23 auto input = MakeTensor<int32_t, 1>(inputTensorInfo, ConvertToDataType<armnn::DataType::Signed32>(
28 ret.outputExpected = MakeTensor<T, 4>(outputTensorInfo, ConvertToDataType<ArmnnType>(
29 { 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
30 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f },
34 std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.
CreateTensorHandle(inputTensorInfo);
35 std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.
CreateTensorHandle(outputTensorInfo);
41 AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get());
42 AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());
44 std::unique_ptr<armnn::IWorkload> workload = workloadFactory.
CreateFill(data, info);
46 inputHandle->Allocate();
47 outputHandle->Allocate();
#define ARMNN_NO_DEPRECATE_WARN_BEGIN
void IgnoreUnused(Ts &&...)
LayerDescriptor m_Parameters
#define ARMNN_NO_DEPRECATE_WARN_END
void CopyDataFromITensorHandle(void *memory, const armnn::ITensorHandle *tensorHandle)
virtual std::unique_ptr< ITensorHandle > CreateTensorHandle(const TensorInfo &tensorInfo, const bool IsMemoryManaged=true) const =0
virtual std::unique_ptr< IWorkload > CreateFill(const FillQueueDescriptor &descriptor, const WorkloadInfo &info) const
Contains information about inputs and outputs to a layer.
void CopyDataToITensorHandle(armnn::ITensorHandle *tensorHandle, const void *memory)