#include <NvInferRuntime.h>

Inheritance diagram for nvinfer1::IPluginV2DynamicExt:

Public Member Functions
IPluginV2DynamicExt *	clone () const _TENSORRT_OVERRIDE=0
	Clone the plugin object. This copies over internal plugin parameters as well and returns a new plugin object with these parameters. If the source plugin is pre-configured with configurePlugin(), the returned object should also be pre-configured. The returned object should allow attachToContext() with a new execution context. Cloned plugin objects can share the same per-engine immutable resource (e.g. weights) with the source object (e.g. via ref-counting) to avoid duplication.

virtual DimsExprs	getOutputDimensions (int outputIndex, const DimsExprs *inputs, int nbInputs, IExprBuilder &exprBuilder)=0
	Get expressions for computing dimensions of an output tensor from dimensions of the input tensors. More...

virtual bool	supportsFormatCombination (int pos, const PluginTensorDesc *inOut, int nbInputs, int nbOutputs)=0
	Return true if plugin supports the format and datatype for the input/output indexed by pos. More...

virtual void	configurePlugin (const DynamicPluginTensorDesc in, int nbInputs, const DynamicPluginTensorDesc out, int nbOutputs)=0
	Configure the layer. More...

virtual size_t	getWorkspaceSize (const PluginTensorDesc inputs, int nbInputs, const PluginTensorDesc outputs, int nbOutputs) const =0
	Find the workspace size required by the layer. More...

virtual int	enqueue (const PluginTensorDesc inputDesc, const PluginTensorDesc outputDesc, const void const inputs, void const outputs, void *workspace, cudaStream_t stream)=0
	Execute the layer. More...

Public Member Functions inherited from nvinfer1::IPluginV2Ext
virtual nvinfer1::DataType	getOutputDataType (int index, const nvinfer1::DataType *inputTypes, int nbInputs) const =0
	Return the DataType of the plugin output at the requested index. The default behavior should be to return the type of the first input, or DataType::kFLOAT if the layer has no inputs. The returned data type must have a format that is supported by the plugin. More...

virtual void	attachToContext (cudnnContext , cublasContext , IGpuAllocator *)
	Attach the plugin object to an execution context and grant the plugin the access to some context resource. More...

virtual void	detachFromContext ()
	Detach the plugin object from its execution context. More...

Public Member Functions inherited from nvinfer1::IPluginV2
virtual const char *	getPluginType () const =0
	Return the plugin type. Should match the plugin name returned by the corresponding plugin creator.

virtual const char *	getPluginVersion () const =0
	Return the plugin version. Should match the plugin version returned by the corresponding plugin creator.

virtual int	getNbOutputs () const =0
	Get the number of outputs from the layer. More...

virtual int	initialize ()=0
	Initialize the layer for execution. This is called when the engine is created. More...

virtual void	terminate ()=0
	Release resources acquired during plugin layer initialization. This is called when the engine is destroyed. More...

virtual size_t	getSerializationSize () const =0
	Find the size of the serialization buffer required. More...

virtual void	serialize (void *buffer) const =0
	Serialize the layer. More...

virtual void	destroy ()=0
	Destroy the plugin object. This will be called when the network, builder or engine is destroyed.

virtual void	setPluginNamespace (const char *pluginNamespace)=0
	Set the namespace that this plugin object belongs to. Ideally, all plugin objects from the same plugin library should have the same namespace.

virtual const char *	getPluginNamespace () const =0
	Return the namespace of the plugin object.

Static Public Attributes
static constexpr int	kFORMAT_COMBINATION_LIMIT = 100

Protected Member Functions
int	getTensorRTVersion () const _TENSORRT_OVERRIDE
	Return the API version with which this plugin was built. More...

TRT_DEPRECATED Dims	getOutputDimensions (int, const Dims *, int) _TENSORRT_FINAL
	Derived classes should not implement this. In a C++11 API it would be override final. More...

TRT_DEPRECATED bool	isOutputBroadcastAcrossBatch (int, const bool *, int) const _TENSORRT_FINAL
	Derived classes should not implement this. In a C++11 API it would be override final. More...

TRT_DEPRECATED bool	canBroadcastInputAcrossBatch (int) const _TENSORRT_FINAL
	Derived classes should not implement this. In a C++11 API it would be override final. More...

TRT_DEPRECATED bool	supportsFormat (DataType, PluginFormat) const _TENSORRT_FINAL
	Derived classes should not implement this. In a C++11 API it would be override final. More...

TRT_DEPRECATED void	configurePlugin (const Dims , int, const Dims , int, const DataType , const DataType , const bool , const bool , PluginFormat, int) _TENSORRT_FINAL
	Derived classes should not implement this. In a C++11 API it would be override final. More...

TRT_DEPRECATED size_t	getWorkspaceSize (int) const _TENSORRT_FINAL
	Derived classes should not implement this. In a C++11 API it would be override final. More...

TRT_DEPRECATED int	enqueue (int, const void const , void *, void , cudaStream_t) _TENSORRT_FINAL
	Derived classes should not implement this. In a C++11 API it would be override final. More...

Protected Member Functions inherited from nvinfer1::IPluginV2Ext
int	getTensorRTVersion () const _TENSORRT_OVERRIDE
	Return the API version with which this plugin was built. The upper byte reserved by TensorRT and is used to differentiate this from IPlguinV2. More...

void	configureWithFormat (const Dims , int, const Dims , int, DataType, PluginFormat, int) _TENSORRT_OVERRIDE
	Derived classes should not implement this. In a C++11 API it would be override final.

Detailed Description

Similar to IPluginV2Ext, but with support for dynamic shapes.

Clients should override the public methods, including the following inherited methods:

virtual int getNbOutputs() const TRTNOEXCEPT = 0;
virtual nvinfer1::DataType getOutputDataType(int index, const nvinfer1::DataType* inputTypes, int nbInputs) const TRTNOEXCEPT = 0;
virtual size_t getSerializationSize() const TRTNOEXCEPT = 0;
virtual void serialize(void* buffer) const TRTNOEXCEPT = 0;
virtual void destroy() TRTNOEXCEPT = 0;
virtual void setPluginNamespace(const char* pluginNamespace) TRTNOEXCEPT = 0;
virtual const char* getPluginNamespace() const TRTNOEXCEPT = 0;

For getOutputDataType, the inputTypes will always be DataType::kFLOAT or DataType::kINT32, and the returned type is canonicalized to DataType::kFLOAT if it is DataType::kHALF or DataType:kINT8. Details about the floating-point precision are elicited later by method supportsFormatCombination.

Member Function Documentation

◆ canBroadcastInputAcrossBatch()

TRT_DEPRECATED bool nvinfer1::IPluginV2DynamicExt::canBroadcastInputAcrossBatch ( int ) const

inlineprotectedvirtual

Derived classes should not implement this. In a C++11 API it would be override final.

With dynamic shapes, there is no implicit batch dimension to broadcast across.

Implements nvinfer1::IPluginV2Ext.

◆ configurePlugin() [1/2]

TRT_DEPRECATED void nvinfer1::IPluginV2DynamicExt::configurePlugin	(	const Dims *	,
		int	,
		const Dims *	,
		int	,
		const DataType *	,
		const DataType *	,
		const bool *	,
		const bool *	,
		PluginFormat	,
		int
	)

inlineprotectedvirtual

Derived classes should not implement this. In a C++11 API it would be override final.

This method is not used because tensors with dynamic shapes do not have an implicit batch dimension, input dimensions might be variable, and outputs might have different floating-point formats..

Instead, derived classes should override the overload of configurePlugin that takes poiners to DynamicPluginTensorDesc.

Implements nvinfer1::IPluginV2Ext.

◆ configurePlugin() [2/2]

virtual void nvinfer1::IPluginV2DynamicExt::configurePlugin	(	const DynamicPluginTensorDesc *	in,
		int	nbInputs,
		const DynamicPluginTensorDesc *	out,
		int	nbOutputs
	)

pure virtual

Configure the layer.

This function is called by the builder prior to initialize(). It provides an opportunity for the layer to make algorithm choices on the basis of bounds on the input and output tensors, and the target value.

This function is also called once when the resource requirements are changed based on the optimization profiles.

Parameters

in	The input tensors attributes that are used for configuration.
nbInputs	Number of input tensors.
out	The output tensors attributes that are used for configuration.
nbOutputs	Number of output tensors.

◆ enqueue() [1/2]

virtual int nvinfer1::IPluginV2DynamicExt::enqueue	(	const PluginTensorDesc *	inputDesc,
		const PluginTensorDesc *	outputDesc,
		const void const	inputs,
		void const	outputs,
		void *	workspace,
		cudaStream_t	stream
	)

pure virtual

Execute the layer.

Parameters

inputDesc	how to interpret the memory for the input tensors.
outputDesc	how to interpret the memory for the output tensors.
inputs	The memory for the input tensors.
outputs	The memory for the output tensors.
workspace	Workspace for execution.
stream	The stream in which to execute the kernels.

Returns: 0 for success, else non-zero (which will cause engine termination).

◆ enqueue() [2/2]

TRT_DEPRECATED int nvinfer1::IPluginV2DynamicExt::enqueue	(	int	,
		const void const	,
		void **	,
		void *	,
		cudaStream_t
	)

inlineprotectedvirtual

Derived classes should not implement this. In a C++11 API it would be override final.

This method is not used because tensors with dynamic shapes can have different sizes in different execution contexts.

Instead, derived classes should override the overload of enqueue that takes pointers to PluginTensorDesc.

Implements nvinfer1::IPluginV2.

◆ getOutputDimensions() [1/2]

virtual DimsExprs nvinfer1::IPluginV2DynamicExt::getOutputDimensions	(	int	outputIndex,
		const DimsExprs *	inputs,
		int	nbInputs,
		IExprBuilder &	exprBuilder
	)

pure virtual

Get expressions for computing dimensions of an output tensor from dimensions of the input tensors.

Parameters

outputIndex	The index of the output tensor
inputs	Expressions for dimensions of the input tensors
nbInputDims	The number of input tensors
exprBuilder	Object for generating new expressions

This function is called by the implementations of IBuilder during analysis of the network.

Example #1: A plugin has a single output that transposes the last two dimensions of the plugin's single input. The body of the override of getOutputDimensions can be:

DimsExprs output(inputs[0]);
std::swap(output.d[output.nbDims-1], output.d[output.nbDims-2]);
return output;

Example #2: A plugin concatenates its two inputs along the first dimension. The body of the override of getOutputDimensions can be:

DimsExprs output(inputs[0]);
output.d[0] = exprBuilder.operation(DimensionOperation::kSUM, inputs[0].d[0], inputs[1].d[0]);
return output;

◆ getOutputDimensions() [2/2]

TRT_DEPRECATED Dims nvinfer1::IPluginV2DynamicExt::getOutputDimensions	(	int	,
		const Dims *	,
		int
	)

inlineprotectedvirtual

Derived classes should not implement this. In a C++11 API it would be override final.

Instead, derived classes should override the overload of getOutputDimensions that returns DimsExprs.

Implements nvinfer1::IPluginV2.

◆ getTensorRTVersion()

int nvinfer1::IPluginV2DynamicExt::getTensorRTVersion ( ) const

inlineprotectedvirtual

Return the API version with which this plugin was built.

Do not override this method as it is used by the TensorRT library to maintain backwards-compatibility with plugins.

Reimplemented from nvinfer1::IPluginV2.

◆ getWorkspaceSize() [1/2]

virtual size_t nvinfer1::IPluginV2DynamicExt::getWorkspaceSize	(	const PluginTensorDesc *	inputs,
		int	nbInputs,
		const PluginTensorDesc *	outputs,
		int	nbOutputs
	)		const

pure virtual

Find the workspace size required by the layer.

This function is called after the plugin is configured, and possibly during execution. The result should be a sufficient workspace size to deal with inputs and outputs of the given size or any smaller problem.

Returns: The workspace size.

◆ getWorkspaceSize() [2/2]

TRT_DEPRECATED size_t nvinfer1::IPluginV2DynamicExt::getWorkspaceSize ( int ) const

inlineprotectedvirtual

Derived classes should not implement this. In a C++11 API it would be override final.

This method is not used because tensors with dynamic shapes do not have an implicit batch dimension, and the other dimensions might not be build-time constants.

Instead, derived classes should override the overload of getWorkspaceSize that takes pointers to PluginTensorDesc. The arguments to that overload provide maximum bounds on all dimensions.

Implements nvinfer1::IPluginV2.

◆ isOutputBroadcastAcrossBatch()

TRT_DEPRECATED bool nvinfer1::IPluginV2DynamicExt::isOutputBroadcastAcrossBatch	(	int	,
		const bool *	,
		int
	)		const

inlineprotectedvirtual

Derived classes should not implement this. In a C++11 API it would be override final.

With dynamic shapes, there is no implicit batch dimension to broadcast across.

Implements nvinfer1::IPluginV2Ext.

◆ supportsFormat()

TRT_DEPRECATED bool nvinfer1::IPluginV2DynamicExt::supportsFormat	(	DataType	,
		PluginFormat
	)		const

inlineprotectedvirtual

Derived classes should not implement this. In a C++11 API it would be override final.

This method is not used because it does not allow a plugin to specify mixed formats.

Instead, derived classes should override supportsFormatCombination, which allows plugins to express mixed formats.

Implements nvinfer1::IPluginV2.

◆ supportsFormatCombination()

virtual bool nvinfer1::IPluginV2DynamicExt::supportsFormatCombination	(	int	pos,
		const PluginTensorDesc *	inOut,
		int	nbInputs,
		int	nbOutputs
	)

pure virtual

Return true if plugin supports the format and datatype for the input/output indexed by pos.

For this method inputs are numbered 0..(nbInputs-1) and outputs are numbered nbInputs..(nbInputs+nbOutputs-1). Using this numbering, pos is an index into InOut, where 0 <= pos < nbInputs+nbOutputs-1.

TensorRT invokes this method to ask if the input/output indexed by pos supports the format/datatype specified by inOut[pos].format and inOut[pos].type. The override should return true if that format/datatype at inOut[pos] are supported by the plugin. If support is conditional on other input/output formats/datatypes, the plugin can make its result conditional on the formats/datatypes in inOut[0..pos-1], which will be set to values that the plugin supports. The override should not inspect inOut[pos+1..nbInputs+nbOutputs-1], which will have invalid values. In other words, the decision for pos must be based on inOut[0..pos] only.

Some examples:

A definition for a plugin that supports only FP16 NCHW:

  return inOut.format[pos] == TensorFormat::kLINEAR && inOut.type[pos] == DataType::kHALF;

A definition for a plugin that supports only FP16 NCHW for its two inputs, and FP32 NCHW for its single output:

  return inOut.format[pos] == TensorFormat::kLINEAR && (inOut.type[pos] == pos < 2 ?  DataType::kHALF : DataType::kFLOAT);

A definition for a "polymorphic" plugin with two inputs and one output that supports any format or type, but the inputs and output must have the same format and type:
```
  return pos == 0 || (inOut.format[pos] == inOut.format[0] && inOut.type[pos] == inOut.type[0]);
```

Warning: TensorRT will stop asking for formats once it finds kFORMAT_COMBINATION_LIMIT on combinations.

Member Data Documentation

◆ kFORMAT_COMBINATION_LIMIT

constexpr int nvinfer1::IPluginV2DynamicExt::kFORMAT_COMBINATION_LIMIT = 100

staticconstexpr

Limit on number of format combinations accepted.

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

NvInferRuntime.h

Public Member Functions

Static Public Attributes

Protected Member Functions

Detailed Description

Member Function Documentation

◆ canBroadcastInputAcrossBatch()

◆ configurePlugin() [1/2]

◆ configurePlugin() [2/2]

◆ enqueue() [1/2]

◆ enqueue() [2/2]

◆ getOutputDimensions() [1/2]

◆ getOutputDimensions() [2/2]

◆ getTensorRTVersion()

◆ getWorkspaceSize() [1/2]

◆ getWorkspaceSize() [2/2]

◆ isOutputBroadcastAcrossBatch()

◆ supportsFormat()

◆ supportsFormatCombination()

Member Data Documentation

◆ kFORMAT_COMBINATION_LIMIT