25 unsigned int dims[] = { 4, 1, 1, 1 };
26 std::vector<float> floatWeights{ 1.0f, 2.0f, 3.0f, 4.0f };
34 fc->
m_Weight = std::make_unique<armnn::ScopedCpuTensorHandle>(weights);
35 fc->GetOutputSlot().SetTensorInfo(info);
41 fc->GetOutputSlot().Connect(output->GetInputSlot(0));
53 Half* data = fc->m_Weight->GetTensor<
Half>();
Optimizer::Optimizations MakeOptimizations(Args &&... args)
std::unique_ptr< ScopedCpuTensorHandle > m_Weight
A unique pointer to store Weight values.
LayerT * AddLayer(Args &&... args)
Adds a new layer, of type LayerType, to the graph constructed with the arguments passed.
int Connect(InputSlot &destination)
static void Pass(Graph &graph, const Optimizations &optimizations)
BOOST_CHECK(profilingService.GetCurrentState()==ProfilingState::WaitingForAck)
A layer user-provided data can be bound to (e.g. inputs, outputs).
ConvertConstants< Float32ToFloat16, IsFloat16Layer > ConvertConstantsFloatToHalf
This layer represents a fully connected operation.
A FullyConnectedDescriptor for the FullyConnectedLayer.
A tensor defined by a TensorInfo (shape and data type) and an immutable backing store.
void SetTensorInfo(const TensorInfo &tensorInfo) override
const OutputSlot & GetOutputSlot(unsigned int index=0) const override
Get the const output slot handle by slot index.