/* * 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/CL/CLTensor.h" #include "arm_compute/runtime/CL/CLTensorAllocator.h" #include "arm_compute/runtime/CL/functions/CLPoolingLayer.h" #include "tests/CL/CLAccessor.h" #include "tests/PaddingCalculator.h" #include "tests/datasets/PoolingLayerDataset.h" #include "tests/datasets/PoolingTypesDataset.h" #include "tests/datasets/ShapeDatasets.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/PoolingLayerFixture.h" namespace arm_compute { namespace test { namespace validation { namespace { /** Input data sets for floating-point data types */ const auto PoolingLayerDatasetFP = combine(combine(combine(datasets::PoolingTypes(), framework::dataset::make("PoolingSize", { Size2D(2, 2), Size2D(3, 3), Size2D(5, 7) })), framework::dataset::make("PadStride", { PadStrideInfo(1, 1, 0, 0), PadStrideInfo(2, 1, 0, 0), PadStrideInfo(1, 2, 1, 1), PadStrideInfo(2, 2, 1, 0) })), framework::dataset::make("ExcludePadding", { true, false })); const auto PoolingLayerDatasetFPSmall = combine(combine(combine(datasets::PoolingTypes(), framework::dataset::make("PoolingSize", { Size2D(2, 2), Size2D(3, 3) })), framework::dataset::make("PadStride", { PadStrideInfo(1, 1, 0, 0), PadStrideInfo(2, 1, 0, 0) })), framework::dataset::make("ExcludePadding", { true, false })); /** Input data sets for asymmetric data type */ const auto PoolingLayerDatasetQASYMM8 = combine(concat(combine(combine(framework::dataset::make("PoolingType", { PoolingType::MAX, PoolingType::AVG, }), framework::dataset::make("PoolingSize", { Size2D(2, 2), Size2D(3, 3) })), framework::dataset::make("PadStride", { PadStrideInfo(1, 1, 0, 0), PadStrideInfo(1, 2, 1, 1), PadStrideInfo(2, 2, 1, 0) })), combine(combine(framework::dataset::make("PoolingType", { PoolingType::AVG }), framework::dataset::make("PoolingSize", { Size2D(5, 7) })), framework::dataset::make("PadStride", { PadStrideInfo(2, 1, 0, 0) }))), framework::dataset::make("ExcludePadding", { true })); const auto PoolingLayerDatasetQASYMM8Small = combine(combine(combine(framework::dataset::make("PoolingType", { PoolingType::MAX, PoolingType::AVG, }), framework::dataset::make("PoolingSize", { Size2D(2, 2), Size2D(5, 7) })), framework::dataset::make("PadStride", { PadStrideInfo(1, 2, 1, 1) })), framework::dataset::make("ExcludePadding", { true })); const auto PoolingLayerDatasetFPIndicesSmall = combine(combine(combine(framework::dataset::make("PoolingType", { PoolingType::MAX }), framework::dataset::make("PoolingSize", { Size2D(2, 2) })), framework::dataset::make("PadStride", { PadStrideInfo(1, 1, 0, 0), PadStrideInfo(2, 2, 0, 0) })), framework::dataset::make("ExcludePadding", { true, false })); constexpr AbsoluteTolerance tolerance_f32(0.001f); /**< Tolerance value for comparing reference's output against implementation's output for 32-bit floating-point type */ constexpr AbsoluteTolerance tolerance_f16(0.01f); /**< Tolerance value for comparing reference's output against implementation's output for 16-bit floating-point type */ constexpr AbsoluteTolerance tolerance_qasymm8(1); /**< Tolerance value for comparing reference's output against implementation's output for 8-bit asymmetric type */ constexpr AbsoluteTolerance tolerance_qasymm8_s(1); /**< Tolerance value for comparing reference's output against implementation's output for 8-bit signed asymmetric type */ const auto pool_data_layout_dataset = framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC }); const auto pool_fp_mixed_precision_dataset = framework::dataset::make("FpMixedPrecision", { true, false }); } // namespace TEST_SUITE(CL) TEST_SUITE(PoolingLayer) // *INDENT-OFF* // clang-format off DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip( framework::dataset::make("InputInfo", { TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Mismatching data type TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Invalid pad/size combination TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Invalid pad/size combination TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QASYMM8), // Invalid parameters TensorInfo(TensorShape(15U, 13U, 5U), 1, DataType::F32), // Non-rectangular Global Pooling TensorInfo(TensorShape(13U, 13U, 5U), 1, DataType::F32), // Invalid output Global Pooling TensorInfo(TensorShape(13U, 13U, 5U), 1, DataType::QASYMM8), TensorInfo(TensorShape(13U, 13U, 5U), 1, DataType::F32), TensorInfo(TensorShape(1U, 16U, 1U), 1, DataType::F32), }), framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(25U, 11U, 2U), 1, DataType::F16), TensorInfo(TensorShape(30U, 11U, 2U), 1, DataType::F32), TensorInfo(TensorShape(25U, 16U, 2U), 1, DataType::F32), TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QASYMM8), TensorInfo(TensorShape(1U, 1U, 5U), 1, DataType::F32), TensorInfo(TensorShape(2U, 2U, 5U), 1, DataType::F32), TensorInfo(TensorShape(12U, 12U, 5U), 1, DataType::QASYMM8), TensorInfo(TensorShape(1U, 1U, 5U), 1, DataType::F32), TensorInfo(TensorShape(1U, 15U, 1U), 1, DataType::F32), })), framework::dataset::make("PoolInfo", { PoolingLayerInfo(PoolingType::AVG, 3, DataLayout::NCHW, PadStrideInfo(1, 1, 0, 0)), PoolingLayerInfo(PoolingType::AVG, 2, DataLayout::NCHW, PadStrideInfo(1, 1, 2, 0)), PoolingLayerInfo(PoolingType::AVG, 2, DataLayout::NCHW, PadStrideInfo(1, 1, 0, 2)), PoolingLayerInfo(PoolingType::L2, 3, DataLayout::NCHW, PadStrideInfo(1, 1, 0, 0)), PoolingLayerInfo(PoolingType::AVG, DataLayout::NCHW), PoolingLayerInfo(PoolingType::MAX, DataLayout::NCHW), PoolingLayerInfo(PoolingType::AVG, 2, DataLayout::NHWC, PadStrideInfo(), false), PoolingLayerInfo(PoolingType::AVG, DataLayout::NCHW), PoolingLayerInfo(PoolingType::MAX, 2, DataLayout::NHWC, PadStrideInfo(1, 1, 0, 0), false), })), framework::dataset::make("Expected", { false, false, false, false, true, false, true, true , false})), input_info, output_info, pool_info, expected) { ARM_COMPUTE_EXPECT(bool(CLPoolingLayer::validate(&input_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), pool_info)) == expected, framework::LogLevel::ERRORS); } // clang-format on // *INDENT-ON* template using CLPoolingLayerFixture = PoolingLayerValidationFixture; template using CLPoolingLayerMixedDataLayoutFixture = PoolingLayerValidationFixture; template using CLSpecialPoolingLayerFixture = SpecialPoolingLayerValidationFixture; template using CLMixedPrecesionPoolingLayerFixture = PoolingLayerValidationMixedPrecisionFixture; template using CLPoolingLayerIndicesFixture = PoolingLayerIndicesValidationFixture; TEST_SUITE(Float) TEST_SUITE(FP32) FIXTURE_DATA_TEST_CASE(RunSpecial, CLSpecialPoolingLayerFixture, framework::DatasetMode::ALL, datasets::PoolingLayerDatasetSpecial() * framework::dataset::make("DataType", DataType::F32)) { // Validate output validate(CLAccessor(_target), _reference, tolerance_f32); } FIXTURE_DATA_TEST_CASE(RunSmall, CLPoolingLayerFixture, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallShapes(), combine(PoolingLayerDatasetFPSmall, framework::dataset::make("DataType", DataType::F32))), pool_data_layout_dataset)) { // Validate output validate(CLAccessor(_target), _reference, tolerance_f32); } FIXTURE_DATA_TEST_CASE(RunMixedDataLayout, CLPoolingLayerMixedDataLayoutFixture, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallShapes(), combine(combine(combine(combine(datasets::PoolingTypes(), framework::dataset::make("PoolingSize", { Size2D(2, 2) })), framework::dataset::make("PadStride", { PadStrideInfo(2, 1, 0, 0) })), framework::dataset::make("ExcludePadding", { false })), framework::dataset::make("DataType", DataType::F32))), pool_data_layout_dataset)) { // Validate output validate(CLAccessor(_target), _reference, tolerance_f32); } FIXTURE_DATA_TEST_CASE(RunLarge, CLPoolingLayerFixture, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeShapes(), combine(PoolingLayerDatasetFP, framework::dataset::make("DataType", DataType::F32))), pool_data_layout_dataset)) { // Validate output validate(CLAccessor(_target), _reference, tolerance_f32); } FIXTURE_DATA_TEST_CASE(RunSmallIndices, CLPoolingLayerIndicesFixture, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallShapes(), combine(PoolingLayerDatasetFPIndicesSmall, framework::dataset::make("DataType", DataType::F32))), pool_data_layout_dataset)) { // Validate output validate(CLAccessor(_target), _reference, tolerance_f32); validate(CLAccessor(_target_indices), _ref_indices); } TEST_SUITE(GlobalPooling) // *INDENT-OFF* // clang-format off FIXTURE_DATA_TEST_CASE(RunSmall, CLPoolingLayerFixture, framework::DatasetMode::ALL, combine(combine(combine(combine(combine(combine( framework::dataset::make("InputShape", { TensorShape(27U, 13U, 2U), TensorShape(27U, 13U, 2U, 4U) }), framework::dataset::make("PoolingType", { PoolingType::AVG, PoolingType::L2, PoolingType::MAX })), framework::dataset::make("PoolingSize", { Size2D(27, 13) })), framework::dataset::make("PadStride", PadStrideInfo(1, 1, 0, 0))), framework::dataset::make("ExcludePadding", false)), framework::dataset::make("DataType", DataType::F32)), framework::dataset::make("DataLayout", DataLayout::NHWC))) { // Validate output validate(CLAccessor(_target), _reference, tolerance_f32); } FIXTURE_DATA_TEST_CASE(RunLarge, CLPoolingLayerFixture, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(combine(combine( framework::dataset::make("InputShape", { TensorShape(79U, 37U, 11U), TensorShape(79U, 37U, 11U, 4U) }), framework::dataset::make("PoolingType", { PoolingType::AVG, PoolingType::L2, PoolingType::MAX })), framework::dataset::make("PoolingSize", { Size2D(79, 37) })), framework::dataset::make("PadStride", PadStrideInfo(1, 1, 0, 0))), framework::dataset::make("ExcludePadding", false)), framework::dataset::make("DataType", DataType::F32)), framework::dataset::make("DataLayout", DataLayout::NHWC))) { // Validate output validate(CLAccessor(_target), _reference, tolerance_f32); } // clang-format on // *INDENT-ON* TEST_SUITE_END() // GlobalPooling TEST_SUITE_END() // FP32 TEST_SUITE(FP16) FIXTURE_DATA_TEST_CASE(RunSmall, CLMixedPrecesionPoolingLayerFixture, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::SmallShapes(), combine(PoolingLayerDatasetFPSmall, framework::dataset::make("DataType", DataType::F16))), pool_data_layout_dataset), pool_fp_mixed_precision_dataset)) { // Validate output validate(CLAccessor(_target), _reference, tolerance_f16); } FIXTURE_DATA_TEST_CASE(RunLarge, CLMixedPrecesionPoolingLayerFixture, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::LargeShapes(), combine(PoolingLayerDatasetFP, framework::dataset::make("DataType", DataType::F16))), pool_data_layout_dataset), pool_fp_mixed_precision_dataset)) { // Validate output validate(CLAccessor(_target), _reference, tolerance_f16); } FIXTURE_DATA_TEST_CASE(RunSmallIndices, CLPoolingLayerIndicesFixture, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallShapes(), combine(PoolingLayerDatasetFPIndicesSmall, framework::dataset::make("DataType", DataType::F16))), pool_data_layout_dataset)) { // Validate output validate(CLAccessor(_target), _reference, tolerance_f32); validate(CLAccessor(_target_indices), _ref_indices); } TEST_SUITE(GlobalPooling) // *INDENT-OFF* // clang-format off FIXTURE_DATA_TEST_CASE(RunSmall, CLPoolingLayerFixture, framework::DatasetMode::ALL, combine(combine(combine(combine(combine(combine( framework::dataset::make("InputShape", { TensorShape(27U, 13U, 2U), TensorShape(27U, 13U, 2U, 4U) }), framework::dataset::make("PoolingType", { PoolingType::AVG, PoolingType::L2, PoolingType::MAX })), framework::dataset::make("PoolingSize", { Size2D(27, 13) })), framework::dataset::make("PadStride", PadStrideInfo(1, 1, 0, 0))), framework::dataset::make("ExcludePadding", false)), framework::dataset::make("DataType", DataType::F16)), framework::dataset::make("DataLayout", DataLayout::NHWC))) { // Validate output validate(CLAccessor(_target), _reference, tolerance_f16); } FIXTURE_DATA_TEST_CASE(RunLarge, CLPoolingLayerFixture, framework::DatasetMode::NIGHTLY, combine(combine(combine(combine(combine(combine( framework::dataset::make("InputShape", { TensorShape(79U, 37U, 11U), TensorShape(79U, 37U, 11U, 4U) }), framework::dataset::make("PoolingType", { PoolingType::AVG, PoolingType::L2, PoolingType::MAX })), framework::dataset::make("PoolingSize", { Size2D(79, 37) })), framework::dataset::make("PadStride", PadStrideInfo(1, 1, 0, 0))), framework::dataset::make("ExcludePadding", false)), framework::dataset::make("DataType", DataType::F16)), framework::dataset::make("DataLayout", DataLayout::NHWC))) { // Validate output validate(CLAccessor(_target), _reference, tolerance_f16); } // clang-format on // *INDENT-ON* TEST_SUITE_END() // GlobalPooling TEST_SUITE_END() // FP16 TEST_SUITE_END() // Float TEST_SUITE(Quantized) template using CLPoolingLayerQuantizedFixture = PoolingLayerValidationQuantizedFixture; template using CLPoolingLayerQuantizedMixedDataLayoutFixture = PoolingLayerValidationQuantizedFixture; TEST_SUITE(QASYMM8) FIXTURE_DATA_TEST_CASE(RunSmall, CLPoolingLayerQuantizedFixture, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallShapes(), combine(PoolingLayerDatasetQASYMM8Small, framework::dataset::make("DataType", DataType::QASYMM8))), pool_data_layout_dataset), framework::dataset::make("InputQuantInfo", { QuantizationInfo(1.f / 255.f, 10), QuantizationInfo(1.f / 255.f, 10) })), framework::dataset::make("OutputQuantInfo", { QuantizationInfo(1.f / 255.f, 5), QuantizationInfo(1.f / 255.f, 10) }))) { // Validate output validate(CLAccessor(_target), _reference, tolerance_qasymm8); } FIXTURE_DATA_TEST_CASE(RunMixedDataLayout, CLPoolingLayerQuantizedMixedDataLayoutFixture, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallShapes(), combine(combine(combine(combine(framework::dataset::make("PoolingType", { PoolingType::MAX, PoolingType::AVG }), framework::dataset::make("PoolingSize", { Size2D(2, 2) })), framework::dataset::make("PadStride", { PadStrideInfo(1, 2, 1, 1) })), framework::dataset::make("ExcludePadding", { true })), framework::dataset::make("DataType", DataType::QASYMM8))), framework::dataset::make("DataLayout", { DataLayout::NHWC, DataLayout::NCHW })), framework::dataset::make("InputQuantInfo", { QuantizationInfo(1.f / 255.f, 10) })), framework::dataset::make("OutputQuantInfo", { QuantizationInfo(1.f / 255.f, 5) }))) { // Validate output validate(CLAccessor(_target), _reference, tolerance_qasymm8); } TEST_SUITE_END() // QASYMM8 TEST_SUITE(QASYMM8_SIGNED) FIXTURE_DATA_TEST_CASE(RunSmall, CLPoolingLayerQuantizedFixture, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallShapes(), combine(PoolingLayerDatasetQASYMM8Small, framework::dataset::make("DataType", DataType::QASYMM8_SIGNED))), pool_data_layout_dataset), framework::dataset::make("InputQuantInfo", { QuantizationInfo(1.f / 127.f, -10), QuantizationInfo(1.f / 127.f, -10) })), framework::dataset::make("OutputQuantInfo", { QuantizationInfo(1.f / 127.f, -5), QuantizationInfo(1.f / 127.f, -10) }))) { // Validate output validate(CLAccessor(_target), _reference, tolerance_qasymm8_s); } FIXTURE_DATA_TEST_CASE(RunMixedDataLayout, CLPoolingLayerQuantizedMixedDataLayoutFixture, framework::DatasetMode::PRECOMMIT, combine(combine(combine(combine(datasets::SmallShapes(), combine(combine(combine(combine(framework::dataset::make("PoolingType", { PoolingType::MAX, PoolingType::AVG }), framework::dataset::make("PoolingSize", { Size2D(2, 2) })), framework::dataset::make("PadStride", { PadStrideInfo(1, 2, 1, 1) })), framework::dataset::make("ExcludePadding", { true })), framework::dataset::make("DataType", DataType::QASYMM8_SIGNED))), framework::dataset::make("DataLayout", { DataLayout::NHWC, DataLayout::NCHW })), framework::dataset::make("InputQuantInfo", { QuantizationInfo(1.f / 127.f, -10) })), framework::dataset::make("OutputQuantInfo", { QuantizationInfo(1.f / 127.f, -10) }))) { // Validate output validate(CLAccessor(_target), _reference, tolerance_qasymm8_s); } TEST_SUITE_END() // QASYMM8_SIGNED TEST_SUITE_END() // Quantized TEST_SUITE_END() // PoolingLayer TEST_SUITE_END() // CL } // namespace validation } // namespace test } // namespace arm_compute