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 --- tests/validation/dynamic_fusion/gpu/cl/Pool2d.cpp | 233 ++++++++++++++++++++++ 1 file changed, 233 insertions(+) create mode 100644 tests/validation/dynamic_fusion/gpu/cl/Pool2d.cpp (limited to 'tests/validation/dynamic_fusion/gpu') 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 +} +} +} -- cgit v1.2.1