31 const std::vector<TensorShape>& inputShapes =
38 unsigned int inputChannels = filterShape[1];
39 unsigned int filterWidth = filterShape[3];
40 unsigned int filterHeight = filterShape[2];
41 unsigned int depthMultiplier = filterShape[0];
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));
54 BOOST_ASSERT_MSG(
m_Weight !=
nullptr,
"DepthwiseConvolution2dLayer: Weights data should not be null.");
62 BOOST_ASSERT_MSG(
m_Bias !=
nullptr,
"DepthwiseConvolution2dLayer: Bias data should not be null.");
70 auto layer = CloneBase<DepthwiseConvolution2dLayer>(graph,
m_Param,
GetName());
71 layer->
m_Weight =
m_Weight ? std::make_unique<ScopedCpuTensorHandle>(*m_Weight) :
nullptr;
73 if (layer->m_Param.m_BiasEnabled)
75 layer->m_Bias =
m_Bias ? std::make_unique<ScopedCpuTensorHandle>(*m_Bias) :
nullptr;
78 return std::move(layer);
81 std::vector<TensorShape>
84 BOOST_ASSERT(inputShapes.size() == 2);
88 BOOST_ASSERT_MSG(inputShape.GetNumDimensions() == 4,
"Convolutions will always have 4D input.");
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()];
100 unsigned int depthMultiplier = filterShape[0];
102 unsigned int filterHeight = filterShape[2];
103 unsigned int dilatedFilterHeight = filterHeight + (
m_Param.
m_DilationY - 1) * (filterHeight - 1);
107 unsigned int filterWidth = filterShape[3];
108 unsigned int dilatedFilterWidth = filterWidth + (
m_Param.
m_DilationX - 1) * (filterWidth - 1);
112 unsigned int outputChannels = inputChannels * depthMultiplier;
113 unsigned int outputBatchSize = inputBatchSize;
116 TensorShape{ outputBatchSize, outputHeight, outputWidth, outputChannels } :
117 TensorShape{ outputBatchSize, outputChannels, outputHeight, outputWidth };
119 return std::vector<TensorShape>{ tensorShape };
127 BOOST_ASSERT_MSG(
m_Weight !=
nullptr,
"DepthwiseConvolution2dLayer: Weights data should not be null.");
131 m_Weight->GetTensorInfo().GetShape()
134 BOOST_ASSERT(inferredShapes.size() == 1);
136 ConditionalThrowIfNotEqual<LayerValidationException>(
137 "DepthwiseConvolution2dLayer: TensorShape set on OutputSlot[0] does not match the inferred shape.",
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.
virtual std::unique_ptr< IWorkload > CreateWorkload(const IWorkloadFactory &factory) const override
Makes a workload for the DepthwiseConvolution2d type.
bool m_BiasEnabled
Enable/disable bias.
DepthwiseConvolution2dDescriptor m_Param
The parameters for the layer (not including tensor-valued weights etc.).
const DepthwiseConvolution2dDescriptor & GetParameters() const
const TensorShape & GetShape() const
uint32_t m_PadBottom
Padding bottom value in the height dimension.
DepthwiseConvolution2dLayer * Clone(Graph &graph) const override
Creates a dynamically-allocated copy of this layer.
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
This layer represents a depthwise convolution 2d operation.
std::unique_ptr< ScopedCpuTensorHandle > m_Bias
A unique pointer to store Bias values.
const ConstCpuTensorHandle * m_Bias
uint32_t m_PadLeft
Padding left value in the width dimension.
ConstantTensors GetConstantTensorsByRef() override
Retrieve the handles to the constant values stored by the layer.
void SerializeLayerParameters(ParameterStringifyFunction &fn) const override
Helper to serialize the layer parameters to string (currently used in DotSerializer and company)...
Copyright (c) 2020 ARM Limited.
uint32_t m_DilationY
Dilation factor value for height dimension.
const ConstCpuTensorHandle * m_Weight
void ValidateTensorShapesFromInputs() override
Check if the input tensor shape(s) will lead to a valid configuration of DepthwiseConvolution2dLayer...
void SerializeLayerParameters(ParameterStringifyFunction &fn) const override
Helper to serialize the layer parameters to string.
void VerifyLayerConnections(unsigned int expectedConnections, const CheckLocation &location) const
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.
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...
DepthwiseConvolution2dLayer(const DepthwiseConvolution2dDescriptor ¶m, const char *name)
Constructor to create a DepthwiseConvolution2dLayer.
A tensor defined by a TensorInfo (shape and data type) and an immutable backing store.
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...
void Accept(ILayerVisitor &visitor) const override
Apply a visitor to this layer.
EmptyOptional is used to initialize the Optional class in case we want to have default value for an O...
uint32_t m_StrideY
Stride value when proceeding through input for the height dimension.
WorkloadInfo PrepInfoAndDesc(QueueDescriptor &descriptor) const
Helper function to reduce duplication in *LayerCreateWorkload.
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.
std::unique_ptr< ScopedCpuTensorHandle > m_Weight
A unique pointer to store Weight values.
std::function< void(const std::string &name, const std::string &value)> ParameterStringifyFunction
std::vector< std::reference_wrapper< std::unique_ptr< ScopedCpuTensorHandle > >> ConstantTensors
virtual std::unique_ptr< IWorkload > CreateDepthwiseConvolution2d(const DepthwiseConvolution2dQueueDescriptor &descriptor, const WorkloadInfo &info) const
const TensorInfo & GetTensorInfo() const override
A DepthwiseConvolution2dDescriptor for the DepthwiseConvolution2dLayer.
uint32_t m_PadRight
Padding right value in the width dimension.