From 6940dd720ebb6b3d1df8ca203ab696daefe58189 Mon Sep 17 00:00:00 2001 From: Jim Flynn Date: Fri, 20 Mar 2020 12:25:56 +0000 Subject: renamed Documentation folder 20.02 and added .nojekyll file Signed-off-by: Jim Flynn --- ...ssarmnn_1_1_depthwise_convolution2d_layer.xhtml | 756 +++++++++++++++++++++ 1 file changed, 756 insertions(+) create mode 100644 20.02/classarmnn_1_1_depthwise_convolution2d_layer.xhtml (limited to '20.02/classarmnn_1_1_depthwise_convolution2d_layer.xhtml') diff --git a/20.02/classarmnn_1_1_depthwise_convolution2d_layer.xhtml b/20.02/classarmnn_1_1_depthwise_convolution2d_layer.xhtml new file mode 100644 index 0000000000..f769fe3632 --- /dev/null +++ b/20.02/classarmnn_1_1_depthwise_convolution2d_layer.xhtml @@ -0,0 +1,756 @@ + + + + + + + + + + + + + +ArmNN: DepthwiseConvolution2dLayer Class Reference + + + + + + + + + + + + + + + + +
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+ + + + ArmNN + + + +
+
+  20.02 +
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+
DepthwiseConvolution2dLayer Class Reference
+
+
+ +

This layer represents a depthwise convolution 2d operation. + More...

+ +

#include <DepthwiseConvolution2dLayer.hpp>

+
+Inheritance diagram for DepthwiseConvolution2dLayer:
+
+
+ + +LayerWithParameters< DepthwiseConvolution2dDescriptor > +Layer +IConnectableLayer + +
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

+Public Member Functions

virtual std::unique_ptr< IWorkloadCreateWorkload (const IWorkloadFactory &factory) const override
 Makes a workload for the DepthwiseConvolution2d type. More...
 
DepthwiseConvolution2dLayerClone (Graph &graph) const override
 Creates a dynamically-allocated copy of this layer. More...
 
void ValidateTensorShapesFromInputs () override
 Check if the input tensor shape(s) will lead to a valid configuration of DepthwiseConvolution2dLayer. More...
 
std::vector< TensorShapeInferOutputShapes (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. More...
 
void Accept (ILayerVisitor &visitor) const override
 Apply a visitor to this layer. More...
 
void SerializeLayerParameters (ParameterStringifyFunction &fn) const override
 Helper to serialize the layer parameters to string. More...
 
- Public Member Functions inherited from LayerWithParameters< DepthwiseConvolution2dDescriptor >
const DepthwiseConvolution2dDescriptorGetParameters () const
 
void SerializeLayerParameters (ParameterStringifyFunction &fn) const override
 Helper to serialize the layer parameters to string (currently used in DotSerializer and company). More...
 
- Public Member Functions inherited from Layer
 Layer (unsigned int numInputSlots, unsigned int numOutputSlots, LayerType type, const char *name)
 
 Layer (unsigned int numInputSlots, unsigned int numOutputSlots, LayerType type, DataLayout layout, const char *name)
 
const std::string & GetNameStr () const
 
const OutputHandlerGetOutputHandler (unsigned int i=0) const
 
OutputHandlerGetOutputHandler (unsigned int i=0)
 
const std::vector< InputSlot > & GetInputSlots () const
 
const std::vector< OutputSlot > & GetOutputSlots () const
 
std::vector< InputSlot >::iterator BeginInputSlots ()
 
std::vector< InputSlot >::iterator EndInputSlots ()
 
std::vector< OutputSlot >::iterator BeginOutputSlots ()
 
std::vector< OutputSlot >::iterator EndOutputSlots ()
 
bool IsOutputUnconnected ()
 
void ResetPriority () const
 
LayerPriority GetPriority () const
 
LayerType GetType () const
 
DataType GetDataType () const
 
const BackendIdGetBackendId () const
 
void SetBackendId (const BackendId &id)
 
virtual void CreateTensorHandles (const TensorHandleFactoryRegistry &registry, const IWorkloadFactory &factory, const bool IsMemoryManaged=true)
 
void VerifyLayerConnections (unsigned int expectedConnections, const CheckLocation &location) const
 
virtual void ReleaseConstantData ()
 
template<typename Op >
void OperateOnConstantTensors (Op op)
 
const char * GetName () const override
 Returns the name of the layer. More...
 
unsigned int GetNumInputSlots () const override
 Returns the number of connectable input slots. More...
 
unsigned int GetNumOutputSlots () const override
 Returns the number of connectable output slots. More...
 
const InputSlotGetInputSlot (unsigned int index) const override
 Get a const input slot handle by slot index. More...
 
InputSlotGetInputSlot (unsigned int index) override
 Get the input slot handle by slot index. More...
 
const OutputSlotGetOutputSlot (unsigned int index=0) const override
 Get the const output slot handle by slot index. More...
 
OutputSlotGetOutputSlot (unsigned int index=0) override
 Get the output slot handle by slot index. More...
 
void SetGuid (LayerGuid guid)
 
LayerGuid GetGuid () const final
 Returns the unique id of the layer. More...
 
void AddRelatedLayerName (const std::string layerName)
 
const std::list< std::string > & GetRelatedLayerNames ()
 
virtual void Reparent (Graph &dest, std::list< Layer *>::const_iterator iterator)=0
 
void BackendSelectionHint (Optional< BackendId > backend) final
 Provide a hint for the optimizer as to which backend to prefer for this layer. More...
 
Optional< BackendIdGetBackendHint () const
 
+ + + + + + + +

+Public Attributes

std::unique_ptr< ScopedCpuTensorHandlem_Weight
 A unique pointer to store Weight values. More...
 
std::unique_ptr< ScopedCpuTensorHandlem_Bias
 A unique pointer to store Bias values. More...
 
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

+Protected Member Functions

 DepthwiseConvolution2dLayer (const DepthwiseConvolution2dDescriptor &param, const char *name)
 Constructor to create a DepthwiseConvolution2dLayer. More...
 
 ~DepthwiseConvolution2dLayer ()=default
 Default destructor. More...
 
ConstantTensors GetConstantTensorsByRef () override
 Retrieve the handles to the constant values stored by the layer. More...
 
- Protected Member Functions inherited from LayerWithParameters< DepthwiseConvolution2dDescriptor >
 LayerWithParameters (unsigned int numInputSlots, unsigned int numOutputSlots, LayerType type, const DepthwiseConvolution2dDescriptor &param, const char *name)
 
 ~LayerWithParameters ()=default
 
WorkloadInfo PrepInfoAndDesc (QueueDescriptor &descriptor) const
 Helper function to reduce duplication in *LayerCreateWorkload. More...
 
- Protected Member Functions inherited from Layer
virtual ~Layer ()=default
 
template<typename QueueDescriptor >
void CollectQueueDescriptorInputs (QueueDescriptor &descriptor, WorkloadInfo &info) const
 
template<typename QueueDescriptor >
void CollectQueueDescriptorOutputs (QueueDescriptor &descriptor, WorkloadInfo &info) const
 
template<typename QueueDescriptor >
WorkloadInfo PrepInfoAndDesc (QueueDescriptor &descriptor) const
 Helper function to reduce duplication in *LayerCreateWorkload. More...
 
template<typename LayerType , typename ... Params>
LayerTypeCloneBase (Graph &graph, Params &&... params) const
 
- Protected Member Functions inherited from IConnectableLayer
 ~IConnectableLayer ()
 Objects are not deletable via the handle. More...
 
+ + + + + + + + + + + + + + +

+Additional Inherited Members

- Public Types inherited from LayerWithParameters< DepthwiseConvolution2dDescriptor >
using DescriptorType = DepthwiseConvolution2dDescriptor
 
- Protected Types inherited from Layer
using ConstantTensors = std::vector< std::reference_wrapper< std::unique_ptr< ScopedCpuTensorHandle > >>
 
- Protected Attributes inherited from LayerWithParameters< DepthwiseConvolution2dDescriptor >
DepthwiseConvolution2dDescriptor m_Param
 The parameters for the layer (not including tensor-valued weights etc.). More...
 
- Protected Attributes inherited from Layer
std::vector< OutputHandlerm_OutputHandlers
 
+

Detailed Description

+

This layer represents a depthwise convolution 2d operation.

+ +

Definition at line 15 of file DepthwiseConvolution2dLayer.hpp.

+

Constructor & Destructor Documentation

+ +

◆ DepthwiseConvolution2dLayer()

+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
DepthwiseConvolution2dLayer (const DepthwiseConvolution2dDescriptorparam,
const char * name 
)
+
+protected
+
+ +

Constructor to create a DepthwiseConvolution2dLayer.

+
Parameters
+ + + +
[in]paramDepthwiseConvolution2dDescriptor to configure the depthwise convolution2d.
[in]nameOptional name for the layer.
+
+
+ +

Definition at line 23 of file DepthwiseConvolution2dLayer.cpp.

+ +

References armnn::DepthwiseConvolution2d.

+
26 {
27 }
LayerWithParameters(unsigned int numInputSlots, unsigned int numOutputSlots, LayerType type, const DepthwiseConvolution2dDescriptor &param, const char *name)
+ +
+
+
+ +

◆ ~DepthwiseConvolution2dLayer()

+ +
+
+ + + + + +
+ + + + + + + +
~DepthwiseConvolution2dLayer ()
+
+protecteddefault
+
+ +

Default destructor.

+ +
+
+

Member Function Documentation

+ +

◆ Accept()

+ +
+
+ + + + + +
+ + + + + + + + +
void Accept (ILayerVisitorvisitor) const
+
+overridevirtual
+
+ +

Apply a visitor to this layer.

+ +

Implements IConnectableLayer.

+ +

Definition at line 147 of file DepthwiseConvolution2dLayer.cpp.

+ +

References Layer::GetName(), LayerWithParameters< DepthwiseConvolution2dDescriptor >::GetParameters(), DepthwiseConvolution2dLayer::m_Bias, DepthwiseConvolution2dLayer::m_Weight, and ILayerVisitor::VisitDepthwiseConvolution2dLayer().

+
148 {
149  ConstTensor weightsTensor(m_Weight->GetTensorInfo(), m_Weight->Map(true));
150  Optional<ConstTensor> optionalBiasTensor = EmptyOptional();
151 
152  if (GetParameters().m_BiasEnabled)
153  {
154  ConstTensor biasTensor(m_Bias->GetTensorInfo(), m_Bias->Map(true));
155  optionalBiasTensor = Optional<ConstTensor>(biasTensor);
156  }
157 
158  visitor.VisitDepthwiseConvolution2dLayer(this, GetParameters(), weightsTensor, optionalBiasTensor, GetName());
159 }
const DepthwiseConvolution2dDescriptor & GetParameters() const
+ +
std::unique_ptr< ScopedCpuTensorHandle > m_Bias
A unique pointer to store Bias values.
+
A tensor defined by a TensorInfo (shape and data type) and an immutable backing store.
Definition: Tensor.hpp:199
+
virtual void VisitDepthwiseConvolution2dLayer(const IConnectableLayer *layer, const DepthwiseConvolution2dDescriptor &convolution2dDescriptor, const ConstTensor &weights, const Optional< ConstTensor > &biases, const char *name=nullptr)=0
Function that a 2D depthwise convolution layer with biases should call back to when its Accept(ILayer...
+
EmptyOptional is used to initialize the Optional class in case we want to have default value for an O...
Definition: Optional.hpp:32
+
const char * GetName() const override
Returns the name of the layer.
Definition: Layer.hpp:305
+
std::unique_ptr< ScopedCpuTensorHandle > m_Weight
A unique pointer to store Weight values.
+
+
+
+ +

◆ Clone()

+ +
+
+ + + + + +
+ + + + + + + + +
DepthwiseConvolution2dLayer * Clone (Graphgraph) const
+
+overridevirtual
+
+ +

Creates a dynamically-allocated copy of this layer.

+
Parameters
+ + +
[in]graphThe graph into which this layer is being cloned.
+
+
+ +

Implements Layer.

+ +

Definition at line 68 of file DepthwiseConvolution2dLayer.cpp.

+ +

References Layer::GetName(), DepthwiseConvolution2dLayer::m_Bias, LayerWithParameters< DepthwiseConvolution2dDescriptor >::m_Param, and DepthwiseConvolution2dLayer::m_Weight.

+
69 {
70  auto layer = CloneBase<DepthwiseConvolution2dLayer>(graph, m_Param, GetName());
71  layer->m_Weight = m_Weight ? std::make_unique<ScopedCpuTensorHandle>(*m_Weight) : nullptr;
72 
73  if (layer->m_Param.m_BiasEnabled)
74  {
75  layer->m_Bias = m_Bias ? std::make_unique<ScopedCpuTensorHandle>(*m_Bias) : nullptr;
76  }
77 
78  return std::move(layer);
79 }
DepthwiseConvolution2dDescriptor m_Param
The parameters for the layer (not including tensor-valued weights etc.).
+
std::unique_ptr< ScopedCpuTensorHandle > m_Bias
A unique pointer to store Bias values.
+
const char * GetName() const override
Returns the name of the layer.
Definition: Layer.hpp:305
+
std::unique_ptr< ScopedCpuTensorHandle > m_Weight
A unique pointer to store Weight values.
+
+
+
+ +

◆ CreateWorkload()

+ +
+
+ + + + + +
+ + + + + + + + +
std::unique_ptr< IWorkload > CreateWorkload (const IWorkloadFactoryfactory) const
+
+overridevirtual
+
+ +

Makes a workload for the DepthwiseConvolution2d type.

+
Parameters
+ + + +
[in]graphThe graph where this layer can be found.
[in]factoryThe workload factory which will create the workload.
+
+
+
Returns
A pointer to the created workload, or nullptr if not created.
+ +

Implements Layer.

+ +

Definition at line 51 of file DepthwiseConvolution2dLayer.cpp.

+ +

References IWorkloadFactory::CreateDepthwiseConvolution2d(), DepthwiseConvolution2dLayer::m_Bias, DepthwiseConvolution2dQueueDescriptor::m_Bias, DepthwiseConvolution2dDescriptor::m_BiasEnabled, LayerWithParameters< DepthwiseConvolution2dDescriptor >::m_Param, DepthwiseConvolution2dLayer::m_Weight, DepthwiseConvolution2dQueueDescriptor::m_Weight, and LayerWithParameters< DepthwiseConvolution2dDescriptor >::PrepInfoAndDesc().

+
52 {
53  // on this level constant data should not be released..
54  BOOST_ASSERT_MSG(m_Weight != nullptr, "DepthwiseConvolution2dLayer: Weights data should not be null.");
55 
57 
58  descriptor.m_Weight = m_Weight.get();
59 
61  {
62  BOOST_ASSERT_MSG(m_Bias != nullptr, "DepthwiseConvolution2dLayer: Bias data should not be null.");
63  descriptor.m_Bias = m_Bias.get();
64  }
65  return factory.CreateDepthwiseConvolution2d(descriptor, PrepInfoAndDesc(descriptor));
66 }
bool m_BiasEnabled
Enable/disable bias.
+
DepthwiseConvolution2dDescriptor m_Param
The parameters for the layer (not including tensor-valued weights etc.).
+
std::unique_ptr< ScopedCpuTensorHandle > m_Bias
A unique pointer to store Bias values.
+ + +
WorkloadInfo PrepInfoAndDesc(QueueDescriptor &descriptor) const
Helper function to reduce duplication in *LayerCreateWorkload.
+
std::unique_ptr< ScopedCpuTensorHandle > m_Weight
A unique pointer to store Weight values.
+
virtual std::unique_ptr< IWorkload > CreateDepthwiseConvolution2d(const DepthwiseConvolution2dQueueDescriptor &descriptor, const WorkloadInfo &info) const
+ +
+
+
+ +

◆ GetConstantTensorsByRef()

+ +
+
+ + + + + +
+ + + + + + + +
Layer::ConstantTensors GetConstantTensorsByRef ()
+
+overrideprotectedvirtual
+
+ +

Retrieve the handles to the constant values stored by the layer.

+
Returns
A vector of the constant tensors stored by this layer.
+ +

Reimplemented from Layer.

+ +

Definition at line 142 of file DepthwiseConvolution2dLayer.cpp.

+ +

References DepthwiseConvolution2dLayer::m_Bias, and DepthwiseConvolution2dLayer::m_Weight.

+
143 {
144  return {m_Weight, m_Bias};
145 }
std::unique_ptr< ScopedCpuTensorHandle > m_Bias
A unique pointer to store Bias values.
+
std::unique_ptr< ScopedCpuTensorHandle > m_Weight
A unique pointer to store Weight values.
+
+
+
+ +

◆ InferOutputShapes()

+ +
+
+ + + + + +
+ + + + + + + + +
std::vector< TensorShape > InferOutputShapes (const std::vector< TensorShape > & inputShapes) const
+
+overridevirtual
+
+ +

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.

+
Parameters
+ + +
[in]inputShapesThe input shapes layer has.
+
+
+
Returns
A vector to the inferred output shape.
+ +

Reimplemented from Layer.

+ +

Definition at line 82 of file DepthwiseConvolution2dLayer.cpp.

+ +

References DepthwiseConvolution2dDescriptor::m_DataLayout, DepthwiseConvolution2dDescriptor::m_DilationX, DepthwiseConvolution2dDescriptor::m_DilationY, DepthwiseConvolution2dDescriptor::m_PadBottom, DepthwiseConvolution2dDescriptor::m_PadLeft, DepthwiseConvolution2dDescriptor::m_PadRight, DepthwiseConvolution2dDescriptor::m_PadTop, LayerWithParameters< DepthwiseConvolution2dDescriptor >::m_Param, DepthwiseConvolution2dDescriptor::m_StrideX, DepthwiseConvolution2dDescriptor::m_StrideY, and armnn::NHWC.

+ +

Referenced by DepthwiseConvolution2dInferOutputShapeTest(), and DepthwiseConvolution2dLayer::ValidateTensorShapesFromInputs().

+
83 {
84  BOOST_ASSERT(inputShapes.size() == 2);
85  const TensorShape& inputShape = inputShapes[0];
86  const TensorShape& filterShape = inputShapes[1];
87 
88  BOOST_ASSERT_MSG(inputShape.GetNumDimensions() == 4, "Convolutions will always have 4D input.");
89 
90  DataLayoutIndexed dataLayoutIndex(m_Param.m_DataLayout);
91 
92  unsigned int inputBatchSize = inputShape[0];
93  unsigned int inputHeight = inputShape[dataLayoutIndex.GetHeightIndex()];
94  unsigned int inputWidth = inputShape[dataLayoutIndex.GetWidthIndex()];
95  unsigned int inputChannels = inputShape[dataLayoutIndex.GetChannelsIndex()];
96 
97  // Expected filter shape: [ M, I, H, W ] - This shape does NOT depend on the data layout
98  // Namely: [ depth multiplier, input channels, filter height, filter width ]
99  // Output channels = input channels * depthMultiplier
100  unsigned int depthMultiplier = filterShape[0];
101 
102  unsigned int filterHeight = filterShape[2];
103  unsigned int dilatedFilterHeight = filterHeight + (m_Param.m_DilationY - 1) * (filterHeight - 1);
104  unsigned int readHeight = (inputHeight + m_Param.m_PadTop + m_Param.m_PadBottom) - dilatedFilterHeight;
105  unsigned int outputHeight = 1 + (readHeight / m_Param.m_StrideY);
106 
107  unsigned int filterWidth = filterShape[3];
108  unsigned int dilatedFilterWidth = filterWidth + (m_Param.m_DilationX - 1) * (filterWidth - 1);
109  unsigned int readWidth = (inputWidth + m_Param.m_PadLeft + m_Param.m_PadRight) - dilatedFilterWidth;
110  unsigned int outputWidth = 1 + (readWidth / m_Param.m_StrideX);
111 
112  unsigned int outputChannels = inputChannels * depthMultiplier;
113  unsigned int outputBatchSize = inputBatchSize;
114 
116  TensorShape{ outputBatchSize, outputHeight, outputWidth, outputChannels } :
117  TensorShape{ outputBatchSize, outputChannels, outputHeight, outputWidth };
118 
119  return std::vector<TensorShape>{ tensorShape };
120 }
DepthwiseConvolution2dDescriptor m_Param
The parameters for the layer (not including tensor-valued weights etc.).
+
uint32_t m_PadBottom
Padding bottom value in the height dimension.
+
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
+
uint32_t m_PadLeft
Padding left value in the width dimension.
+ +
uint32_t m_DilationY
Dilation factor value for height dimension.
+
uint32_t m_StrideX
Stride value when proceeding through input for the width dimension.
+
uint32_t m_DilationX
Dilation factor value for width dimension.
+
uint32_t m_PadTop
Padding top value in the height dimension.
+
Provides access to the appropriate indexes for Channels, Height and Width based on DataLayout...
+
uint32_t m_StrideY
Stride value when proceeding through input for the height dimension.
+ +
uint32_t m_PadRight
Padding right value in the width dimension.
+
+
+
+ +

◆ SerializeLayerParameters()

+ +
+
+ + + + + +
+ + + + + + + + +
void SerializeLayerParameters (ParameterStringifyFunctionfn) const
+
+overridevirtual
+
+ +

Helper to serialize the layer parameters to string.

+

(currently used in DotSerializer and company).

+ +

Reimplemented from Layer.

+ +

Definition at line 29 of file DepthwiseConvolution2dLayer.cpp.

+ +

References InputSlot::GetConnection(), Layer::GetInputSlot(), TensorInfo::GetShape(), IOutputSlot::GetTensorInfo(), DepthwiseConvolution2dDescriptor::m_DataLayout, LayerWithParameters< DepthwiseConvolution2dDescriptor >::m_Param, DepthwiseConvolution2dLayer::m_Weight, and LayerWithParameters< Parameters >::SerializeLayerParameters().

+
30 {
31  const std::vector<TensorShape>& inputShapes =
32  {
34  m_Weight->GetTensorInfo().GetShape()
35  };
36  const TensorShape filterShape = inputShapes[1];
37  DataLayoutIndexed dataLayoutIndex(m_Param.m_DataLayout);
38  unsigned int inputChannels = filterShape[1];
39  unsigned int filterWidth = filterShape[3];
40  unsigned int filterHeight = filterShape[2];
41  unsigned int depthMultiplier = filterShape[0];
42 
43  fn("FilterWidth",std::to_string(filterWidth));
44  fn("FilterHeight",std::to_string(filterHeight));
45  fn("DepthMultiplier",std::to_string(depthMultiplier));
46  fn("InputChannels",std::to_string(inputChannels));
47 
49 }
DepthwiseConvolution2dDescriptor m_Param
The parameters for the layer (not including tensor-valued weights etc.).
+
const TensorShape & GetShape() const
Definition: Tensor.hpp:88
+
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
+
void SerializeLayerParameters(ParameterStringifyFunction &fn) const override
Helper to serialize the layer parameters to string (currently used in DotSerializer and company)...
+ +
const IOutputSlot * GetConnection() const override
Definition: Layer.hpp:199
+
const InputSlot & GetInputSlot(unsigned int index) const override
Get a const input slot handle by slot index.
Definition: Layer.hpp:310
+
Provides access to the appropriate indexes for Channels, Height and Width based on DataLayout...
+
virtual const TensorInfo & GetTensorInfo() const =0
+
std::unique_ptr< ScopedCpuTensorHandle > m_Weight
A unique pointer to store Weight values.
+
+
+
+ +

◆ ValidateTensorShapesFromInputs()

+ +
+
+ + + + + +
+ + + + + + + +
void ValidateTensorShapesFromInputs ()
+
+overridevirtual
+
+ +

Check if the input tensor shape(s) will lead to a valid configuration of DepthwiseConvolution2dLayer.

+ +

Implements Layer.

+ +

Definition at line 122 of file DepthwiseConvolution2dLayer.cpp.

+ +

References CHECK_LOCATION, InputSlot::GetConnection(), Layer::GetInputSlot(), Layer::GetOutputSlot(), TensorInfo::GetShape(), IOutputSlot::GetTensorInfo(), OutputSlot::GetTensorInfo(), DepthwiseConvolution2dLayer::InferOutputShapes(), DepthwiseConvolution2dLayer::m_Weight, and Layer::VerifyLayerConnections().

+
123 {
125 
126  // on this level constant data should not be released..
127  BOOST_ASSERT_MSG(m_Weight != nullptr, "DepthwiseConvolution2dLayer: Weights data should not be null.");
128 
129  auto inferredShapes = InferOutputShapes({
131  m_Weight->GetTensorInfo().GetShape()
132  });
133 
134  BOOST_ASSERT(inferredShapes.size() == 1);
135 
136  ConditionalThrowIfNotEqual<LayerValidationException>(
137  "DepthwiseConvolution2dLayer: TensorShape set on OutputSlot[0] does not match the inferred shape.",
139  inferredShapes[0]);
140 }
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.
+
const TensorShape & GetShape() const
Definition: Tensor.hpp:88
+
const IOutputSlot * GetConnection() const override
Definition: Layer.hpp:199
+
void VerifyLayerConnections(unsigned int expectedConnections, const CheckLocation &location) const
Definition: Layer.cpp:338
+
const InputSlot & GetInputSlot(unsigned int index) const override
Get a const input slot handle by slot index.
Definition: Layer.hpp:310
+
#define CHECK_LOCATION()
Definition: Exceptions.hpp:192
+
const OutputSlot & GetOutputSlot(unsigned int index=0) const override
Get the const output slot handle by slot index.
Definition: Layer.hpp:312
+
virtual const TensorInfo & GetTensorInfo() const =0
+
std::unique_ptr< ScopedCpuTensorHandle > m_Weight
A unique pointer to store Weight values.
+
const TensorInfo & GetTensorInfo() const override
Definition: Layer.cpp:63
+
+
+
+

Member Data Documentation

+ +

◆ m_Bias

+ + + +

◆ m_Weight

+ + +
The documentation for this class was generated from the following files: +
+
+ + + + -- cgit v1.2.1