23 using namespace armcomputetensorutils;
31 const arm_compute::TensorInfo aclInputInfo = BuildArmComputeTensorInfo(input, descriptor.
m_DataLayout);
32 const arm_compute::TensorInfo aclOutputInfo = BuildArmComputeTensorInfo(output, descriptor.
m_DataLayout);
33 const arm_compute::TensorInfo aclWeightsInfo = BuildArmComputeTensorInfo(weights, descriptor.
m_DataLayout);
35 arm_compute::TensorInfo aclBiasesInfo;
36 arm_compute::TensorInfo *optionalAclBiasesInfo =
nullptr;
42 aclBiasesInfo = BuildArmComputeTensorInfo(biases.
value(), descriptor.
m_DataLayout);
43 optionalAclBiasesInfo = &aclBiasesInfo;
46 arm_compute::PadStrideInfo layerInfo = BuildArmComputePadStrideInfo(descriptor);
48 return arm_compute::NEDeconvolutionLayer::validate(&aclInputInfo,
50 optionalAclBiasesInfo,
57 std::shared_ptr<arm_compute::MemoryManagerOnDemand>& memoryManager)
62 arm_compute::ITensor& input = PolymorphicDowncast<IAclTensorHandle*>(
m_Data.
m_Inputs[0])->GetTensor();
63 arm_compute::ITensor& output = PolymorphicDowncast<IAclTensorHandle*>(
m_Data.
m_Outputs[0])->GetTensor();
66 input.info()->set_data_layout(aclDataLayout);
67 output.info()->set_data_layout(aclDataLayout);
69 m_KernelTensor = std::make_unique<arm_compute::Tensor>();
74 m_BiasTensor = std::make_unique<arm_compute::Tensor>();
78 arm_compute::PadStrideInfo padStrideInfo = BuildArmComputePadStrideInfo(
m_Data.
m_Parameters);
97 m_Layer = std::make_unique<arm_compute::NEDeconvolutionLayer>(memoryManager);
98 m_Layer->configure(&input, m_KernelTensor.get(), m_BiasTensor.get(), &output, padStrideInfo);
119 void NeonTransposeConvolution2dWorkload::FreeUnusedTensors()
121 FreeTensorIfUnused(m_KernelTensor);
122 FreeTensorIfUnused(m_BiasTensor);
A TransposeConvolution2dDescriptor for the TransposeConvolution2dLayer.
bool m_BiasEnabled
Enable/disable bias.
void Execute() const override
arm_compute::Status NeonTransposeConvolution2dWorkloadValidate(const TensorInfo &input, const TensorInfo &output, const TransposeConvolution2dDescriptor &descriptor, const TensorInfo &weights, const Optional< TensorInfo > &biases)
void ValidateInputsOutputs(const std::string &descName, unsigned int numExpectedIn, unsigned int numExpectedOut) const
Copyright (c) 2021 ARM Limited and Contributors.
NeonTransposeConvolution2dWorkload(const TransposeConvolution2dQueueDescriptor &descriptor, const WorkloadInfo &info, std::shared_ptr< arm_compute::MemoryManagerOnDemand > &memoryManager)
LayerDescriptor m_Parameters
const TensorInfo & GetTensorInfo() const
std::vector< TensorInfo > m_InputTensorInfos
TransposeConvolution2dQueueDescriptor m_Data
bool has_value() const noexcept
#define ARMNN_ASSERT(COND)
std::vector< TensorInfo > m_OutputTensorInfos
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
profiling::ProfilingGuid GetGuid() const final
Optional< TensorInfo > m_BiasTensorInfo
std::vector< ITensorHandle * > m_Outputs
#define ARMNN_REPORT_PROFILING_WORKLOAD_DESC(name, desc, infos, guid)
void InitializeArmComputeTensorData(arm_compute::Tensor &tensor, const ConstTensorHandle *handle)
Contains information about TensorInfos of a layer.
const ConstTensorHandle * m_Weight
std::vector< ITensorHandle * > m_Inputs
#define ARMNN_SCOPED_PROFILING_EVENT_NEON_GUID(name, guid)
const ConstTensorHandle * m_Bias
Optional< TensorInfo > m_WeightsTensorInfo