ArmNN
 25.11
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ConcatLayer Class Reference

This layer represents a merge operation. More...

#include <ConcatLayer.hpp>

Inheritance diagram for ConcatLayer:
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Collaboration diagram for ConcatLayer:
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Public Member Functions

virtual std::unique_ptr< IWorkloadCreateWorkload (const IWorkloadFactory &factory) const override
 Makes a workload for the Concat type.
virtual void CreateTensorHandles (const TensorHandleFactoryRegistry &registry, const IWorkloadFactory &factory, const bool IsMemoryManaged=true) override
 Set the outputs to be appropriate sub tensors of the input if sub tensors are supported otherwise creates tensor handlers.
ConcatLayerClone (Graph &graph) const override
 Creates a dynamically-allocated copy of this layer.
void ValidateTensorShapesFromInputs () override
 Check if the input tensor shape(s) will lead to a valid configuration of ConcatLayer.
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.
void ExecuteStrategy (IStrategy &strategy) const override
 Apply a visitor to this layer.
Public Member Functions inherited from LayerWithParameters< OriginsDescriptor >
const OriginsDescriptorGetParameters () const override
 If the layer has a descriptor return it.
void SerializeLayerParameters (ParameterStringifyFunction &fn) const override
 Helper to serialize the layer parameters to string (currently used in DotSerializer and company).
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)
ShapeInferenceMethod GetShapeInferenceMethod () const
bool GetAllowExpandedDims () const
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 override
 Returns the armnn::LayerType of this layer.
DataType GetDataType () const
const BackendIdGetBackendId () const
void SetBackendId (const BackendId &id) override
 Set the backend of the IConnectableLayer.
void VerifyLayerConnections (unsigned int expectedConnections, const CheckLocation &location) const
std::vector< TensorShapeInferOutputShapes (const std::vector< TensorShape > &inputShapes) const override
 Infer the shape of the output(s) based on the provided input shape(s)
virtual void ReleaseConstantData ()
template<typename Op>
void OperateOnConstantTensors (Op op)
const char * GetName () const override
 Returns the name of the layer.
unsigned int GetNumInputSlots () const override
 Returns the number of connectable input slots.
unsigned int GetNumOutputSlots () const override
 Returns the number of connectable output slots.
const InputSlotGetInputSlot (unsigned int index) const override
 Get a const input slot handle by slot index.
InputSlotGetInputSlot (unsigned int index) override
 Get the input slot handle by slot index.
const OutputSlotGetOutputSlot (unsigned int index=0) const override
 Get the const output slot handle by slot index.
OutputSlotGetOutputSlot (unsigned int index=0) override
 Get the output slot handle by slot index.
void SetGuid (LayerGuid guid)
LayerGuid GetGuid () const final
 Returns the unique id of the layer.
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.
Optional< BackendIdGetBackendHint () const
void SetShapeInferenceMethod (ShapeInferenceMethod shapeInferenceMethod)
void SetAllowExpandedDims (bool allowExpandedDims)
template<typename T>
std::shared_ptr< T > GetAdditionalInformation () const
void SetAdditionalInfoForObject (const AdditionalInfoObjectPtr &additionalInfo)

Protected Member Functions

 ConcatLayer (const OriginsDescriptor &param, const char *name)
 Constructor to create a ConcatLayer.
 ~ConcatLayer ()=default
 Default destructor.
Protected Member Functions inherited from LayerWithParameters< OriginsDescriptor >
 LayerWithParameters (unsigned int numInputSlots, unsigned int numOutputSlots, LayerType type, const OriginsDescriptor &param, const char *name)
 ~LayerWithParameters ()=default
WorkloadInfo PrepInfoAndDesc (QueueDescriptor &descriptor) const
 Helper function to reduce duplication in *LayerCreateWorkload.
void ExecuteStrategy (IStrategy &strategy) const override
 Apply a visitor to this layer.
Layer::ImmutableConstantTensors GetConnectedConstantAsInputTensors () const
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
void ValidateAndCopyShape (const TensorShape &outputShape, const TensorShape &inferredShape, const ShapeInferenceMethod shapeInferenceMethod, const std::string &layerName, const unsigned int outputSlotIndex=0)
void VerifyShapeInferenceType (const TensorShape &outputShape, ShapeInferenceMethod shapeInferenceMethod)
template<typename QueueDescriptor>
WorkloadInfo PrepInfoAndDesc (QueueDescriptor &descriptor) const
 Helper function to reduce duplication in *LayerCreateWorkload.
template<typename LayerType, typename ... Params>
LayerTypeCloneBase (Graph &graph, Params &&... params) const
virtual ConstantTensors GetConstantTensorsByRef () override final
virtual ImmutableConstantTensors GetConstantTensorsByRef () const override
void SetAdditionalInfo (QueueDescriptor &descriptor) const
Protected Member Functions inherited from IConnectableLayer
 ~IConnectableLayer ()
 Objects are not deletable via the handle.

Additional Inherited Members

Public Types inherited from LayerWithParameters< OriginsDescriptor >
using DescriptorType
Public Types inherited from IConnectableLayer
using ConstantTensors = std::vector<std::reference_wrapper<std::shared_ptr<ConstTensorHandle>>>
using ImmutableConstantTensors = std::vector<std::reference_wrapper<const std::shared_ptr<ConstTensorHandle>>>
Protected Attributes inherited from LayerWithParameters< OriginsDescriptor >
OriginsDescriptor m_Param
 The parameters for the layer (not including tensor-valued weights etc.).
Protected Attributes inherited from Layer
AdditionalInfoObjectPtr m_AdditionalInfoObject
std::vector< OutputHandlerm_OutputHandlers
ShapeInferenceMethod m_ShapeInferenceMethod

Detailed Description

This layer represents a merge operation.

Definition at line 13 of file ConcatLayer.hpp.

Constructor & Destructor Documentation

◆ ConcatLayer()

ConcatLayer ( const OriginsDescriptor & param,
const char * name )
protected

Constructor to create a ConcatLayer.

Parameters
[in]paramOriginsDescriptor to configure the concat operation.
[in]nameOptional name for the layer.

Definition at line 18 of file ConcatLayer.cpp.

19 : LayerWithParameters(param.GetNumViews(), 1, LayerType::Concat, param, name)
20{
21}

References armnn::Concat, and LayerWithParameters< OriginsDescriptor >::LayerWithParameters().

Referenced by Clone().

◆ ~ConcatLayer()

~ConcatLayer ( )
protecteddefault

Default destructor.

Member Function Documentation

◆ Clone()

ConcatLayer * Clone ( Graph & graph) 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 208 of file ConcatLayer.cpp.

209{
210 return CloneBase<ConcatLayer>(graph, m_Param, GetName());
211}

References Layer::CloneBase(), ConcatLayer(), Layer::GetName(), and LayerWithParameters< OriginsDescriptor >::m_Param.

◆ CreateTensorHandles()

void CreateTensorHandles ( const TensorHandleFactoryRegistry & registry,
const IWorkloadFactory & factory,
const bool IsMemoryManaged = true )
overridevirtual

Set the outputs to be appropriate sub tensors of the input if sub tensors are supported otherwise creates tensor handlers.

Parameters
[in]registryContains all the registered tensor handle factories available for use.
[in]factoryThe workload factory which will create the workload.
[in]IsMemoryManagedDetermine whether or not to assign a memory manager during creation
[in]MemorySourceDetermine the source of memory e.g Malloc

Reimplemented from Layer.

Definition at line 186 of file ConcatLayer.cpp.

189{
190 OutputSlot& slot = GetOutputSlot(0);
191 ITensorHandleFactory::FactoryId factoryId = slot.GetTensorHandleFactoryId();
192
193 if (factoryId == ITensorHandleFactory::LegacyFactoryId)
194 {
195 CreateTensors(registry, workloadFactory, isMemoryManaged);
196 }
197 else
198 {
199 ITensorHandleFactory* handleFactory = registry.GetFactory(factoryId);
200 if (!handleFactory)
201 {
202 throw armnn::NullPointerException("handleFactory is returning a nullptr.");
203 }
204 CreateTensors(registry, *handleFactory, isMemoryManaged);
205 }
206}

References TensorHandleFactoryRegistry::GetFactory(), Layer::GetOutputSlot(), OutputSlot::GetTensorHandleFactoryId(), and ITensorHandleFactory::LegacyFactoryId.

◆ CreateWorkload()

std::unique_ptr< IWorkload > CreateWorkload ( const IWorkloadFactory & factory) const
overridevirtual

Makes a workload for the Concat 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 23 of file ConcatLayer.cpp.

24{
25 ConcatQueueDescriptor descriptor;
26
27 // Copies the view origins to the descriptor.
28 descriptor.m_ViewOrigins.reserve(m_Param.GetNumViews());
29 for (unsigned int i = 0; i < m_Param.GetNumViews(); ++i)
30 {
31 descriptor.m_ViewOrigins.emplace_back(
32 std::vector<unsigned int>(m_Param.GetViewOrigin(i), m_Param.GetViewOrigin(i) + m_Param.GetNumDimensions()));
33 }
34 SetAdditionalInfo(descriptor);
35
36 return factory.CreateWorkload(LayerType::Concat, descriptor, PrepInfoAndDesc(descriptor));
37}

References armnn::Concat, IWorkloadFactory::CreateWorkload(), LayerWithParameters< OriginsDescriptor >::m_Param, ConcatQueueDescriptor::m_ViewOrigins, LayerWithParameters< OriginsDescriptor >::PrepInfoAndDesc(), and Layer::SetAdditionalInfo().

◆ ExecuteStrategy()

void ExecuteStrategy ( IStrategy & strategy) const
overridevirtual

Apply a visitor to this layer.

Implements IConnectableLayer.

Definition at line 341 of file ConcatLayer.cpp.

342{
343 strategy.ExecuteStrategy(this, GetParameters(), {}, GetName());
344}

References IStrategy::ExecuteStrategy(), Layer::GetName(), and LayerWithParameters< OriginsDescriptor >::GetParameters().

◆ 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.

Implements IConnectableLayer.

Definition at line 213 of file ConcatLayer.cpp.

214{
215 if (inputShapes.size() != m_Param.GetNumViews())
216 {
217 throw armnn::Exception("inputShapes' and m_NumViews' sizes do not match (\""
218 + std::to_string(inputShapes.size()) +
219 "\" vs \""
220 + std::to_string(m_Param.GetNumViews()) + "\")");
221 }
222
223 unsigned int numDims = m_Param.GetNumDimensions();
224 for (unsigned int i=0; i< inputShapes.size(); i++)
225 {
226 auto& inputShape = inputShapes[i];
227
228 ConditionalThrowIfNotEqual<LayerValidationException>(
229 "ConcatLayer: Num Dimensions must match all inputs.",
230 numDims,
231 inputShape.GetNumDimensions());
232 }
233
234 // Finds the bounding box (extents) of all the views.
235 std::vector<unsigned int> extentMin(numDims);
236 std::vector<unsigned int> extentMax(numDims);
237 for (unsigned int i = 0; i < inputShapes.size(); i++)
238 {
239 const uint32_t* origin = m_Param.GetViewOrigin(i);
240 const armnn::TensorShape& shape = inputShapes[i];
241 for (unsigned int d = 0; d < numDims; d++)
242 {
243 extentMin[d] = std::min(extentMin[d], origin[d]);
244 extentMax[d] = std::max(extentMax[d], origin[d] + shape[d]);
245 }
246 }
247
248 // Checks that the bounding box starts at the origin.
249 if (!std::all_of(extentMin.begin(), extentMin.end(), [](unsigned int s) { return s == 0; }))
250 {
251 throw LayerValidationException("ConcatLayer: there is no view that starts at the origin");
252 }
253
254 // Checks that there are no overlaps of views (this would lead to undefined output at those locations).
255 // Checks each pair of views against each other
256 // (and doesn't bother to check against self, or check the same pair both ways round).
257 for (unsigned int a = 0; a < inputShapes.size(); a++)
258 {
259 const uint32_t* aOrigin = m_Param.GetViewOrigin(a);
260 const armnn::TensorShape& aShape = inputShapes[a];
261 for (unsigned int b = 0; b < a; b++)
262 {
263 const uint32_t* bOrigin = m_Param.GetViewOrigin(b);
264 const armnn::TensorShape& bShape = inputShapes[b];
265
266 bool allAxesOverlap = true;
267 for (unsigned int d = 0; d < numDims && allAxesOverlap; d++)
268 {
269 unsigned int a1 = aOrigin[d];
270 unsigned int a2 = aOrigin[d] + aShape[d];
271
272 unsigned int b1 = bOrigin[d];
273 unsigned int b2 = bOrigin[d] + bShape[d];
274
275 if (a2 <= b1 || b2 <= a1)
276 {
277 allAxesOverlap = false;
278 }
279 }
280 if (allAxesOverlap)
281 {
282 throw LayerValidationException("ConcatLayer: Some views overlap.");
283 }
284 }
285 }
286
287 // Checks that there are no "holes", i.e. regions of the output which is not covered by a view.
288 // Because we already checked that there are no overlaps, this can be done simply by checking that
289 // the total 'volume' of the views is the same as the output.
290 unsigned int totalViewsVolume = 0;
291 for (unsigned int i = 0; i < inputShapes.size(); i++)
292 {
293 totalViewsVolume += inputShapes[i].GetNumElements();
294 }
295 unsigned int outputVolume = 1;
296 for (unsigned int d = 0; d < numDims; d++)
297 {
298 outputVolume *= (extentMax[d] - extentMin[d]);
299 }
300
301 ConditionalThrowIfNotEqual<LayerValidationException>(
302 "ConcatLayer: there are some gaps between views",
303 totalViewsVolume,
304 outputVolume);
305
306 return std::vector<TensorShape>({ TensorShape({numDims, extentMax.data()}) });
307}

References armnn::ConditionalThrowIfNotEqual(), and LayerWithParameters< OriginsDescriptor >::m_Param.

Referenced by ValidateTensorShapesFromInputs().

◆ ValidateTensorShapesFromInputs()

void ValidateTensorShapesFromInputs ( )
overridevirtual

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

Parameters
[in]shapeInferenceMethodIndicates if output shape shall be overwritten or just validated.

Implements Layer.

Definition at line 309 of file ConcatLayer.cpp.

310{
311 // Validates Concat layer.
312 ConditionalThrowIfNotEqual<LayerValidationException>(
313 "ConcatLayer: Num Inputs must match num views.",
314 m_Param.GetNumViews(),
315 GetNumInputSlots());
316
317 VerifyLayerConnections(m_Param.GetNumViews(), CHECK_LOCATION());
318
319 const TensorShape& outputShape = GetOutputSlot(0).GetTensorInfo().GetShape();
320
321 VerifyShapeInferenceType(outputShape, m_ShapeInferenceMethod);
322
323 std::vector<TensorShape> inputShapes;
324 for (unsigned int i = 0; i < GetNumInputSlots(); ++i)
325 {
326 inputShapes.push_back(GetInputSlot(i).GetTensorInfo().GetShape());
327 }
328
329 auto inferredShapes = InferOutputShapes(inputShapes);
330
331 if (inferredShapes.size() != 1)
332 {
333 throw armnn::Exception("inferredShapes has "
334 + std::to_string(inferredShapes.size()) +
335 " elements - should only have 1.");
336 }
337
338 ValidateAndCopyShape(outputShape, inferredShapes[0], m_ShapeInferenceMethod, "ConcatLayer");
339}
#define CHECK_LOCATION()
armnn::TensorInfo GetTensorInfo(unsigned int numberOfBatches, unsigned int numberOfChannels, unsigned int height, unsigned int width, const armnn::DataLayout dataLayout, const armnn::DataType dataType)

References CHECK_LOCATION, armnn::ConditionalThrowIfNotEqual(), Layer::GetInputSlot(), Layer::GetNumInputSlots(), Layer::GetOutputSlot(), TensorInfo::GetShape(), OutputSlot::GetTensorInfo(), armnnUtils::GetTensorInfo(), InferOutputShapes(), LayerWithParameters< OriginsDescriptor >::m_Param, Layer::m_ShapeInferenceMethod, Layer::ValidateAndCopyShape(), Layer::VerifyLayerConnections(), and Layer::VerifyShapeInferenceType().


The documentation for this class was generated from the following files: