41 auto layer = CloneBase<BatchToSpaceNdLayer>(graph,
m_Param,
GetName());
42 return std::move(layer);
72 ARMNN_ASSERT(inputShape[0] % accumulatedBlockShape == 0);
74 outputShape[0] = inputShape[0] / accumulatedBlockShape;
87 "BatchToSpaceLayer: Overall height crop should be less than or equal to the uncropped output height.");
90 "BatchToSpaceLayer: Overall width crop should be less than or equal to the uncropped output width.");
92 outputShape[heightIndex] = outputHeight - heightCrop;
93 outputShape[widthIndex] = outputWidth - widthCrop;
95 return std::vector<TensorShape>({ outputShape });
BatchToSpaceNdDescriptor m_Param
The parameters for the layer (not including tensor-valued weights etc.).
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.
unsigned int GetWidthIndex() const
const TensorShape & GetShape() const
virtual std::unique_ptr< IWorkload > CreateWorkload(const IWorkloadFactory &factory) const override
Makes a workload for the BatchToSpaceNd type.
void ExecuteStrategy(IStrategy &strategy) const override
Apply a visitor to this layer.
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
void VerifyShapeInferenceType(const TensorShape &outputShape, ShapeInferenceMethod shapeInferenceMethod)
BatchToSpaceNdLayer(const BatchToSpaceNdDescriptor ¶m, const char *name)
Constructor to create a BatchToSpaceNdLayer.
Copyright (c) 2021 ARM Limited and Contributors.
const BatchToSpaceNdDescriptor & GetParameters() const override
A BatchToSpaceNdDescriptor for the BatchToSpaceNdLayer.
void ValidateAndCopyShape(const TensorShape &outputShape, const TensorShape &inferredShape, const ShapeInferenceMethod shapeInferenceMethod, const std::string &layerName, const unsigned int outputSlotIndex=0)
unsigned int GetHeightIndex() const
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 ValidateTensorShapesFromInputs() override
Check if the input tensor shape(s) will lead to a valid configuration of BatchToSpaceNdLayer.
#define ARMNN_ASSERT_MSG(COND, MSG)
std::vector< unsigned int > m_BlockShape
Block shape values.
Provides access to the appropriate indexes for Channels, Height and Width based on DataLayout...
This layer represents a BatchToSpaceNd operation.
#define ARMNN_ASSERT(COND)
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
BatchToSpaceNdLayer * Clone(Graph &graph) const override
Creates a dynamically-allocated copy of this layer.
void SetAdditionalInfo(QueueDescriptor &descriptor) const
std::vector< std::pair< unsigned int, unsigned int > > m_Crops
The values to crop from the input dimension.
WorkloadInfo PrepInfoAndDesc(QueueDescriptor &descriptor) const
Helper function to reduce duplication in *LayerCreateWorkload.
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.
void BatchToSpaceNd(const DataLayoutIndexed &dataLayout, const TensorInfo &inputTensorInfo, const TensorInfo &outputTensorInfo, const std::vector< unsigned int > &blockShape, const std::vector< std::pair< unsigned int, unsigned int >> &cropsData, Decoder< float > &inputDecoder, Encoder< float > &outputEncoder)
virtual std::unique_ptr< IWorkload > CreateWorkload(LayerType type, const QueueDescriptor &descriptor, const WorkloadInfo &info) const
const TensorInfo & GetTensorInfo() const override
ShapeInferenceMethod m_ShapeInferenceMethod
LayerType
When adding a new layer, adapt also the LastLayer enum value in the enum class LayerType below...