ArmNN
 22.11
StackQueueDescriptor Struct Reference

#include <WorkloadData.hpp>

Inheritance diagram for StackQueueDescriptor:
QueueDescriptorWithParameters< StackDescriptor > QueueDescriptor

Public Member Functions

void Validate (const WorkloadInfo &workloadInfo) const
 
- Public Member Functions inherited from QueueDescriptorWithParameters< StackDescriptor >
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< StackDescriptor >
StackDescriptor 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< StackDescriptor >
 QueueDescriptorWithParameters ()=default
 
 QueueDescriptorWithParameters (QueueDescriptorWithParameters const &)=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 152 of file WorkloadData.hpp.

Member Function Documentation

◆ Validate()

void Validate ( const WorkloadInfo workloadInfo) const

Definition at line 943 of file WorkloadData.cpp.

References armnn::BFloat16, armnn::Boolean, armnn::Float16, armnn::Float32, TensorShape::GetNumDimensions(), WorkloadInfo::m_InputTensorInfos, WorkloadInfo::m_OutputTensorInfos, armnn::QAsymmS8, armnn::QAsymmU8, armnn::QSymmS16, and armnn::Signed32.

944 {
945  const std::string descriptorName{"StackQueueDescriptor"};
946 
947  ValidateNumOutputs(workloadInfo, descriptorName, 1);
948 
949  if (m_Parameters.m_NumInputs != workloadInfo.m_InputTensorInfos.size())
950  {
951  throw InvalidArgumentException(descriptorName + ": Must have the defined number of input tensors.");
952  }
953 
954  // All inputs must have the same shape, which is defined in parameters
955  const TensorShape& inputShape = m_Parameters.m_InputShape;
956  for (unsigned int i = 0; i < workloadInfo.m_InputTensorInfos.size(); ++i)
957  {
958  if (workloadInfo.m_InputTensorInfos[i].GetShape() != inputShape)
959  {
960  throw InvalidArgumentException(descriptorName + ": All input tensor shapes must match the defined shape.");
961  }
962  }
963 
964  if (inputShape.GetNumDimensions() > 4)
965  {
966  throw InvalidArgumentException(descriptorName + ": Input tensor may have up to 4 dimensions.");
967  }
968 
969  // m_Axis is 0-based and may take values from 0 to the number of input dimensions (inclusive),
970  // since the output tensor has an additional dimension.
971  if (m_Parameters.m_Axis > inputShape.GetNumDimensions())
972  {
973  throw InvalidArgumentException(descriptorName + ": Axis may not be greater "
974  "than the number of input dimensions.");
975  }
976 
977  // Output shape must be as inferred from the input shape
978  const TensorShape& outputShape = workloadInfo.m_OutputTensorInfos[0].GetShape();
979  for (unsigned int i = 0; i < m_Parameters.m_Axis; ++i)
980  {
981  if (outputShape[i] != inputShape[i])
982  {
983  throw InvalidArgumentException(descriptorName + ": Output tensor must "
984  "match shape inferred from input tensor.");
985  }
986  }
987 
988  if (outputShape[m_Parameters.m_Axis] != m_Parameters.m_NumInputs)
989  {
990  throw InvalidArgumentException(descriptorName + ": Output tensor must "
991  "match shape inferred from input tensor.");
992  }
993 
994  for (unsigned int i = m_Parameters.m_Axis + 1; i < inputShape.GetNumDimensions() + 1; ++i)
995  {
996  if (outputShape[i] != inputShape[i-1])
997  {
998  throw InvalidArgumentException(descriptorName + ": Output tensor must "
999  "match shape inferred from input tensor.");
1000  }
1001  }
1002 
1003  if (outputShape.GetNumDimensions() > 5)
1004  {
1005  throw InvalidArgumentException(descriptorName + ": Output tensor may have up to 5 dimensions.");
1006  }
1007 
1008  // Check the supported data types
1009  std::vector<DataType> supportedTypes =
1010  {
1019  };
1020 
1021  ValidateDataTypes(workloadInfo.m_InputTensorInfos[0], supportedTypes, descriptorName);
1022 
1023  for (unsigned int i = 1ul; i < workloadInfo.m_InputTensorInfos.size(); ++i)
1024  {
1025  ValidateTensorDataTypesMatch(workloadInfo.m_InputTensorInfos[0],
1026  workloadInfo.m_InputTensorInfos[i],
1027  descriptorName,
1028  "input_0",
1029  "input_" + std::to_string(i));
1030  }
1031 
1032  ValidateTensorDataTypesMatch(workloadInfo.m_InputTensorInfos[0],
1033  workloadInfo.m_OutputTensorInfos[0],
1034  descriptorName,
1035  "input_0",
1036  "output");
1037 }
uint32_t m_Axis
0-based axis along which to stack the input tensors.
TensorShape m_InputShape
Required shape of all input tensors.
std::vector< TensorInfo > m_InputTensorInfos
std::vector< TensorInfo > m_OutputTensorInfos
uint32_t m_NumInputs
Number of input tensors.
unsigned int GetNumDimensions() const
Function that returns the tensor rank.
Definition: Tensor.cpp:174

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