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DepthToSpaceLayer.cpp
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1 //
2 // Copyright © 2019-2024 Arm Ltd and Contributors. All rights reserved.
3 // SPDX-License-Identifier: MIT
4 //
5 
6 #include "DepthToSpaceLayer.hpp"
7 #include "LayerCloneBase.hpp"
8 
9 #include <armnn/TypesUtils.hpp>
10 
12 
15 
16 #include <numeric>
17 
18 namespace armnn
19 {
20 
22  : LayerWithParameters(1, 1, LayerType::DepthToSpace, param, name)
23 {}
24 
25 std::unique_ptr<IWorkload> DepthToSpaceLayer::CreateWorkload(const IWorkloadFactory& factory) const
26 {
27  DepthToSpaceQueueDescriptor descriptor;
30 
31  SetAdditionalInfo(descriptor);
32 
33  return factory.CreateWorkload(LayerType::DepthToSpace, descriptor, PrepInfoAndDesc(descriptor));
34 }
35 
37 {
38  return CloneBase<DepthToSpaceLayer>(graph, m_Param, GetName());
39 }
40 
41 std::vector<TensorShape> DepthToSpaceLayer::InferOutputShapes(const std::vector<TensorShape>& inputShapes) const
42 {
43  if (inputShapes.size() != 1)
44  {
45  throw armnn::Exception("inputShapes' size is \"" + std::to_string(inputShapes.size()) +
46  "\" - should be \"1\".");
47  }
48 
49  TensorShape inputShape = inputShapes[0];
50  TensorShape outputShape(inputShape);
51 
53 
54  unsigned int hIndex = dimensionIndices.GetHeightIndex();
55  unsigned int wIndex = dimensionIndices.GetWidthIndex();
56  unsigned int cIndex = dimensionIndices.GetChannelsIndex();
57 
58  outputShape[hIndex] = inputShape[hIndex] * m_Param.m_BlockSize;
59  outputShape[wIndex] = inputShape[wIndex] * m_Param.m_BlockSize;
60 
61  outputShape[cIndex] = inputShape[cIndex] / (m_Param.m_BlockSize * m_Param.m_BlockSize);
62 
63  return std::vector<TensorShape>({ outputShape });
64 }
65 
67 {
69 
70  const TensorShape& outputShape = GetOutputSlot(0).GetTensorInfo().GetShape();
71 
73 
74  std::vector<TensorShape> inferredShapes = InferOutputShapes({
76 
77  if (inferredShapes.size() != 1)
78  {
79  throw armnn::LayerValidationException("inferredShapes has "
80  + std::to_string(inferredShapes.size()) +
81  " elements - should only have 1.");
82  }
83 
84  ValidateAndCopyShape(outputShape, inferredShapes[0], m_ShapeInferenceMethod, "DepthToSpaceLayer");
85 }
86 
88 {
89  strategy.ExecuteStrategy(this, GetParameters(), {}, GetName());
90 }
91 
92 } // namespace armnn
#define CHECK_LOCATION()
Definition: Exceptions.hpp:203
This layer represents a DepthToSpace operation.
DepthToSpaceLayer * Clone(Graph &graph) const override
Creates a dynamically-allocated copy of this layer.
DepthToSpaceLayer(const DepthToSpaceDescriptor &param, const char *name)
Constructor to create a DepthToSpaceLayer.
void ExecuteStrategy(IStrategy &strategy) const override
Apply a visitor to this layer.
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,...
void ValidateTensorShapesFromInputs() override
Check if the input tensor shape(s) will lead to a valid configuration of DepthToSpaceLayer.
virtual std::unique_ptr< IWorkload > CreateWorkload(const IWorkloadFactory &factory) const override
Makes a workload for the DepthToSpace type.
Base class for all ArmNN exceptions so that users can filter to just those.
Definition: Exceptions.hpp:47
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
virtual std::unique_ptr< IWorkload > CreateWorkload(LayerType type, const QueueDescriptor &descriptor, const WorkloadInfo &info) const =0
Backends should implement their own CreateWorkload function with a switch statement.
const TensorInfo & GetTensorInfo() const override
Gets the TensorInfo for this InputSlot.
Definition: Layer.cpp:614
void VerifyLayerConnections(unsigned int expectedConnections, const CheckLocation &location) const
Definition: Layer.cpp:410
const OutputSlot & GetOutputSlot(unsigned int index=0) const override
Get the const output slot handle by slot index.
Definition: Layer.hpp:339
void VerifyShapeInferenceType(const TensorShape &outputShape, ShapeInferenceMethod shapeInferenceMethod)
Definition: Layer.cpp:526
const char * GetName() const override
Returns the name of the layer.
Definition: Layer.hpp:332
const InputSlot & GetInputSlot(unsigned int index) const override
Get a const input slot handle by slot index.
Definition: Layer.hpp:337
void ValidateAndCopyShape(const TensorShape &outputShape, const TensorShape &inferredShape, const ShapeInferenceMethod shapeInferenceMethod, const std::string &layerName, const unsigned int outputSlotIndex=0)
Definition: Layer.cpp:457
void SetAdditionalInfo(QueueDescriptor &descriptor) const
Definition: Layer.cpp:303
ShapeInferenceMethod m_ShapeInferenceMethod
Definition: Layer.hpp:441
WorkloadInfo PrepInfoAndDesc(QueueDescriptor &descriptor) const
Helper function to reduce duplication in *Layer::CreateWorkload.
DepthToSpaceDescriptor m_Param
The parameters for the layer (not including tensor-valued weights etc.).
const DepthToSpaceDescriptor & GetParameters() const override
const TensorInfo & GetTensorInfo() const override
Definition: Layer.cpp:100
const TensorShape & GetShape() const
Definition: Tensor.hpp:193
Provides access to the appropriate indexes for Channels, Height and Width based on DataLayout.
unsigned int GetWidthIndex() const
unsigned int GetHeightIndex() const
unsigned int GetChannelsIndex() const
Copyright (c) 2021 ARM Limited and Contributors.
LayerType
When adding a new layer, adapt also the LastLayer enum value in the enum class LayerType below.
Definition: Types.hpp:494
void DepthToSpace(const TensorInfo &inputInfo, const DepthToSpaceDescriptor &descriptor, const void *inputData, void *outputData, unsigned int dataTypeSize)
A SpaceToDepthDescriptor for the SpaceToDepthLayer.
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
unsigned int m_BlockSize
Scalar specifying the input block size. It must be >= 1.