/* * Copyright (c) 2019 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/runtime/Allocator.h" #include "arm_compute/runtime/MemoryManagerOnDemand.h" #include "arm_compute/runtime/NEON/functions/NEConvolutionLayer.h" #include "arm_compute/runtime/NEON/functions/NENormalizationLayer.h" #include "arm_compute/runtime/OffsetLifetimeManager.h" #include "arm_compute/runtime/PoolManager.h" #include "support/ToolchainSupport.h" #include "tests/AssetsLibrary.h" #include "tests/NEON/Accessor.h" #include "tests/framework/Asserts.h" #include "tests/framework/Macros.h" #include "tests/framework/datasets/Datasets.h" #include "tests/validation/Validation.h" #include "tests/validation/fixtures/UNIT/DynamicTensorFixture.h" namespace arm_compute { namespace test { namespace validation { namespace { constexpr AbsoluteTolerance absolute_tolerance_float(0.0001f); /**< Absolute Tolerance value for comparing reference's output against implementation's output for DataType::F32 */ RelativeTolerance tolerance_f32(0.1f); /**< Tolerance value for comparing reference's output against implementation's output for DataType::F32 */ constexpr float tolerance_num = 0.07f; /**< Tolerance number */ using NENormLayerWrapper = SimpleFunctionWrapper; template <> void NENormLayerWrapper::configure(arm_compute::ITensor *src, arm_compute::ITensor *dst) { _func.configure(src, dst, NormalizationLayerInfo(NormType::CROSS_MAP, 3)); } } // namespace TEST_SUITE(NEON) TEST_SUITE(UNIT) TEST_SUITE(DynamicTensor) using OffsetMemoryManagementService = MemoryManagementService; using NEDynamicTensorType3SingleFunction = DynamicTensorType3SingleFunction; /** Tests the memory manager with dynamic input and output tensors. * * Create and manage the tensors needed to run a simple function. After the function is executed, * change the input and output size requesting more memory and go through the manage/allocate process. * The memory manager should be able to update the inner structures and allocate the requested memory * */ FIXTURE_DATA_TEST_CASE(DynamicTensorType3Single, NEDynamicTensorType3SingleFunction, framework::DatasetMode::ALL, framework::dataset::zip(framework::dataset::make("Level0Shape", { TensorShape(12U, 11U, 3U), TensorShape(256U, 8U, 12U) }), framework::dataset::make("Level1Shape", { TensorShape(67U, 31U, 15U), TensorShape(11U, 2U, 3U) }))) { if(input_l0.total_size() < input_l1.total_size()) { ARM_COMPUTE_EXPECT(internal_l0.size < internal_l1.size, framework::LogLevel::ERRORS); ARM_COMPUTE_EXPECT(cross_l0.size < cross_l1.size, framework::LogLevel::ERRORS); } else { ARM_COMPUTE_EXPECT(internal_l0.size == internal_l1.size, framework::LogLevel::ERRORS); ARM_COMPUTE_EXPECT(cross_l0.size == cross_l1.size, framework::LogLevel::ERRORS); } } using NEDynamicTensorType3ComplexFunction = DynamicTensorType3ComplexFunction; /** Tests the memory manager with dynamic input and output tensors. * * Create and manage the tensors needed to run a complex function. After the function is executed, * change the input and output size requesting more memory and go through the manage/allocate process. * The memory manager should be able to update the inner structures and allocate the requested memory * */ FIXTURE_DATA_TEST_CASE(DynamicTensorType3Complex, NEDynamicTensorType3ComplexFunction, framework::DatasetMode::ALL, framework::dataset::zip(framework::dataset::zip(framework::dataset::zip(framework::dataset::zip( framework::dataset::make("InputShape", { std::vector{ TensorShape(12U, 12U, 6U), TensorShape(128U, 128U, 6U) } }), framework::dataset::make("WeightsManager", { TensorShape(3U, 3U, 6U, 3U) })), framework::dataset::make("BiasShape", { TensorShape(3U) })), framework::dataset::make("OutputShape", { std::vector{ TensorShape(12U, 12U, 3U), TensorShape(128U, 128U, 3U) } })), framework::dataset::make("PadStrideInfo", { PadStrideInfo(1U, 1U, 1U, 1U) }))) { for(unsigned int i = 0; i < num_iterations; ++i) { run_iteration(i); validate(Accessor(dst_target), dst_ref, tolerance_f32, tolerance_num, absolute_tolerance_float); } } TEST_SUITE_END() // DynamicTensor TEST_SUITE_END() // UNIT TEST_SUITE_END() // NEON } // namespace validation } // namespace test } // namespace arm_compute