| /* |
| * Copyright (c) 2019-2021 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/BlobLifetimeManager.h" |
| #include "arm_compute/runtime/CL/CLBufferAllocator.h" |
| #include "arm_compute/runtime/CL/functions/CLConvolutionLayer.h" |
| #include "arm_compute/runtime/CL/functions/CLL2NormalizeLayer.h" |
| #include "arm_compute/runtime/MemoryGroup.h" |
| #include "arm_compute/runtime/MemoryManagerOnDemand.h" |
| #include "arm_compute/runtime/PoolManager.h" |
| #include "src/core/CL/kernels/CLFillBorderKernel.h" |
| #include "src/core/CL/kernels/CLL2NormalizeLayerKernel.h" |
| #include "src/core/CL/kernels/CLReductionOperationKernel.h" |
| #include "tests/AssetsLibrary.h" |
| #include "tests/CL/CLAccessor.h" |
| #include "tests/Globals.h" |
| #include "tests/Utils.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<float> absolute_tolerance_float(0.0001f); /**< Absolute Tolerance value for comparing reference's output against implementation's output for DataType::F32 */ |
| RelativeTolerance<float> 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 */ |
| } // namespace |
| |
| #ifndef DOXYGEN_SKIP_THIS |
| using CLL2NormLayerWrapper = SimpleFunctionWrapper<MemoryManagerOnDemand, CLL2NormalizeLayer, ICLTensor>; |
| template <> |
| void CLL2NormLayerWrapper::configure(ICLTensor *src, ICLTensor *dst) |
| { |
| _func.configure(src, dst, 0, 0.0001f); |
| } |
| #endif // DOXYGEN_SKIP_THIS |
| TEST_SUITE(CL) |
| TEST_SUITE(UNIT) |
| TEST_SUITE(DynamicTensor) |
| |
| using BlobMemoryManagementService = MemoryManagementService<CLBufferAllocator, BlobLifetimeManager, PoolManager, MemoryManagerOnDemand>; |
| using CLDynamicTensorType3SingleFunction = DynamicTensorType3SingleFunction<CLTensor, CLAccessor, BlobMemoryManagementService, CLL2NormLayerWrapper>; |
| |
| /** 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, CLDynamicTensorType3SingleFunction, 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) }))) |
| { |
| ARM_COMPUTE_EXPECT(internal_l0.size() == internal_l1.size(), framework::LogLevel::ERRORS); |
| ARM_COMPUTE_EXPECT(cross_l0.size() == cross_l1.size(), framework::LogLevel::ERRORS); |
| |
| const unsigned int internal_size = internal_l0.size(); |
| const unsigned int cross_size = cross_l0.size(); |
| if(input_l0.total_size() < input_l1.total_size()) |
| { |
| for(unsigned int i = 0; i < internal_size; ++i) |
| { |
| ARM_COMPUTE_EXPECT(internal_l0[i].size < internal_l1[i].size, framework::LogLevel::ERRORS); |
| } |
| for(unsigned int i = 0; i < cross_size; ++i) |
| { |
| ARM_COMPUTE_EXPECT(cross_l0[i].size < cross_l1[i].size, framework::LogLevel::ERRORS); |
| } |
| } |
| else |
| { |
| for(unsigned int i = 0; i < internal_size; ++i) |
| { |
| ARM_COMPUTE_EXPECT(internal_l0[i].size == internal_l1[i].size, framework::LogLevel::ERRORS); |
| } |
| for(unsigned int i = 0; i < cross_size; ++i) |
| { |
| ARM_COMPUTE_EXPECT(cross_l0[i].size == cross_l1[i].size, framework::LogLevel::ERRORS); |
| } |
| } |
| } |
| |
| using CLDynamicTensorType3ComplexFunction = DynamicTensorType3ComplexFunction<CLTensor, CLAccessor, BlobMemoryManagementService, CLConvolutionLayer>; |
| /** 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, CLDynamicTensorType3ComplexFunction, framework::DatasetMode::ALL, |
| framework::dataset::zip(framework::dataset::zip(framework::dataset::zip(framework::dataset::zip( |
| framework::dataset::make("InputShape", { std::vector<TensorShape>{ TensorShape(12U, 12U, 16U), TensorShape(64U, 64U, 16U) } }), |
| framework::dataset::make("WeightsManager", { TensorShape(3U, 3U, 16U, 5U) })), |
| framework::dataset::make("BiasShape", { TensorShape(5U) })), |
| framework::dataset::make("OutputShape", { std::vector<TensorShape>{ TensorShape(12U, 12U, 5U), TensorShape(64U, 64U, 5U) } })), |
| framework::dataset::make("PadStrideInfo", { PadStrideInfo(1U, 1U, 1U, 1U) }))) |
| { |
| for(unsigned int i = 0; i < num_iterations; ++i) |
| { |
| run_iteration(i); |
| validate(CLAccessor(dst_target), dst_ref, tolerance_f32, tolerance_num, absolute_tolerance_float); |
| } |
| } |
| |
| using CLDynamicTensorType2PipelineFunction = DynamicTensorType2PipelineFunction<CLTensor, CLAccessor, BlobMemoryManagementService, CLConvolutionLayer>; |
| /** Tests the memory manager with dynamic input and output tensors. |
| * |
| * Create and manage the tensors needed to run a pipeline. After the function is executed, resize the input size and rerun. |
| */ |
| FIXTURE_DATA_TEST_CASE(DynamicTensorType2Pipeline, CLDynamicTensorType2PipelineFunction, framework::DatasetMode::ALL, |
| framework::dataset::make("InputShape", { std::vector<TensorShape>{ TensorShape(12U, 12U, 6U), TensorShape(128U, 128U, 6U) } })) |
| { |
| } |
| |
| TEST_SUITE_END() // DynamicTensor |
| TEST_SUITE_END() // UNIT |
| TEST_SUITE_END() // CL |
| } // namespace validation |
| } // namespace test |
| } // namespace arm_compute |