ArmNN
 22.08
PadLayer.cpp
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1 //
2 // Copyright © 2017 Arm Ltd and Contributors. All rights reserved.
3 // SPDX-License-Identifier: MIT
4 //
5 
6 #include "PadLayer.hpp"
7 #include "LayerCloneBase.hpp"
8 
12 
13 #include <cstring>
14 
15 namespace armnn
16 {
17 
18 PadLayer::PadLayer(const armnn::PadDescriptor& param, const char* name)
19  : LayerWithParameters(1, 1, LayerType::Pad, param, name)
20 {}
21 
22 std::unique_ptr<IWorkload> PadLayer::CreateWorkload(const armnn::IWorkloadFactory& factory) const
23 {
24  PadQueueDescriptor descriptor;
27  SetAdditionalInfo(descriptor);
28 
29  return factory.CreateWorkload(LayerType::Pad, descriptor, PrepInfoAndDesc(descriptor));
30 }
31 
33 {
34  auto layer = CloneBase<PadLayer>(graph, m_Param, GetName());
35 
36  layer->m_Param.m_PadList = m_Param.m_PadList;
37  layer->m_Param.m_PaddingMode = m_Param.m_PaddingMode;
38 
39  return std::move(layer);
40 }
41 
42 std::vector<TensorShape> PadLayer::InferOutputShapes(const std::vector<TensorShape>& inputShapes) const
43 {
44  ARMNN_ASSERT(inputShapes.size() == 1);
45  const TensorShape& inputShape = inputShapes[0];
46 
47  unsigned int rank = inputShape.GetNumDimensions();
48  ARMNN_ASSERT(m_Param.m_PadList.size() == rank);
49  ARMNN_ASSERT(rank != 0);
50 
51  std::vector<unsigned int> outputDimensionSizes(rank);
52  for (unsigned int i = 0; i < rank; ++i)
53  {
54  outputDimensionSizes[i] = inputShape[i] + m_Param.m_PadList[i].first + m_Param.m_PadList[i].second;
55  }
56 
57  TensorShape tensorShape = TensorShape( rank, outputDimensionSizes.data());
58  return std::vector<TensorShape>({ tensorShape });
59 }
60 
62 {
64 
65  const TensorShape& outputShape = GetOutputSlot(0).GetTensorInfo().GetShape();
66 
68 
69  auto inferredShapes = InferOutputShapes({ GetInputSlot(0).GetConnection()->GetTensorInfo().GetShape() });
70 
71  ARMNN_ASSERT(inferredShapes.size() == 1);
72 
73  ValidateAndCopyShape(outputShape, inferredShapes[0], m_ShapeInferenceMethod, "PadLayer");
74 }
75 
76 void PadLayer::ExecuteStrategy(IStrategy& strategy) const
77 {
78  strategy.ExecuteStrategy(this, GetParameters(), {}, GetName());
79 }
80 
81 } // namespace armnn
PadDescriptor m_Param
The parameters for the layer (not including tensor-valued weights etc.).
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.
Definition: PadLayer.cpp:42
const TensorShape & GetShape() const
Definition: Tensor.hpp:191
virtual std::unique_ptr< IWorkload > CreateWorkload(const IWorkloadFactory &factory) const override
Makes a workload for the Pad type.
Definition: PadLayer.cpp:22
std::vector< std::pair< unsigned int, unsigned int > > m_PadList
Specifies the padding for input dimension.
void VerifyShapeInferenceType(const TensorShape &outputShape, ShapeInferenceMethod shapeInferenceMethod)
Definition: Layer.cpp:491
Copyright (c) 2021 ARM Limited and Contributors.
const PadDescriptor & GetParameters() const override
This layer represents a pad operation.
Definition: PadLayer.hpp:14
const IOutputSlot * GetConnection() const override
Definition: Layer.hpp:206
void ValidateAndCopyShape(const TensorShape &outputShape, const TensorShape &inferredShape, const ShapeInferenceMethod shapeInferenceMethod, const std::string &layerName, const unsigned int outputSlotIndex=0)
Definition: Layer.cpp:422
void VerifyLayerConnections(unsigned int expectedConnections, const CheckLocation &location) const
Definition: Layer.cpp:378
A PadDescriptor for the PadLayer.
const InputSlot & GetInputSlot(unsigned int index) const override
Get a const input slot handle by slot index.
Definition: Layer.hpp:324
#define ARMNN_ASSERT(COND)
Definition: Assert.hpp:14
void Pad(const TensorInfo &inputInfo, const TensorInfo &outputInfo, const ITensorHandle *inputHandle, ITensorHandle *outputHandle, const PadQueueDescriptor &data)
Definition: Pad.cpp:39
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
#define CHECK_LOCATION()
Definition: Exceptions.hpp:203
PaddingMode m_PaddingMode
Specifies the Padding mode (Constant, Reflect or Symmetric)
void SetAdditionalInfo(QueueDescriptor &descriptor) const
Definition: Layer.cpp:274
PadLayer(const PadDescriptor &param, const char *name)
Constructor to create a PadLayer.
Definition: PadLayer.cpp:18
unsigned int GetNumDimensions() const
Function that returns the tensor rank.
Definition: Tensor.cpp:174
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.
Definition: Layer.hpp:326
virtual const TensorInfo & GetTensorInfo() const =0
const char * GetName() const override
Returns the name of the layer.
Definition: Layer.hpp:319
void ValidateTensorShapesFromInputs() override
Check if the input tensor shape(s) will lead to a valid configuration of PadLayer.
Definition: PadLayer.cpp:61
void ExecuteStrategy(IStrategy &strategy) const override
Apply a visitor to this layer.
Definition: PadLayer.cpp:76
PadLayer * Clone(Graph &graph) const override
Creates a dynamically-allocated copy of this layer.
Definition: PadLayer.cpp:32
virtual std::unique_ptr< IWorkload > CreateWorkload(LayerType type, const QueueDescriptor &descriptor, const WorkloadInfo &info) const
const TensorInfo & GetTensorInfo() const override
Definition: Layer.cpp:92
ShapeInferenceMethod m_ShapeInferenceMethod
Definition: Layer.hpp:423
LayerType
When adding a new layer, adapt also the LastLayer enum value in the enum class LayerType below...
Definition: Types.hpp:468