NVIDIA NvNeural SDK  2022.2
GPU inference framework for NVIDIA Nsight Deep Learning Designer
nvneural::INetworkReshapeDebugger Class Referenceabstract

INetworkReshapeDebugger defines a callback interface for reshape operations. More...

#include <nvneural/NetworkTypes.h>

Inheritance diagram for nvneural::INetworkReshapeDebugger:
nvneural::IRefObject

Public Member Functions

virtual NeuralResult beginReshapeLayer (ILayer *pLayer) noexcept=0
 Callback emitted when a layer is about to reshape. More...
 
virtual NeuralResult endReshapeLayer (ILayer *pLayer, NeuralResult reshapeStatus) noexcept=0
 Callback emitted when a layer is finished reshaping. More...
 
- Public Member Functions inherited from nvneural::IRefObject
virtual RefCount addRef () const noexcept=0
 Increments the object's reference count. More...
 
virtual const void * queryInterface (TypeId interface) const noexcept=0
 This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.
 
virtual void * queryInterface (TypeId interface) noexcept=0
 Retrieves a new object interface pointer. More...
 
virtual RefCount release () const noexcept=0
 Decrements the object's reference count and destroy the object if the reference count reaches zero. More...
 

Static Public Attributes

static const IRefObject::TypeId typeID = 0x6e2cb6b746e5f2dul
 Interface TypeId for InterfaceOf purposes.
 
- Static Public Attributes inherited from nvneural::IRefObject
static const TypeId typeID = 0x14ecc3f9de638e1dul
 Interface TypeId for InterfaceOf purposes.
 

Additional Inherited Members

- Public Types inherited from nvneural::IRefObject
using RefCount = std::uint32_t
 Typedef used to track the number of active references to an object.
 
using TypeId = std::uint64_t
 Every interface must define a unique TypeId. This should be randomized.
 
- Protected Member Functions inherited from nvneural::IRefObject
virtual ~IRefObject ()=default
 A protected destructor prevents accidental stack-allocation of IRefObjects or use with other smart pointer classes like std::unique_ptr.
 

Detailed Description

INetworkReshapeDebugger defines a callback interface for reshape operations.

If attached to a network, the network will issue callbacks during reshape. Tools can use this information to attribute log messages to the individual layers being reshaped with a higher degree of accuracy than simple convention (e.g., schemes like "%s: message".arg(name())).

Member Function Documentation

◆ beginReshapeLayer()

virtual NeuralResult nvneural::INetworkReshapeDebugger::beginReshapeLayer ( ILayer pLayer)
pure virtualnoexcept

Callback emitted when a layer is about to reshape.

Parameters
pLayerLayer to be reshaped.
Returns
Success; any other return code aborts reshape immediately with that return value.

◆ endReshapeLayer()

virtual NeuralResult nvneural::INetworkReshapeDebugger::endReshapeLayer ( ILayer pLayer,
NeuralResult  reshapeStatus 
)
pure virtualnoexcept

Callback emitted when a layer is finished reshaping.

Parameters
pLayerLayer that was reshaped.
reshapeStatusReturn code from the layer's reshape operation.
Returns
Success; any other return code aborts reshape immediately with that return value.

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