ArmNN
 25.11
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DepthToSpaceQueueDescriptor Struct Reference

#include <WorkloadData.hpp>

Inheritance diagram for DepthToSpaceQueueDescriptor:
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Collaboration diagram for DepthToSpaceQueueDescriptor:
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Public Member Functions

void Validate (const WorkloadInfo &workloadInfo) const
Public Member Functions inherited from QueueDescriptorWithParameters< DepthToSpaceDescriptor >
virtual ~QueueDescriptorWithParameters ()=default
Public Member Functions inherited from QueueDescriptor
virtual ~QueueDescriptor ()=default
void ValidateTensorNumDimensions (const TensorInfo &tensor, std::string const &descName, unsigned int numDimensions, std::string const &tensorName) const
void ValidateTensorNumDimNumElem (const TensorInfo &tensorInfo, unsigned int numDimension, unsigned int numElements, std::string const &tensorName) const
void ValidateInputsOutputs (const std::string &descName, unsigned int numExpectedIn, unsigned int numExpectedOut) const
template<typename T>
const T * GetAdditionalInformation () const

Additional Inherited Members

Public Attributes inherited from QueueDescriptorWithParameters< DepthToSpaceDescriptor >
DepthToSpaceDescriptor m_Parameters
Public Attributes inherited from QueueDescriptor
std::vector< ITensorHandle * > m_Inputs
std::vector< ITensorHandle * > m_Outputs
void * m_AdditionalInfoObject
bool m_AllowExpandedDims = false
Protected Member Functions inherited from QueueDescriptorWithParameters< DepthToSpaceDescriptor >
 QueueDescriptorWithParameters ()=default
QueueDescriptorWithParametersoperator= (QueueDescriptorWithParameters const &)=default
Protected Member Functions inherited from QueueDescriptor
 QueueDescriptor ()
 QueueDescriptor (QueueDescriptor const &)=default
QueueDescriptoroperator= (QueueDescriptor const &)=default

Detailed Description

Definition at line 661 of file WorkloadData.hpp.

Member Function Documentation

◆ Validate()

void Validate ( const WorkloadInfo & workloadInfo) const

Definition at line 3699 of file WorkloadData.cpp.

3700{
3701 const std::string descriptorName{"DepthToSpaceQueueDescriptor"};
3702
3703 ValidateNumInputs(workloadInfo, descriptorName, 1);
3704 ValidateNumOutputs(workloadInfo, descriptorName, 1);
3705
3706 const TensorInfo& inputInfo = workloadInfo.m_InputTensorInfos[0];
3707 const TensorInfo& outputInfo = workloadInfo.m_OutputTensorInfos[0];
3708
3709 ValidateTensorNumDimensions(inputInfo, descriptorName, 4, "input");
3710 ValidateTensorNumDimensions(outputInfo, descriptorName, 4, "output");
3711
3712 std::vector<DataType> supportedTypes =
3713 {
3721 };
3722
3723 ValidateDataTypes(inputInfo, supportedTypes, descriptorName);
3724 ValidateDataTypes(outputInfo, supportedTypes, descriptorName);
3725
3726 ValidateTensorNumElementsMatch(inputInfo, outputInfo, descriptorName, "input", "output");
3727
3728 if (m_Parameters.m_BlockSize == 0)
3729 {
3730 throw InvalidArgumentException(descriptorName + ": Block size cannot be 0.");
3731 }
3732
3733 DataLayoutIndexed dimensionIndices(m_Parameters.m_DataLayout);
3734 const unsigned int wIndex = dimensionIndices.GetWidthIndex();
3735 const unsigned int hIndex = dimensionIndices.GetHeightIndex();
3736 const unsigned int cIndex = dimensionIndices.GetChannelsIndex();
3737
3738 const TensorShape& outputShape = outputInfo.GetShape();
3739 if (outputShape[hIndex] % m_Parameters.m_BlockSize != 0 || outputShape[wIndex] % m_Parameters.m_BlockSize != 0)
3740 {
3741 throw InvalidArgumentException(descriptorName + ": Output width and height shape"
3742 "must be divisible by block size.");
3743 }
3744
3745 const TensorShape& inputShape = inputInfo.GetShape();
3746 if (inputShape[cIndex] % (m_Parameters.m_BlockSize * m_Parameters.m_BlockSize) != 0)
3747 {
3748 throw InvalidArgumentException(descriptorName + ": The depth of the input tensor"
3749 "must be divisible by the square of block size." );
3750 }
3751}
const TensorShape & GetShape() const
Definition Tensor.hpp:193
void ValidateTensorNumDimensions(const TensorInfo &tensor, std::string const &descName, unsigned int numDimensions, std::string const &tensorName) const
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
unsigned int m_BlockSize
Scalar specifying the input block size. It must be >= 1.
std::vector< TensorInfo > m_OutputTensorInfos
std::vector< TensorInfo > m_InputTensorInfos

References armnn::BFloat16, armnn::Float16, armnn::Float32, DataLayoutIndexed::GetChannelsIndex(), DataLayoutIndexed::GetHeightIndex(), TensorInfo::GetShape(), DataLayoutIndexed::GetWidthIndex(), WorkloadInfo::m_InputTensorInfos, WorkloadInfo::m_OutputTensorInfos, QueueDescriptorWithParameters< DepthToSpaceDescriptor >::m_Parameters, armnn::QAsymmS8, armnn::QAsymmU8, armnn::QSymmS16, armnn::Signed32, and QueueDescriptor::ValidateTensorNumDimensions().


The documentation for this struct was generated from the following files: