| // |
| // Copyright © 2017 Arm Ltd. All rights reserved. |
| // SPDX-License-Identifier: MIT |
| // |
| |
| #pragma once |
| |
| #include <Graph.hpp> |
| #include <SubgraphView.hpp> |
| #include <SubgraphViewSelector.hpp> |
| #include <ResolveType.hpp> |
| |
| #include <armnn/BackendRegistry.hpp> |
| |
| #include <armnn/Types.hpp> |
| #include <backendsCommon/TensorHandle.hpp> |
| |
| #include <test/TestUtils.hpp> |
| |
| #include <algorithm> |
| |
| // Checks that two collections have the exact same contents (in any order) |
| // The given collections do not have to contain duplicates |
| // Cannot use std::sort here because std lists have their own std::list::sort method |
| template <typename CollectionType> |
| bool AreEqual(const CollectionType& lhs, const CollectionType& rhs) |
| { |
| if (lhs.size() != rhs.size()) |
| { |
| return false; |
| } |
| |
| auto lhs_it = std::find_if(lhs.begin(), lhs.end(), [&rhs](auto& item) |
| { |
| return std::find(rhs.begin(), rhs.end(), item) == rhs.end(); |
| }); |
| |
| return lhs_it == lhs.end(); |
| } |
| |
| // Checks that the given collection contains the specified item |
| template <typename CollectionType> |
| bool Contains(const CollectionType& collection, const typename CollectionType::value_type& item) |
| { |
| return std::find(collection.begin(), collection.end(), item) != collection.end(); |
| } |
| |
| // Checks that the given map contains the specified key |
| template <typename MapType> |
| bool Contains(const MapType& map, const typename MapType::key_type& key) |
| { |
| return map.find(key) != map.end(); |
| } |
| |
| // Utility template for comparing tensor elements |
| template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
| bool Compare(T a, T b, float tolerance = 0.000001f) |
| { |
| if (ArmnnType == armnn::DataType::Boolean) |
| { |
| // NOTE: Boolean is represented as uint8_t (with zero equals |
| // false and everything else equals true), therefore values |
| // need to be casted to bool before comparing them |
| return static_cast<bool>(a) == static_cast<bool>(b); |
| } |
| |
| // NOTE: All other types can be cast to float and compared with |
| // a certain level of tolerance |
| return std::fabs(static_cast<float>(a) - static_cast<float>(b)) <= tolerance; |
| } |
| |
| template <typename ConvolutionLayer> |
| void SetWeightAndBias(ConvolutionLayer* layer, const armnn::TensorInfo& weightInfo, const armnn::TensorInfo& biasInfo) |
| { |
| layer->m_Weight = std::make_unique<armnn::ScopedTensorHandle>(weightInfo); |
| layer->m_Bias = std::make_unique<armnn::ScopedTensorHandle>(biasInfo); |
| |
| layer->m_Weight->Allocate(); |
| layer->m_Bias->Allocate(); |
| } |
| |
| armnn::SubgraphView::InputSlots CreateInputsFrom(const std::vector<armnn::Layer*>& layers); |
| |
| armnn::SubgraphView::OutputSlots CreateOutputsFrom(const std::vector<armnn::Layer*>& layers); |
| |
| armnn::SubgraphView::SubgraphViewPtr CreateSubgraphViewFrom(armnn::SubgraphView::InputSlots&& inputs, |
| armnn::SubgraphView::OutputSlots&& outputs, |
| armnn::SubgraphView::Layers&& layers); |
| |
| armnn::IBackendInternalUniquePtr CreateBackendObject(const armnn::BackendId& backendId); |
| |
| armnn::TensorShape MakeTensorShape(unsigned int batches, |
| unsigned int channels, |
| unsigned int height, |
| unsigned int width, |
| armnn::DataLayout layout); |