A tensor in a network definition. More...

#include <NvInfer.h>

Public Member Functions
virtual void	setName (const char *name)=0
	Set the tensor name. More...

virtual const char *	getName () const =0
	Get the tensor name. More...

virtual void	setDimensions (Dims dimensions)=0
	Set the dimensions of a tensor. More...

virtual Dims	getDimensions () const =0
	Get the dimensions of a tensor. More...

virtual void	setType (DataType type)=0
	Set the data type of a tensor. More...

virtual DataType	getType () const =0
	Get the data type of a tensor. More...

virtual bool	setDynamicRange (float min, float max)=0
	Set dynamic range for the tensor. More...

virtual TRT_DEPRECATED float	getDynamicRange () const =0
	Get dynamic range for the tensor. More...

virtual bool	isNetworkInput () const =0
	Whether the tensor is a network input.

virtual bool	isNetworkOutput () const =0
	Whether the tensor is a network output.

virtual void	setBroadcastAcrossBatch (bool broadcastAcrossBatch)=0
	Set whether to enable broadcast of tensor across the batch. More...

virtual bool	getBroadcastAcrossBatch () const =0
	Check if tensor is broadcast across the batch. More...

virtual TensorLocation	getLocation () const =0
	Get the storage location of a tensor. More...

virtual void	setLocation (TensorLocation location)=0
	Set the storage location of a tensor. More...

virtual bool	dynamicRangeIsSet () const =0
	Query whether dynamic range is set. More...

virtual void	resetDynamicRange ()=0
	Undo effect of setDynamicRange.

virtual float	getDynamicRangeMin () const =0
	Get minimum of dynamic range. More...

virtual float	getDynamicRangeMax () const =0
	Get maximum of dynamic range. More...

virtual void	setAllowedFormats (TensorFormats formats)=0
	Set allowed formats for this tensor. By default all formats are allowed. Shape tensors (for which isShapeTensor() returns true) may only have row major linear format. More...

virtual TensorFormats	getAllowedFormats () const =0
	Get a bitmask of TensorFormat values that the tensor supports. For a shape tensor, only row major linear format is allowed. More...

virtual bool	isShapeTensor () const =0
	Whether the tensor is a shape tensor. More...

virtual bool	isExecutionTensor () const =0
	Whether the tensor is an execution tensor. More...

Detailed Description

A tensor in a network definition.

to remove a tensor from a network definition, use INetworkDefinition::removeTensor()

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

Member Function Documentation

◆ dynamicRangeIsSet()

virtual bool nvinfer1::ITensor::dynamicRangeIsSet ( ) const

pure virtual

Query whether dynamic range is set.

Returns: True if dynamic range is set, false otherwise.

◆ getAllowedFormats()

virtual TensorFormats nvinfer1::ITensor::getAllowedFormats ( ) const

pure virtual

Get a bitmask of TensorFormat values that the tensor supports. For a shape tensor, only row major linear format is allowed.

Returns: The value specified by setAllowedFormats or all possible formats.

See also: ITensor::setAllowedFormats()

◆ getBroadcastAcrossBatch()

virtual bool nvinfer1::ITensor::getBroadcastAcrossBatch ( ) const

pure virtual

Check if tensor is broadcast across the batch.

When a tensor is broadcast across a batch, it has the same value for every member in the batch. Memory is only allocated once for the single member. If the network is in explicit batch mode, this function returns true if the leading dimension is 1.

Returns: True if tensor is broadcast across the batch, false otherwise.

See also: setBroadcastAcrossBatch()

◆ getDimensions()

virtual Dims nvinfer1::ITensor::getDimensions ( ) const

pure virtual

Get the dimensions of a tensor.

Returns: The dimensions of the tensor.

Warning: getDimensions() returns a -1 for dimensions that are derived from a wildcard dimension.

See also: setDimensions()

◆ getDynamicRange()

virtual TRT_DEPRECATED float nvinfer1::ITensor::getDynamicRange ( ) const

pure virtual

Get dynamic range for the tensor.

Returns: maximal absolute value of the dynamic range, -1.0f if no dynamic range is set.

Deprecated:: This interface is superceded by getDynamicRangeMin and getDynamicRangeMax.

◆ getDynamicRangeMax()

virtual float nvinfer1::ITensor::getDynamicRangeMax ( ) const

pure virtual

Get maximum of dynamic range.

Returns: Maximum of dynamic range, or quiet NaN if range was not set.

◆ getDynamicRangeMin()

virtual float nvinfer1::ITensor::getDynamicRangeMin ( ) const

pure virtual

Get minimum of dynamic range.

Returns: Minimum of dynamic range, or quiet NaN if range was not set.

◆ getLocation()

virtual TensorLocation nvinfer1::ITensor::getLocation ( ) const

pure virtual

Get the storage location of a tensor.

Returns: The location of tensor data.

See also: setLocation()

◆ getName()

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

pure virtual

Get the tensor name.

Returns: The name, as a pointer to a NULL-terminated character sequence.

See also: setName()

◆ getType()

virtual DataType nvinfer1::ITensor::getType ( ) const

pure virtual

Get the data type of a tensor.

Returns: The data type of the tensor.

See also: setType()

◆ isExecutionTensor()

virtual bool nvinfer1::ITensor::isExecutionTensor ( ) const

pure virtual

Whether the tensor is an execution tensor.

If a tensor is an execution tensor and becomes an engine input or output, then ICudaEngine::isExecutionBinding will be true for that tensor.

Tensors are usually execution tensors. The exceptions are tensors used solely for shape calculations or whose contents not needed to compute the outputs.

A tensor with isShapeTensor() == false and isExecutionTensor() == false can still show up as an input to the engine if its dimensions are required. In that case, only its dimensions need to be set at runtime and a nullptr can be passed instead of a pointer to its contents.

◆ isShapeTensor()

virtual bool nvinfer1::ITensor::isShapeTensor ( ) const

pure virtual

Whether the tensor is a shape tensor.

If a tensor is a shape tensor and becomes an engine input or output, then ICudaEngine::isShapeBinding will be true for that tensor.

It is possible for a tensor to be both a shape tensor and an execution tensor.

Returns: True if tensor is a shape tensor, false otherwise.

◆ setAllowedFormats()

virtual void nvinfer1::ITensor::setAllowedFormats ( TensorFormats formats )

pure virtual

Set allowed formats for this tensor. By default all formats are allowed. Shape tensors (for which isShapeTensor() returns true) may only have row major linear format.

Parameters

formats A bitmask of TensorFormat values that are supported for this tensor.

See also: ITensor::getAllowedFormats()

◆ setBroadcastAcrossBatch()

virtual void nvinfer1::ITensor::setBroadcastAcrossBatch ( bool broadcastAcrossBatch )

pure virtual

Set whether to enable broadcast of tensor across the batch.

When a tensor is broadcast across a batch, it has the same value for every member in the batch. Memory is only allocated once for the single member.

This method is only valid for network input tensors, since the flags of layer output tensors are inferred based on layer inputs and parameters. If this state is modified for a tensor in the network, the states of all dependent tensors will be recomputed. If the tensor is for an explicit batch network, then this function does nothing.

Warning: The broadcast flag is ignored when using explicit batch network mode.

Parameters

broadcastAcrossBatch Whether to enable broadcast of tensor across the batch.

See also: getBroadcastAcrossBatch()

◆ setDimensions()

virtual void nvinfer1::ITensor::setDimensions ( Dims dimensions )

pure virtual

Set the dimensions of a tensor.

For a network input the name is assigned by the application. For a network output it is computed based on the layer parameters and the inputs to the layer. If a tensor size or a parameter is modified in the network, the dimensions of all dependent tensors will be recomputed.

This call is only legal for network input tensors, since the dimensions of layer output tensors are inferred based on layer inputs and parameters.

Parameters

dimensions The dimensions of the tensor.

See also: getDimensions()

◆ setDynamicRange()

virtual bool nvinfer1::ITensor::setDynamicRange	(	float	min,
		float	max
	)

pure virtual

Set dynamic range for the tensor.

Currently, only symmetric ranges are supported. Therefore, the larger of the absolute values of the provided bounds is used.

Returns: Whether the dynamic range was set successfully.

Requires that min and max be finite, and min <= max.

◆ setLocation()

virtual void nvinfer1::ITensor::setLocation ( TensorLocation location )

pure virtual

Set the storage location of a tensor.

Parameters

location the location of tensor data

Only network input tensors for storing sequence lengths for RNNv2 are supported. Using host storage for layers that do not support it will generate errors at build time.

See also: getLocation()

◆ setName()

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

pure virtual

Set the tensor name.

For a network input, the name is assigned by the application. For tensors which are layer outputs, a default name is assigned consisting of the layer name followed by the index of the output in brackets.

This method copies the name string.

Parameters

name The name.

See also: getName()

◆ setType()

virtual void nvinfer1::ITensor::setType ( DataType type )

pure virtual

Set the data type of a tensor.

Parameters

type	The data type of the tensor.

The type is unchanged if the tensor is not a network input tensor, or marked as an output tensor or shape output tensor.

See also: getType()

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

NvInfer.h

Public Member Functions

Detailed Description

Member Function Documentation

◆ dynamicRangeIsSet()

◆ getAllowedFormats()

◆ getBroadcastAcrossBatch()

◆ getDimensions()

◆ getDynamicRange()

◆ getDynamicRangeMax()

◆ getDynamicRangeMin()

◆ getLocation()

◆ getName()

◆ getType()

◆ isExecutionTensor()

◆ isShapeTensor()

◆ setAllowedFormats()

◆ setBroadcastAcrossBatch()

◆ setDimensions()

◆ setDynamicRange()

◆ setLocation()

◆ setName()

◆ setType()