SmartEngine  1.6.0
Classes | Public Member Functions | List of all members
SmartEngine.NeuralNetworks.Loss Class Reference

The loss of a NeuralNetwork is computed using the formula (Expected Ouput - Actual Output)^2 The mean of all these values across the output tensor is used when crunching down the loss to a single value. More...

Inheritance diagram for SmartEngine.NeuralNetworks.Loss:
SmartEngine.NeuralNetworks.GraphNode SmartEngine.Object SmartEngine.Disposable

Classes

class  CInfo
 Loss constructor info More...
 

Public Member Functions

 Loss (CInfo cinfo)
 
float GetLoss ()
 Returns the mean L2 loss using the current network and expected state More...
 
- Public Member Functions inherited from SmartEngine.NeuralNetworks.GraphNode
Matrix Execute ()
 Synchronously execute the graph. The returned matrix is read-only. More...
 
IEnumerator RetrieveOutputAsync ()
 Asynchronously execute the graph. The output of the graph can be retrieved with the LastExecutionResult property when the returned enumerator completes. More...
 
- Public Member Functions inherited from SmartEngine.Object
void AddRef ()
 Increments the internal reference count on this object. It is not common to use this method directly. More...
 
void Release ()
 Decrements the internal reference count on this object. It is not common to use this method directly. More...
 
- Public Member Functions inherited from SmartEngine.Disposable
void Dispose ()
 Cleans up any internal state. It is not safe to use an object after it has been disposed. More...
 

Additional Inherited Members

- Properties inherited from SmartEngine.NeuralNetworks.GraphNode
string Name [get]
 Returns the name of the graph node. More...
 
Matrix LastExecutionResult [get]
 Get the results of last execution of the graph. The returned matrix is read-only. More...
 
int OutputDimension [get]
 Returns the dimension of a single row of this node's output. The Output property's length will be a multiple of this value. More...
 

Detailed Description

The loss of a NeuralNetwork is computed using the formula (Expected Ouput - Actual Output)^2 The mean of all these values across the output tensor is used when crunching down the loss to a single value.

Member Function Documentation

◆ GetLoss()

float SmartEngine.NeuralNetworks.Loss.GetLoss ( )

Returns the mean L2 loss using the current network and expected state

Returns