatMul.cpp new file mode 100644 index 0000000000..3bfbc16e71 --- /dev/null +++ b/tests/validation/NEON/MatMul.cpp @@ -0,0 +1,205 @@ +/* + * 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 -- cgit v1.2.1