24 outputTensorInfo.SetQuantizationScale(0.1f);
26 auto input = MakeTensor<T, 4>(inputTensorInfo, ConvertToDataType<ArmnnType>(
27 { -37.5f, -15.2f, -8.76f, -2.0f, -1.5f, -1.3f, -0.5f, -0.4f, 0.0f,
28 1.0f, 0.4f, 0.5f, 1.3f, 1.5f, 2.0f, 8.76f, 15.2f, 37.5f },
32 ret.outputExpected = MakeTensor<T, 4>(outputTensorInfo, ConvertToDataType<ArmnnType>(
33 { -38.0f, -16.0f, -9.0f, -2.0f, -2.0f, -2.0f, -1.0f, -1.0f, 0.0f,
34 1.0f, 0.0f, 0.0f, 1.0f, 1.0f, 2.0f, 8.0f, 15.0f, 37.0f },
37 std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.
CreateTensorHandle(inputTensorInfo);
38 std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.
CreateTensorHandle(outputTensorInfo);
42 AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get());
43 AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());
45 std::unique_ptr<armnn::IWorkload> workload = workloadFactory.
CreateFloor(data, info);
47 inputHandle->Allocate();
48 outputHandle->Allocate();
void IgnoreUnused(Ts &&...)
void SetQuantizationScale(float scale)
void CopyDataFromITensorHandle(void *memory, const armnn::ITensorHandle *tensorHandle)
virtual std::unique_ptr< ITensorHandle > CreateTensorHandle(const TensorInfo &tensorInfo, const bool IsMemoryManaged=true) const =0
Contains information about inputs and outputs to a layer.
virtual std::unique_ptr< IWorkload > CreateFloor(const FloorQueueDescriptor &descriptor, const WorkloadInfo &info) const
void CopyDataToITensorHandle(armnn::ITensorHandle *tensorHandle, const void *memory)