ArmNN
 24.02
FullyConnectedLayer.cpp
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1 //
2 // Copyright © 2017-2023 Arm Ltd and Contributors. All rights reserved.
3 // SPDX-License-Identifier: MIT
4 //
6 
7 #include "LayerCloneBase.hpp"
8 
9 #include <armnn/TypesUtils.hpp>
13 
14 namespace armnn
15 {
16 
18  : LayerWithParameters(param.GetNumInputs(), 1, LayerType::FullyConnected, param, name)
19 {
20 }
21 
22 std::unique_ptr<IWorkload> FullyConnectedLayer::CreateWorkload(const IWorkloadFactory& factory) const
23 {
25  SetAdditionalInfo(descriptor);
26  return factory.CreateWorkload(LayerType::FullyConnected, descriptor, PrepInfoAndDesc(descriptor));
27 }
28 
30 {
31  auto layer = CloneBase<FullyConnectedLayer>(graph, m_Param, GetName());
32  return std::move(layer);
33 }
34 
35 std::vector<TensorShape> FullyConnectedLayer::InferOutputShapes(const std::vector<TensorShape>& inputShapes) const
36 {
37  ARMNN_ASSERT(inputShapes.size() == 2);
38  const TensorShape& inputShape = inputShapes[0];
39  const TensorShape weightShape = inputShapes[1];
40 
41  // Output for FC is [1, w[1]].
42  unsigned int batches = inputShape[0];
43  unsigned int dimIdx = m_Param.m_TransposeWeightMatrix ? 0 : 1;
44 
45  return std::vector<TensorShape>({ TensorShape({batches, weightShape[dimIdx]})});
46 }
47 
49 {
50  const TensorShape& outputShape = GetOutputSlot(0).GetTensorInfo().GetShape();
51 
53 
54  std::vector<TensorShape> inferredShapes = InferOutputShapes(
57 
58  ARMNN_ASSERT(inferredShapes.size() == 1);
59  ARMNN_ASSERT(inferredShapes[0].GetDimensionality() == Dimensionality::Specified);
60 
61  ValidateAndCopyShape(outputShape, inferredShapes[0], m_ShapeInferenceMethod, "FullyConnectedLayer");
62 }
63 
65 {
67  return tensors;
68 }
69 
71 {
72  strategy.ExecuteStrategy(this, GetParameters(), {}, GetName());
73 }
74 
75 } // namespace armnn
ARMNN_ASSERT
#define ARMNN_ASSERT(COND)
Definition: Assert.hpp:14
armnn::FullyConnectedLayer::ValidateTensorShapesFromInputs
void ValidateTensorShapesFromInputs() override
Check if the input tensor shape(s) will lead to a valid configuration of FullyConnectedLayer.
Definition: FullyConnectedLayer.cpp:48
armnn::FullyConnectedDescriptor
A FullyConnectedDescriptor for the FullyConnectedLayer.
Definition: Descriptors.hpp:507
FullyConnectedLayer.hpp
armnn::FullyConnectedLayer::GetConstantTensorsByRef
ImmutableConstantTensors GetConstantTensorsByRef() const override
Retrieve the handles to the constant values stored by the layer.
Definition: FullyConnectedLayer.cpp:64
armnn::FullyConnectedQueueDescriptor
Definition: WorkloadData.hpp:180
armnn::FullyConnectedLayer::ExecuteStrategy
void ExecuteStrategy(IStrategy &strategy) const override
Apply a visitor to this layer.
Definition: FullyConnectedLayer.cpp:70
armnn::OutputSlot::GetTensorInfo
const TensorInfo & GetTensorInfo() const override
Definition: Layer.cpp:92
WorkloadData.hpp
armnn::FullyConnectedDescriptor::m_TransposeWeightMatrix
bool m_TransposeWeightMatrix
Enable/disable transpose weight matrix.
Definition: Descriptors.hpp:528
TypesUtils.hpp
armnn::Layer::ValidateAndCopyShape
void ValidateAndCopyShape(const TensorShape &outputShape, const TensorShape &inferredShape, const ShapeInferenceMethod shapeInferenceMethod, const std::string &layerName, const unsigned int outputSlotIndex=0)
Definition: Layer.cpp:435
armnn::Layer::GetOutputSlot
const OutputSlot & GetOutputSlot(unsigned int index=0) const override
Get the const output slot handle by slot index.
Definition: Layer.hpp:339
armnn::IStrategy
Definition: IStrategy.hpp:16
armnn::Layer::GetInputSlot
const InputSlot & GetInputSlot(unsigned int index) const override
Get a const input slot handle by slot index.
Definition: Layer.hpp:337
armnn::LayerWithParameters< FullyConnectedDescriptor >::GetParameters
const FullyConnectedDescriptor & GetParameters() const override
Definition: LayerWithParameters.hpp:19
WorkloadFactory.hpp
armnn::LayerWithParameters
Definition: LayerWithParameters.hpp:14
armnn::FullyConnected
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.
Definition: FullyConnected.cpp:15
armnn::Layer::GetName
const char * GetName() const override
Returns the name of the layer.
Definition: Layer.hpp:332
armnn::FullyConnectedLayer::FullyConnectedLayer
FullyConnectedLayer(const FullyConnectedDescriptor &param, const char *name)
Constructor to create a FullyConnectedLayer.
Definition: FullyConnectedLayer.cpp:17
armnn::IConnectableLayer::ImmutableConstantTensors
std::vector< std::reference_wrapper< const std::shared_ptr< ConstTensorHandle > >> ImmutableConstantTensors
Definition: INetwork.hpp:141
armnn::InputSlot::GetTensorInfo
const TensorInfo & GetTensorInfo() const override
Gets the TensorInfo for this InputSlot.
Definition: Layer.cpp:592
armnn::LayerWithParameters< FullyConnectedDescriptor >::GetConnectedConstantAsInputTensors
Layer::ImmutableConstantTensors GetConnectedConstantAsInputTensors() const
Definition: LayerWithParameters.hpp:59
armnn::TensorShape
Definition: Tensor.hpp:20
armnn::FullyConnectedLayer::Clone
FullyConnectedLayer * Clone(Graph &graph) const override
Creates a dynamically-allocated copy of this layer.
Definition: FullyConnectedLayer.cpp:29
armnn::LayerWithParameters< FullyConnectedDescriptor >::m_Param
FullyConnectedDescriptor m_Param
The parameters for the layer (not including tensor-valued weights etc.).
Definition: LayerWithParameters.hpp:52
armnn::LayerWithParameters< FullyConnectedDescriptor >::PrepInfoAndDesc
WorkloadInfo PrepInfoAndDesc(QueueDescriptor &descriptor) const
Helper function to reduce duplication in *Layer::CreateWorkload.
Definition: LayerWithParameters.hpp:44
armnn::IWorkloadFactory
Definition: WorkloadFactory.hpp:22
armnn::Layer::VerifyShapeInferenceType
void VerifyShapeInferenceType(const TensorShape &outputShape, ShapeInferenceMethod shapeInferenceMethod)
Definition: Layer.cpp:504
armnn::FullyConnectedLayer
This layer represents a fully connected operation.
Definition: FullyConnectedLayer.hpp:15
armnn::Layer::SetAdditionalInfo
void SetAdditionalInfo(QueueDescriptor &descriptor) const
Definition: Layer.cpp:287
armnn::GetNumInputs
uint32_t GetNumInputs(bool biasEnabled)
Definition: Descriptors.cpp:454
armnn::LayerType::FullyConnected
@ FullyConnected
armnn::Dimensionality::Specified
@ Specified
TensorHandle.hpp
armnn::TensorInfo::GetShape
const TensorShape & GetShape() const
Definition: Tensor.hpp:193
armnn
Copyright (c) 2021 ARM Limited and Contributors.
Definition: 01_00_quick_start.dox:6
armnn::FullyConnectedLayer::CreateWorkload
virtual std::unique_ptr< IWorkload > CreateWorkload(const IWorkloadFactory &factory) const override
Makes a workload for the FullyConnected type.
Definition: FullyConnectedLayer.cpp:22
armnn::Layer::m_ShapeInferenceMethod
ShapeInferenceMethod m_ShapeInferenceMethod
Definition: Layer.hpp:441
armnn::LayerType
LayerType
When adding a new layer, adapt also the LastLayer enum value in the enum class LayerType below.
Definition: Types.hpp:491
armnn::Graph
Definition: Graph.hpp:30
armnn::IWorkloadFactory::CreateWorkload
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.
armnn::IStrategy::ExecuteStrategy
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
LayerCloneBase.hpp
armnn::FullyConnectedLayer::InferOutputShapes
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,...
Definition: FullyConnectedLayer.cpp:35