47 ARMNN_ASSERT_MSG(inputShape.GetNumDimensions() == 5,
"Pooling3dLayer will always have 5D input.");
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;
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 });
Pooling3dDescriptor m_Param
The parameters for the layer (not including tensor-valued weights etc.).
unsigned int GetWidthIndex() const
uint32_t m_StrideY
Stride value when proceeding through input for the height dimension.
const TensorShape & GetShape() const
uint32_t m_PoolWidth
Pooling width value.
uint32_t m_PoolDepth
Pooling depth value.
void ValidateTensorShapesFromInputs() override
Check if the input tensor shape(s) will lead to a valid configuration of Pooling3dLayer.
#define ARMNN_NO_DEPRECATE_WARN_BEGIN
virtual std::unique_ptr< IWorkload > CreateWorkload(const IWorkloadFactory &factory) const override
Makes a workload for the Pooling3d type.
Pooling3dLayer(const Pooling3dDescriptor ¶m, const char *name)
Constructor to create a Pooling3dLayer.
uint32_t m_PadRight
Padding right value in the width dimension.
unsigned int GetDepthIndex() const
void VerifyShapeInferenceType(const TensorShape &outputShape, ShapeInferenceMethod shapeInferenceMethod)
Copyright (c) 2021 ARM Limited and Contributors.
DataLayout m_DataLayout
The data layout to be used (NCDHW, NDHWC).
const Pooling3dDescriptor & GetParameters() const override
uint32_t m_PadFront
Padding front value in the depth dimension.
uint32_t m_PoolHeight
Pooling height value.
void ValidateAndCopyShape(const TensorShape &outputShape, const TensorShape &inferredShape, const ShapeInferenceMethod shapeInferenceMethod, const std::string &layerName, const unsigned int outputSlotIndex=0)
unsigned int GetHeightIndex() const
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_PadBack
Padding back value in the depth dimension.
#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...
OutputShapeRounding m_OutputShapeRounding
The rounding method for the output shape. (Floor, Ceiling).
uint32_t m_PadBottom
Padding bottom value in the height dimension.
#define ARMNN_ASSERT(COND)
This layer represents a pooling 3d operation.
A Pooling3dDescriptor for the Pooling3dLayer.
uint32_t m_StrideZ
Stride value when proceeding through input for the depth dimension.
void SetAdditionalInfo(QueueDescriptor &descriptor) const
ARMNN_NO_DEPRECATE_WARN_BEGIN void Accept(ILayerVisitor &visitor) const override
uint32_t m_PadLeft
Padding left value in the width dimension.
uint32_t m_PadTop
Padding top value in 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
void Pooling3d(Decoder< float > &rInputDecoder, Encoder< float > &rOutputEncoder, const TensorInfo &inputInfo, const TensorInfo &outputInfo, const Pooling3dDescriptor ¶ms)
Computes the Pooling3d operation.
const char * GetName() const override
Returns the name of the layer.
uint32_t m_StrideX
Stride value when proceeding through input for the width dimension.
virtual std::unique_ptr< IWorkload > CreateWorkload(LayerType type, const QueueDescriptor &descriptor, const WorkloadInfo &info) const
const TensorInfo & GetTensorInfo() const override
unsigned int GetChannelsIndex() const
ShapeInferenceMethod m_ShapeInferenceMethod
Pooling3dLayer * Clone(Graph &graph) const override
Creates a dynamically-allocated copy of this layer.
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.
LayerType
When adding a new layer, adapt also the LastLayer enum value in the enum class LayerType below...