Python TensorDual.log Exemples

Exemple #1

Fichier : TensorLoss.py Projet : TheYargonaut/super-connected-neural-net

def jsDivergence( targetReal, targetInft, predReal, predInft ):
    m = td.multiply( 0.5, 0.0, *td.add( targetReal, targetInft, predReal, predInft ) )
    tpart = td.multiply( targetReal, targetInft, *td.log( *td.divide( targetReal, targetInft, *m ) ) )
    ppart = td.multiply( predReal, predInft, *td.log( *td.divide( predReal, predInft, *m ) ) )
    return td.multiply( 0.5, 0.0, *td.add( *tpart, *ppart ) )

Exemple #2

Fichier : TensorLoss.py Projet : TheYargonaut/super-connected-neural-net

def crossEntropy( targetReal, targetInft, predReal, predInft ):
    return td.multiply( *td.neg( targetReal, targetInft ), *td.log( predReal, predInft ) )

Exemple #3

Fichier : TensorLoss.py Projet : TheYargonaut/super-connected-neural-net

def klDivergence( targetReal, targetInft, predReal, predInft ):
    return td.multiply( targetReal, targetInft, *td.log( *td.divide( targetReal, targetInft, predReal, predInft ) ) )

Exemple #4

Fichier : TensorActivation.py Projet : TheYargonaut/super-connected-neural-net

def softplus(real, inft):
    return td.log(*td.add(*td.exp(real, inft), 1.0, 0.0))