6 #include <boost/test/unit_test.hpp> 17 using namespace armnn;
23 auto neonBackend = std::make_unique<NeonBackend>();
24 auto clBackend = std::make_unique<ClBackend>();
27 neonBackend->RegisterTensorHandleFactories(registry);
28 clBackend->RegisterTensorHandleFactories(registry);
30 const BackendId& neonBackendId = neonBackend->GetId();
31 const BackendId& clBackendId = clBackend->GetId();
34 backends[neonBackendId] = std::move(neonBackend);
35 backends[clBackendId] = std::move(clBackend);
67 std::vector<std::string> errors;
70 BOOST_TEST(result.m_Error ==
false);
71 BOOST_TEST(result.m_Warning ==
false);
104 BOOST_TEST(copyCount == 0);
115 BOOST_TEST(importCount == 0);
122 #if defined(ARMNNREF_ENABLED) 126 auto refBackend = std::make_unique<RefBackend>();
134 #if defined(ARMCOMPUTENEON_ENABLED) 138 auto neonBackend = std::make_unique<NeonBackend>();
144 #if defined(ARMCOMPUTECL_ENABLED) 148 auto clBackend = std::make_unique<ClBackend>();
BOOST_AUTO_TEST_SUITE(TensorflowLiteParser)
No strategy has been defined. Used internally to verify integrity of optimizations.
LayerT * AddLayer(Args &&... args)
Adds a new layer, of type LayerType, to the graph constructed with the arguments passed.
int Connect(InputSlot &destination)
EdgeStrategy GetEdgeStrategyForConnection(unsigned int connectionIdx) const
Copyright (c) 2021 ARM Limited and Contributors.
void SetBackendId(const BackendId &id)
Constant weights can be accessed through the descriptors, On the other hand, non-const weights can be...
const InputSlot & GetInputSlot(unsigned int index) const override
Get a const input slot handle by slot index.
A layer user-provided data can be bound to (e.g. inputs, outputs).
void ForEachLayer(Func func) const
BackendCapability
BackendCapability class.
This layer represents a softmax operation.
LayerType GetType() const override
Returns the armnn::LayerType of this layer.
BOOST_AUTO_TEST_CASE(CheckConvolution2dLayer)
BOOST_AUTO_TEST_SUITE_END()
const OutputSlot & GetOutputSlot(unsigned int index=0) const override
Get the const output slot handle by slot index.
OptimizationResult SelectTensorHandleStrategy(Graph &optGraph, BackendsMap &backends, TensorHandleFactoryRegistry ®istry, bool importEnabled, Optional< std::vector< std::string > &> errMessages)
ITensorHandleFactory::FactoryId GetTensorHandleFactoryId() const
Graph & TopologicalSort()
Sorts layers in topological order and return this.
A SoftmaxDescriptor for the SoftmaxLayer.
void AddCompatibilityLayers(std::map< BackendId, std::unique_ptr< class IBackendInternal >> &backends, TensorHandleFactoryRegistry ®istry)
Modifies the graph in-place, removing edges connecting layers using different compute devices...
std::map< BackendId, std::unique_ptr< class IBackendInternal > > BackendsMap