xref: /aosp_15_r20/external/armnn/src/armnn/layers/SpaceToBatchNdLayer.cpp (revision 89c4ff92f2867872bb9e2354d150bf0c8c502810)
1 //
2 // Copyright © 2017 Arm Ltd and Contributors. All rights reserved.
3 // SPDX-License-Identifier: MIT
4 //
5 
6 #include "SpaceToBatchNdLayer.hpp"
7 #include "LayerCloneBase.hpp"
8 
9 #include <armnn/TypesUtils.hpp>
10 
11 #include <armnnUtils/DataLayoutIndexed.hpp>
12 
13 #include <armnn/backends/WorkloadData.hpp>
14 #include <armnn/backends/WorkloadFactory.hpp>
15 
16 #include <numeric>
17 
18 using namespace armnnUtils;
19 
20 namespace armnn
21 {
22 
SpaceToBatchNdLayer(const SpaceToBatchNdDescriptor param,const char * name)23 SpaceToBatchNdLayer::SpaceToBatchNdLayer(const SpaceToBatchNdDescriptor param, const char* name)
24     : LayerWithParameters(1, 1, LayerType::SpaceToBatchNd, param, name)
25 {}
26 
CreateWorkload(const IWorkloadFactory & factory) const27 std::unique_ptr<IWorkload> SpaceToBatchNdLayer::CreateWorkload(const IWorkloadFactory& factory) const
28 {
29     SpaceToBatchNdQueueDescriptor descriptor;
30     descriptor.m_Parameters.m_BlockShape = m_Param.m_BlockShape;
31     descriptor.m_Parameters.m_PadList    = m_Param.m_PadList;
32     SetAdditionalInfo(descriptor);
33 
34     return factory.CreateWorkload(LayerType::SpaceToBatchNd, descriptor, PrepInfoAndDesc(descriptor));
35 }
36 
Clone(Graph & graph) const37 SpaceToBatchNdLayer* SpaceToBatchNdLayer::Clone(Graph& graph) const
38 {
39     IgnoreUnused(graph);
40     return CloneBase<SpaceToBatchNdLayer>(graph, m_Param, GetName());
41 }
42 
InferOutputShapes(const std::vector<TensorShape> & inputShapes) const43 std::vector<TensorShape> SpaceToBatchNdLayer::InferOutputShapes(const std::vector<TensorShape>& inputShapes) const
44 {
45     ARMNN_ASSERT(inputShapes.size() == 1);
46 
47     TensorShape inputShape = inputShapes[0];
48     TensorShape outputShape(inputShape);
49 
50     outputShape[0] = inputShape[0] * std::accumulate(m_Param.m_BlockShape.begin(),
51                                                      m_Param.m_BlockShape.end(),
52                                                      1U,
53                                                      std::multiplies<>());
54 
55     DataLayoutIndexed dimensionIndices = m_Param.m_DataLayout;
56     unsigned int heightIndex = dimensionIndices.GetHeightIndex();
57     unsigned int widthIndex = dimensionIndices.GetWidthIndex();
58 
59     std::pair<unsigned int, unsigned int> heightPad = m_Param.m_PadList[0];
60     std::pair<unsigned int, unsigned int> widthPad = m_Param.m_PadList[1];
61 
62     outputShape[heightIndex] =
63         (inputShape[heightIndex] + heightPad.first + heightPad.second) / m_Param.m_BlockShape[0];
64     outputShape[widthIndex] =
65         (inputShape[widthIndex] + widthPad.first + widthPad.second) / m_Param.m_BlockShape[1];
66 
67     return std::vector<TensorShape>({ outputShape });
68 }
69 
ValidateTensorShapesFromInputs()70 void SpaceToBatchNdLayer::ValidateTensorShapesFromInputs()
71 {
72     VerifyLayerConnections(1, CHECK_LOCATION());
73 
74     const TensorShape& outputShape = GetOutputSlot(0).GetTensorInfo().GetShape();
75 
76     VerifyShapeInferenceType(outputShape, m_ShapeInferenceMethod);
77 
78     std::vector<TensorShape> inferredShapes = InferOutputShapes({
79         GetInputSlot(0).GetConnection()->GetTensorInfo().GetShape() });
80 
81     ARMNN_ASSERT(inferredShapes.size() == 1);
82 
83     ValidateAndCopyShape(outputShape, inferredShapes[0], m_ShapeInferenceMethod, "SpaceToBatchNdLayer");
84 }
85 
ExecuteStrategy(IStrategy & strategy) const86 void SpaceToBatchNdLayer::ExecuteStrategy(IStrategy& strategy) const
87 {
88     strategy.ExecuteStrategy(this, GetParameters(), {}, GetName());
89 }
90 
91 } // namespace
92