From a18d85c6d2c0025938c2dc10e553eb82c01922f2 Mon Sep 17 00:00:00 2001 From: Mohammed Suhail Munshi Date: Tue, 3 Jan 2023 10:16:16 +0000 Subject: Dynamic Fusion Pooling Layer 2d - Adds Dynamic fusion PoolingLayer2D as Unfusable Operator - Indices are not supported - Adds tests for F32/F16 Datatypes Resolves : [COMPMID-5520] Signed-off-by: Mohammed Suhail Munshi Change-Id: I0d112545eb9209c836bf9ea153069f8627531e0a Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/8893 Reviewed-by: Gunes Bayir Comments-Addressed: Arm Jenkins Tested-by: Arm Jenkins Benchmark: Arm Jenkins --- .../datasets/dynamic_fusion/PoolingLayerDataset.h | 122 +++++++++++ tests/validation/dynamic_fusion/gpu/cl/Pool2d.cpp | 233 +++++++++++++++++++++ .../fixtures/dynamic_fusion/gpu/cl/Pool2dFixture.h | 190 +++++++++++++++++ tests/validation/reference/PoolingLayer.cpp | 3 +- 4 files changed, 546 insertions(+), 2 deletions(-) create mode 100644 tests/datasets/dynamic_fusion/PoolingLayerDataset.h create mode 100644 tests/validation/dynamic_fusion/gpu/cl/Pool2d.cpp create mode 100644 tests/validation/fixtures/dynamic_fusion/gpu/cl/Pool2dFixture.h (limited to 'tests') diff --git a/tests/datasets/dynamic_fusion/PoolingLayerDataset.h b/tests/datasets/dynamic_fusion/PoolingLayerDataset.h new file mode 100644 index 0000000000..c4911f4940 --- /dev/null +++ b/tests/datasets/dynamic_fusion/PoolingLayerDataset.h @@ -0,0 +1,122 @@ +/* + * 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/TensorShape.h" +#include "arm_compute/core/Types.h" +#include "utils/TypePrinter.h" +#include "arm_compute/dynamic_fusion/sketch/attributes/Pool2dAttributes.h" + + +using Pool2dAttributes = arm_compute::experimental::dynamic_fusion::Pool2dAttributes; + +namespace arm_compute +{ +namespace test +{ +namespace datasets +{ + +class DynamicFusionPoolingLayerDataset +{ +public: + using type = std::tuple; + + struct iterator + { + iterator(std::vector::const_iterator src_it, + std::vector::const_iterator infos_it) + : _src_it{ std::move(src_it) }, + _infos_it{ std::move(infos_it) } + { + } + + std::string description() const + { + std::stringstream description; + description << "In=" << *_src_it << ":"; + description << "Info=" << *_infos_it << ":"; + return description.str(); + } + + DynamicFusionPoolingLayerDataset::type operator*() const + { + return std::make_tuple(*_src_it, *_infos_it); + } + + iterator &operator++() + { + ++_src_it; + ++_infos_it; + + return *this; + } + + private: + std::vector::const_iterator _src_it; + std::vector::const_iterator _infos_it; + }; + + iterator begin() const + { + return iterator(_src_shapes.begin(), _infos.begin()); + } + + int size() const + { + return std::min(_src_shapes.size(), _infos.size()); + } + + void add_config(TensorShape src, Pool2dAttributes info) + { + _src_shapes.emplace_back(std::move(src)); + _infos.emplace_back(std::move(info)); + } + +protected: + DynamicFusionPoolingLayerDataset() = default; + DynamicFusionPoolingLayerDataset(DynamicFusionPoolingLayerDataset &&) = default; + +private: + std::vector _src_shapes{}; + std::vector _infos{}; +}; + +// Special pooling dataset +class PoolingLayerDatasetSpecialDynamicFusion final : public DynamicFusionPoolingLayerDataset +{ +public: + PoolingLayerDatasetSpecialDynamicFusion() + { + // NCHW DataLayout + // Special cases + add_config(TensorShape(2U, 3U, 4U, 1U), Pool2dAttributes().pool_type(PoolingType::AVG).pool_size(Size2D(2,2)).stride(Size2D(3,3))); + add_config(TensorShape(60U, 52U, 3U, 2U), Pool2dAttributes().pool_type(PoolingType::AVG).pool_size(Size2D(100,100)).stride(Size2D(5,5)).pad(Padding2D(50,50,50,50))); + // Asymmetric padding + add_config(TensorShape(112U, 112U, 32U), Pool2dAttributes().pool_type(PoolingType::MAX).pool_size(Size2D(3,3)).pad(Padding2D(0,1,0,1)).stride(Size2D(2,2))); + add_config(TensorShape(14U, 14U, 832U), Pool2dAttributes().pool_type(PoolingType::MAX).pool_size(Size2D(2,2)).stride(Size2D(1,1)).pad(Padding2D(0,0,0,0))); + + } +}; +} // namespace datasets +} // namespace test +} // namespace arm_compute \ No newline at end of file diff --git a/tests/validation/dynamic_fusion/gpu/cl/Pool2d.cpp b/tests/validation/dynamic_fusion/gpu/cl/Pool2d.cpp new file mode 100644 index 0000000000..a7772aef4d --- /dev/null +++ b/tests/validation/dynamic_fusion/gpu/cl/Pool2d.cpp @@ -0,0 +1,233 @@ +/* + * 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/dynamic_fusion/sketch/gpu/operators/GpuPool2d.h" + +#include "tests/CL/CLAccessor.h" +#include "tests/datasets/ShapeDatasets.h" +#include "tests/datasets/dynamic_fusion/PoolingLayerDataset.h" +#include "tests/framework/Fixture.h" +#include "tests/framework/Macros.h" +#include "tests/framework/datasets/Datasets.h" +#include "tests/validation/Validation.h" +#include "tests/validation/fixtures/dynamic_fusion/gpu/cl/Pool2dFixture.h" + +namespace arm_compute +{ +namespace test +{ +namespace validation +{ +TEST_SUITE(CL) +TEST_SUITE(DYNAMIC_FUSION) +TEST_SUITE(POOL2D) + +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 */ + +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) })), + framework::dataset::make("Pad", { Padding2D() })), + framework::dataset::make("Stride", { Size2D(1, 1), Size2D(2, 1), Size2D(5, 7) })), + framework::dataset::make("ExcludePadding", { true })); + +const auto pool_fp_mixed_precision_dataset = framework::dataset::make("FpMixedPrecision", { true, false }); + +template +using DynamicFusionGpuPool2dFixture = DynamicFusionGpuPool2dValidationFixture; + +template +using DFSpecialGpuPool2dFixture = DynamicFusionGpuPool2dSpecialValidationFixture; + +template +using DFPoolMixedPrecisionFixture = DynamicFusionGpuPool2dMixedPrecisionValidationFixture; +// *INDENT-OFF* +// clang-format off + +DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip( + framework::dataset::make("InputInfo", { TensorInfo(TensorShape(2U, 27U, 13U), 1, DataType::F32, DataLayout::NHWC), // Mismatching data type + TensorInfo(TensorShape(2U, 27U, 13U), 1, DataType::F32, DataLayout::NHWC), // Invalid pad/size combination + TensorInfo(TensorShape(2U, 27U, 13U), 1, DataType::F32, DataLayout::NHWC), // Invalid pad/size combination + TensorInfo(TensorShape(2U, 27U, 13U), 1, DataType::QASYMM8, DataLayout::NHWC), // Invalid parameters, unsupported pooling + TensorInfo(TensorShape(5U, 15U, 13U), 1, DataType::F32, DataLayout::NHWC), // Valid Non-rectangular Global Pooling + TensorInfo(TensorShape(5U, 13U, 13U), 1, DataType::F32, DataLayout::NHWC), // Invalid output Global Pooling + TensorInfo(TensorShape(5U, 13U, 13U), 1, DataType::QASYMM8, DataLayout::NHWC), // Invalid - Quantized not supported. + TensorInfo(TensorShape(5U, 13U, 13U), 1, DataType::F32, DataLayout::NHWC), // Valid global pooling + TensorInfo(TensorShape(13U, 13U, 5U), 1, DataType::F32, DataLayout::NCHW), // Unsupported data layout + }), + framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(2U, 25U, 11U), 1, DataType::F16, DataLayout::NHWC), + TensorInfo(TensorShape(2U, 30U, 11U), 1, DataType::F32, DataLayout::NHWC), + TensorInfo(TensorShape(2U, 25U, 16U), 1, DataType::F32, DataLayout::NHWC), + TensorInfo(TensorShape(2U, 27U, 13U), 1, DataType::QASYMM8, DataLayout::NHWC), + TensorInfo(TensorShape(5U, 1U, 1U), 1, DataType::F32, DataLayout::NHWC), + TensorInfo(TensorShape(5U, 2U, 2U), 1, DataType::F32, DataLayout::NHWC), + TensorInfo(TensorShape(5U, 12U, 12U), 1, DataType::QASYMM8, DataLayout::NHWC), + TensorInfo(TensorShape(5U, 1U, 1U), 1, DataType::F32, DataLayout::NHWC), + TensorInfo(TensorShape(1U, 1U, 5U), 1, DataType::F32, DataLayout::NHWC), + })), + framework::dataset::make("Pool2dAttributes", { + Pool2dAttributes().pool_type(PoolingType::AVG).pool_size(Size2D(3,3)).pad(Padding2D(0,0,0,0)).stride(Size2D(1,1)), + Pool2dAttributes().pool_type(PoolingType::AVG).pool_size(Size2D(2,2)).pad(Padding2D(2,2,0,0)).stride(Size2D(1,1)), + Pool2dAttributes().pool_type(PoolingType::AVG).pool_size(Size2D(2,2)).pad(Padding2D(0,0,2,2)).stride(Size2D(1,1)), + Pool2dAttributes().pool_type(PoolingType::L2).pool_size(Size2D(3,3)).pad(Padding2D(0,0,0,0)).stride(Size2D(1,1)), + Pool2dAttributes().pool_type(PoolingType::AVG).pool_size(Size2D(15U, 13U)), + Pool2dAttributes().pool_type(PoolingType::MAX).pool_size(Size2D(13U, 13U)), + Pool2dAttributes().pool_type(PoolingType::AVG).pool_size(Size2D(2,2)).pad(Padding2D()).stride(Size2D(1,1)), + Pool2dAttributes().pool_type(PoolingType::AVG).pool_size(Size2D(13U,13U)), + Pool2dAttributes().pool_type(PoolingType::AVG).pool_size(Size2D(13U,13U)), + })), + framework::dataset::make("Expected", { false, false, false, false, true, false, false, true, false })), + input_info, output_info, pool2d_attr, expected) +{ + // Create a new workload sketch + auto cl_compile_ctx = CLKernelLibrary::get().get_compile_context(); + auto gpu_ctx = GpuWorkloadContext{ &cl_compile_ctx }; + GpuWorkloadSketch sketch{ &gpu_ctx }; + + // Declare GpuPool2d settings + const GpuPool2dSettings &settings = GpuPool2dSettings().mixed_precision(false); + + // Validate Pool2d Configuration + auto src_info = sketch.create_tensor_info(input_info); + auto dst_info = sketch.create_tensor_info(output_info); + bool res = bool(GpuPool2d::validate_op(sketch, &src_info, &dst_info, pool2d_attr, settings)); + ARM_COMPUTE_EXPECT(res == expected, framework::LogLevel::ERRORS); +} + +// clang-format on +// *INDENT-ON* + +TEST_SUITE(Float) +TEST_SUITE(FP32) +FIXTURE_DATA_TEST_CASE(RunSmall, DynamicFusionGpuPool2dFixture, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallNoneUnitShapes(), PoolingLayerDatasetFP), + framework::dataset::make("DataType", DataType::F32))) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_f32); +} +FIXTURE_DATA_TEST_CASE(RunLarge, DynamicFusionGpuPool2dFixture, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeShapes(), PoolingLayerDatasetFP), + framework::dataset::make("DataType", DataType::F32))) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_f32); +} +FIXTURE_DATA_TEST_CASE(RunSpecial, DFSpecialGpuPool2dFixture, framework::DatasetMode::ALL, combine(datasets::PoolingLayerDatasetSpecialDynamicFusion(), + framework::dataset::make("DataType", DataType::F32))) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_f32); +} + +TEST_SUITE(GlobalPooling) +FIXTURE_DATA_TEST_CASE(RunSmall, DynamicFusionGpuPool2dFixture, 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::MAX })), + framework::dataset::make("PoolingSize", { Size2D(27, 13) })), + framework::dataset::make("Pad", { Padding2D() })), + framework::dataset::make("Stride", { Size2D(1, 1) })), + framework::dataset::make("ExcludePadding", true)), + framework::dataset::make("DataType", DataType::F32))) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_f32); +} + +FIXTURE_DATA_TEST_CASE(RunLarge, DynamicFusionGpuPool2dFixture, 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::MAX })), + framework::dataset::make("PoolingSize", { Size2D(79, 37) })), + framework::dataset::make("Pad", { Padding2D() })), + framework::dataset::make("Stride", { Size2D(1, 1) })), + framework::dataset::make("ExcludePadding", true)), + framework::dataset::make("DataType", DataType::F32))) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_f32); +} +TEST_SUITE_END() // GlobalPooling +TEST_SUITE_END() // FP32 + +TEST_SUITE(FP16) +FIXTURE_DATA_TEST_CASE(RunSmall, DFPoolMixedPrecisionFixture, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::SmallNoneUnitShapes(), PoolingLayerDatasetFP), + framework::dataset::make("DataType", DataType::F16)), + pool_fp_mixed_precision_dataset)) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_f16); +} +FIXTURE_DATA_TEST_CASE(RunLarge, DFPoolMixedPrecisionFixture, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::LargeShapes(), PoolingLayerDatasetFP), + framework::dataset::make("DataType", DataType::F16)), + pool_fp_mixed_precision_dataset)) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_f16); +} + +TEST_SUITE(GlobalPooling) +FIXTURE_DATA_TEST_CASE(RunSmall, DynamicFusionGpuPool2dFixture, 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::MAX })), + framework::dataset::make("PoolingSize", { Size2D(27, 13) })), + framework::dataset::make("Pad", { Padding2D() })), + framework::dataset::make("Stride", { Size2D(1, 1) })), + framework::dataset::make("ExcludePadding", true)), + framework::dataset::make("DataType", DataType::F16))) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_f16); +} + +FIXTURE_DATA_TEST_CASE(RunLarge, DynamicFusionGpuPool2dFixture, 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::MAX })), + framework::dataset::make("PoolingSize", { Size2D(79, 37) })), + framework::dataset::make("Pad", { Padding2D() })), + framework::dataset::make("Stride", { Size2D(1, 1) })), + framework::dataset::make("ExcludePadding", true)), + framework::dataset::make("DataType", DataType::F16))) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_f16); +} +TEST_SUITE_END() // GlobalPooling +TEST_SUITE_END() // FP16 +TEST_SUITE_END() // FLOAT + +TEST_SUITE_END() // POOL2D +TEST_SUITE_END() // DYNAMIC_FUSION +TEST_SUITE_END() // CL +} +} +} diff --git a/tests/validation/fixtures/dynamic_fusion/gpu/cl/Pool2dFixture.h b/tests/validation/fixtures/dynamic_fusion/gpu/cl/Pool2dFixture.h new file mode 100644 index 0000000000..efb67f8b11 --- /dev/null +++ b/tests/validation/fixtures/dynamic_fusion/gpu/cl/Pool2dFixture.h @@ -0,0 +1,190 @@ +/* + * 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. + */ +#ifndef TESTS_VALIDATION_FIXTURES_DYNAMIC_FUSION_GPU_CL_POOL2DFIXTURE +#define TESTS_VALIDATION_FIXTURES_DYNAMIC_FUSION_GPU_CL_POOL2DFIXTURE + +#include "arm_compute/core/CL/CLKernelLibrary.h" +#include "arm_compute/core/TensorInfo.h" +#include "arm_compute/core/Types.h" +#include "arm_compute/core/utils/misc/ShapeCalculator.h" + +#include "arm_compute/dynamic_fusion/runtime/gpu/cl/ClWorkloadRuntime.h" +#include "arm_compute/dynamic_fusion/sketch/attributes/Pool2dAttributes.h" +#include "arm_compute/dynamic_fusion/sketch/gpu/GpuWorkloadSketch.h" +#include "arm_compute/dynamic_fusion/sketch/gpu/operators/GpuPool2d.h" +#include "src/dynamic_fusion/utils/Utils.h" + +#include "tests/CL/CLAccessor.h" +#include "tests/framework/Fixture.h" +#include "tests/validation/reference/PoolingLayer.h" + +using namespace arm_compute::experimental::dynamic_fusion; + +namespace arm_compute +{ +namespace test +{ +namespace validation +{ +template +class DynamicFusionGpuPool2dValidationGenericFixture : public framework::Fixture +{ +public: + template + void setup(TensorShape input_shape, const Pool2dAttributes &pool_attr, DataType data_type, bool mixed_precision) + { + _target = compute_target(input_shape, pool_attr, data_type, mixed_precision); + _reference = compute_reference(input_shape, convert_pool_attr_to_pool_info(pool_attr, mixed_precision), data_type); + } + +protected: + template + void fill(U &&tensor, int i) + { + switch(tensor.data_type()) + { + case DataType::F16: + { + arm_compute::utils::uniform_real_distribution_16bit distribution{ -1.0f, 1.0f }; + library->fill(tensor, distribution, i); + break; + } + case DataType::F32: + { + std::uniform_real_distribution distribution(-1.0f, 1.0f); + library->fill(tensor, distribution, i); + break; + } + default: + library->fill_tensor_uniform(tensor, i); + } + } + + // Given input is in nchw format + TensorType compute_target(TensorShape input_shape, const Pool2dAttributes &pool_attr, const DataType data_type, bool mixed_precision) + { + CLScheduler::get().default_reinit(); + + // Change shape due to NHWC data layout, test shapes are NCHW + permute(input_shape, PermutationVector(2U, 0U, 1U)); + + // Create a new workload sketch + auto cl_compile_ctx = CLKernelLibrary::get().get_compile_context(); + auto gpu_ctx = GpuWorkloadContext{ &cl_compile_ctx }; + GpuWorkloadSketch sketch{ &gpu_ctx }; + + // Create sketch tensors + auto input_info = sketch.create_tensor_info(TensorInfo(input_shape, 1, data_type, DataLayout::NHWC)); + auto dst_info = sketch.create_tensor_info(); + + // Create Pool2dSettings + GpuPool2dSettings pool_settings = GpuPool2dSettings().mixed_precision(mixed_precision); + + FunctionType::create_op(sketch, &input_info, &dst_info, pool_attr, pool_settings); + + // Configure runtime + ClWorkloadRuntime runtime; + runtime.configure(sketch); + // (Important) Allocate auxiliary tensor memory if there are any + for(auto &data : runtime.get_auxiliary_tensors()) + { + auto tensor = data.first; + const auto aux_mem_req = data.second; + tensor->allocator()->init(*data.first->info(), aux_mem_req.alignment); + tensor->allocator()->allocate(); // Use ACL allocated memory + } + // Construct user tensors + TensorType t_input{}; + TensorType t_dst{}; + + // Initialize user tensors + t_input.allocator()->init(input_info); + t_dst.allocator()->init(dst_info); + + // Allocate and fill user tensors + t_input.allocator()->allocate(); + t_dst.allocator()->allocate(); + + fill(AccessorType(t_input), 0); + + // Run runtime + runtime.run({ &t_input, &t_dst }); + return t_dst; + } + + SimpleTensor compute_reference(TensorShape shape, PoolingLayerInfo pool_info, DataType data_type) + { + // Create reference + SimpleTensor src(shape, data_type, 1, QuantizationInfo()); + // Fill reference + fill(src, 0); + return reference::pooling_layer(src, pool_info, QuantizationInfo(), nullptr, DataLayout::NCHW); + } + + TensorType _target{}; + SimpleTensor _reference{}; +}; + +template +class DynamicFusionGpuPool2dValidationFixture : public DynamicFusionGpuPool2dValidationGenericFixture +{ +public: + template + void setup(TensorShape input_shape, PoolingType pool_type, Size2D pool_size, Padding2D pad, Size2D stride, bool exclude_padding, DataType data_type) + { + DynamicFusionGpuPool2dValidationGenericFixture::setup(input_shape, + Pool2dAttributes().pool_type(pool_type).pool_size(pool_size).pad(pad).stride(stride).exclude_padding(exclude_padding), + data_type, false); + } +}; + +template +class DynamicFusionGpuPool2dMixedPrecisionValidationFixture : public DynamicFusionGpuPool2dValidationGenericFixture +{ +public: + template + void setup(TensorShape input_shape, PoolingType pool_type, Size2D pool_size, Padding2D pad, Size2D stride, bool exclude_padding, DataType data_type, bool mixed_precision) + { + DynamicFusionGpuPool2dValidationGenericFixture::setup(input_shape, + Pool2dAttributes().pool_type(pool_type).pool_size(pool_size).pad(pad).stride(stride).exclude_padding(exclude_padding), + data_type, mixed_precision); + } +}; + +template +class DynamicFusionGpuPool2dSpecialValidationFixture : public DynamicFusionGpuPool2dValidationGenericFixture +{ +public: + template + void setup(TensorShape input_shape, Pool2dAttributes pool_attr, DataType data_type) + { + DynamicFusionGpuPool2dValidationGenericFixture::setup(input_shape, pool_attr, data_type, false); + } +}; + +} // namespace validation +} // namespace test +} // namespace arm_compute + +#endif /* TESTS_VALIDATION_FIXTURES_DYNAMIC_FUSION_GPU_CL_POOL2DFIXTURE */ diff --git a/tests/validation/reference/PoolingLayer.cpp b/tests/validation/reference/PoolingLayer.cpp index 9e671e3173..378d91d829 100644 --- a/tests/validation/reference/PoolingLayer.cpp +++ b/tests/validation/reference/PoolingLayer.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2021 Arm Limited. + * Copyright (c) 2017-2021, 2023 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -40,7 +40,6 @@ using namespace arm_compute::misc::shape_calculator; template ::value, int>::type> SimpleTensor pooling_layer_internal(const SimpleTensor &src, const PoolingLayerInfo &info, SimpleTensor *indices, DataLayout data_layout) { - ARM_COMPUTE_ERROR_ON(info.is_global_pooling && (src.shape().x() != src.shape().y())); // Create reference SimpleTensor dst{ compute_pool_shape(TensorInfo(src.shape(), 1, src.data_type()), info), src.data_type(), 1 }; auto pooled_shape = compute_pool_shape(TensorInfo(src.shape(), 1, src.data_type()), info); -- cgit v1.2.1