239 lines
16 KiB
C++
239 lines
16 KiB
C++
/*
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* Copyright (c) 2017-2020 Arm Limited.
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*
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* SPDX-License-Identifier: MIT
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*
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* Permission is hereby granted, free of charge, to any person obtaining a copy
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* of this software and associated documentation files (the "Software"), to
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* deal in the Software without restriction, including without limitation the
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* rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
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* sell copies of the Software, and to permit persons to whom the Software is
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* furnished to do so, subject to the following conditions:
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*
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* The above copyright notice and this permission notice shall be included in all
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* copies or substantial portions of the Software.
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*
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* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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* SOFTWARE.
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*/
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#include "arm_compute/core/Types.h"
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#include "arm_compute/runtime/CL/CLTensor.h"
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#include "arm_compute/runtime/CL/CLTensorAllocator.h"
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#include "arm_compute/runtime/CL/functions/CLPoolingLayer.h"
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#include "tests/CL/CLAccessor.h"
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#include "tests/PaddingCalculator.h"
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#include "tests/datasets/PoolingLayerDataset.h"
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#include "tests/datasets/PoolingTypesDataset.h"
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#include "tests/datasets/ShapeDatasets.h"
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#include "tests/framework/Asserts.h"
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#include "tests/framework/Macros.h"
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#include "tests/framework/datasets/Datasets.h"
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#include "tests/validation/Validation.h"
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#include "tests/validation/fixtures/PoolingLayerFixture.h"
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namespace arm_compute
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{
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namespace test
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{
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namespace validation
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{
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namespace
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{
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/** Input data sets for floating-point data types */
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const auto PoolingLayerDatasetFP = combine(combine(combine(datasets::PoolingTypes(), framework::dataset::make("PoolingSize", { Size2D(2, 2), Size2D(3, 3), Size2D(5, 7) })),
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framework::dataset::make("PadStride", { PadStrideInfo(1, 1, 0, 0), PadStrideInfo(2, 1, 0, 0), PadStrideInfo(1, 2, 1, 1), PadStrideInfo(2, 2, 1, 0) })),
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framework::dataset::make("ExcludePadding", { true, false }));
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const auto PoolingLayerDatasetFPSmall = combine(combine(combine(datasets::PoolingTypes(), framework::dataset::make("PoolingSize", { Size2D(2, 2), Size2D(3, 3) })),
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framework::dataset::make("PadStride", { PadStrideInfo(1, 1, 0, 0), PadStrideInfo(2, 1, 0, 0) })),
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framework::dataset::make("ExcludePadding", { true, false }));
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/** Input data sets for asymmetric data type */
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const auto PoolingLayerDatasetQASYMM8 = combine(concat(combine(combine(framework::dataset::make("PoolingType",
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{
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PoolingType::MAX, PoolingType::AVG,
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}),
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framework::dataset::make("PoolingSize", { Size2D(2, 2), Size2D(3, 3) })),
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framework::dataset::make("PadStride", { PadStrideInfo(1, 1, 0, 0), PadStrideInfo(1, 2, 1, 1), PadStrideInfo(2, 2, 1, 0) })),
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combine(combine(framework::dataset::make("PoolingType", { PoolingType::AVG }), framework::dataset::make("PoolingSize", { Size2D(5, 7) })), framework::dataset::make("PadStride", { PadStrideInfo(2, 1, 0, 0) }))),
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framework::dataset::make("ExcludePadding", { true }));
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const auto PoolingLayerDatasetQASYMM8Small = combine(combine(combine(framework::dataset::make("PoolingType",
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{
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PoolingType::MAX, PoolingType::AVG,
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}),
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framework::dataset::make("PoolingSize", { Size2D(2, 2), Size2D(5, 7) })),
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framework::dataset::make("PadStride", { PadStrideInfo(1, 2, 1, 1) })),
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framework::dataset::make("ExcludePadding", { true }));
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const auto PoolingLayerDatasetFPIndicesSmall = combine(combine(combine(framework::dataset::make("PoolingType",
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{ PoolingType::MAX }),
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framework::dataset::make("PoolingSize", { Size2D(2, 2) })),
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framework::dataset::make("PadStride", { PadStrideInfo(1, 1, 0, 0), PadStrideInfo(2, 2, 0, 0) })),
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framework::dataset::make("ExcludePadding", { true, false }));
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constexpr AbsoluteTolerance<float> tolerance_f32(0.001f); /**< Tolerance value for comparing reference's output against implementation's output for 32-bit floating-point type */
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constexpr AbsoluteTolerance<float> tolerance_f16(0.01f); /**< Tolerance value for comparing reference's output against implementation's output for 16-bit floating-point type */
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constexpr AbsoluteTolerance<uint8_t> tolerance_qasymm8(1); /**< Tolerance value for comparing reference's output against implementation's output for 8-bit asymmetric type */
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constexpr AbsoluteTolerance<int8_t> tolerance_qasymm8_s(1); /**< Tolerance value for comparing reference's output against implementation's output for 8-bit signed asymmetric type */
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const auto pool_data_layout_dataset = framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC });
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const auto pool_fp_mixed_precision_dataset = framework::dataset::make("FpMixedPrecision", { true, false });
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} // namespace
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TEST_SUITE(CL)
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TEST_SUITE(PoolingLayer)
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// *INDENT-OFF*
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// clang-format off
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DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(
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framework::dataset::make("InputInfo", { TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Mismatching data type
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TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Invalid pad/size combination
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TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Invalid pad/size combination
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TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QASYMM8), // Invalid parameters
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TensorInfo(TensorShape(15U, 13U, 5U), 1, DataType::F32), // Non-rectangular Global Pooling
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TensorInfo(TensorShape(13U, 13U, 5U), 1, DataType::F32), // Invalid output Global Pooling
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TensorInfo(TensorShape(13U, 13U, 5U), 1, DataType::QASYMM8),
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TensorInfo(TensorShape(13U, 13U, 5U), 1, DataType::F32),
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}),
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framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(25U, 11U, 2U), 1, DataType::F16),
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TensorInfo(TensorShape(30U, 11U, 2U), 1, DataType::F32),
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TensorInfo(TensorShape(25U, 16U, 2U), 1, DataType::F32),
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TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::QASYMM8),
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TensorInfo(TensorShape(1U, 1U, 5U), 1, DataType::F32),
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TensorInfo(TensorShape(2U, 2U, 5U), 1, DataType::F32),
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TensorInfo(TensorShape(12U, 12U, 5U), 1, DataType::QASYMM8),
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TensorInfo(TensorShape(1U, 1U, 5U), 1, DataType::F32),
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})),
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framework::dataset::make("PoolInfo", { PoolingLayerInfo(PoolingType::AVG, 3, DataLayout::NCHW, PadStrideInfo(1, 1, 0, 0)),
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PoolingLayerInfo(PoolingType::AVG, 2, DataLayout::NCHW, PadStrideInfo(1, 1, 2, 0)),
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PoolingLayerInfo(PoolingType::AVG, 2, DataLayout::NCHW, PadStrideInfo(1, 1, 0, 2)),
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PoolingLayerInfo(PoolingType::L2, 3, DataLayout::NCHW, PadStrideInfo(1, 1, 0, 0)),
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PoolingLayerInfo(PoolingType::AVG, DataLayout::NCHW),
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PoolingLayerInfo(PoolingType::MAX, DataLayout::NCHW),
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PoolingLayerInfo(PoolingType::AVG, 2, DataLayout::NHWC, PadStrideInfo(), false),
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PoolingLayerInfo(PoolingType::AVG, DataLayout::NCHW),
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})),
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framework::dataset::make("Expected", { false, false, false, false, true, false, true, true })),
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input_info, output_info, pool_info, expected)
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{
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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);
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}
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// clang-format on
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// *INDENT-ON*
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template <typename T>
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using CLPoolingLayerFixture = PoolingLayerValidationFixture<CLTensor, CLAccessor, CLPoolingLayer, T>;
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template <typename T>
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using CLSpecialPoolingLayerFixture = SpecialPoolingLayerValidationFixture<CLTensor, CLAccessor, CLPoolingLayer, T>;
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template <typename T>
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using CLMixedPrecesionPoolingLayerFixture = PoolingLayerValidationMixedPrecisionFixture<CLTensor, CLAccessor, CLPoolingLayer, T>;
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template <typename T>
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using CLPoolingLayerIndicesFixture = PoolingLayerIndicesValidationFixture<CLTensor, CLAccessor, CLPoolingLayer, T>;
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TEST_SUITE(Float)
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TEST_SUITE(FP32)
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FIXTURE_DATA_TEST_CASE(RunSpecial, CLSpecialPoolingLayerFixture<float>, framework::DatasetMode::ALL, datasets::PoolingLayerDatasetSpecial() * framework::dataset::make("DataType", DataType::F32))
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{
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// Validate output
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validate(CLAccessor(_target), _reference, tolerance_f32);
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}
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FIXTURE_DATA_TEST_CASE(RunSmall, CLPoolingLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallShapes(), combine(PoolingLayerDatasetFPSmall,
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framework::dataset::make("DataType",
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DataType::F32))),
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pool_data_layout_dataset))
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{
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// Validate output
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validate(CLAccessor(_target), _reference, tolerance_f32);
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}
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FIXTURE_DATA_TEST_CASE(RunLarge, CLPoolingLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeShapes(), combine(PoolingLayerDatasetFP,
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framework::dataset::make("DataType",
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DataType::F32))),
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pool_data_layout_dataset))
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{
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// Validate output
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validate(CLAccessor(_target), _reference, tolerance_f32);
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}
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FIXTURE_DATA_TEST_CASE(RunSmallIndices, CLPoolingLayerIndicesFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallShapes(), combine(PoolingLayerDatasetFPIndicesSmall,
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framework::dataset::make("DataType",
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DataType::F32))),
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pool_data_layout_dataset))
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{
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// Validate output
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validate(CLAccessor(_target), _reference, tolerance_f32);
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validate(CLAccessor(_target_indices), _ref_indices);
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}
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TEST_SUITE_END() // FP32
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TEST_SUITE(FP16)
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FIXTURE_DATA_TEST_CASE(RunSmall, CLMixedPrecesionPoolingLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::SmallShapes(), combine(PoolingLayerDatasetFPSmall,
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framework::dataset::make("DataType", DataType::F16))),
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pool_data_layout_dataset),
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pool_fp_mixed_precision_dataset))
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{
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// Validate output
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validate(CLAccessor(_target), _reference, tolerance_f16);
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}
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FIXTURE_DATA_TEST_CASE(RunLarge, CLMixedPrecesionPoolingLayerFixture<half>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::LargeShapes(), combine(PoolingLayerDatasetFP,
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framework::dataset::make("DataType", DataType::F16))),
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pool_data_layout_dataset),
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pool_fp_mixed_precision_dataset))
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{
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// Validate output
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validate(CLAccessor(_target), _reference, tolerance_f16);
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}
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FIXTURE_DATA_TEST_CASE(RunSmallIndices, CLPoolingLayerIndicesFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallShapes(), combine(PoolingLayerDatasetFPIndicesSmall,
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framework::dataset::make("DataType",
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DataType::F16))),
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pool_data_layout_dataset))
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{
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// Validate output
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validate(CLAccessor(_target), _reference, tolerance_f32);
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validate(CLAccessor(_target_indices), _ref_indices);
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}
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TEST_SUITE_END() // FP16
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TEST_SUITE_END() // Float
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TEST_SUITE(Quantized)
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template <typename T>
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using CLPoolingLayerQuantizedFixture = PoolingLayerValidationQuantizedFixture<CLTensor, CLAccessor, CLPoolingLayer, T>;
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TEST_SUITE(QASYMM8)
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FIXTURE_DATA_TEST_CASE(RunSmall, CLPoolingLayerQuantizedFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallShapes(), combine(PoolingLayerDatasetQASYMM8Small,
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framework::dataset::make("DataType", DataType::QASYMM8))),
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pool_data_layout_dataset))
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{
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// Validate output
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validate(CLAccessor(_target), _reference, tolerance_qasymm8);
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}
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TEST_SUITE_END() // QASYMM8
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TEST_SUITE(QASYMM8_SIGNED)
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FIXTURE_DATA_TEST_CASE(RunSmall, CLPoolingLayerQuantizedFixture<int8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallShapes(), combine(PoolingLayerDatasetQASYMM8Small,
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framework::dataset::make("DataType", DataType::QASYMM8_SIGNED))),
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pool_data_layout_dataset))
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{
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// Validate output
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validate(CLAccessor(_target), _reference, tolerance_qasymm8_s);
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}
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TEST_SUITE_END() // QASYMM8_SIGNED
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TEST_SUITE_END() // Quantized
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TEST_SUITE_END() // PoolingLayer
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TEST_SUITE_END() // CL
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} // namespace validation
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} // namespace test
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} // namespace arm_compute
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