/* * Copyright (c) 2017-2021 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/NEGEMM.h" #include "arm_compute/runtime/Tensor.h" #include "arm_compute/runtime/TensorAllocator.h" #include "src/core/NEON/kernels/NEGEMMInterleave4x4Kernel.h" #include "src/core/NEON/kernels/NEGEMMMatrixMultiplyKernel.h" #include "src/core/NEON/kernels/NEGEMMTranspose1xWKernel.h" #include "tests/NEON/Accessor.h" #include "tests/NEON/Helper.h" #include "tests/PaddingCalculator.h" #include "tests/datasets/LargeGEMMDataset.h" #include "tests/datasets/SmallGEMMDataset.h" #include "tests/datasets/TinyGEMMDataset.h" #include "tests/framework/Asserts.h" #include "tests/framework/Macros.h" #include "tests/framework/datasets/Datasets.h" #include "tests/validation/Validation.h" #include "tests/validation/fixtures/GEMMFixture.h" #include "tests/validation/fixtures/GEMMInterleave4x4Fixture.h" #include "tests/validation/fixtures/GEMMTranspose1xWFixture.h" namespace arm_compute { namespace test { namespace validation { namespace { constexpr AbsoluteTolerance tolerance_f(0.001f); /**< Tolerance value for comparing reference's output against implementation's output for FP32 data types */ #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC RelativeTolerance rel_tolerance_f16(half(0.2)); /**< Relative tolerance value for comparing reference's output against implementation's output for FP16 data types */ const AbsoluteTolerance abs_tolerance_f16(0.2f); /**< Absolute tolerance value for comparing reference's output against implementation's output for FP16 data types */ constexpr float tolerance_num = 0.07f; /**< Tolerance number for FP16 data types */ #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ /** CNN data types */ const auto CNNDataTypes = framework::dataset::make("DataType", { #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC DataType::F16, #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ DataType::F32, }); const auto data_interleave = framework::dataset::make("M", 8, 12) * framework::dataset::make("N", 8, 12); const auto data_transpose = framework::dataset::make("M", 8, 14) * framework::dataset::make("N", 7, 14); /** Zero padding test */ template bool validate_zero_padding(unsigned int dim0_value, unsigned int dim1_value) { const TensorShape in_shape(dim0_value, dim1_value); // Create tensors Tensor in = create_tensor(in_shape, DataType::U32); Tensor dst; ARM_COMPUTE_EXPECT(in.info()->is_resizable(), framework::LogLevel::ERRORS); // Validate zero-padding FunctionType func; func.configure(&in, &dst); return in.info()->padding().empty(); } /* Zero padding test for GEMM kernels */ bool validate_gemm_zero_padding(const TensorShape shape0, const TensorShape shape1) { // Create tensors Tensor in0 = create_tensor(shape0, DataType::F32); Tensor in1 = create_tensor(shape1, DataType::F32); Tensor dst; // Validate zero-padding NEGEMMMatrixMultiplyKernel gemm; gemm.configure(&in0, &in1, &dst, 1.0, false); return in0.info()->padding().empty() && in1.info()->padding().empty() && dst.info()->padding().empty(); } } // namespace TEST_SUITE(NEON) TEST_SUITE(GEMM) TEST_SUITE(TRANSPOSE_1XW) using NEGEMMTranspose1xW = NESynthetizeFunctionWithZeroConstantBorder; DATA_TEST_CASE(ValidateZeroPadding, framework::DatasetMode::ALL, zip( framework::dataset::make("N", { 1, 23, 63, 101 }), framework::dataset::make("K", { 1, 47, 29, 27 })), n_value, k_value) { bool status = validate_zero_padding(n_value, k_value); ARM_COMPUTE_EXPECT(status, framework::LogLevel::ERRORS); } TEST_SUITE(U32) using NEGEMMTranspose1xWFixture = GEMMTranspose1xWValidationFixture; FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMTranspose1xWFixture, framework::DatasetMode::PRECOMMIT, data_transpose * framework::dataset::make("DataType", DataType::U32)) { // Validate output validate(Accessor(_target), _reference); } TEST_SUITE_END() // U32 TEST_SUITE(U16) using NEGEMMTranspose1xWFixture = GEMMTranspose1xWValidationFixture; FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMTranspose1xWFixture, framework::DatasetMode::PRECOMMIT, data_transpose * framework::dataset::make("DataType", DataType::U16)) { // Validate output validate(Accessor(_target), _reference); } TEST_SUITE_END() // U16 TEST_SUITE(U8) using NEGEMMTranspose1xWFixture = GEMMTranspose1xWValidationFixture; FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMTranspose1xWFixture, framework::DatasetMode::PRECOMMIT, data_transpose * framework::dataset::make("DataType", DataType::U8)) { // Validate output validate(Accessor(_target), _reference); } TEST_SUITE_END() // U8 TEST_SUITE_END() // TRANSPOSE_1XW TEST_SUITE(INTERLEAVE_4X4) using NEGEMMInterleave4x4 = NESynthetizeFunctionWithZeroConstantBorder; DATA_TEST_CASE(ValidateZeroPadding, framework::DatasetMode::ALL, zip( framework::dataset::make("M", { 1, 23, 63, 101 }), framework::dataset::make("K", { 1, 47, 29, 27 })), m_value, k_value) { bool status = validate_zero_padding(m_value, k_value); ARM_COMPUTE_EXPECT(status, framework::LogLevel::ERRORS); } TEST_SUITE(U32) using NEGEMMInterleave4x4Fixture = GEMMInterleave4x4ValidationFixture; FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMInterleave4x4Fixture, framework::DatasetMode::PRECOMMIT, data_interleave * framework::dataset::make("DataType", DataType::U32)) { // Validate output validate(Accessor(_target), _reference); } TEST_SUITE_END() // U32 TEST_SUITE(U16) using NEGEMMInterleave4x4Fixture = GEMMInterleave4x4ValidationFixture; FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMInterleave4x4Fixture, framework::DatasetMode::PRECOMMIT, data_interleave * framework::dataset::make("DataType", DataType::U16)) { // Validate output validate(Accessor(_target), _reference); } TEST_SUITE_END() // U16 TEST_SUITE(U8) using NEGEMMInterleave4x4Fixture = GEMMInterleave4x4ValidationFixture; FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMInterleave4x4Fixture, framework::DatasetMode::PRECOMMIT, data_interleave * framework::dataset::make("DataType", DataType::QASYMM8)) { // Validate output validate(Accessor(_target), _reference); } TEST_SUITE_END() // U8 TEST_SUITE_END() // INTERLEAVE_4X4 template using NEGEMMFixture = GEMMValidationFixture; template using NEGEMMFixtureDisabledC = GEMMValidationFixture; TEST_SUITE(Float) DATA_TEST_CASE(ValidateZeroPadding, framework::DatasetMode::ALL, zip(framework::dataset::make("In0", { TensorShape(21U, 13U), TensorShape(31U, 1U), TensorShape(31U, 1U), TensorShape(8U, 2U), TensorShape(38U, 12U), TensorShape(32U, 1U) }), framework::dataset::make("In1", { TensorShape(33U, 21U), TensorShape(23U, 31U), TensorShape(23U, 31U), TensorShape(16U, 8U), TensorShape(21U, 38U), TensorShape(17U, 32U) })), shape0, shape1) { bool status = validate_gemm_zero_padding(shape0, shape1); ARM_COMPUTE_EXPECT(status, framework::LogLevel::ERRORS); } #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC TEST_SUITE(FP16) FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMFixture, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallGEMMDataset(), framework::dataset::make("ReshapeWeights", { true, false })), framework::dataset::make("DataType", DataType::F16))) { // Validate output validate(Accessor(_target), _reference, rel_tolerance_f16, tolerance_num, abs_tolerance_f16); } FIXTURE_DATA_TEST_CASE(RunLarge, NEGEMMFixture, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeGEMMDataset(), framework::dataset::make("ReshapeWeights", { true, false })), framework::dataset::make("DataType", DataType::F16))) { // Validate output validate(Accessor(_target), _reference, rel_tolerance_f16, tolerance_num, abs_tolerance_f16); } TEST_SUITE_END() #endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ TEST_SUITE(FP32) FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMFixture, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallGEMMDataset(), framework::dataset::make("ReshapeWeights", { true, false })), framework::dataset::make("DataType", DataType::F32))) { // Validate output validate(Accessor(_target), _reference, tolerance_f); } FIXTURE_DATA_TEST_CASE(RunLarge, NEGEMMFixture, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeGEMMDataset(), framework::dataset::make("ReshapeWeights", { true, false })), framework::dataset::make("DataType", DataType::F32))) { // Validate output validate(Accessor(_target), _reference, tolerance_f); } TEST_SUITE(DisabledC) FIXTURE_DATA_TEST_CASE(RunSmall, NEGEMMFixtureDisabledC, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallGEMMDataset(), framework::dataset::make("ReshapeWeights", { true, false })), framework::dataset::make("DataType", DataType::F32))) { // Validate output validate(Accessor(_target), _reference, tolerance_f); } TEST_SUITE_END() TEST_SUITE_END() TEST_SUITE_END() TEST_SUITE_END() TEST_SUITE_END() } // namespace validation } // namespace test } // namespace arm_compute