From 4840dfb7543d66652dc11c5ff39c8f5c1e2f9370 Mon Sep 17 00:00:00 2001 From: Ryan OShea Date: Tue, 25 Aug 2020 12:35:58 +0100 Subject: Updating Doxygen Documentation for 20.08 release Signed-off-by: Ryan OShea Change-Id: I605409f8720de5353feceb161b39f8a5f0598180 --- 20.08/_prelu_layer_8cpp_source.xhtml | 153 +++++++++++++++++++++++++++++++++++ 1 file changed, 153 insertions(+) create mode 100644 20.08/_prelu_layer_8cpp_source.xhtml (limited to '20.08/_prelu_layer_8cpp_source.xhtml') diff --git a/20.08/_prelu_layer_8cpp_source.xhtml b/20.08/_prelu_layer_8cpp_source.xhtml new file mode 100644 index 0000000000..0e765a6acc --- /dev/null +++ b/20.08/_prelu_layer_8cpp_source.xhtml @@ -0,0 +1,153 @@ + + + + + + + + + + + + + +ArmNN: src/armnn/layers/PreluLayer.cpp Source File + + + + + + + + + + + + + + + + +
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PreluLayer.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 "PreluLayer.hpp"
7 
8 #include "LayerCloneBase.hpp"
9 
10 #include <backendsCommon/WorkloadData.hpp>
11 #include <backendsCommon/WorkloadFactory.hpp>
12 #include <backendsCommon/CpuTensorHandle.hpp>
13 
14 namespace armnn
15 {
16 
17 PreluLayer::PreluLayer(const char* name)
18  : Layer(2, 1, LayerType::Prelu, name)
19 {}
20 
21 std::unique_ptr<IWorkload> PreluLayer::CreateWorkload(const IWorkloadFactory& factory) const
22 {
23  PreluQueueDescriptor descriptor;
24 
25  return factory.CreatePrelu(descriptor, PrepInfoAndDesc(descriptor));
26 }
27 
28 PreluLayer* PreluLayer::Clone(Graph& graph) const
29 {
30  auto layer = CloneBase<PreluLayer>(graph, GetName());
31 
32  return std::move(layer);
33 }
34 
35 std::vector<TensorShape> PreluLayer::InferOutputShapes(const std::vector<TensorShape>& inputShapes) const
36 {
37  ARMNN_ASSERT(inputShapes.size() == 2);
38 
39  const TensorShape& inputShape = inputShapes[0];
40  const TensorShape& alphaShape = inputShapes[1];
41 
42  const unsigned int inputShapeDimensions = inputShape.GetNumDimensions();
43  const unsigned int alphaShapeDimensions = alphaShape.GetNumDimensions();
44 
45  ARMNN_ASSERT(inputShapeDimensions > 0);
46  ARMNN_ASSERT(alphaShapeDimensions > 0);
47 
48  // The size of the output is the maximum size along each dimension of the input operands,
49  // it starts with the trailing dimensions, and works its way forward
50 
51  unsigned int outputDimensions = std::max(inputShapeDimensions, alphaShapeDimensions);
52 
53  TensorShape outputShape(outputDimensions);
54 
55  int inputShapeIndex = boost::numeric_cast<int>(inputShapeDimensions) - 1;
56  int alphaShapeIndex = boost::numeric_cast<int>(alphaShapeDimensions) - 1;
57  unsigned int outputShapeIndex = outputDimensions - 1;
58 
59  // Loop backwards through the common part of the shapes
60  while (inputShapeIndex >= 0 && alphaShapeIndex >= 0)
61  {
62  unsigned int inputDimension = inputShape[boost::numeric_cast<unsigned int>(inputShapeIndex)];
63  unsigned int alphaDimension = alphaShape[boost::numeric_cast<unsigned int>(alphaShapeIndex)];
64 
65  // Check that the inputs are broadcast compatible
66  ARMNN_ASSERT_MSG(inputDimension == alphaDimension || inputDimension == 1 || alphaDimension == 1,
67  "PreluLayer: Dimensions should either match or one should be of size 1");
68 
69  outputShape[outputShapeIndex] = std::max(inputDimension, alphaDimension);
70 
71  inputShapeIndex--;
72  alphaShapeIndex--;
73  outputShapeIndex--;
74  }
75 
76  // Loop backwards through the remaing part of the input shape (if any)
77  while (inputShapeIndex >= 0)
78  {
79  outputShape[outputShapeIndex] = inputShape[boost::numeric_cast<unsigned int>(inputShapeIndex)];
80 
81  inputShapeIndex--;
82  outputShapeIndex--;
83  }
84 
85  // Loop backwards through the remaing part of the alpha shape (if any)
86  while (alphaShapeIndex >= 0)
87  {
88  outputShape[outputShapeIndex] = alphaShape[boost::numeric_cast<unsigned int>(alphaShapeIndex)];
89 
90  alphaShapeIndex--;
91  outputShapeIndex--;
92  }
93 
94  return { outputShape };
95 }
96 
97 void PreluLayer::ValidateTensorShapesFromInputs()
98 {
99  VerifyLayerConnections(2, CHECK_LOCATION());
100 
101  const TensorShape& outputShape = GetOutputSlot(0).GetTensorInfo().GetShape();
102 
103  VerifyShapeInferenceType(outputShape, m_ShapeInferenceMethod);
104 
105  std::vector<TensorShape> inferredShapes = InferOutputShapes(
106  {
107  GetInputSlot(0).GetConnection()->GetTensorInfo().GetShape(),
108  GetInputSlot(1).GetConnection()->GetTensorInfo().GetShape()
109  });
110 
111  ARMNN_ASSERT(inferredShapes.size() == 1);
112 
113  ValidateAndCopyShape(outputShape, inferredShapes[0], m_ShapeInferenceMethod, "PreluLayer");
114 }
115 
116 void PreluLayer::Accept(ILayerVisitor& visitor) const
117 {
118  visitor.VisitPreluLayer(this, GetName());
119 }
120 
121 } // namespace armnn
armnn::PreluLayer::CreateWorkload
virtual std::unique_ptr< IWorkload > CreateWorkload(const IWorkloadFactory &factory) const override
Makes a workload for the PReLU type.
Definition: PreluLayer.cpp:21
+
WorkloadData.hpp
+
armnn::TensorInfo::GetShape
const TensorShape & GetShape() const
Definition: Tensor.hpp:187
+
armnn::PreluLayer::Clone
PreluLayer * Clone(Graph &graph) const override
Creates a dynamically-allocated copy of this layer.
Definition: PreluLayer.cpp:28
+
WorkloadFactory.hpp
+ +
armnn::ILayerVisitor::VisitPreluLayer
virtual void VisitPreluLayer(const IConnectableLayer *layer, const char *name=nullptr)=0
Function that a PReLU activation layer should call back to when its Accept(ILayerVisitor&) function i...
+
armnn::PreluLayer::Accept
void Accept(ILayerVisitor &visitor) const override
Apply a visitor to this layer.
Definition: PreluLayer.cpp:116
+
armnn::Layer::VerifyShapeInferenceType
void VerifyShapeInferenceType(const TensorShape &outputShape, ShapeInferenceMethod shapeInferenceMethod)
Definition: Layer.cpp:432
+
armnn
Copyright (c) 2020 ARM Limited.
Definition: 00_introduction.dox:25
+
armnn::PreluLayer::PreluLayer
PreluLayer(const char *name)
Constructor to create a PreluLayer.
Definition: PreluLayer.cpp:17
+ + +
armnn::InputSlot::GetConnection
const IOutputSlot * GetConnection() const override
Definition: Layer.hpp:199
+
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:392
+ +
armnn::Layer::VerifyLayerConnections
void VerifyLayerConnections(unsigned int expectedConnections, const CheckLocation &location) const
Definition: Layer.cpp:344
+
PreluLayer.hpp
+
armnn::Layer::GetInputSlot
const InputSlot & GetInputSlot(unsigned int index) const override
Get a const input slot handle by slot index.
Definition: Layer.hpp:312
+
ARMNN_ASSERT_MSG
#define ARMNN_ASSERT_MSG(COND, MSG)
Definition: Assert.hpp:15
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armnn::PreluLayer::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, otherwise infers the output shapes from given input shapes and layer properties.
Definition: PreluLayer.cpp:35
+
armnn::Layer::PrepInfoAndDesc
WorkloadInfo PrepInfoAndDesc(QueueDescriptor &descriptor) const
Helper function to reduce duplication in *LayerCreateWorkload.
Definition: Layer.hpp:366
+
ARMNN_ASSERT
#define ARMNN_ASSERT(COND)
Definition: Assert.hpp:14
+
armnn::numeric_cast
std::enable_if_t< std::is_unsigned< Source >::value &&std::is_unsigned< Dest >::value, Dest > numeric_cast(Source source)
Definition: NumericCast.hpp:33
+
CHECK_LOCATION
#define CHECK_LOCATION()
Definition: Exceptions.hpp:197
+ +
CpuTensorHandle.hpp
+
armnn::TensorShape::GetNumDimensions
unsigned int GetNumDimensions() const
Function that returns the tensor rank.
Definition: Tensor.cpp:175
+ +
armnn::Layer::GetOutputSlot
const OutputSlot & GetOutputSlot(unsigned int index=0) const override
Get the const output slot handle by slot index.
Definition: Layer.hpp:314
+ +
armnn::IOutputSlot::GetTensorInfo
virtual const TensorInfo & GetTensorInfo() const =0
+
armnn::Layer::GetName
const char * GetName() const override
Returns the name of the layer.
Definition: Layer.hpp:307
+
armnn::PreluLayer::ValidateTensorShapesFromInputs
void ValidateTensorShapesFromInputs() override
Check if the input tensor shape(s) will lead to a valid configuration of PreluLayer.
Definition: PreluLayer.cpp:97
+
armnn::OutputSlot::GetTensorInfo
const TensorInfo & GetTensorInfo() const override
Definition: Layer.cpp:63
+
armnn::Layer::m_ShapeInferenceMethod
ShapeInferenceMethod m_ShapeInferenceMethod
Definition: Layer.hpp:387
+ +
LayerCloneBase.hpp
+ +
armnn::IWorkloadFactory::CreatePrelu
virtual std::unique_ptr< IWorkload > CreatePrelu(const PreluQueueDescriptor &descriptor, const WorkloadInfo &info) const
Definition: WorkloadFactory.cpp:1501
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