41 unsigned int numDims = input0.GetNumDimensions();
43 std::vector<unsigned int> dims(numDims);
44 for (
unsigned int i = 0; i < numDims; i++)
46 unsigned int dim0 = input0[i];
47 unsigned int dim1 = input1[i];
50 "Dimensions should either match or one should be of size 1.");
52 dims[i] = std::max(dim0, dim1);
55 return std::vector<TensorShape>({
TensorShape(numDims, dims.data()) });
virtual std::unique_ptr< IWorkload > CreateWorkload(const IWorkloadFactory &factory) const override
Makes a workload for the LogicalBinary type.
void ValidateTensorShapesFromInputs() override
Check if the input tensor shape(s) will lead to a valid configuration of LogicalBinaryLayer.
LogicalBinaryDescriptor m_Param
The parameters for the layer (not including tensor-valued weights etc.).
void ExecuteStrategy(IStrategy &strategy) const override
Apply a visitor to this layer.
LogicalBinaryLayer(const LogicalBinaryDescriptor ¶m, const char *name)
Constructor to create a LogicalBinaryLayer.
const TensorShape & GetShape() const
A LogicalBinaryDescriptor for the LogicalBinaryLayer.
void VerifyShapeInferenceType(const TensorShape &outputShape, ShapeInferenceMethod shapeInferenceMethod)
Copyright (c) 2021 ARM Limited and Contributors.
const LogicalBinaryDescriptor & GetParameters() const override
void ValidateAndCopyShape(const TensorShape &outputShape, const TensorShape &inferredShape, const ShapeInferenceMethod shapeInferenceMethod, const std::string &layerName, const unsigned int outputSlotIndex=0)
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.
This layer represents a Logical Binary operation.
#define ARMNN_ASSERT_MSG(COND, MSG)
#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
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.
LogicalBinaryLayer * Clone(Graph &graph) const override
Creates a dynamically-allocated copy of this layer.
unsigned int GetNumDimensions() const
Function that returns the tensor rank.
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.
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...