patch/20.02/_depthwise_convolution2d_layer_8cpp_source.xhtml

 //
 // Copyright © 2017 Arm Ltd. All rights reserved.
 // SPDX-License-Identifier: MIT
 //

 #include "DepthwiseConvolution2dLayer.hpp"
 #include "LayerCloneBase.hpp"

 #include <armnn/TypesUtils.hpp>

 #include <armnnUtils/DataLayoutIndexed.hpp>

 #include <backendsCommon/CpuTensorHandle.hpp>
 #include <backendsCommon/WorkloadFactory.hpp>

 #include <string>

 using namespace armnnUtils;

 namespace armnn
 {

 DepthwiseConvolution2dLayer::DepthwiseConvolution2dLayer(const DepthwiseConvolution2dDescriptor& param,
                                                          const char* name)
     : LayerWithParameters(1, 1, LayerType::DepthwiseConvolution2d, param, name)
 {
 }

 void DepthwiseConvolution2dLayer::SerializeLayerParameters(ParameterStringifyFunction& fn) const
 {
     const std::vector<TensorShape>& inputShapes =
     {
         GetInputSlot(0).GetConnection()->GetTensorInfo().GetShape(),
         m_Weight->GetTensorInfo().GetShape()
     };
     const TensorShape filterShape = inputShapes[1];
     DataLayoutIndexed dataLayoutIndex(m_Param.m_DataLayout);
     unsigned int inputChannels = filterShape[1];
     unsigned int filterWidth = filterShape[3];
     unsigned int filterHeight = filterShape[2];
     unsigned int depthMultiplier = filterShape[0];

     fn("FilterWidth",std::to_string(filterWidth));
     fn("FilterHeight",std::to_string(filterHeight));
     fn("DepthMultiplier",std::to_string(depthMultiplier));
     fn("InputChannels",std::to_string(inputChannels));

     LayerWithParameters<DepthwiseConvolution2dDescriptor>::SerializeLayerParameters(fn);
 }

 std::unique_ptr<IWorkload> DepthwiseConvolution2dLayer::CreateWorkload(const IWorkloadFactory& factory) const
 {
     // on this level constant data should not be released..
     BOOST_ASSERT_MSG(m_Weight != nullptr, "DepthwiseConvolution2dLayer: Weights data should not be null.");

     DepthwiseConvolution2dQueueDescriptor descriptor;

     descriptor.m_Weight = m_Weight.get();

     if (m_Param.m_BiasEnabled)
     {
         BOOST_ASSERT_MSG(m_Bias != nullptr, "DepthwiseConvolution2dLayer: Bias data should not be null.");
         descriptor.m_Bias = m_Bias.get();
     }
     return factory.CreateDepthwiseConvolution2d(descriptor, PrepInfoAndDesc(descriptor));
 }

 DepthwiseConvolution2dLayer* DepthwiseConvolution2dLayer::Clone(Graph& graph) const
 {
     auto layer      = CloneBase<DepthwiseConvolution2dLayer>(graph, m_Param, GetName());
     layer->m_Weight = m_Weight ? std::make_unique<ScopedCpuTensorHandle>(*m_Weight) : nullptr;

     if (layer->m_Param.m_BiasEnabled)
     {
         layer->m_Bias = m_Bias ? std::make_unique<ScopedCpuTensorHandle>(*m_Bias) : nullptr;
     }

     return std::move(layer);
 }

 std::vector<TensorShape>
 DepthwiseConvolution2dLayer::InferOutputShapes(const std::vector<TensorShape>& inputShapes) const
 {
     BOOST_ASSERT(inputShapes.size() == 2);
     const TensorShape& inputShape  = inputShapes[0];
     const TensorShape& filterShape = inputShapes[1];

     BOOST_ASSERT_MSG(inputShape.GetNumDimensions() == 4, "Convolutions will always have 4D input.");

     DataLayoutIndexed dataLayoutIndex(m_Param.m_DataLayout);

     unsigned int inputBatchSize = inputShape[0];
     unsigned int inputHeight    = inputShape[dataLayoutIndex.GetHeightIndex()];
     unsigned int inputWidth     = inputShape[dataLayoutIndex.GetWidthIndex()];
     unsigned int inputChannels  = inputShape[dataLayoutIndex.GetChannelsIndex()];

     // Expected filter shape: [ M, I, H, W ] - This shape does NOT depend on the data layout
     // Namely: [ depth multiplier, input channels, filter height, filter width ]
     // Output channels = input channels * depthMultiplier
     unsigned int depthMultiplier = filterShape[0];

     unsigned int filterHeight = filterShape[2];
     unsigned int dilatedFilterHeight = filterHeight + (m_Param.m_DilationY - 1) * (filterHeight - 1);
     unsigned int readHeight   = (inputHeight + m_Param.m_PadTop + m_Param.m_PadBottom) - dilatedFilterHeight;
     unsigned int outputHeight = 1 + (readHeight / m_Param.m_StrideY);

     unsigned int filterWidth = filterShape[3];
     unsigned int dilatedFilterWidth = filterWidth + (m_Param.m_DilationX - 1) * (filterWidth - 1);
     unsigned int readWidth   = (inputWidth + m_Param.m_PadLeft + m_Param.m_PadRight) - dilatedFilterWidth;
     unsigned int outputWidth = 1 + (readWidth / m_Param.m_StrideX);

     unsigned int outputChannels  = inputChannels * depthMultiplier;
     unsigned int outputBatchSize = inputBatchSize;

     TensorShape tensorShape = m_Param.m_DataLayout == armnn::DataLayout::NHWC ?
                               TensorShape{ outputBatchSize, outputHeight, outputWidth, outputChannels } :
                               TensorShape{ outputBatchSize, outputChannels, outputHeight, outputWidth };

     return std::vector<TensorShape>{ tensorShape };
 }

 void DepthwiseConvolution2dLayer::ValidateTensorShapesFromInputs()
 {
     VerifyLayerConnections(1, CHECK_LOCATION());

     // on this level constant data should not be released..
     BOOST_ASSERT_MSG(m_Weight != nullptr, "DepthwiseConvolution2dLayer: Weights data should not be null.");

     auto inferredShapes = InferOutputShapes({
         GetInputSlot(0).GetConnection()->GetTensorInfo().GetShape(),
         m_Weight->GetTensorInfo().GetShape()
      });

     BOOST_ASSERT(inferredShapes.size() == 1);

     ConditionalThrowIfNotEqual<LayerValidationException>(
         "DepthwiseConvolution2dLayer: TensorShape set on OutputSlot[0] does not match the inferred shape.",
         GetOutputSlot(0).GetTensorInfo().GetShape(),
         inferredShapes[0]);
 }

 Layer::ConstantTensors DepthwiseConvolution2dLayer::GetConstantTensorsByRef()
 {
     return {m_Weight, m_Bias};
 }

 void DepthwiseConvolution2dLayer::Accept(ILayerVisitor& visitor) const
 {
     ConstTensor weightsTensor(m_Weight->GetTensorInfo(), m_Weight->Map(true));
     Optional<ConstTensor> optionalBiasTensor = EmptyOptional();

     if (GetParameters().m_BiasEnabled)
     {
         ConstTensor biasTensor(m_Bias->GetTensorInfo(), m_Bias->Map(true));
         optionalBiasTensor = Optional<ConstTensor>(biasTensor);
     }

     visitor.VisitDepthwiseConvolution2dLayer(this, GetParameters(), weightsTensor, optionalBiasTensor, GetName());
 }

 } // namespace armnn
armnn::DepthwiseConvolution2dLayer::InferOutputShapes
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.
Definition: DepthwiseConvolution2dLayer.cpp:82

+armnn::DepthwiseConvolution2dLayer::CreateWorkload
virtual std::unique_ptr< IWorkload > CreateWorkload(const IWorkloadFactory &factory) const override
Makes a workload for the DepthwiseConvolution2d type.
Definition: DepthwiseConvolution2dLayer.cpp:51

+DataLayoutIndexed.hpp

+armnn::DepthwiseConvolution2dDescriptor::m_BiasEnabled
bool m_BiasEnabled
Enable/disable bias.
Definition: Descriptors.hpp:490

+armnn::LayerWithParameters< DepthwiseConvolution2dDescriptor >::m_Param
DepthwiseConvolution2dDescriptor m_Param
The parameters for the layer (not including tensor-valued weights etc.).
Definition: LayerWithParameters.hpp:50

+armnn::LayerWithParameters< DepthwiseConvolution2dDescriptor >::GetParameters
const DepthwiseConvolution2dDescriptor & GetParameters() const
Definition: LayerWithParameters.hpp:18

+armnn::TensorInfo::GetShape
const TensorShape & GetShape() const
Definition: Tensor.hpp:88

+armnn::DepthwiseConvolution2dDescriptor::m_PadBottom
uint32_t m_PadBottom
Padding bottom value in the height dimension.
Definition: Descriptors.hpp:480

+armnn::Optional
Definition: Optional.hpp:270

+armnn::DepthwiseConvolution2dLayer::Clone
DepthwiseConvolution2dLayer * Clone(Graph &graph) const override
Creates a dynamically-allocated copy of this layer.
Definition: DepthwiseConvolution2dLayer.cpp:68

+WorkloadFactory.hpp

+armnn::DepthwiseConvolution2dDescriptor::m_DataLayout
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
Definition: Descriptors.hpp:492

+armnn::IWorkloadFactory
Definition: WorkloadFactory.hpp:21

+armnn::DepthwiseConvolution2dLayer
This layer represents a depthwise convolution 2d operation.
Definition: DepthwiseConvolution2dLayer.hpp:15

+armnn::DepthwiseConvolution2dLayer::m_Bias
std::unique_ptr< ScopedCpuTensorHandle > m_Bias
A unique pointer to store Bias values.
Definition: DepthwiseConvolution2dLayer.hpp:21

+armnn::DepthwiseConvolution2dQueueDescriptor::m_Bias
const ConstCpuTensorHandle * m_Bias
Definition: WorkloadData.hpp:192

+armnn::DepthwiseConvolution2dDescriptor::m_PadLeft
uint32_t m_PadLeft
Padding left value in the width dimension.
Definition: Descriptors.hpp:474

+armnn::DepthwiseConvolution2dLayer::GetConstantTensorsByRef
ConstantTensors GetConstantTensorsByRef() override
Retrieve the handles to the constant values stored by the layer.
Definition: DepthwiseConvolution2dLayer.cpp:142

+armnn::LayerWithParameters::SerializeLayerParameters
void SerializeLayerParameters(ParameterStringifyFunction &fn) const override
Helper to serialize the layer parameters to string (currently used in DotSerializer and company)...
Definition: LayerWithParameters.hpp:22

+armnn
Copyright (c) 2020 ARM Limited.
Definition: 00_introduction.dox:25

+armnn::TensorShape
Definition: Tensor.hpp:20

+armnn::InputSlot::GetConnection
const IOutputSlot * GetConnection() const override
Definition: Layer.hpp:199

+armnn::DepthwiseConvolution2dDescriptor::m_DilationY
uint32_t m_DilationY
Dilation factor value for height dimension.
Definition: Descriptors.hpp:488

+armnn::DepthwiseConvolution2dQueueDescriptor::m_Weight
const ConstCpuTensorHandle * m_Weight
Definition: WorkloadData.hpp:191

+armnn::DepthwiseConvolution2dLayer::ValidateTensorShapesFromInputs
void ValidateTensorShapesFromInputs() override
Check if the input tensor shape(s) will lead to a valid configuration of DepthwiseConvolution2dLayer...
Definition: DepthwiseConvolution2dLayer.cpp:122

+armnn::DepthwiseConvolution2dLayer::SerializeLayerParameters
void SerializeLayerParameters(ParameterStringifyFunction &fn) const override
Helper to serialize the layer parameters to string.
Definition: DepthwiseConvolution2dLayer.cpp:29

+armnn::Layer::VerifyLayerConnections
void VerifyLayerConnections(unsigned int expectedConnections, const CheckLocation &location) const
Definition: Layer.cpp:338

+armnn::Layer::GetInputSlot
const InputSlot & GetInputSlot(unsigned int index) const override
Get a const input slot handle by slot index.
Definition: Layer.hpp:310

+TypesUtils.hpp

+armnn::DepthwiseConvolution2dDescriptor::m_StrideX
uint32_t m_StrideX
Stride value when proceeding through input for the width dimension.
Definition: Descriptors.hpp:482

+armnn::DepthwiseConvolution2dDescriptor::m_DilationX
uint32_t m_DilationX
Dilation factor value for width dimension.
Definition: Descriptors.hpp:486

+armnn::DepthwiseConvolution2dDescriptor::m_PadTop
uint32_t m_PadTop
Padding top value in the height dimension.
Definition: Descriptors.hpp:478

+armnnUtils::DataLayoutIndexed
Provides access to the appropriate indexes for Channels, Height and Width based on DataLayout...
Definition: DataLayoutIndexed.hpp:17

+armnn::DepthwiseConvolution2dLayer::DepthwiseConvolution2dLayer
DepthwiseConvolution2dLayer(const DepthwiseConvolution2dDescriptor &param, const char *name)
Constructor to create a DepthwiseConvolution2dLayer.
Definition: DepthwiseConvolution2dLayer.cpp:23

+armnn::ConstTensor
A tensor defined by a TensorInfo (shape and data type) and an immutable backing store.
Definition: Tensor.hpp:199

+armnn::ILayerVisitor::VisitDepthwiseConvolution2dLayer
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...

+DepthwiseConvolution2dLayer.hpp

+CHECK_LOCATION
#define CHECK_LOCATION()
Definition: Exceptions.hpp:192

+armnn::Graph
Definition: Graph.hpp:29

+armnn::LayerType::DepthwiseConvolution2d

+CpuTensorHandle.hpp

+armnn::DepthwiseConvolution2dLayer::Accept
void Accept(ILayerVisitor &visitor) const override
Apply a visitor to this layer.
Definition: DepthwiseConvolution2dLayer.cpp:147

+armnn::EmptyOptional
EmptyOptional is used to initialize the Optional class in case we want to have default value for an O...
Definition: Optional.hpp:32

+armnn::DepthwiseConvolution2dDescriptor::m_StrideY
uint32_t m_StrideY
Stride value when proceeding through input for the height dimension.
Definition: Descriptors.hpp:484

+armnn::LayerWithParameters< DepthwiseConvolution2dDescriptor >::PrepInfoAndDesc
WorkloadInfo PrepInfoAndDesc(QueueDescriptor &descriptor) const
Helper function to reduce duplication in *LayerCreateWorkload.
Definition: LayerWithParameters.hpp:43

+armnn::ILayerVisitor
Definition: ILayerVisitor.hpp:16

+armnnUtils
Definition: DataLayoutIndexed.hpp:13

+armnn::Layer::GetOutputSlot
const OutputSlot & GetOutputSlot(unsigned int index=0) const override
Get the const output slot handle by slot index.
Definition: Layer.hpp:312

+armnn::IOutputSlot::GetTensorInfo
virtual const TensorInfo & GetTensorInfo() const =0

+armnn::Layer::GetName
const char * GetName() const override
Returns the name of the layer.
Definition: Layer.hpp:305

+armnn::LayerWithParameters
Definition: LayerWithParameters.hpp:13

+armnn::DepthwiseConvolution2dLayer::m_Weight
std::unique_ptr< ScopedCpuTensorHandle > m_Weight
A unique pointer to store Weight values.
Definition: DepthwiseConvolution2dLayer.hpp:19

+armnn::ParameterStringifyFunction
std::function< void(const std::string &name, const std::string &value)> ParameterStringifyFunction
Definition: SerializeLayerParameters.hpp:14

+armnn::Layer::ConstantTensors
std::vector< std::reference_wrapper< std::unique_ptr< ScopedCpuTensorHandle > >> ConstantTensors
Definition: Layer.hpp:363

+armnn::IWorkloadFactory::CreateDepthwiseConvolution2d
virtual std::unique_ptr< IWorkload > CreateDepthwiseConvolution2d(const DepthwiseConvolution2dQueueDescriptor &descriptor, const WorkloadInfo &info) const
Definition: WorkloadFactory.cpp:1177

+armnn::OutputSlot::GetTensorInfo
const TensorInfo & GetTensorInfo() const override
Definition: Layer.cpp:63

+armnn::DepthwiseConvolution2dDescriptor
A DepthwiseConvolution2dDescriptor for the DepthwiseConvolution2dLayer.
Definition: Descriptors.hpp:444

+armnn::DepthwiseConvolution2dQueueDescriptor
Definition: WorkloadData.hpp:183

+armnn::DataLayout::NHWC

+LayerCloneBase.hpp

+armnn::LayerType
LayerType
Definition: InternalTypes.hpp:14

+armnn::DepthwiseConvolution2dDescriptor::m_PadRight
uint32_t m_PadRight
Padding right value in the width dimension.
Definition: Descriptors.hpp:476

+