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49 unsigned int inWidth = inputShape[dimensionIndices.
GetWidthIndex()];
50 unsigned int inHeight = inputShape[dimensionIndices.
GetHeightIndex()];
51 unsigned int inDepth = inputShape[dimensionIndices.
GetDepthIndex()];
53 unsigned int inBatchSize = inputShape[0];
56 unsigned int outWidth = 1;
57 unsigned int outHeight = 1;
58 unsigned int outDepth = 1;
62 "Stride can only be zero when performing global pooling");
64 auto CalcSize = [](
auto inSize,
auto lowPad,
auto highPad,
auto poolSize,
auto stride,
auto outputShapeRounding)
66 unsigned int readSize = inSize + lowPad + highPad - poolSize;
67 float div =
static_cast<float>(readSize) /
static_cast<float>(stride);
69 unsigned int size = 0;
70 switch (outputShapeRounding)
73 size =
static_cast<unsigned int>(
ceil(div)) + 1;
75 case OutputShapeRounding ::Floor:
76 size =
static_cast<unsigned int>(floor(div)) + 1;
84 if ((size - 1)*stride >= inSize + lowPad)
99 unsigned int outChannels = inChannels;
100 unsigned int outBatchSize = inBatchSize;
103 TensorShape( { outBatchSize, outDepth, outHeight, outWidth, outChannels } ) :
104 TensorShape( { outBatchSize, outChannels, outDepth, outHeight, outWidth });
106 return std::vector<TensorShape>({ tensorShape });
uint32_t m_PadTop
Padding top value in the height dimension.
uint32_t m_StrideX
Stride value when proceeding through input for the width dimension.
uint32_t m_PadRight
Padding right value in the width dimension.
void VerifyLayerConnections(unsigned int expectedConnections, const CheckLocation &location) const
unsigned int GetDepthIndex() const
A Pooling3dDescriptor for the Pooling3dLayer.
uint32_t m_PoolWidth
Pooling width value.
unsigned int GetWidthIndex() const
OutputShapeRounding m_OutputShapeRounding
The rounding method for the output shape. (Floor, Ceiling).
void VerifyShapeInferenceType(const TensorShape &outputShape, ShapeInferenceMethod shapeInferenceMethod)
uint32_t m_PadLeft
Padding left value in the width dimension.
void SetAdditionalInfo(QueueDescriptor &descriptor) const
ShapeInferenceMethod m_ShapeInferenceMethod
void ValidateAndCopyShape(const TensorShape &outputShape, const TensorShape &inferredShape, const ShapeInferenceMethod shapeInferenceMethod, const std::string &layerName, const unsigned int outputSlotIndex=0)
Copyright (c) 2021 ARM Limited and Contributors.
unsigned int GetChannelsIndex() const
const TensorInfo & GetTensorInfo() const override
void Pooling3d(Decoder< float > &rInputDecoder, Encoder< float > &rOutputEncoder, const TensorInfo &inputInfo, const TensorInfo &outputInfo, const Pooling3dDescriptor ¶ms)
Computes the Pooling3d operation.
LayerType
When adding a new layer, adapt also the LastLayer enum value in the enum class LayerType below.
virtual const TensorInfo & GetTensorInfo() const =0
const OutputSlot & GetOutputSlot(unsigned int index=0) const override
Get the const output slot handle by slot index.
uint32_t m_PadFront
Padding front value in the depth dimension.
Pooling3dLayer * Clone(Graph &graph) const override
Creates a dynamically-allocated copy of this layer.
uint32_t m_PadBack
Padding back value in the depth dimension.
WorkloadInfo PrepInfoAndDesc(QueueDescriptor &descriptor) const
Helper function to reduce duplication in *Layer::CreateWorkload.
uint32_t m_StrideZ
Stride value when proceeding through input for the depth dimension.
void ValidateTensorShapesFromInputs() override
Check if the input tensor shape(s) will lead to a valid configuration of Pooling3dLayer.
Pooling3dLayer(const Pooling3dDescriptor ¶m, const char *name)
Constructor to create a Pooling3dLayer.
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,...
uint32_t m_PoolDepth
Pooling depth value.
const TensorShape & GetShape() const
#define ARMNN_ASSERT_MSG(COND, MSG)
This layer represents a pooling 3d operation.
void ExecuteStrategy(IStrategy &strategy) const override
Apply a visitor to this layer.
const InputSlot & GetInputSlot(unsigned int index) const override
Get a const input slot handle by slot index.
virtual void ExecuteStrategy(const IConnectableLayer *layer, const armnn::BaseDescriptor &descriptor, const std::vector< armnn::ConstTensor > &constants, const char *name, const armnn::LayerBindingId id=0)=0
unsigned int GetNumDimensions() const
Function that returns the tensor rank.
#define ARMNN_ASSERT(COND)
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_PadBottom
Padding bottom value in the height dimension.
virtual std::unique_ptr< IWorkload > CreateWorkload(LayerType type, const QueueDescriptor &descriptor, const WorkloadInfo &info) const
unsigned int GetHeightIndex() const
uint32_t m_PoolHeight
Pooling height value.
const char * GetName() const override
Returns the name of the layer.
const Pooling3dDescriptor & GetParameters() const override
Pooling3dDescriptor m_Param
The parameters for the layer (not including tensor-valued weights etc.).
DataLayout m_DataLayout
The data layout to be used (NCDHW, NDHWC).
virtual std::unique_ptr< IWorkload > CreateWorkload(const IWorkloadFactory &factory) const override
Makes a workload for the Pooling3d type.