12 class ScopedCpuTensorHandle;
20 std::unique_ptr<ScopedCpuTensorHandle>
m_Weight;
22 std::unique_ptr<ScopedCpuTensorHandle>
m_Bias;
42 std::vector<TensorShape>
InferOutputShapes(
const std::vector<TensorShape>& inputShapes)
const override;
void Accept(ILayerVisitor &visitor) const override
Apply a visitor to this layer.
~Convolution2dLayer()=default
Default destructor.
std::unique_ptr< ScopedCpuTensorHandle > m_Bias
A unique pointer to store Bias values.
A Convolution2dDescriptor for the Convolution2dLayer.
Convolution2dLayer(const Convolution2dDescriptor ¶m, const char *name)
Constructor to create a Convolution2dLayer.
Copyright (c) 2020 ARM Limited.
void ValidateTensorShapesFromInputs() override
Check if the input tensor shape(s) will lead to a valid configuration of Convolution2dLayer.
std::unique_ptr< ScopedCpuTensorHandle > m_Weight
A unique pointer to store Weight values.
Convolution2dLayer * Clone(Graph &graph) const override
Creates a dynamically-allocated copy of this layer.
ConstantTensors GetConstantTensorsByRef() override
Retrieve the handles to the constant values stored by the layer.
virtual std::unique_ptr< IWorkload > CreateWorkload(const IWorkloadFactory &factory) const override
Makes a workload for the Convolution2d type.
void SerializeLayerParameters(ParameterStringifyFunction &fn) const override
Helper to serialize the layer parameters to string.
This layer represents a convolution 2d operation.
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::function< void(const std::string &name, const std::string &value)> ParameterStringifyFunction
std::vector< std::reference_wrapper< std::unique_ptr< ScopedCpuTensorHandle > >> ConstantTensors