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.).
const LogicalBinaryDescriptor & GetParameters() const
LogicalBinaryLayer(const LogicalBinaryDescriptor ¶m, const char *name)
Constructor to create a LogicalBinaryLayer.
const TensorShape & GetShape() const
#define ARMNN_NO_DEPRECATE_WARN_BEGIN
A LogicalBinaryDescriptor for the LogicalBinaryLayer.
void VerifyShapeInferenceType(const TensorShape &outputShape, ShapeInferenceMethod shapeInferenceMethod)
Copyright (c) 2021 ARM Limited and Contributors.
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_NO_DEPRECATE_WARN_END
#define ARMNN_ASSERT_MSG(COND, MSG)
#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 std::unique_ptr< IWorkload > CreateLogicalBinary(const LogicalBinaryQueueDescriptor &descriptor, const WorkloadInfo &Info) const
ARMNN_NO_DEPRECATE_WARN_BEGIN void Accept(ILayerVisitor &visitor) const override
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.
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...