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 <armnn/utility/NumericCast.hpp>
11
12 #include <armnn/backends/TensorHandle.hpp>
13 #include <armnn/backends/WorkloadData.hpp>
14 #include <armnn/backends/WorkloadFactory.hpp>
15
16 namespace armnn
17 {
18
PreluLayer(const char * name)19 PreluLayer::PreluLayer(const char* name)
20 : Layer(2, 1, LayerType::Prelu, name)
21 {}
22
CreateWorkload(const IWorkloadFactory & factory) const23 std::unique_ptr<IWorkload> PreluLayer::CreateWorkload(const IWorkloadFactory& factory) const
24 {
25 PreluQueueDescriptor descriptor;
26 SetAdditionalInfo(descriptor);
27
28 return factory.CreateWorkload(LayerType::Prelu, descriptor, PrepInfoAndDesc(descriptor));
29 }
30
Clone(Graph & graph) const31 PreluLayer* PreluLayer::Clone(Graph& graph) const
32 {
33 auto layer = CloneBase<PreluLayer>(graph, GetName());
34
35 return std::move(layer);
36 }
37
InferOutputShapes(const std::vector<TensorShape> & inputShapes) const38 std::vector<TensorShape> PreluLayer::InferOutputShapes(const std::vector<TensorShape>& inputShapes) const
39 {
40 ARMNN_ASSERT(inputShapes.size() == 2);
41
42 const TensorShape& inputShape = inputShapes[0];
43 const TensorShape& alphaShape = inputShapes[1];
44
45 const unsigned int inputShapeDimensions = inputShape.GetNumDimensions();
46 const unsigned int alphaShapeDimensions = alphaShape.GetNumDimensions();
47
48 ARMNN_ASSERT(inputShapeDimensions > 0);
49 ARMNN_ASSERT(alphaShapeDimensions > 0);
50
51 // The size of the output is the maximum size along each dimension of the input operands,
52 // it starts with the trailing dimensions, and works its way forward
53
54 unsigned int outputDimensions = std::max(inputShapeDimensions, alphaShapeDimensions);
55
56 TensorShape outputShape(outputDimensions);
57
58 int inputShapeIndex = armnn::numeric_cast<int>(inputShapeDimensions) - 1;
59 int alphaShapeIndex = armnn::numeric_cast<int>(alphaShapeDimensions) - 1;
60 unsigned int outputShapeIndex = outputDimensions - 1;
61
62 // Loop backwards through the common part of the shapes
63 while (inputShapeIndex >= 0 && alphaShapeIndex >= 0)
64 {
65 unsigned int inputDimension = inputShape[armnn::numeric_cast<unsigned int>(inputShapeIndex)];
66 unsigned int alphaDimension = alphaShape[armnn::numeric_cast<unsigned int>(alphaShapeIndex)];
67
68 // Check that the inputs are broadcast compatible
69 ARMNN_ASSERT_MSG(inputDimension == alphaDimension || inputDimension == 1 || alphaDimension == 1,
70 "PreluLayer: Dimensions should either match or one should be of size 1");
71
72 outputShape[outputShapeIndex] = std::max(inputDimension, alphaDimension);
73
74 inputShapeIndex--;
75 alphaShapeIndex--;
76 outputShapeIndex--;
77 }
78
79 // Loop backwards through the remaing part of the input shape (if any)
80 while (inputShapeIndex >= 0)
81 {
82 outputShape[outputShapeIndex] = inputShape[armnn::numeric_cast<unsigned int>(inputShapeIndex)];
83
84 inputShapeIndex--;
85 outputShapeIndex--;
86 }
87
88 // Loop backwards through the remaing part of the alpha shape (if any)
89 while (alphaShapeIndex >= 0)
90 {
91 outputShape[outputShapeIndex] = alphaShape[armnn::numeric_cast<unsigned int>(alphaShapeIndex)];
92
93 alphaShapeIndex--;
94 outputShapeIndex--;
95 }
96
97 return { outputShape };
98 }
99
ValidateTensorShapesFromInputs()100 void PreluLayer::ValidateTensorShapesFromInputs()
101 {
102 VerifyLayerConnections(2, CHECK_LOCATION());
103
104 const TensorShape& outputShape = GetOutputSlot(0).GetTensorInfo().GetShape();
105
106 VerifyShapeInferenceType(outputShape, m_ShapeInferenceMethod);
107
108 std::vector<TensorShape> inferredShapes = InferOutputShapes(
109 {
110 GetInputSlot(0).GetConnection()->GetTensorInfo().GetShape(),
111 GetInputSlot(1).GetConnection()->GetTensorInfo().GetShape()
112 });
113
114 ARMNN_ASSERT(inferredShapes.size() == 1);
115
116 ValidateAndCopyShape(outputShape, inferredShapes[0], m_ShapeInferenceMethod, "PreluLayer");
117 }
118
ExecuteStrategy(IStrategy & strategy) const119 void PreluLayer::ExecuteStrategy(IStrategy& strategy) const
120 {
121 strategy.ExecuteStrategy(this, GetParameters(), {}, GetName());
122 }
123
124 } // namespace armnn
125