xref: /aosp_15_r20/external/armnn/src/armnn/layers/PadLayer.cpp (revision 89c4ff92f2867872bb9e2354d150bf0c8c502810)
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 
9 #include <armnn/backends/TensorHandle.hpp>
10 #include <armnn/backends/WorkloadData.hpp>
11 #include <armnn/backends/WorkloadFactory.hpp>
12 
13 #include <cstring>
14 
15 namespace armnn
16 {
17 
PadLayer(const armnn::PadDescriptor & param,const char * name)18 PadLayer::PadLayer(const armnn::PadDescriptor& param, const char* name)
19     : LayerWithParameters(1, 1, LayerType::Pad, param, name)
20 {}
21 
CreateWorkload(const armnn::IWorkloadFactory & factory) const22 std::unique_ptr<IWorkload> PadLayer::CreateWorkload(const armnn::IWorkloadFactory& factory) const
23 {
24     PadQueueDescriptor descriptor;
25     descriptor.m_Parameters.m_PadList = m_Param.m_PadList;
26     descriptor.m_Parameters.m_PaddingMode = m_Param.m_PaddingMode;
27     SetAdditionalInfo(descriptor);
28 
29     return factory.CreateWorkload(LayerType::Pad, descriptor, PrepInfoAndDesc(descriptor));
30 }
31 
Clone(Graph & graph) const32 PadLayer* PadLayer::Clone(Graph& graph) const
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 
InferOutputShapes(const std::vector<TensorShape> & inputShapes) const42 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 
ValidateTensorShapesFromInputs()61 void PadLayer::ValidateTensorShapesFromInputs()
62 {
63     VerifyLayerConnections(1, CHECK_LOCATION());
64 
65     const TensorShape& outputShape = GetOutputSlot(0).GetTensorInfo().GetShape();
66 
67     VerifyShapeInferenceType(outputShape, m_ShapeInferenceMethod);
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 
ExecuteStrategy(IStrategy & strategy) const76 void PadLayer::ExecuteStrategy(IStrategy& strategy) const
77 {
78     strategy.ExecuteStrategy(this, GetParameters(), {}, GetName());
79 }
80 
81 } // namespace armnn
82