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 --- .../fixtures/dynamic_fusion/gpu/cl/Pool2dFixture.h | 190 +++++++++++++++++++++ 1 file changed, 190 insertions(+) create mode 100644 tests/validation/fixtures/dynamic_fusion/gpu/cl/Pool2dFixture.h (limited to 'tests/validation/fixtures/dynamic_fusion') 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 */ -- cgit v1.2.1