32 const std::vector<TensorShape>& inputShapes =
39 unsigned int filterWidth = filterShape[dataLayoutIndex.
GetWidthIndex()];
40 unsigned int filterHeight = filterShape[dataLayoutIndex.
GetHeightIndex()];
41 unsigned int outChannels = filterShape[0];
43 fn(
"OutputChannels",std::to_string(outChannels));
44 fn(
"FilterWidth",std::to_string(filterWidth));
45 fn(
"FilterHeight",std::to_string(filterHeight));
71 auto layer = CloneBase<Convolution2dLayer>(graph,
m_Param,
GetName());
75 if (layer->m_Param.m_BiasEnabled)
80 return std::move(layer);
90 ARMNN_ASSERT_MSG(inputShape.GetNumDimensions() == 4,
"Convolutions will always have 4D input.");
97 unsigned int inWidth = inputShape[dataLayoutIndex.
GetWidthIndex()];
98 unsigned int inHeight = inputShape[dataLayoutIndex.
GetHeightIndex()];
99 unsigned int inBatchSize = inputShape[0];
101 unsigned int filterWidth = filterShape[dataLayoutIndex.
GetWidthIndex()];
102 unsigned int dilatedFilterWidth = filterWidth + (
m_Param.
m_DilationX - 1) * (filterWidth - 1);
106 unsigned int filterHeight = filterShape[dataLayoutIndex.
GetHeightIndex()];
107 unsigned int dilatedFilterHeight = filterHeight + (
m_Param.
m_DilationY - 1) * (filterHeight - 1);
111 unsigned int outChannels = filterShape[0];
112 unsigned int outBatchSize = inBatchSize;
115 TensorShape( { outBatchSize, outHeight, outWidth, outChannels } ) :
116 TensorShape( { outBatchSize, outChannels, outHeight, outWidth });
118 return std::vector<TensorShape>({ tensorShape });
134 m_Weight->GetTensorInfo().GetShape() });
160 visitor.VisitConvolution2dLayer(
this,
GetParameters(), weightsTensor, optionalBiasTensor,
GetName());
167 std::vector<armnn::ConstTensor> constTensors { { managedWeight.
GetTensorInfo(), managedWeight.
Map() } };
uint32_t m_PadBottom
Padding bottom value in the height dimension.
bool m_BiasEnabled
Enable/disable bias.
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
Convolution2dDescriptor m_Param
The parameters for the layer (not including tensor-valued weights etc.).
const Convolution2dDescriptor & GetParameters() const
unsigned int GetWidthIndex() const
const TensorShape & GetShape() const
#define ARMNN_NO_DEPRECATE_WARN_BEGIN
A Convolution2dDescriptor for the Convolution2dLayer.
virtual void ExecuteStrategy(const armnn::IConnectableLayer *layer, const armnn::BaseDescriptor &descriptor, const std::vector< armnn::ConstTensor > &constants, const char *name, const armnn::LayerBindingId id=0)=0
const ConstTensorHandle * m_Weight
std::shared_ptr< ConstTensorHandle > m_Weight
A unique pointer to store Weight values.
const ConstTensorHandle * m_Bias
void SerializeLayerParameters(ParameterStringifyFunction &fn) const override
Helper to serialize the layer parameters to string (currently used in DotSerializer and company)...
uint32_t m_PadRight
Padding right value in the width dimension.
Convolution2dLayer(const Convolution2dDescriptor ¶m, const char *name)
Constructor to create a Convolution2dLayer.
void VerifyShapeInferenceType(const TensorShape &outputShape, ShapeInferenceMethod shapeInferenceMethod)
const TensorInfo & GetTensorInfo() const
Copyright (c) 2021 ARM Limited and Contributors.
uint32_t m_DilationY
Dilation along y axis.
void ValidateAndCopyShape(const TensorShape &outputShape, const TensorShape &inferredShape, const ShapeInferenceMethod shapeInferenceMethod, const std::string &layerName, const unsigned int outputSlotIndex=0)
#define ARMNN_SCOPED_PROFILING_EVENT(backendId, name)
unsigned int GetHeightIndex() const
void VerifyLayerConnections(unsigned int expectedConnections, const CheckLocation &location) const
uint32_t m_PadTop
Padding top value in the height dimension.
const InputSlot & GetInputSlot(unsigned int index) const override
Get a const input slot handle by slot index.
uint32_t m_StrideX
Stride value when proceeding through input for the width dimension.
void ValidateTensorShapesFromInputs() override
Check if the input tensor shape(s) will lead to a valid configuration of Convolution2dLayer.
std::vector< std::reference_wrapper< std::shared_ptr< ConstTensorHandle > >> ConstantTensors
#define ARMNN_NO_DEPRECATE_WARN_END
#define ARMNN_ASSERT_MSG(COND, MSG)
Provides access to the appropriate indexes for Channels, Height and Width based on DataLayout...
A tensor defined by a TensorInfo (shape and data type) and an immutable backing store.
#define ARMNN_ASSERT(COND)
Convolution2dLayer * Clone(Graph &graph) const override
Creates a dynamically-allocated copy of this layer.
ARMNN_NO_DEPRECATE_WARN_END void ExecuteStrategy(IStrategy &strategy) const override
Apply a visitor to this layer.
ConstantTensors GetConstantTensorsByRef() override
Retrieve the handles to the constant values stored by the layer.
uint32_t m_StrideY
Stride value when proceeding through input for the height dimension.
std::shared_ptr< ConstTensorHandle > m_Bias
A unique pointer to store Bias values.
void SetAdditionalInfo(QueueDescriptor &descriptor) const
uint32_t m_DilationX
Dilation along x axis.
virtual std::unique_ptr< IWorkload > CreateWorkload(const IWorkloadFactory &factory) const override
Makes a workload for the Convolution2d type.
EmptyOptional is used to initialize the Optional class in case we want to have default value for an O...
void SerializeLayerParameters(ParameterStringifyFunction &fn) const override
Helper to serialize the layer parameters to string.
WorkloadInfo PrepInfoAndDesc(QueueDescriptor &descriptor) const
Helper function to reduce duplication in *LayerCreateWorkload.
ARMNN_NO_DEPRECATE_WARN_BEGIN void Accept(ILayerVisitor &visitor) const override
const OutputSlot & GetOutputSlot(unsigned int index=0) const override
Get the const output slot handle by slot index.
virtual const TensorInfo & GetTensorInfo() const =0
const char * GetName() const override
Returns the name of the layer.
This layer represents a convolution 2d operation.
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.
std::function< void(const std::string &name, const std::string &value)> ParameterStringifyFunction
const void * Map(bool blocking=true)
RAII Managed resource Unmaps MemoryArea once out of scope.
const TensorInfo & GetTensorInfo() const override
ShapeInferenceMethod m_ShapeInferenceMethod
uint32_t m_PadLeft
Padding left value in the width dimension.
virtual std::unique_ptr< IWorkload > CreateConvolution2d(const Convolution2dQueueDescriptor &descriptor, const WorkloadInfo &info) const
LayerType
When adding a new layer, adapt also the LastLayer enum value in the enum class LayerType below...