19 #include <boost/cast.hpp> 24 using namespace armcomputetensorutils;
32 const arm_compute::TensorInfo aclInputInfo = BuildArmComputeTensorInfo(input, descriptor.
m_DataLayout);
33 const arm_compute::TensorInfo aclOutputInfo = BuildArmComputeTensorInfo(output, descriptor.
m_DataLayout);
34 const arm_compute::TensorInfo aclWeightsInfo = BuildArmComputeTensorInfo(weights, descriptor.
m_DataLayout);
36 arm_compute::TensorInfo aclBiasesInfo;
37 arm_compute::TensorInfo *optionalAclBiasesInfo =
nullptr;
43 aclBiasesInfo = BuildArmComputeTensorInfo(biases.
value(), descriptor.
m_DataLayout);
44 optionalAclBiasesInfo = &aclBiasesInfo;
47 arm_compute::PadStrideInfo layerInfo = BuildArmComputePadStrideInfo(descriptor);
49 return arm_compute::NEDeconvolutionLayer::validate(&aclInputInfo,
51 optionalAclBiasesInfo,
58 std::shared_ptr<arm_compute::MemoryManagerOnDemand>& memoryManager)
63 arm_compute::ITensor& input = boost::polymorphic_downcast<IAclTensorHandle*>(
m_Data.
m_Inputs[0])->GetTensor();
64 arm_compute::ITensor& output = boost::polymorphic_downcast<IAclTensorHandle*>(
m_Data.
m_Outputs[0])->GetTensor();
67 input.info()->set_data_layout(aclDataLayout);
68 output.info()->set_data_layout(aclDataLayout);
70 m_KernelTensor = std::make_unique<arm_compute::Tensor>();
75 m_BiasTensor = std::make_unique<arm_compute::Tensor>();
79 arm_compute::PadStrideInfo padStrideInfo = BuildArmComputePadStrideInfo(
m_Data.
m_Parameters);
81 m_Layer = std::make_unique<arm_compute::NEDeconvolutionLayer>(memoryManager);
82 m_Layer->configure(&input, m_KernelTensor.get(), m_BiasTensor.get(), &output, padStrideInfo);
84 BOOST_ASSERT(m_Layer);
103 void NeonTransposeConvolution2dWorkload::FreeUnusedTensors()
105 FreeTensorIfUnused(m_KernelTensor);
106 FreeTensorIfUnused(m_BiasTensor);
const TensorInfo & GetTensorInfo() const
#define ARMNN_SCOPED_PROFILING_EVENT_NEON(name)
LayerDescriptor m_Parameters
arm_compute::Status NeonTransposeConvolution2dWorkloadValidate(const TensorInfo &input, const TensorInfo &output, const TransposeConvolution2dDescriptor &descriptor, const TensorInfo &weights, const Optional< TensorInfo > &biases)
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
A TransposeConvolution2dDescriptor for the TransposeConvolution2dLayer.
void Execute() const override
const TransposeConvolution2dQueueDescriptor m_Data
NeonTransposeConvolution2dWorkload(const TransposeConvolution2dQueueDescriptor &descriptor, const WorkloadInfo &info, std::shared_ptr< arm_compute::MemoryManagerOnDemand > &memoryManager)
void ValidateInputsOutputs(const std::string &descName, unsigned int numExpectedIn, unsigned int numExpectedOut) const
const ConstCpuTensorHandle * m_Bias
const ConstCpuTensorHandle * m_Weight
std::vector< ITensorHandle * > m_Outputs
std::vector< ITensorHandle * > m_Inputs
bool m_BiasEnabled
Enable/disable bias.
bool has_value() const noexcept
void InitializeArmComputeTensorData(arm_compute::Tensor &tensor, const ConstCpuTensorHandle *handle)