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

Inheritance diagram for nvinfer1::IConcatenationLayer:

Collaboration diagram for nvinfer1::IConcatenationLayer:

Public Member Functions
virtual void	setAxis (int32_t axis)=0
	Set the axis along which concatenation occurs. More...

virtual int32_t	getAxis () const =0
	Get the axis along which concatenation occurs. 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	~IConcatenationLayer ()

Detailed Description

A concatenation layer in a network definition.

The output channel size is the sum of the channel sizes of the inputs. The other output sizes are the same as the other input sizes, which must all match.

Warning: Do not inherit from this class, as doing so will break forward-compatibility of the API and ABI.

Constructor & Destructor Documentation

◆ ~IConcatenationLayer()

virtual nvinfer1::IConcatenationLayer::~IConcatenationLayer ( )

inlineprotectedvirtual

Member Function Documentation

◆ setAxis()

virtual void nvinfer1::IConcatenationLayer::setAxis ( int32_t axis )

pure virtual

Set the axis along which concatenation occurs.

0 is the major axis (excluding the batch dimension). The default is the number of non-batch axes in the tensor minus three (e.g. for an NCHW input it would be 0), or 0 if there are fewer than 3 non-batch axes.

When running this layer on the DLA, only concat across the Channel axis is valid.

Parameters

axis	The axis along which concatenation occurs.

◆ getAxis()

virtual int32_t nvinfer1::IConcatenationLayer::getAxis ( ) const

pure virtual

Get the axis along which concatenation occurs.

See also: setAxis()

◆ 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

◆ ~IConcatenationLayer()

Member Function Documentation

◆ setAxis()

◆ getAxis()

◆ getType()

◆ setName()

◆ getName()

◆ getNbInputs()

◆ getInput()

◆ getNbOutputs()

◆ getOutput()

◆ setInput()

◆ setPrecision()

◆ getPrecision()

◆ precisionIsSet()

◆ resetPrecision()

◆ setOutputType()

◆ getOutputType()

◆ outputTypeIsSet()

◆ resetOutputType()