A Pooling layer in a network definition. More...

Inheritance diagram for nvinfer1::IPoolingLayer:

Collaboration diagram for nvinfer1::IPoolingLayer:

Public Member Functions
virtual void	setPoolingType (PoolingType type)=0
	Set the type of activation to be performed. More...

virtual PoolingType	getPoolingType () const =0
	Get the type of activation to be performed. More...

	__attribute__ ((deprecated)) virtual void setWindowSize(DimsHW windowSize)=0
	Set the window size for pooling. More...

	__attribute__ ((deprecated)) virtual DimsHW getWindowSize() const =0
	Get the window size for pooling. More...

	__attribute__ ((deprecated)) virtual void setStride(DimsHW stride)=0
	Set the stride for pooling. More...

	__attribute__ ((deprecated)) virtual DimsHW getStride() const =0
	Get the stride for pooling. More...

	__attribute__ ((deprecated)) virtual void setPadding(DimsHW padding)=0
	Set the padding for pooling. More...

	__attribute__ ((deprecated)) virtual DimsHW getPadding() const =0
	Get the padding for pooling. More...

virtual void	setBlendFactor (float blendFactor)=0
	Set the blending factor for the max_average_blend mode: max_average_blendPool = (1-blendFactor)maxPool + blendFactoravgPool blendFactor is a user value in [0,1] with the default value of 0.0 This value only applies for the kMAX_AVERAGE_BLEND mode. More...

virtual float	getBlendFactor () const =0
	Get the blending factor for the max_average_blend mode: max_average_blendPool = (1-blendFactor)maxPool + blendFactoravgPool blendFactor is a user value in [0,1] with the default value of 0.0 In modes other than kMAX_AVERAGE_BLEND, blendFactor is ignored. More...

virtual void	setAverageCountExcludesPadding (bool exclusive)=0
	Set whether average pooling uses as a denominator the overlap area between the window and the unpadded input. More...

virtual bool	getAverageCountExcludesPadding () const =0
	Get whether exclusive pooling uses as a denominator the overlap area betwen the window and the unpadded input. More...

virtual void	setPrePadding (Dims padding)=0
	Set the multi-dimension pre-padding for pooling. More...

virtual Dims	getPrePadding () const =0
	Get the pre-padding. More...

virtual void	setPostPadding (Dims padding)=0
	Set the multi-dimension post-padding for pooling. More...

virtual Dims	getPostPadding () const =0
	Get the padding. More...

virtual void	setPaddingMode (PaddingMode paddingMode)=0
	Set the padding mode. More...

virtual PaddingMode	getPaddingMode () const =0
	Get the padding mode. More...

virtual void	setWindowSizeNd (Dims windowSize)=0
	Set the multi-dimension window size for pooling. More...

virtual Dims	getWindowSizeNd () const =0
	Get the multi-dimension window size for pooling. More...

virtual void	setStrideNd (Dims stride)=0
	Set the multi-dimension stride for pooling. More...

virtual Dims	getStrideNd () const =0
	Get the multi-dimension stride for pooling. More...

virtual void	setPaddingNd (Dims padding)=0
	Set the multi-dimension padding for pooling. More...

virtual Dims	getPaddingNd () const =0
	Get the multi-dimension padding for pooling. More...

virtual LayerType	getType () const =0
	Return the type of a layer. More...

virtual void	setName (const char *name)=0
	Set the name of a layer. More...

virtual const char *	getName () const =0
	Return the name of a layer. More...

virtual int32_t	getNbInputs () const =0
	Get the number of inputs of a layer. More...

virtual ITensor *	getInput (int32_t index) const =0
	Get the layer input corresponding to the given index. More...

virtual int32_t	getNbOutputs () const =0
	Get the number of outputs of a layer. More...

virtual ITensor *	getOutput (int32_t index) const =0
	Get the layer output corresponding to the given index. More...

virtual void	setInput (int32_t index, ITensor &tensor)=0
	Replace an input of this layer with a specific tensor. More...

virtual void	setPrecision (DataType dataType)=0
	Set the computational precision of this layer. More...

virtual DataType	getPrecision () const =0
	get the computational precision of this layer More...

virtual bool	precisionIsSet () const =0
	whether the computational precision has been set for this layer More...

virtual void	resetPrecision ()=0
	reset the computational precision for this layer More...

virtual void	setOutputType (int32_t index, DataType dataType)=0
	Set the output type of this layer. More...

virtual DataType	getOutputType (int32_t index) const =0
	get the output type of this layer More...

virtual bool	outputTypeIsSet (int32_t index) const =0
	whether the output type has been set for this layer More...

virtual void	resetOutputType (int32_t index)=0
	reset the output type for this layer More...

Protected Member Functions
virtual	~IPoolingLayer ()

Detailed Description

A Pooling layer in a network definition.

The layer applies a reduction operation within a window over the input.

Warning: When running pooling layer with DeviceType::kDLA in Int8 mode, the dynamic ranges for input and output tensors must be equal.; Do not inherit from this class, as doing so will break forward-compatibility of the API and ABI.

Constructor & Destructor Documentation

◆ ~IPoolingLayer()

virtual nvinfer1::IPoolingLayer::~IPoolingLayer ( )

inlineprotectedvirtual

Member Function Documentation

◆ setPoolingType()

virtual void nvinfer1::IPoolingLayer::setPoolingType ( PoolingType type )

pure virtual

Set the type of activation to be performed.

DLA only supports kMAX and kAVERAGE pooling types.

See also: getPoolingType(), PoolingType

◆ getPoolingType()

virtual PoolingType nvinfer1::IPoolingLayer::getPoolingType ( ) const

pure virtual

Get the type of activation to be performed.

See also: setPoolingType(), PoolingType

◆ attribute() [1/6]

nvinfer1::IPoolingLayer::__attribute__ ( (deprecated) )

pure virtual

Set the window size for pooling.

If executing this layer on DLA, both height and width of window size must be in the range [1,8].

See also: getWindowSize()

Deprecated:: Superseded by setWindowSizeNd and will be removed in TensorRT 9.0.

◆ attribute() [2/6]

nvinfer1::IPoolingLayer::__attribute__ ( (deprecated) ) const

pure virtual

Get the window size for pooling.

See also: setWindowSize()

Deprecated:: Superseded by getWindowSizeNd and will be removed in TensorRT 9.0.

◆ attribute() [3/6]

nvinfer1::IPoolingLayer::__attribute__ ( (deprecated) )

pure virtual

Set the stride for pooling.

Default: 1

If executing this layer on DLA, both height and width of stride must be in the range [1,16].

See also: getStride()

Deprecated:: Superseded by setStrideNd and will be removed in TensorRT 9.0.

◆ attribute() [4/6]

nvinfer1::IPoolingLayer::__attribute__ ( (deprecated) ) const

pure virtual

Get the stride for pooling.

See also: setStride()

Deprecated:: Superseded by getStrideNd and will be removed in TensorRT 9.0.

◆ attribute() [5/6]

nvinfer1::IPoolingLayer::__attribute__ ( (deprecated) )

pure virtual

Set the padding for pooling.

Default: 0

If executing this layer on DLA, both height and width of padding must be in the range [0,7].

See also: getPadding()

Deprecated:: Superseded by setPaddingNd and will be removed in TensorRT 9.0.

◆ attribute() [6/6]

nvinfer1::IPoolingLayer::__attribute__ ( (deprecated) ) const

pure virtual

Get the padding for pooling.

Default: 0

See also: setPadding()

Deprecated:: Superseded by getPaddingNd and will be removed in TensorRT 9.0.

◆ setBlendFactor()

virtual void nvinfer1::IPoolingLayer::setBlendFactor ( float blendFactor )

pure virtual

Set the blending factor for the max_average_blend mode: max_average_blendPool = (1-blendFactor)*maxPool + blendFactor*avgPool blendFactor is a user value in [0,1] with the default value of 0.0 This value only applies for the kMAX_AVERAGE_BLEND mode.

Since DLA does not support kMAX_AVERAGE_BLEND, blendFactor is ignored on the DLA.

See also: getBlendFactor()

◆ getBlendFactor()

virtual float nvinfer1::IPoolingLayer::getBlendFactor ( ) const

pure virtual

Get the blending factor for the max_average_blend mode: max_average_blendPool = (1-blendFactor)*maxPool + blendFactor*avgPool blendFactor is a user value in [0,1] with the default value of 0.0 In modes other than kMAX_AVERAGE_BLEND, blendFactor is ignored.

See also: setBlendFactor()

◆ setAverageCountExcludesPadding()

virtual void nvinfer1::IPoolingLayer::setAverageCountExcludesPadding ( bool exclusive )

pure virtual

Set whether average pooling uses as a denominator the overlap area between the window and the unpadded input.

If this is not set, the denominator is the overlap between the pooling window and the padded input.

If executing this layer on the DLA, only inclusive padding is supported.

Default: true

If executing this layer on the DLA, this is ignored as the DLA does not support exclusive padding.

See also: getAverageCountExcludesPadding()

◆ getAverageCountExcludesPadding()

virtual bool nvinfer1::IPoolingLayer::getAverageCountExcludesPadding ( ) const

pure virtual

Get whether exclusive pooling uses as a denominator the overlap area betwen the window and the unpadded input.

See also: setAverageCountExcludesPadding()

◆ setPrePadding()

virtual void nvinfer1::IPoolingLayer::setPrePadding ( Dims padding )

pure virtual

Set the multi-dimension pre-padding for pooling.

The start of the input will be padded by this number of elements in each dimension. Padding value depends on pooling type, -inf is used for max pooling and zero padding for average pooling.

Default: (0, 0, ..., 0)

If executing this layer on DLA, only support 2D padding, both height and width of padding must be in the range [0,7].

See also: getPrePadding()

◆ getPrePadding()

virtual Dims nvinfer1::IPoolingLayer::getPrePadding ( ) const

pure virtual

Get the pre-padding.

See also: setPrePadding()

◆ setPostPadding()

virtual void nvinfer1::IPoolingLayer::setPostPadding ( Dims padding )

pure virtual

Set the multi-dimension post-padding for pooling.

The end of the input will be padded by this number of elements in each dimension. Padding value depends on pooling type, -inf is used for max pooling and zero padding for average pooling.

Default: (0, 0, ..., 0)

If executing this layer on DLA, only support 2D padding, both height and width of padding must be in the range [0,7].

See also: getPostPadding()

◆ getPostPadding()

virtual Dims nvinfer1::IPoolingLayer::getPostPadding ( ) const

pure virtual

Get the padding.

See also: setPadding()

◆ setPaddingMode()

virtual void nvinfer1::IPoolingLayer::setPaddingMode ( PaddingMode paddingMode )

pure virtual

Set the padding mode.

Padding mode takes precedence if both setPaddingMode and setPre/PostPadding are used.

Default: kEXPLICIT_ROUND_DOWN

See also: getPaddingMode()

◆ getPaddingMode()

virtual PaddingMode nvinfer1::IPoolingLayer::getPaddingMode ( ) const

pure virtual

Get the padding mode.

Default: kEXPLICIT_ROUND_DOWN

See also: setPaddingMode()

◆ setWindowSizeNd()

virtual void nvinfer1::IPoolingLayer::setWindowSizeNd ( Dims windowSize )

pure virtual

Set the multi-dimension window size for pooling.

If executing this layer on DLA, only support 2D window size, both height and width of window size must be in the range [1,8].

See also: getWindowSizeNd() setWindowSize() getWindowSize()

◆ getWindowSizeNd()

virtual Dims nvinfer1::IPoolingLayer::getWindowSizeNd ( ) const

pure virtual

Get the multi-dimension window size for pooling.

See also: setWindowSizeNd()

◆ setStrideNd()

virtual void nvinfer1::IPoolingLayer::setStrideNd ( Dims stride )

pure virtual

Set the multi-dimension stride for pooling.

Default: (1, 1, ..., 1)

If executing this layer on DLA, only support 2D stride, both height and width of stride must be in the range [1,16].

See also: getStrideNd() setStride() getStride()

◆ getStrideNd()

virtual Dims nvinfer1::IPoolingLayer::getStrideNd ( ) const

pure virtual

Get the multi-dimension stride for pooling.

See also: setStrideNd()

◆ setPaddingNd()

virtual void nvinfer1::IPoolingLayer::setPaddingNd ( Dims padding )

pure virtual

Set the multi-dimension padding for pooling.

The input will be padded by this number of elements in each dimension. Padding is symmetric. Padding value depends on pooling type, -inf is used for max pooling and zero padding for average pooling.

Default: (0, 0, ..., 0)

If executing this layer on DLA, only support 2D padding, both height and width of padding must be in the range [0,7].

See also: getPaddingNd() setPadding() getPadding()

◆ getPaddingNd()

virtual Dims nvinfer1::IPoolingLayer::getPaddingNd ( ) const

pure virtual

Get the multi-dimension padding for pooling.

If the padding is asymmetric, the pre-padding is returned.

See also: setPaddingNd()

◆ getType()

virtual LayerType nvinfer1::ILayer::getType ( ) const

pure virtualinherited

Return the type of a layer.

See also: LayerType

◆ setName()

virtual void nvinfer1::ILayer::setName ( const char * name )

pure virtualinherited

Set the name of a layer.

This method copies the name string.

See also: getName()

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◆ getName()

virtual const char* nvinfer1::ILayer::getName ( ) const

pure virtualinherited

Return the name of a layer.

See also: setName()

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◆ getNbInputs()

virtual int32_t nvinfer1::ILayer::getNbInputs ( ) const

pure virtualinherited

Get the number of inputs of a layer.

◆ getInput()

virtual ITensor* nvinfer1::ILayer::getInput ( int32_t index ) const

pure virtualinherited

Get the layer input corresponding to the given index.

Parameters

index The index of the input tensor.

Returns: The input tensor, or nullptr if the index is out of range or the tensor is optional (ISliceLayer, IRNNLayer and IRNNv2Layer).

◆ getNbOutputs()

virtual int32_t nvinfer1::ILayer::getNbOutputs ( ) const

pure virtualinherited

Get the number of outputs of a layer.

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◆ getOutput()

virtual ITensor* nvinfer1::ILayer::getOutput ( int32_t index ) const

pure virtualinherited

Get the layer output corresponding to the given index.

Returns: The indexed output tensor, or nullptr if the index is out of range or the tensor is optional (IRNNLayer and IRNNv2Layer).

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◆ setInput()

virtual void nvinfer1::ILayer::setInput	(	int32_t	index,
		ITensor &	tensor
	)

pure virtualinherited

Replace an input of this layer with a specific tensor.

Parameters

index	the index of the input to modify.
tensor	the new input tensor Except for IShuffleLayer, ISliceLayer, IResizeLayer and ILoopOutputLayer, this method cannot change the number of inputs to a layer. The index argument must be less than the value of getNbInputs().

See overloaded setInput() comments for the layers special behavior.

Parameters

index	the index of the input to modify.
tensor	the new input tensor

Implemented in nvinfer1::IFillLayer, nvinfer1::ILoopOutputLayer, nvinfer1::IRecurrenceLayer, nvinfer1::IResizeLayer, nvinfer1::ISliceLayer, nvinfer1::IShuffleLayer, nvinfer1::IDeconvolutionLayer, nvinfer1::IFullyConnectedLayer, and nvinfer1::IConvolutionLayer.

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◆ setPrecision()

virtual void nvinfer1::ILayer::setPrecision ( DataType dataType )

pure virtualinherited

Set the computational precision of this layer.

Setting the precision allows TensorRT to choose implementation which run at this computational precision. Layer input type would also get inferred from layer computational precision. TensorRT could still choose a non-conforming fastest implementation ignoring set layer precision. Use BuilderFlag::kSTRICT_TYPES to force choose implementations with requested precision. In case no implementation is found with requested precision, TensorRT would choose available fastest implementation. If precision is not set, TensorRT will select the layer computational precision and layer input type based on performance considerations and the flags specified to the builder.

Parameters

precision the computational precision.

See also: getPrecision() precisionIsSet() resetPrecision()

◆ getPrecision()

virtual DataType nvinfer1::ILayer::getPrecision ( ) const

pure virtualinherited

get the computational precision of this layer

Returns: the computational precision

See also: setPrecision() precisionIsSet() resetPrecision()

◆ precisionIsSet()

virtual bool nvinfer1::ILayer::precisionIsSet ( ) const

pure virtualinherited

whether the computational precision has been set for this layer

Returns: whether the computational precision has been explicitly set

See also: setPrecision() getPrecision() resetPrecision()

◆ resetPrecision()

virtual void nvinfer1::ILayer::resetPrecision ( )

pure virtualinherited

reset the computational precision for this layer

See also: setPrecision() getPrecision() precisionIsSet()

◆ setOutputType()

virtual void nvinfer1::ILayer::setOutputType	(	int32_t	index,
		DataType	dataType
	)

pure virtualinherited

Set the output type of this layer.

Setting the output type constrains TensorRT to choose implementations which generate output data with the given type. If it is not set, TensorRT will select output type based on layer computational precision. TensorRT could still choose non-conforming output type based on fastest implementation. Use BuilderFlag::kSTRICT_TYPES to force choose requested output type. In case layer precision is not specified, output type would depend on chosen implementation based on performance considerations and the flags specified to the builder.

This method cannot be used to set the data type of the second output tensor of the TopK layer. The data type of the second output tensor of the topK layer is always Int32. Also the output type of all layers that are shape operations must be DataType::kINT32, and all attempts to set the output type to some other data type will be ignored except for issuing an error message.

Note that the layer output type is generally not identical to the data type of the output tensor, as TensorRT may insert implicit reformatting operations to convert the former to the latter. Calling layer->setOutputType(i, type) has no effect on the data type of the i-th output tensor of layer, and users need to call layer->getOutput(i)->setType(type) to change the tensor data type. This is particularly relevant if the tensor is marked as a network output, since only setType() [but not setOutputType()] will affect the data representation in the corresponding output binding.

Parameters

index	the index of the output to set
dataType	the type of the output

See also: getOutputType() outputTypeIsSet() resetOutputType()

◆ getOutputType()

virtual DataType nvinfer1::ILayer::getOutputType ( int32_t index ) const

pure virtualinherited

get the output type of this layer

Parameters

index the index of the output

Returns: the output precision. If no precision has been set, DataType::kFLOAT will be returned, unless the output type is inherently DataType::kINT32.

See also: getOutputType() outputTypeIsSet() resetOutputType()

◆ outputTypeIsSet()

virtual bool nvinfer1::ILayer::outputTypeIsSet ( int32_t index ) const

pure virtualinherited

whether the output type has been set for this layer

Parameters

index the index of the output

Returns: whether the output type has been explicitly set

See also: setOutputType() getOutputType() resetOutputType()

◆ resetOutputType()

virtual void nvinfer1::ILayer::resetOutputType ( int32_t index )

pure virtualinherited

reset the output type for this layer

Parameters

index the index of the output

See also: setOutputType() getOutputType() outputTypeIsSet()

The documentation for this class was generated from the following file:

NvInfer.h

Public Member Functions

Protected Member Functions

Detailed Description

Constructor & Destructor Documentation

◆ ~IPoolingLayer()

Member Function Documentation

◆ setPoolingType()

◆ getPoolingType()

◆ __attribute__() [1/6]

◆ __attribute__() [2/6]

◆ __attribute__() [3/6]

◆ __attribute__() [4/6]

◆ __attribute__() [5/6]

◆ __attribute__() [6/6]

◆ setBlendFactor()

◆ getBlendFactor()

◆ setAverageCountExcludesPadding()

◆ getAverageCountExcludesPadding()

◆ setPrePadding()

◆ getPrePadding()

◆ setPostPadding()

◆ getPostPadding()

◆ setPaddingMode()

◆ getPaddingMode()

◆ setWindowSizeNd()

◆ getWindowSizeNd()

◆ setStrideNd()

◆ getStrideNd()

◆ setPaddingNd()

◆ getPaddingNd()

◆ getType()

◆ setName()

◆ getName()

◆ getNbInputs()

◆ getInput()

◆ getNbOutputs()

◆ getOutput()

◆ setInput()

◆ setPrecision()

◆ getPrecision()

◆ precisionIsSet()

◆ resetPrecision()

◆ setOutputType()

◆ getOutputType()

◆ outputTypeIsSet()

◆ resetOutputType()

◆ attribute() [1/6]

◆ attribute() [2/6]

◆ attribute() [3/6]

◆ attribute() [4/6]

◆ attribute() [5/6]

◆ attribute() [6/6]