BNNS.ActivationFunction.linearWithBias(alpha:beta:)
An activation function that returns its input multiplied by a scale and added to a bias.
Declaration
case linearWithBias(alpha: Float, beta: Float)Discussion
This constant defines an activation function that returns values using the following operation:
alpha*x + betaThe following illustrates the output that the activation function generates from inputs in the range -10...10, an alpha of 2.0, and a beta of 10.0:
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See Also
Activation Functions
BNNS.ActivationFunction.absBNNS.ActivationFunction.celu(alpha:)BNNS.ActivationFunction.clamp(bounds:)BNNS.ActivationFunction.clampedLeakyRectifiedLinear(alpha:beta:)BNNS.ActivationFunction.elu(alpha:)BNNS.ActivationFunction.geluApproximation(alpha:beta:)BNNS.ActivationFunction.geluApproximation2(alpha:beta:)BNNS.ActivationFunction.gumbel(alpha:beta:)BNNS.ActivationFunction.gumbelMax(alpha:beta:)BNNS.ActivationFunction.hardShrink(alpha:)BNNS.ActivationFunction.hardSigmoid(alpha:beta:)BNNS.ActivationFunction.hardSwish(alpha:beta:)BNNS.ActivationFunction.identityBNNS.ActivationFunction.leakyRectifiedLinear(alpha:)BNNS.ActivationFunction.linear(alpha:)