Inheritance diagram for nvinfer1::plugin::ResizeNearest:

Collaboration diagram for nvinfer1::plugin::ResizeNearest:

[legend]

Public Member Functions
	ResizeNearest (float scale)

	ResizeNearest (const void *data, size_t length)

	~ResizeNearest () override=default

int	getNbOutputs () const override
	Get the number of outputs from the layer. More...

Dims	getOutputDimensions (int index, const Dims *inputs, int nbInputDims) override

int	initialize () override
	Initialize the layer for execution. More...

void	terminate () override
	Release resources acquired during plugin layer initialization. More...

void	destroy () override
	Destroy the plugin object. More...

size_t	getWorkspaceSize (int) const override

int	enqueue (int batch_size, const void const inputs, void *outputs, void workspace, cudaStream_t stream) override

size_t	getSerializationSize () const override
	Find the size of the serialization buffer required. More...

void	serialize (void *buffer) const override
	Serialize the layer. More...

bool	supportsFormat (DataType type, PluginFormat format) const override
	Check format support. More...

const char *	getPluginType () const override
	Return the plugin type. More...

const char *	getPluginVersion () const override
	Return the plugin version. More...

IPluginV2Ext *	clone () const override
	Clone the plugin object. More...

void	setPluginNamespace (const char *libNamespace) override
	Set the namespace that this plugin object belongs to. More...

const char *	getPluginNamespace () const override
	Return the namespace of the plugin object. More...

DataType	getOutputDataType (int index, const nvinfer1::DataType *inputTypes, int nbInputs) const override

bool	isOutputBroadcastAcrossBatch (int outputIndex, const bool *inputIsBroadcasted, int nbInputs) const override

bool	canBroadcastInputAcrossBatch (int inputIndex) const override

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

void	configurePlugin (const Dims inputDims, int nbInputs, const Dims outputDims, int nbOutputs, const DataType inputTypes, const DataType outputTypes, const bool inputIsBroadcast, const bool outputIsBroadcast, PluginFormat floatFormat, int maxBatchSize) override

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

virtual nvinfer1::DataType	getOutputDataType (int32_t index, const nvinfer1::DataType *inputTypes, int32_t nbInputs) const =0
	Return the DataType of the plugin output at the requested index. More...

virtual bool	isOutputBroadcastAcrossBatch (int32_t outputIndex, const bool *inputIsBroadcasted, int32_t nbInputs) const =0
	Return true if output tensor is broadcast across a batch. More...

virtual bool	canBroadcastInputAcrossBatch (int32_t inputIndex) const =0
	Return true if plugin can use input that is broadcast across batch without replication. More...

virtual void	configurePlugin (const Dims inputDims, int32_t nbInputs, const Dims outputDims, int32_t nbOutputs, const DataType inputTypes, const DataType outputTypes, const bool inputIsBroadcast, const bool outputIsBroadcast, PluginFormat floatFormat, int32_t maxBatchSize)=0
	Configure the layer with input and output data types. More...

virtual Dims	getOutputDimensions (int32_t index, const Dims *inputs, int32_t nbInputDims)=0
	Get the dimension of an output tensor. More...

virtual size_t	getWorkspaceSize (int32_t maxBatchSize) const =0
	Find the workspace size required by the layer. More...

virtual int32_t	enqueue (int32_t batchSize, const void const inputs, void *outputs, void workspace, cudaStream_t stream)=0
	Execute the layer. More...

Protected Member Functions
int32_t	getTensorRTVersion () const
	Return the API version with which this plugin was built. More...

void	configureWithFormat (const Dims , int32_t, const Dims , int32_t, DataType, PluginFormat, int32_t)
	Derived classes should not implement this. More...

Private Attributes
float	mScale

Dims	mInputDims

Dims	mOutputDims

std::string	mNameSpace

Constructor & Destructor Documentation

◆ ResizeNearest() [1/2]

ResizeNearest::ResizeNearest ( float scale )

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◆ ResizeNearest() [2/2]

ResizeNearest::ResizeNearest	(	const void *	data,
		size_t	length
	)

◆ ~ResizeNearest()

nvinfer1::plugin::ResizeNearest::~ResizeNearest ( )

overridedefault

Member Function Documentation

◆ getNbOutputs()

int ResizeNearest::getNbOutputs ( ) const

overridevirtual

Get the number of outputs from the layer.

Returns: The number of outputs.

This function is called by the implementations of INetworkDefinition and IBuilder. In particular, it is called prior to any call to initialize().

Implements nvinfer1::IPluginV2.

◆ getOutputDimensions() [1/2]

Dims ResizeNearest::getOutputDimensions	(	int	index,
		const Dims *	inputs,
		int	nbInputDims
	)

override

◆ initialize()

int ResizeNearest::initialize ( )

overridevirtual

Initialize the layer for execution.

This is called when the engine is created.

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

Implements nvinfer1::IPluginV2.

◆ terminate()

void ResizeNearest::terminate ( )

overridevirtual

Release resources acquired during plugin layer initialization.

This is called when the engine is destroyed.

See also: initialize()

Implements nvinfer1::IPluginV2.

◆ destroy()

void ResizeNearest::destroy ( )

overridevirtual

Destroy the plugin object.

This will be called when the network, builder or engine is destroyed.

Implements nvinfer1::IPluginV2.

◆ getWorkspaceSize() [1/2]

size_t ResizeNearest::getWorkspaceSize ( int ) const

override

◆ enqueue() [1/2]

int ResizeNearest::enqueue	(	int	batch_size,
		const void const	inputs,
		void **	outputs,
		void *	workspace,
		cudaStream_t	stream
	)

override

◆ getSerializationSize()

size_t ResizeNearest::getSerializationSize ( ) const

overridevirtual

Find the size of the serialization buffer required.

Returns: The size of the serialization buffer.

Implements nvinfer1::IPluginV2.

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◆ serialize()

void ResizeNearest::serialize ( void * buffer ) const

overridevirtual

Serialize the layer.

Parameters

buffer A pointer to a buffer to serialize data. Size of buffer must be equal to value returned by getSerializationSize.

See also: getSerializationSize()

Implements nvinfer1::IPluginV2.

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◆ supportsFormat()

bool ResizeNearest::supportsFormat	(	DataType	type,
		PluginFormat	format
	)		const

overridevirtual

Check format support.

Parameters

type	DataType requested.
format	PluginFormat requested.

Returns: true if the plugin supports the type-format combination.

This function is called by the implementations of INetworkDefinition, IBuilder, and safe::ICudaEngine/ICudaEngine. In particular, it is called when creating an engine and when deserializing an engine.

Warning: for the format field, the values PluginFormat::kCHW4, PluginFormat::kCHW16, and PluginFormat::kCHW32 will not be passed in, this is to keep backward compatibility with TensorRT 5.x series. Use PluginV2IOExt or PluginV2DynamicExt for other PluginFormats.; DataType:kBOOL not supported.

Implements nvinfer1::IPluginV2.

◆ getPluginType()

const char * ResizeNearest::getPluginType ( ) const

overridevirtual

Return the plugin type.

Should match the plugin name returned by the corresponding plugin creator

See also: IPluginCreator::getPluginName()

Implements nvinfer1::IPluginV2.

◆ getPluginVersion()

const char * ResizeNearest::getPluginVersion ( ) const

overridevirtual

Return the plugin version.

Should match the plugin version returned by the corresponding plugin creator

See also: IPluginCreator::getPluginVersion()

Implements nvinfer1::IPluginV2.

◆ clone()

IPluginV2Ext * ResizeNearest::clone ( ) const

overridevirtual

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.

Implements nvinfer1::IPluginV2Ext.

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◆ setPluginNamespace()

void ResizeNearest::setPluginNamespace ( const char * pluginNamespace )

overridevirtual

Set the namespace that this plugin object belongs to.

Ideally, all plugin objects from the same plugin library should have the same namespace.

Implements nvinfer1::IPluginV2.

◆ getPluginNamespace()

const char * ResizeNearest::getPluginNamespace ( ) const

overridevirtual

Return the namespace of the plugin object.

Implements nvinfer1::IPluginV2.

◆ getOutputDataType() [1/2]

DataType ResizeNearest::getOutputDataType	(	int	index,
		const nvinfer1::DataType *	inputTypes,
		int	nbInputs
	)		const

override

◆ isOutputBroadcastAcrossBatch() [1/2]

bool ResizeNearest::isOutputBroadcastAcrossBatch	(	int	outputIndex,
		const bool *	inputIsBroadcasted,
		int	nbInputs
	)		const

override

◆ canBroadcastInputAcrossBatch() [1/2]

bool ResizeNearest::canBroadcastInputAcrossBatch ( int inputIndex ) const

override

◆ attachToContext()

void ResizeNearest::attachToContext	(	cudnnContext *	,
		cublasContext *	,
		IGpuAllocator *
	)

overridevirtual

Attach the plugin object to an execution context and grant the plugin the access to some context resource.

Parameters

cudnn	The cudnn context handle of the execution context
cublas	The cublas context handle of the execution context
allocator	The allocator used by the execution context

This function is called automatically for each plugin when a new execution context is created. If the plugin needs per-context resource, it can be allocated here. The plugin can also get context-owned CUDNN and CUBLAS context here.

Reimplemented from nvinfer1::IPluginV2Ext.

◆ configurePlugin() [1/2]

void ResizeNearest::configurePlugin	(	const Dims *	inputDims,
		int	nbInputs,
		const Dims *	outputDims,
		int	nbOutputs,
		const DataType *	inputTypes,
		const DataType *	outputTypes,
		const bool *	inputIsBroadcast,
		const bool *	outputIsBroadcast,
		PluginFormat	floatFormat,
		int	maxBatchSize
	)

override

◆ detachFromContext()

void ResizeNearest::detachFromContext ( )

overridevirtual

Detach the plugin object from its execution context.

This function is called automatically for each plugin when a execution context is destroyed. If the plugin owns per-context resource, it can be released here.

Reimplemented from nvinfer1::IPluginV2Ext.

◆ getOutputDataType() [2/2]

virtual nvinfer1::DataType nvinfer1::IPluginV2Ext::getOutputDataType	(	int32_t	index,
		const nvinfer1::DataType *	inputTypes,
		int32_t	nbInputs
	)		const

pure virtualinherited

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.

See also: supportsFormat()

Warning: DataType:kBOOL not supported.

◆ isOutputBroadcastAcrossBatch() [2/2]

virtual bool nvinfer1::IPluginV2Ext::isOutputBroadcastAcrossBatch	(	int32_t	outputIndex,
		const bool *	inputIsBroadcasted,
		int32_t	nbInputs
	)		const

pure virtualinherited

Return true if output tensor is broadcast across a batch.

Parameters

outputIndex	The index of the output
inputIsBroadcasted	The ith element is true if the tensor for the ith input is broadcast across a batch.
nbInputs	The number of inputs

The values in inputIsBroadcasted refer to broadcasting at the semantic level, i.e. are unaffected by whether method canBroadcastInputAcrossBatch requests physical replication of the values.

◆ canBroadcastInputAcrossBatch() [2/2]

virtual bool nvinfer1::IPluginV2Ext::canBroadcastInputAcrossBatch ( int32_t inputIndex ) const

pure virtualinherited

Return true if plugin can use input that is broadcast across batch without replication.

Parameters

inputIndex Index of input that could be broadcast.

For each input whose tensor is semantically broadcast across a batch, TensorRT calls this method before calling configurePlugin. If canBroadcastInputAcrossBatch returns true, TensorRT will not replicate the input tensor; i.e., there will be a single copy that the plugin should share across the batch. If it returns false, TensorRT will replicate the input tensor so that it appears like a non-broadcasted tensor.

This method is called only for inputs that can be broadcast.

◆ configurePlugin() [2/2]

virtual void nvinfer1::IPluginV2Ext::configurePlugin	(	const Dims *	inputDims,
		int32_t	nbInputs,
		const Dims *	outputDims,
		int32_t	nbOutputs,
		const DataType *	inputTypes,
		const DataType *	outputTypes,
		const bool *	inputIsBroadcast,
		const bool *	outputIsBroadcast,
		PluginFormat	floatFormat,
		int32_t	maxBatchSize
	)

pure virtualinherited

Configure the layer with input and output data types.

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 its weights, dimensions, data types and maximum batch size.

Parameters

inputDims	The input tensor dimensions.
nbInputs	The number of inputs.
outputDims	The output tensor dimensions.
nbOutputs	The number of outputs.
inputTypes	The data types selected for the plugin inputs.
outputTypes	The data types selected for the plugin outputs.
inputIsBroadcast	True for each input that the plugin must broadcast across the batch.
outputIsBroadcast	True for each output that TensorRT will broadcast across the batch.
floatFormat	The format selected for the engine for the floating point inputs/outputs.
maxBatchSize	The maximum batch size.

The dimensions passed here do not include the outermost batch size (i.e. for 2-D image networks, they will be 3-dimensional CHW dimensions). When inputIsBroadcast or outputIsBroadcast is true, the outermost batch size for that input or output should be treated as if it is one. inputIsBroadcast[i] is true only if the input is semantically broadcast across the batch and canBroadcastInputAcrossBatch(i) returned true. outputIsBroadcast[i] is true only if isOutputBroadcastAcrossBatch(i) returned true.

Warning: for the floatFormat field, the values PluginFormat::kCHW4, PluginFormat::kCHW16, and PluginFormat::kCHW32 will not be passed in, this is to keep backward compatibility with TensorRT 5.x series. Use PluginV2IOExt or PluginV2DynamicExt for other PluginFormats.

◆ getTensorRTVersion()

int32_t nvinfer1::IPluginV2Ext::getTensorRTVersion ( ) const

inlineprotectedvirtualinherited

Return the API version with which this plugin was built.

The upper byte reserved by TensorRT and is used to differentiate this from IPlguinV2.

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

Reimplemented from nvinfer1::IPluginV2.

◆ configureWithFormat()

void nvinfer1::IPluginV2Ext::configureWithFormat	(	const Dims *	,
		int32_t	,
		const Dims *	,
		int32_t	,
		DataType	,
		PluginFormat	,
		int32_t
	)

inlineprotectedvirtualinherited

Derived classes should not implement this.

In a C++11 API it would be override final.

Implements nvinfer1::IPluginV2.

◆ getOutputDimensions() [2/2]

virtual Dims nvinfer1::IPluginV2::getOutputDimensions	(	int32_t	index,
		const Dims *	inputs,
		int32_t	nbInputDims
	)

pure virtualinherited

Get the dimension of an output tensor.

Parameters

index	The index of the output tensor.
inputs	The input tensors.
nbInputDims	The number of input tensors.

This function is called by the implementations of INetworkDefinition and IBuilder. In particular, it is called prior to any call to initialize().

◆ getWorkspaceSize() [2/2]

virtual size_t nvinfer1::IPluginV2::getWorkspaceSize ( int32_t maxBatchSize ) const

pure virtualinherited

Find the workspace size required by the layer.

This function is called during engine startup, after initialize(). The workspace size returned should be sufficient for any batch size up to the maximum.

Returns: The workspace size.

◆ enqueue() [2/2]

virtual int32_t nvinfer1::IPluginV2::enqueue	(	int32_t	batchSize,
		const void const	inputs,
		void **	outputs,
		void *	workspace,
		cudaStream_t	stream
	)

pure virtualinherited

Execute the layer.

Parameters

batchSize	The number of inputs in the batch.
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).

Member Data Documentation

◆ mScale

float nvinfer1::plugin::ResizeNearest::mScale

private

◆ mInputDims

Dims nvinfer1::plugin::ResizeNearest::mInputDims

private

◆ mOutputDims

Dims nvinfer1::plugin::ResizeNearest::mOutputDims

private

◆ mNameSpace

std::string nvinfer1::plugin::ResizeNearest::mNameSpace

private

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

resizeNearestPlugin.h
resizeNearestPlugin.cpp

Public Member Functions

Protected Member Functions

Private Attributes

Constructor & Destructor Documentation

◆ ResizeNearest() [1/2]

◆ ResizeNearest() [2/2]

◆ ~ResizeNearest()

Member Function Documentation

◆ getNbOutputs()

◆ getOutputDimensions() [1/2]

◆ initialize()

◆ terminate()

◆ destroy()

◆ getWorkspaceSize() [1/2]

◆ enqueue() [1/2]

◆ getSerializationSize()

◆ serialize()

◆ supportsFormat()

◆ getPluginType()

◆ getPluginVersion()

◆ clone()

◆ setPluginNamespace()

◆ getPluginNamespace()

◆ getOutputDataType() [1/2]

◆ isOutputBroadcastAcrossBatch() [1/2]

◆ canBroadcastInputAcrossBatch() [1/2]

◆ attachToContext()

◆ configurePlugin() [1/2]

◆ detachFromContext()

◆ getOutputDataType() [2/2]

◆ isOutputBroadcastAcrossBatch() [2/2]

◆ canBroadcastInputAcrossBatch() [2/2]

◆ configurePlugin() [2/2]

◆ getTensorRTVersion()

◆ configureWithFormat()

◆ getOutputDimensions() [2/2]

◆ getWorkspaceSize() [2/2]

◆ enqueue() [2/2]

Member Data Documentation

◆ mScale

◆ mInputDims

◆ mOutputDims

◆ mNameSpace