Generate an output tensor with specified mode. More...

#include <NvInfer.h>

Inheritance diagram for nvinfer1::IFillLayer:

Public Member Functions
virtual void	setDimensions (Dims dimensions) noexcept=0
	Set the output tensor's dimensions. More...

virtual Dims	getDimensions () const noexcept=0
	Get the output tensor's dimensions. More...

virtual void	setOperation (FillOperation op) noexcept=0
	Set the fill operation for the layer. More...

virtual FillOperation	getOperation () const noexcept=0
	Get the fill operation for the layer. More...

virtual void	setAlpha (double alpha) noexcept=0
	Set the alpha parameter. More...

virtual double	getAlpha () const noexcept=0
	Get the value of alpha parameter. More...

virtual void	setBeta (double beta) noexcept=0
	Set the beta parameter. More...

virtual double	getBeta () const noexcept=0
	Get the value of beta parameter. More...

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

Public Member Functions inherited from nvinfer1::ILayer
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.

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.

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

Detailed Description

Generate an output tensor with specified mode.

The fill layer has two variants, static and dynamic. Static fill specifies its parameters at layer creation time via Dims and the get/set accessor functions of the IFillLayer. Dynamic fill specifies one or more of its parameters as ITensors, by using ILayer::setTensor to add a corresponding input. The corresponding static parameter is used if an input is missing or null.

The shape of the output is specified by the parameter Dimension, or if non-null and present, the first input, which must be a 1D Int32 shape tensor. Thus an application can determine if the IFillLayer has a dynamic output shape based on whether it has a non-null first input.

Alpha and Beta are treated differently based on the Fill Operation specified. See details in IFillLayer::setAlpha(), IFillLayer::setBeta(), and IFillLayer::setInput().

See also: FillOperation

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

Member Function Documentation

◆ getAlpha()

virtual double nvinfer1::IFillLayer::getAlpha ( ) const

pure virtualnoexcept

Get the value of alpha parameter.

Returns: A double value of alpha.

If the second input is present and non-null, this function returns a Dims with nbDims = -1.

See also: setAlpha

◆ getBeta()

virtual double nvinfer1::IFillLayer::getBeta ( ) const

pure virtualnoexcept

Get the value of beta parameter.

Returns: A double value of beta.

If the third input is present and non-null, this function returns a Dims with nbDims = -1.

See also: setBeta

◆ getDimensions()

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

pure virtualnoexcept

Get the output tensor's dimensions.

Returns: The output tensor's dimensions, or an invalid Dims structure.

If the first input is present and non-null, this function returns a Dims with nbDims = -1.

See also: setDimensions

◆ getOperation()

virtual FillOperation nvinfer1::IFillLayer::getOperation ( ) const

pure virtualnoexcept

Get the fill operation for the layer.

See also: setOperation(), FillOperation

◆ setAlpha()

virtual void nvinfer1::IFillLayer::setAlpha ( double alpha )

pure virtualnoexcept

Set the alpha parameter.

Parameters

alpha has different meanings for each operator:

Operation | Usage kLINSPACE | the start value; kRANDOMUNIFORM | the minimum value;

If the second input is set, it is reset to null.

See also: getAlpha

◆ setBeta()

virtual void nvinfer1::IFillLayer::setBeta ( double beta )

pure virtualnoexcept

Set the beta parameter.

Parameters

beta	has different meanings for each operator:

Operation | Usage kLINSPACE | the delta value; kRANDOMUNIFORM | the maximal value;

If the third input is set, it is reset to null.

See also: getBeta

◆ setDimensions()

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

pure virtualnoexcept

Set the output tensor's dimensions.

Parameters

dimensions The output tensor's dimensions.

If the first input is set, it is reset to null.

See also: getDimensions

◆ setInput()

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

pure virtual

replace an input of this layer with a specific tensor.

Parameters

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

Indices for kLINSPACE are described as:

0: Shape tensor, represents the output tensor's dimensions.
1: Start, a scalar, represents the start value.
2: Delta, a 1D tensor, length equals to shape tensor's nbDims, represents the delta value for each dimension.

Indices for kRANDOM_UNIFORM are described as:

0: Shape tensor, represents the output tensor's dimensions.
1: Minimum, a scalar, represents the minimum random value.
2: Maximum, a scalar, represents the maximal random value.

Using the corresponding setter resets the input to null.

If either inputs 1 or 2, is non-null, then both must be non-null and have the same data type.

If this function is called for an index greater or equal to getNbInputs(), then afterwards getNbInputs() returns index + 1, and any missing intervening inputs are set to null.

Implements nvinfer1::ILayer.