org.bytedeco.tensorrt.nvinfer

Class IPluginV2IOExt

java.lang.Object

org.bytedeco.javacpp.Pointer

org.bytedeco.tensorrt.nvinfer.IPluginV2

org.bytedeco.tensorrt.nvinfer.IPluginV2Ext

org.bytedeco.tensorrt.nvinfer.IPluginV2IOExt

All Implemented Interfaces:

AutoCloseable

@Namespace(value="nvinfer1")
 @Properties(inherit=nvinfer.class)
public class IPluginV2IOExt
extends IPluginV2Ext

\class IPluginV2IOExt \brief Plugin class for user-implemented layers. Plugins are a mechanism for applications to implement custom layers. This interface provides additional capabilities to the IPluginV2Ext interface by extending different I/O data types and tensor formats.

See Also:

IPluginV2Ext

Nested Class Summary

Nested classes/interfaces inherited from class org.bytedeco.javacpp.Pointer

Pointer.CustomDeallocator, Pointer.Deallocator, Pointer.NativeDeallocator, Pointer.ReferenceCounter

Field Summary

Fields inherited from class org.bytedeco.javacpp.Pointer

address, capacity, limit, position

Constructor Summary

Constructors

Constructor and Description
IPluginV2IOExt(Pointer p) Pointer cast constructor.

Method Summary

Modifier and Type	Method and Description
void	configurePlugin(PluginTensorDesc in, int nbInput, PluginTensorDesc out, int nbOutput) \brief Configure the layer.
boolean	supportsFormatCombination(int pos, PluginTensorDesc inOut, int nbInputs, int nbOutputs) \brief Return true if plugin supports the format and datatype for the input/output indexed by pos.

Methods inherited from class org.bytedeco.tensorrt.nvinfer.IPluginV2Ext

attachToContext, canBroadcastInputAcrossBatch, clone, configurePlugin, configurePlugin, configurePlugin, configurePlugin, configurePlugin, configurePlugin, detachFromContext, getOutputDataType, getOutputDataType, getOutputDataType, isOutputBroadcastAcrossBatch, isOutputBroadcastAcrossBatch

Methods inherited from class org.bytedeco.tensorrt.nvinfer.IPluginV2

configureWithFormat, configureWithFormat, destroy, enqueue, enqueue, getNbOutputs, getOutputDimensions, getPluginNamespace, getPluginType, getPluginVersion, getSerializationSize, getTensorRTVersion, getWorkspaceSize, initialize, serialize, setPluginNamespace, setPluginNamespace, supportsFormat, supportsFormat, terminate

Methods inherited from class org.bytedeco.javacpp.Pointer

address, asBuffer, asByteBuffer, availablePhysicalBytes, calloc, capacity, capacity, close, deallocate, deallocate, deallocateReferences, deallocator, deallocator, equals, fill, formatBytes, free, getDirectBufferAddress, getPointer, getPointer, getPointer, getPointer, hashCode, interruptDeallocatorThread, isNull, isNull, limit, limit, malloc, maxBytes, maxPhysicalBytes, memchr, memcmp, memcpy, memmove, memset, offsetAddress, offsetof, offsetof, parseBytes, physicalBytes, physicalBytesInaccurate, position, position, put, realloc, referenceCount, releaseReference, retainReference, setNull, sizeof, sizeof, toString, totalBytes, totalCount, totalPhysicalBytes, withDeallocator, zero

Methods inherited from class java.lang.Object

finalize, getClass, notify, notifyAll, wait, wait, wait

Constructor Detail

IPluginV2IOExt

public IPluginV2IOExt(Pointer p)

Pointer cast constructor. Invokes Pointer(Pointer).

Method Detail

configurePlugin

@NoException(value=true)
public void configurePlugin(@Const
                                                     PluginTensorDesc in,
                                                     int nbInput,
                                                     @Const
                                                     PluginTensorDesc out,
                                                     int nbOutput)

\brief 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 the provided I/O PluginTensorDesc.

Parameters:

in - The input tensors attributes that are used for configuration.

nbInput - Number of input tensors.

out - The output tensors attributes that are used for configuration.

nbOutput - Number of output tensors. \usage - Allowed context for the API call - Thread-safe: Yes, this method is required to be thread-safe and may be called from multiple threads when building networks on multiple devices sharing the same plugin. However, TensorRT will not call this method from two threads simultaneously on a given clone of a plugin.

supportsFormatCombination

@Cast(value="bool")
 @NoException(value=true)
public boolean supportsFormatCombination(int pos,
                                                                                       @Const
                                                                                       PluginTensorDesc inOut,
                                                                                       int nbInputs,
                                                                                       int nbOutputs)

\brief 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. 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. \usage - Allowed context for the API call - Thread-safe: Yes, this method is required to be thread-safe and may be called from multiple threads when building networks on multiple devices sharing the same plugin.