24.02
|
Go to the documentation of this file.
31 auto layer = CloneBase<FullyConnectedLayer>(graph,
m_Param,
GetName());
32 return std::move(layer);
42 unsigned int batches = inputShape[0];
45 return std::vector<TensorShape>({
TensorShape({batches, weightShape[dimIdx]})});
#define ARMNN_ASSERT(COND)
void ValidateTensorShapesFromInputs() override
Check if the input tensor shape(s) will lead to a valid configuration of FullyConnectedLayer.
A FullyConnectedDescriptor for the FullyConnectedLayer.
ImmutableConstantTensors GetConstantTensorsByRef() const override
Retrieve the handles to the constant values stored by the layer.
void ExecuteStrategy(IStrategy &strategy) const override
Apply a visitor to this layer.
const TensorInfo & GetTensorInfo() const override
bool m_TransposeWeightMatrix
Enable/disable transpose weight matrix.
void ValidateAndCopyShape(const TensorShape &outputShape, const TensorShape &inferredShape, const ShapeInferenceMethod shapeInferenceMethod, const std::string &layerName, const unsigned int outputSlotIndex=0)
const OutputSlot & GetOutputSlot(unsigned int index=0) const override
Get the const output slot handle by slot index.
const InputSlot & GetInputSlot(unsigned int index) const override
Get a const input slot handle by slot index.
const FullyConnectedDescriptor & GetParameters() const override
void FullyConnected(const TensorShape &rInputShape, Decoder< float > &rInputDecoder, const TensorShape &rOutputShape, Encoder< float > &rOutputEncoder, const TensorShape &rWeightsShape, Decoder< float > &rWeightDecoder, Decoder< float > *pBiasDecoder, const bool biasEnabled, const unsigned int K, const bool transposeWeights)
Performs a matrix multiplication and optionally adds a bias.
const char * GetName() const override
Returns the name of the layer.
FullyConnectedLayer(const FullyConnectedDescriptor ¶m, const char *name)
Constructor to create a FullyConnectedLayer.
std::vector< std::reference_wrapper< const std::shared_ptr< ConstTensorHandle > >> ImmutableConstantTensors
Layer::ImmutableConstantTensors GetConnectedConstantAsInputTensors() const
FullyConnectedLayer * Clone(Graph &graph) const override
Creates a dynamically-allocated copy of this layer.
FullyConnectedDescriptor m_Param
The parameters for the layer (not including tensor-valued weights etc.).
WorkloadInfo PrepInfoAndDesc(QueueDescriptor &descriptor) const
Helper function to reduce duplication in *Layer::CreateWorkload.
void VerifyShapeInferenceType(const TensorShape &outputShape, ShapeInferenceMethod shapeInferenceMethod)
This layer represents a fully connected operation.
void SetAdditionalInfo(QueueDescriptor &descriptor) const
uint32_t GetNumInputs(bool biasEnabled)
const TensorShape & GetShape() const
Copyright (c) 2021 ARM Limited and Contributors.
virtual std::unique_ptr< IWorkload > CreateWorkload(const IWorkloadFactory &factory) const override
Makes a workload for the FullyConnected type.
ShapeInferenceMethod m_ShapeInferenceMethod
LayerType
When adding a new layer, adapt also the LastLayer enum value in the enum class LayerType below.
virtual std::unique_ptr< IWorkload > CreateWorkload(LayerType type, const QueueDescriptor &descriptor, const WorkloadInfo &info) const =0
Backends should implement their own CreateWorkload function with a switch statement.
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,...