49 unsigned int outBatch = inputShape[0];
52 TensorShape( { outBatch, outHeight, outWidth, outChannels } ) :
53 TensorShape( { outBatch, outChannels, outHeight, outWidth });
60 return std::vector<TensorShape>({ tensorShape });
void ValidateTensorShapesFromInputs() override
Check if the input tensor shape(s) will lead to a valid configuration of ResizeLayer.
ResizeDescriptor m_Param
The parameters for the layer (not including tensor-valued weights etc.).
const TensorShape & GetShape() const
ResizeLayer(const ResizeDescriptor ¶m, const char *name)
Constructor to create a ResizeLayer.
void VerifyShapeInferenceType(const TensorShape &outputShape, ShapeInferenceMethod shapeInferenceMethod)
Copyright (c) 2021 ARM Limited and Contributors.
const ResizeDescriptor & GetParameters() const override
void ValidateAndCopyShape(const TensorShape &outputShape, const TensorShape &inferredShape, const ShapeInferenceMethod shapeInferenceMethod, const std::string &layerName, const unsigned int outputSlotIndex=0)
A ResizeDescriptor for the ResizeLayer.
void VerifyLayerConnections(unsigned int expectedConnections, const CheckLocation &location) const
const InputSlot & GetInputSlot(unsigned int index) const override
Get a const input slot handle by slot index.
void ExecuteStrategy(IStrategy &strategy) const override
Apply a visitor to this layer.
Provides access to the appropriate indexes for Channels, Height and Width based on DataLayout...
uint32_t m_TargetWidth
Target width value.
bool m_HalfPixelCenters
Half Pixel Centers.
#define ARMNN_ASSERT(COND)
std::vector< TensorShape > InferOutputShapes(const std::vector< TensorShape > &inputShapes) const override
By default returns inputShapes if the number of inputs are equal to number of outputs, otherwise infers the output shapes from given input shapes and layer properties.
virtual void ExecuteStrategy(const IConnectableLayer *layer, const armnn::BaseDescriptor &descriptor, const std::vector< armnn::ConstTensor > &constants, const char *name, const armnn::LayerBindingId id=0)=0
uint32_t m_TargetHeight
Target height value.
void SetAdditionalInfo(QueueDescriptor &descriptor) const
bool m_AlignCorners
Aligned corners.
ResizeLayer * Clone(Graph &graph) const override
Creates a dynamically-allocated copy of this layer.
virtual std::unique_ptr< IWorkload > CreateWorkload(const IWorkloadFactory &factory) const override
Makes a workload for the Resize type.
WorkloadInfo PrepInfoAndDesc(QueueDescriptor &descriptor) const
Helper function to reduce duplication in *Layer::CreateWorkload.
const OutputSlot & GetOutputSlot(unsigned int index=0) const override
Get the const output slot handle by slot index.
virtual const TensorInfo & GetTensorInfo() const =0
const char * GetName() const override
Returns the name of the layer.
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
virtual std::unique_ptr< IWorkload > CreateWorkload(LayerType type, const QueueDescriptor &descriptor, const WorkloadInfo &info) const
const TensorInfo & GetTensorInfo() const override
unsigned int GetChannelsIndex() const
ShapeInferenceMethod m_ShapeInferenceMethod
void Resize(Decoder< float > &in, const TensorInfo &inputInfo, Encoder< float > &out, const TensorInfo &outputInfo, DataLayoutIndexed dataLayout, armnn::ResizeMethod resizeMethod, bool alignCorners, bool halfPixelCenters)
This layer represents a resize operation.
LayerType
When adding a new layer, adapt also the LastLayer enum value in the enum class LayerType below...