Layer type for shuffling data. More...

Inheritance diagram for nvinfer1::IShuffleLayer:

Collaboration diagram for nvinfer1::IShuffleLayer:

Public Member Functions
virtual void	setFirstTranspose (Permutation permutation)=0
	Set the permutation applied by the first transpose operation. More...

virtual Permutation	getFirstTranspose () const =0
	Get the permutation applied by the first transpose operation. More...

virtual void	setReshapeDimensions (Dims dimensions)=0
	Set the reshaped dimensions. More...

virtual Dims	getReshapeDimensions () const =0
	Get the reshaped dimensions. More...

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

virtual void	setSecondTranspose (Permutation permutation)=0
	Set the permutation applied by the second transpose operation. More...

virtual Permutation	getSecondTranspose () const =0
	Get the permutation applied by the second transpose operation. More...

virtual void	setZeroIsPlaceholder (bool zeroIsPlaceholder)=0
	Set meaning of 0 in reshape dimensions. More...

virtual bool	getZeroIsPlaceholder () const =0
	Get meaning of 0 in reshape dimensions. 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	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	~IShuffleLayer ()

Detailed Description

Layer type for shuffling data.

This class shuffles data by applying in sequence: a transpose operation, a reshape operation and a second transpose operation. The dimension types of the output are those of the reshape dimension.

The layer has an optional second input. If present, it must be a 1D Int32 shape tensor, and the reshape dimensions are taken from it.

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

Constructor & Destructor Documentation

◆ ~IShuffleLayer()

virtual nvinfer1::IShuffleLayer::~IShuffleLayer ( )

inlineprotectedvirtual

Member Function Documentation

◆ setFirstTranspose()

virtual void nvinfer1::IShuffleLayer::setFirstTranspose ( Permutation permutation )

pure virtual

Set the permutation applied by the first transpose operation.

Parameters

permutation The dimension permutation applied before the reshape.

The default is the identity permutation.

See also: getFirstTranspose

◆ getFirstTranspose()

virtual Permutation nvinfer1::IShuffleLayer::getFirstTranspose ( ) const

pure virtual

Get the permutation applied by the first transpose operation.

Returns: The dimension permutation applied before the reshape.

See also: setFirstTranspose

◆ setReshapeDimensions()

virtual void nvinfer1::IShuffleLayer::setReshapeDimensions ( Dims dimensions )

pure virtual

Set the reshaped dimensions.

Parameters

dimensions The reshaped dimensions.

Two special values can be used as dimensions.

Value 0 copies the corresponding dimension from input. This special value can be used more than once in the dimensions. If number of reshape dimensions is less than input, 0s are resolved by aligning the most significant dimensions of input.

Value -1 infers that particular dimension by looking at input and rest of the reshape dimensions. Note that only a maximum of one dimension is permitted to be specified as -1.

The product of the new dimensions must be equal to the product of the old.

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

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◆ getReshapeDimensions()

virtual Dims nvinfer1::IShuffleLayer::getReshapeDimensions ( ) const

pure virtual

Get the reshaped dimensions.

Returns: The reshaped dimensions.

If a second input is present and non-null, or setReshapeDimensions has not yet been called, this function returns Dims with nbDims == -1.

◆ setInput()

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

pure virtual

Append or replace an input of this layer with a specific tensor.

Parameters

index	the index of the input to modify.
tensor	the new input tensor Sets the input tensor for the given index. The index must be 0 for a static shuffle layer. A static shuffle layer is converted to a dynamic shuffle layer by calling setInput with an index 1. A dynamic shuffle layer cannot be converted back to a static shuffle layer.

For a dynamic shuffle layer, the values 0 and 1 are valid. The indices in the dynamic case are as follows:

0: Data or Shape tensor to be shuffled.
1: The dimensions for the reshape operation, as a 1D Int32 shape tensor.

If this function is called with a value 1, then the function getNbInputs() changes from returning 1 to 2.

Implements nvinfer1::ILayer.

◆ setSecondTranspose()

virtual void nvinfer1::IShuffleLayer::setSecondTranspose ( Permutation permutation )

pure virtual

Set the permutation applied by the second transpose operation.

Parameters

permutation The dimension permutation applied after the reshape.

The default is the identity permutation.

The permutation is applied as outputDimensionIndex = permutation.order[inputDimensionIndex], so to permute from CHW order to HWC order, the required permutation is [1, 2, 0].

See also: getSecondTranspose

◆ getSecondTranspose()

virtual Permutation nvinfer1::IShuffleLayer::getSecondTranspose ( ) const

pure virtual

Get the permutation applied by the second transpose operation.

Returns: The dimension permutation applied after the reshape.

See also: setSecondTranspose

◆ setZeroIsPlaceholder()

virtual void nvinfer1::IShuffleLayer::setZeroIsPlaceholder ( bool zeroIsPlaceholder )

pure virtual

Set meaning of 0 in reshape dimensions.

If true, then a 0 in the reshape dimensions denotes copying the corresponding dimension from the first input tensor. If false, then a 0 in the reshape dimensions denotes a zero-length dimension.

Default: true

See also: getZeroIsPlaceholder();

◆ getZeroIsPlaceholder()

virtual bool nvinfer1::IShuffleLayer::getZeroIsPlaceholder ( ) const

pure virtual

Get meaning of 0 in reshape dimensions.

Returns: true if 0 is placeholder for corresponding input dimension, false if 0 denotes a zero-length dimension.

See also: setZeroIsPlaceholder

◆ 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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◆ 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

◆ ~IShuffleLayer()

Member Function Documentation

◆ setFirstTranspose()

◆ getFirstTranspose()

◆ setReshapeDimensions()

◆ getReshapeDimensions()

◆ setInput()

◆ setSecondTranspose()

◆ getSecondTranspose()

◆ setZeroIsPlaceholder()

◆ getZeroIsPlaceholder()

◆ getType()

◆ setName()

◆ getName()

◆ getNbInputs()

◆ getInput()

◆ getNbOutputs()

◆ getOutput()

◆ setPrecision()

◆ getPrecision()

◆ precisionIsSet()

◆ resetPrecision()

◆ setOutputType()

◆ getOutputType()

◆ outputTypeIsSet()

◆ resetOutputType()