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234 lines
16 KiB
234 lines
16 KiB
/*
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* Copyright (c) 2023 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/dynamic_fusion/sketch/gpu/operators/GpuPool2d.h"
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#include "tests/CL/CLAccessor.h"
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#include "tests/datasets/ShapeDatasets.h"
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#include "tests/datasets/dynamic_fusion/PoolingLayerDataset.h"
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#include "tests/framework/Fixture.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/dynamic_fusion/gpu/cl/Pool2dFixture.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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TEST_SUITE(CL)
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TEST_SUITE(DYNAMIC_FUSION)
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TEST_SUITE(POOL2D)
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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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const auto PoolingLayerDatasetFP = combine(combine(combine(combine(framework::dataset::make("PoolingType", { PoolingType::MAX, PoolingType::AVG }), framework::dataset::make("PoolingSize", { Size2D(2, 2), Size2D(3, 3) })),
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framework::dataset::make("Pad", { Padding2D() })),
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framework::dataset::make("Stride", { Size2D(1, 1), Size2D(2, 1), Size2D(5, 7) })),
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framework::dataset::make("ExcludePadding", { true }));
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const auto pool_fp_mixed_precision_dataset = framework::dataset::make("FpMixedPrecision", { true, false });
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template <typename T>
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using DynamicFusionGpuPool2dFixture = DynamicFusionGpuPool2dValidationFixture<CLTensor, CLAccessor, GpuPool2d, T>;
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template <typename T>
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using DFSpecialGpuPool2dFixture = DynamicFusionGpuPool2dSpecialValidationFixture<CLTensor, CLAccessor, GpuPool2d, T>;
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template <typename T>
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using DFPoolMixedPrecisionFixture = DynamicFusionGpuPool2dMixedPrecisionValidationFixture<CLTensor, CLAccessor, GpuPool2d, T>;
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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(2U, 27U, 13U), 1, DataType::F32, DataLayout::NHWC), // Mismatching data type
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TensorInfo(TensorShape(2U, 27U, 13U), 1, DataType::F32, DataLayout::NHWC), // Invalid pad/size combination
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TensorInfo(TensorShape(2U, 27U, 13U), 1, DataType::F32, DataLayout::NHWC), // Invalid pad/size combination
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TensorInfo(TensorShape(2U, 27U, 13U), 1, DataType::QASYMM8, DataLayout::NHWC), // Invalid parameters, unsupported pooling
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TensorInfo(TensorShape(5U, 15U, 13U), 1, DataType::F32, DataLayout::NHWC), // Valid Non-rectangular Global Pooling
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TensorInfo(TensorShape(5U, 13U, 13U), 1, DataType::F32, DataLayout::NHWC), // Invalid output Global Pooling
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TensorInfo(TensorShape(5U, 13U, 13U), 1, DataType::QASYMM8, DataLayout::NHWC), // Invalid - Quantized not supported.
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TensorInfo(TensorShape(5U, 13U, 13U), 1, DataType::F32, DataLayout::NHWC), // Valid global pooling
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TensorInfo(TensorShape(13U, 13U, 5U), 1, DataType::F32, DataLayout::NCHW), // Unsupported data layout
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}),
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framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(2U, 25U, 11U), 1, DataType::F16, DataLayout::NHWC),
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TensorInfo(TensorShape(2U, 30U, 11U), 1, DataType::F32, DataLayout::NHWC),
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TensorInfo(TensorShape(2U, 25U, 16U), 1, DataType::F32, DataLayout::NHWC),
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TensorInfo(TensorShape(2U, 27U, 13U), 1, DataType::QASYMM8, DataLayout::NHWC),
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TensorInfo(TensorShape(5U, 1U, 1U), 1, DataType::F32, DataLayout::NHWC),
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TensorInfo(TensorShape(5U, 2U, 2U), 1, DataType::F32, DataLayout::NHWC),
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TensorInfo(TensorShape(5U, 12U, 12U), 1, DataType::QASYMM8, DataLayout::NHWC),
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TensorInfo(TensorShape(5U, 1U, 1U), 1, DataType::F32, DataLayout::NHWC),
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TensorInfo(TensorShape(1U, 1U, 5U), 1, DataType::F32, DataLayout::NHWC),
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})),
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framework::dataset::make("Pool2dAttributes", {
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Pool2dAttributes().pool_type(PoolingType::AVG).pool_size(Size2D(3,3)).pad(Padding2D(0,0,0,0)).stride(Size2D(1,1)),
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Pool2dAttributes().pool_type(PoolingType::AVG).pool_size(Size2D(2,2)).pad(Padding2D(2,2,0,0)).stride(Size2D(1,1)),
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Pool2dAttributes().pool_type(PoolingType::AVG).pool_size(Size2D(2,2)).pad(Padding2D(0,0,2,2)).stride(Size2D(1,1)),
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Pool2dAttributes().pool_type(PoolingType::L2).pool_size(Size2D(3,3)).pad(Padding2D(0,0,0,0)).stride(Size2D(1,1)),
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Pool2dAttributes().pool_type(PoolingType::AVG).pool_size(Size2D(15U, 13U)),
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Pool2dAttributes().pool_type(PoolingType::MAX).pool_size(Size2D(13U, 13U)),
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Pool2dAttributes().pool_type(PoolingType::AVG).pool_size(Size2D(2,2)).pad(Padding2D()).stride(Size2D(1,1)),
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Pool2dAttributes().pool_type(PoolingType::AVG).pool_size(Size2D(13U,13U)),
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Pool2dAttributes().pool_type(PoolingType::AVG).pool_size(Size2D(13U,13U)),
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})),
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framework::dataset::make("Expected", { false, false, false, false, true, false, false, true, false })),
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input_info, output_info, pool2d_attr, expected)
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{
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// Create a new workload sketch
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auto cl_compile_ctx = CLKernelLibrary::get().get_compile_context();
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auto gpu_ctx = GpuWorkloadContext{ &cl_compile_ctx };
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GpuWorkloadSketch sketch{ &gpu_ctx };
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// Declare GpuPool2d settings
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const GpuPool2dSettings &settings = GpuPool2dSettings().mixed_precision(false);
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// Validate Pool2d Configuration
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auto src_info = sketch.create_tensor_info(input_info);
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auto dst_info = sketch.create_tensor_info(output_info);
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bool res = bool(GpuPool2d::validate_op(sketch, &src_info, &dst_info, pool2d_attr, settings));
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ARM_COMPUTE_EXPECT(res == 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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TEST_SUITE(Float)
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TEST_SUITE(FP32)
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FIXTURE_DATA_TEST_CASE(RunSmall, DynamicFusionGpuPool2dFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallNoneUnitShapes(), PoolingLayerDatasetFP),
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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(RunLarge, DynamicFusionGpuPool2dFixture<float>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeShapes(), PoolingLayerDatasetFP),
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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(RunSpecial, DFSpecialGpuPool2dFixture<float>, framework::DatasetMode::ALL, combine(datasets::PoolingLayerDatasetSpecialDynamicFusion(),
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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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TEST_SUITE(GlobalPooling)
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FIXTURE_DATA_TEST_CASE(RunSmall, DynamicFusionGpuPool2dFixture<float>, framework::DatasetMode::ALL,
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combine(combine(combine(combine(combine(combine(
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framework::dataset::make("InputShape", { TensorShape(27U, 13U, 2U),
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TensorShape(27U, 13U, 2U, 4U)
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}),
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framework::dataset::make("PoolingType", { PoolingType::AVG, PoolingType::MAX })),
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framework::dataset::make("PoolingSize", { Size2D(27, 13) })),
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framework::dataset::make("Pad", { Padding2D() })),
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framework::dataset::make("Stride", { Size2D(1, 1) })),
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framework::dataset::make("ExcludePadding", true)),
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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(RunLarge, DynamicFusionGpuPool2dFixture<float>, framework::DatasetMode::NIGHTLY,
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combine(combine(combine(combine(combine(combine(
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framework::dataset::make("InputShape", { TensorShape(79U, 37U, 11U),
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TensorShape(79U, 37U, 11U, 4U)
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}),
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framework::dataset::make("PoolingType", { PoolingType::AVG, PoolingType::MAX })),
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framework::dataset::make("PoolingSize", { Size2D(79, 37) })),
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framework::dataset::make("Pad", { Padding2D() })),
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framework::dataset::make("Stride", { Size2D(1, 1) })),
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framework::dataset::make("ExcludePadding", true)),
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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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TEST_SUITE_END() // GlobalPooling
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TEST_SUITE_END() // FP32
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TEST_SUITE(FP16)
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FIXTURE_DATA_TEST_CASE(RunSmall, DFPoolMixedPrecisionFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::SmallNoneUnitShapes(), PoolingLayerDatasetFP),
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framework::dataset::make("DataType", DataType::F16)),
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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, DFPoolMixedPrecisionFixture<half>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::LargeShapes(), PoolingLayerDatasetFP),
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framework::dataset::make("DataType", DataType::F16)),
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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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TEST_SUITE(GlobalPooling)
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FIXTURE_DATA_TEST_CASE(RunSmall, DynamicFusionGpuPool2dFixture<half>, framework::DatasetMode::ALL,
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combine(combine(combine(combine(combine(combine(
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framework::dataset::make("InputShape", { TensorShape(27U, 13U, 2U),
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TensorShape(27U, 13U, 2U, 4U)
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}),
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framework::dataset::make("PoolingType", { PoolingType::AVG, PoolingType::MAX })),
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framework::dataset::make("PoolingSize", { Size2D(27, 13) })),
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framework::dataset::make("Pad", { Padding2D() })),
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framework::dataset::make("Stride", { Size2D(1, 1) })),
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framework::dataset::make("ExcludePadding", true)),
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framework::dataset::make("DataType", DataType::F16)))
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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, DynamicFusionGpuPool2dFixture<half>, framework::DatasetMode::NIGHTLY,
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combine(combine(combine(combine(combine(combine(
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framework::dataset::make("InputShape", { TensorShape(79U, 37U, 11U),
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TensorShape(79U, 37U, 11U, 4U)
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}),
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framework::dataset::make("PoolingType", { PoolingType::AVG, PoolingType::MAX })),
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framework::dataset::make("PoolingSize", { Size2D(79, 37) })),
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framework::dataset::make("Pad", { Padding2D() })),
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framework::dataset::make("Stride", { Size2D(1, 1) })),
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framework::dataset::make("ExcludePadding", true)),
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framework::dataset::make("DataType", DataType::F16)))
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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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TEST_SUITE_END() // GlobalPooling
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TEST_SUITE_END() // FP16
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TEST_SUITE_END() // FLOAT
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TEST_SUITE_END() // POOL2D
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TEST_SUITE_END() // DYNAMIC_FUSION
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TEST_SUITE_END() // CL
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}
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}
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}
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