12 class ScopedCpuTensorHandle;
19 std::unique_ptr<ScopedCpuTensorHandle>
m_Weight;
21 std::unique_ptr<ScopedCpuTensorHandle>
m_Bias;
41 std::vector<TensorShape>
InferOutputShapes(
const std::vector<TensorShape>& inputShapes)
const override;
void Accept(ILayerVisitor &visitor) const override
Apply a visitor to this layer.
virtual std::unique_ptr< IWorkload > CreateWorkload(const IWorkloadFactory &factory) const override
Makes a workload for the FullyConnected type.
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.
std::unique_ptr< ScopedCpuTensorHandle > m_Weight
A unique pointer to store Weight values.
ConstantTensors GetConstantTensorsByRef() override
Retrieve the handles to the constant values stored by the layer.
void ValidateTensorShapesFromInputs() override
Check if the input tensor shape(s) will lead to a valid configuration of FullyConnectedLayer.
FullyConnectedLayer * Clone(Graph &graph) const override
Creates a dynamically-allocated copy of this layer.
Copyright (c) 2020 ARM Limited.
FullyConnectedLayer(const FullyConnectedDescriptor ¶m, const char *name)
Constructor to create a FullyConnectedLayer.
~FullyConnectedLayer()=default
Default destructor.
This layer represents a fully connected operation.
A FullyConnectedDescriptor for the FullyConnectedLayer.
std::unique_ptr< ScopedCpuTensorHandle > m_Bias
A unique pointer to store Bias values.
std::vector< std::reference_wrapper< std::unique_ptr< ScopedCpuTensorHandle > >> ConstantTensors